Attachment 528426 Details for Bug 653994 – dev-python/pyudev-0.21.0:20180424-150811.log

dev-python/pyudev-0.21.0:20180424-150811.log

pyudev-0.21.0:20180424-150811.log (text/plain), 341.60 KB, created by eroen on 2018-04-24 15:18:06 UTC

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Description:

Filename:

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Creator: eroen

Created: 2018-04-24 15:18:06 UTC

Size: 341.60 KB

patch

obsolete

> * Package:    dev-python/pyudev-0.21.0
> * Repository: gentoo
> * Maintainer: python@gentoo.org
> * USE:        abi_x86_64 amd64 elibc_glibc kernel_linux python_targets_python2_7 python_targets_python3_4 python_targets_python3_5 python_targets_python3_6 test userland_GNU
> * FEATURES:   compressdebug installsources network-sandbox preserve-libs sandbox splitdebug test userpriv usersandbox
>>>> Unpacking source...
>>>> Unpacking pyudev-0.21.0.tar.gz to /var/tmp/portage/dev-python/pyudev-0.21.0/work
>>>> Source unpacked in /var/tmp/portage/dev-python/pyudev-0.21.0/work
>>>> Preparing source in /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0 ...
> * If your PORTAGE_TMPDIR is longer in length then '/var/tmp/',
> * change it to /var/tmp to ensure tests will pass.
> * Applying pyudev-0.19.0-skip-non-deterministic-test.patch ...
> [ ok ]
>>>> Source prepared.
>>>> Configuring source in /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0 ...
>>>> Source configured.
>>>> Compiling source in /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0 ...
> * python2_7: running distutils-r1_run_phase distutils-r1_python_compile
>/usr/bin/python2.7 setup.py build
>running build
>running build_py
>creating /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python2_7/lib/pyudev
>copying src/pyudev/_compat.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python2_7/lib/pyudev
>copying src/pyudev/wx.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python2_7/lib/pyudev
>copying src/pyudev/core.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python2_7/lib/pyudev
>copying src/pyudev/monitor.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python2_7/lib/pyudev
>copying src/pyudev/__init__.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python2_7/lib/pyudev
>copying src/pyudev/discover.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python2_7/lib/pyudev
>copying src/pyudev/glib.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python2_7/lib/pyudev
>copying src/pyudev/pyqt4.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python2_7/lib/pyudev
>copying src/pyudev/pyside.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python2_7/lib/pyudev
>copying src/pyudev/version.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python2_7/lib/pyudev
>copying src/pyudev/_util.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python2_7/lib/pyudev
>copying src/pyudev/pyqt5.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python2_7/lib/pyudev
>copying src/pyudev/_qt_base.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python2_7/lib/pyudev
>creating /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python2_7/lib/pyudev/device
>copying src/pyudev/device/_device.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python2_7/lib/pyudev/device
>copying src/pyudev/device/_errors.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python2_7/lib/pyudev/device
>copying src/pyudev/device/__init__.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python2_7/lib/pyudev/device
>creating /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python2_7/lib/pyudev/_os
>copying src/pyudev/_os/__init__.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python2_7/lib/pyudev/_os
>copying src/pyudev/_os/poll.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python2_7/lib/pyudev/_os
>copying src/pyudev/_os/pipe.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python2_7/lib/pyudev/_os
>creating /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python2_7/lib/pyudev/_ctypeslib
>copying src/pyudev/_ctypeslib/libc.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python2_7/lib/pyudev/_ctypeslib
>copying src/pyudev/_ctypeslib/__init__.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python2_7/lib/pyudev/_ctypeslib
>copying src/pyudev/_ctypeslib/_errorcheckers.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python2_7/lib/pyudev/_ctypeslib
>copying src/pyudev/_ctypeslib/libudev.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python2_7/lib/pyudev/_ctypeslib
>copying src/pyudev/_ctypeslib/utils.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python2_7/lib/pyudev/_ctypeslib
>warning: build_py: byte-compiling is disabled, skipping.
>
> * python3_4: running distutils-r1_run_phase distutils-r1_python_compile
>/usr/bin/python3.4 setup.py build
>running build
>running build_py
>creating /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_4/lib/pyudev
>copying src/pyudev/_compat.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_4/lib/pyudev
>copying src/pyudev/wx.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_4/lib/pyudev
>copying src/pyudev/core.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_4/lib/pyudev
>copying src/pyudev/monitor.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_4/lib/pyudev
>copying src/pyudev/__init__.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_4/lib/pyudev
>copying src/pyudev/discover.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_4/lib/pyudev
>copying src/pyudev/glib.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_4/lib/pyudev
>copying src/pyudev/pyqt4.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_4/lib/pyudev
>copying src/pyudev/pyside.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_4/lib/pyudev
>copying src/pyudev/version.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_4/lib/pyudev
>copying src/pyudev/_util.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_4/lib/pyudev
>copying src/pyudev/pyqt5.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_4/lib/pyudev
>copying src/pyudev/_qt_base.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_4/lib/pyudev
>creating /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_4/lib/pyudev/device
>copying src/pyudev/device/_device.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_4/lib/pyudev/device
>copying src/pyudev/device/_errors.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_4/lib/pyudev/device
>copying src/pyudev/device/__init__.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_4/lib/pyudev/device
>creating /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_4/lib/pyudev/_os
>copying src/pyudev/_os/__init__.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_4/lib/pyudev/_os
>copying src/pyudev/_os/poll.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_4/lib/pyudev/_os
>copying src/pyudev/_os/pipe.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_4/lib/pyudev/_os
>creating /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_4/lib/pyudev/_ctypeslib
>copying src/pyudev/_ctypeslib/libc.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_4/lib/pyudev/_ctypeslib
>copying src/pyudev/_ctypeslib/__init__.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_4/lib/pyudev/_ctypeslib
>copying src/pyudev/_ctypeslib/_errorcheckers.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_4/lib/pyudev/_ctypeslib
>copying src/pyudev/_ctypeslib/libudev.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_4/lib/pyudev/_ctypeslib
>copying src/pyudev/_ctypeslib/utils.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_4/lib/pyudev/_ctypeslib
>warning: build_py: byte-compiling is disabled, skipping.
>
> * python3_5: running distutils-r1_run_phase distutils-r1_python_compile
>/usr/bin/python3.5 setup.py build
>running build
>running build_py
>creating /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_5/lib/pyudev
>copying src/pyudev/_compat.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_5/lib/pyudev
>copying src/pyudev/wx.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_5/lib/pyudev
>copying src/pyudev/core.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_5/lib/pyudev
>copying src/pyudev/monitor.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_5/lib/pyudev
>copying src/pyudev/__init__.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_5/lib/pyudev
>copying src/pyudev/discover.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_5/lib/pyudev
>copying src/pyudev/glib.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_5/lib/pyudev
>copying src/pyudev/pyqt4.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_5/lib/pyudev
>copying src/pyudev/pyside.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_5/lib/pyudev
>copying src/pyudev/version.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_5/lib/pyudev
>copying src/pyudev/_util.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_5/lib/pyudev
>copying src/pyudev/pyqt5.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_5/lib/pyudev
>copying src/pyudev/_qt_base.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_5/lib/pyudev
>creating /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_5/lib/pyudev/device
>copying src/pyudev/device/_device.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_5/lib/pyudev/device
>copying src/pyudev/device/_errors.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_5/lib/pyudev/device
>copying src/pyudev/device/__init__.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_5/lib/pyudev/device
>creating /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_5/lib/pyudev/_os
>copying src/pyudev/_os/__init__.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_5/lib/pyudev/_os
>copying src/pyudev/_os/poll.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_5/lib/pyudev/_os
>copying src/pyudev/_os/pipe.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_5/lib/pyudev/_os
>creating /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_5/lib/pyudev/_ctypeslib
>copying src/pyudev/_ctypeslib/libc.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_5/lib/pyudev/_ctypeslib
>copying src/pyudev/_ctypeslib/__init__.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_5/lib/pyudev/_ctypeslib
>copying src/pyudev/_ctypeslib/_errorcheckers.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_5/lib/pyudev/_ctypeslib
>copying src/pyudev/_ctypeslib/libudev.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_5/lib/pyudev/_ctypeslib
>copying src/pyudev/_ctypeslib/utils.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_5/lib/pyudev/_ctypeslib
>warning: build_py: byte-compiling is disabled, skipping.
>
> * python3_6: running distutils-r1_run_phase distutils-r1_python_compile
>/usr/bin/python3.6 setup.py build
>running build
>running build_py
>creating /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_6/lib/pyudev
>copying src/pyudev/_compat.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_6/lib/pyudev
>copying src/pyudev/wx.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_6/lib/pyudev
>copying src/pyudev/core.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_6/lib/pyudev
>copying src/pyudev/monitor.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_6/lib/pyudev
>copying src/pyudev/__init__.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_6/lib/pyudev
>copying src/pyudev/discover.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_6/lib/pyudev
>copying src/pyudev/glib.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_6/lib/pyudev
>copying src/pyudev/pyqt4.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_6/lib/pyudev
>copying src/pyudev/pyside.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_6/lib/pyudev
>copying src/pyudev/version.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_6/lib/pyudev
>copying src/pyudev/_util.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_6/lib/pyudev
>copying src/pyudev/pyqt5.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_6/lib/pyudev
>copying src/pyudev/_qt_base.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_6/lib/pyudev
>creating /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_6/lib/pyudev/device
>copying src/pyudev/device/_device.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_6/lib/pyudev/device
>copying src/pyudev/device/_errors.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_6/lib/pyudev/device
>copying src/pyudev/device/__init__.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_6/lib/pyudev/device
>creating /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_6/lib/pyudev/_os
>copying src/pyudev/_os/__init__.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_6/lib/pyudev/_os
>copying src/pyudev/_os/poll.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_6/lib/pyudev/_os
>copying src/pyudev/_os/pipe.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_6/lib/pyudev/_os
>creating /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_6/lib/pyudev/_ctypeslib
>copying src/pyudev/_ctypeslib/libc.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_6/lib/pyudev/_ctypeslib
>copying src/pyudev/_ctypeslib/__init__.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_6/lib/pyudev/_ctypeslib
>copying src/pyudev/_ctypeslib/_errorcheckers.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_6/lib/pyudev/_ctypeslib
>copying src/pyudev/_ctypeslib/libudev.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_6/lib/pyudev/_ctypeslib
>copying src/pyudev/_ctypeslib/utils.py -> /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0-python3_6/lib/pyudev/_ctypeslib
>warning: build_py: byte-compiling is disabled, skipping.
>
>>>> Source compiled.
>>>> Test phase: dev-python/pyudev-0.21.0
> * python2_7: running distutils-r1_run_phase python_test
>============================================= test session starts ==============================================
>platform linux2 -- Python 2.7.14, pytest-3.4.1, py-1.5.3, pluggy-0.6.0 -- /usr/bin/python2.7
>cachedir: .pytest_cache
>rootdir: /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0, inifile: setup.cfg
>plugins: xprocess-0.12.1, xdist-1.20.1, virtualenv-1.2.11, subtesthack-0.1.1, shutil-1.2.11, localserver-0.3.7, isort-0.1.0, forked-0.2, flake8-0.8.1, expect-1.1.0, cov-2.5.1, hypothesis-3.50.1, flaky-3.4.0, betamax-0.8.0, backports.unittest-mock-1.3
>collecting ... collected 192 items
>
>tests/test_core.py::test_udev_version PASSED                                                             [  0%]
>tests/test_core.py::TestContext::test_sys_path PASSED                                                    [  1%]
>tests/test_core.py::TestContext::test_device_path PASSED                                                 [  1%]
>tests/test_core.py::TestContext::test_run_path PASSED                                                    [  2%]
>tests/test_core.py::TestContext::test_log_priority_get PASSED                                            [  2%]
>tests/test_core.py::TestContext::test_log_priority_get_mock PASSED                                       [  3%]
>tests/test_core.py::TestContext::test_log_priority_set_mock PASSED                                       [  3%]
>tests/test_core.py::TestContext::test_log_priority_roundtrip PASSED                                      [  4%]
>tests/test_device.py::TestAttributes::test_getitem <- tests/_device_tests/_attributes_tests.py PASSED    [  4%]
>tests/test_device.py::TestAttributes::test_getitem_nonexisting <- tests/_device_tests/_attributes_tests.py PASSED [  5%]
>tests/test_device.py::TestAttributes::test_non_iterable <- tests/_device_tests/_attributes_tests.py PASSED [  5%]
>tests/test_device.py::TestAttributes::test_asstring <- tests/_device_tests/_attributes_tests.py SKIPPED  [  6%]
>tests/test_device.py::TestAttributes::test_asint <- tests/_device_tests/_attributes_tests.py SKIPPED     [  6%]
>tests/test_device.py::TestAttributes::test_asbool <- tests/_device_tests/_attributes_tests.py SKIPPED    [  7%]
>tests/test_device.py::TestAttributes::test_available_attributes <- tests/_device_tests/_attributes_tests.py PASSED [  7%]
>tests/test_device.py::TestDevice::test_parent <- tests/_device_tests/_device_tests.py PASSED             [  8%]
>tests/test_device.py::TestDevice::test_child_of_parent <- tests/_device_tests/_device_tests.py PASSED    [  8%]
>tests/test_device.py::TestDevice::test_children <- tests/_device_tests/_device_tests.py PASSED           [  9%]
>tests/test_device.py::TestDevice::test_ancestors <- tests/_device_tests/_device_tests.py PASSED          [  9%]
>tests/test_device.py::TestDevice::test_find_parent <- tests/_device_tests/_device_tests.py PASSED        [ 10%]
>tests/test_device.py::TestDevice::test_find_parent_no_devtype_mock <- tests/_device_tests/_device_tests.py PASSED [ 10%]
>tests/test_device.py::TestDevice::test_find_parent_with_devtype_mock <- tests/_device_tests/_device_tests.py PASSED [ 11%]
>tests/test_device.py::TestDevice::test_traverse <- tests/_device_tests/_device_tests.py PASSED           [ 11%]
>tests/test_device.py::TestDevice::test_sys_path <- tests/_device_tests/_device_tests.py PASSED           [ 12%]
>tests/test_device.py::TestDevice::test_device_path <- tests/_device_tests/_device_tests.py PASSED        [ 13%]
>tests/test_device.py::TestDevice::test_subsystem <- tests/_device_tests/_device_tests.py PASSED          [ 13%]
>tests/test_device.py::TestDevice::test_device_sys_name <- tests/_device_tests/_device_tests.py PASSED    [ 14%]
>tests/test_device.py::TestDevice::test_sys_number <- tests/_device_tests/_device_tests.py PASSED         [ 14%]
>tests/test_device.py::TestDevice::test_type <- tests/_device_tests/_device_tests.py PASSED               [ 15%]
>tests/test_device.py::TestDevice::test_driver <- tests/_device_tests/_device_tests.py PASSED             [ 15%]
>tests/test_device.py::TestDevice::test_device_node <- tests/_device_tests/_device_tests.py PASSED        [ 16%]
>tests/test_device.py::TestDevice::test_device_number <- tests/_device_tests/_device_tests.py PASSED      [ 16%]
>tests/test_device.py::TestDevice::test_is_initialized <- tests/_device_tests/_device_tests.py PASSED     [ 17%]
>tests/test_device.py::TestDevice::test_is_initialized_mock <- tests/_device_tests/_device_tests.py PASSED [ 17%]
>tests/test_device.py::TestDevice::test_time_since_initialized <- tests/_device_tests/_device_tests.py PASSED [ 18%]
>tests/test_device.py::TestDevice::test_time_since_initialized_mock <- tests/_device_tests/_device_tests.py PASSED [ 18%]
>tests/test_device.py::TestDevice::test_links <- tests/_device_tests/_device_tests.py PASSED              [ 19%]
>tests/test_device.py::TestDevice::test_action <- tests/_device_tests/_device_tests.py PASSED             [ 19%]
>tests/test_device.py::TestDevice::test_action_mock <- tests/_device_tests/_device_tests.py PASSED        [ 20%]
>tests/test_device.py::TestDevice::test_sequence_number <- tests/_device_tests/_device_tests.py PASSED    [ 20%]
>tests/test_device.py::TestDevice::test_attributes <- tests/_device_tests/_device_tests.py PASSED         [ 21%]
>tests/test_device.py::TestDevice::test_no_leak <- tests/_device_tests/_device_tests.py PASSED            [ 21%]
>tests/test_device.py::TestDevice::test_tags <- tests/_device_tests/_device_tests.py PASSED               [ 22%]
>tests/test_device.py::TestDevice::test_iteration <- tests/_device_tests/_device_tests.py PASSED          [ 22%]
>tests/test_device.py::TestDevice::test_length <- tests/_device_tests/_device_tests.py SKIPPED            [ 23%]
>tests/test_device.py::TestDevice::test_key_subset <- tests/_device_tests/_device_tests.py PASSED         [ 23%]
>tests/test_device.py::TestDevice::test_getitem <- tests/_device_tests/_device_tests.py PASSED            [ 24%]
>tests/test_device.py::TestDevice::test_getitem_devname <- tests/_device_tests/_device_tests.py PASSED    [ 25%]
>tests/test_device.py::TestDevice::test_getitem_nonexisting <- tests/_device_tests/_device_tests.py PASSED [ 25%]
>tests/test_device.py::TestDevice::test_asint <- tests/_device_tests/_device_tests.py SKIPPED             [ 26%]
>tests/test_device.py::TestDevice::test_asbool <- tests/_device_tests/_device_tests.py SKIPPED            [ 26%]
>tests/test_device.py::TestDevice::test_hash <- tests/_device_tests/_device_tests.py PASSED               [ 27%]
>tests/test_device.py::TestDevice::test_equality <- tests/_device_tests/_device_tests.py PASSED           [ 27%]
>tests/test_device.py::TestDevice::test_inequality <- tests/_device_tests/_device_tests.py PASSED         [ 28%]
>tests/test_device.py::TestDevice::test_device_ordering <- tests/_device_tests/_device_tests.py PASSED    [ 28%]
>tests/test_device.py::TestDevice::test_id_wwn_with_extension <- tests/_device_tests/_device_tests.py PASSED [ 29%]
>tests/test_device.py::TestDevices::test_from_path <- tests/_device_tests/_devices_tests.py PASSED        [ 29%]
>tests/test_device.py::TestDevices::test_from_path_strips_leading_slash <- tests/_device_tests/_devices_tests.py PASSED [ 30%]
>tests/test_device.py::TestDevices::test_from_sys_path <- tests/_device_tests/_devices_tests.py PASSED    [ 30%]
>tests/test_device.py::TestDevices::test_from_sys_path_device_not_found <- tests/_device_tests/_devices_tests.py PASSED [ 31%]
>tests/test_device.py::TestDevices::test_from_name <- tests/_device_tests/_devices_tests.py PASSED        [ 31%]
>tests/test_device.py::TestDevices::test_from_name_no_device_in_existing_subsystem <- tests/_device_tests/_devices_tests.py PASSED [ 32%]
>tests/test_device.py::TestDevices::test_from_name_nonexisting_subsystem <- tests/_device_tests/_devices_tests.py PASSED [ 32%]
>tests/test_device.py::TestDevices::test_from_device_number <- tests/_device_tests/_devices_tests.py PASSED [ 33%]
>tests/test_device.py::TestDevices::test_from_device_number_wrong_type <- tests/_device_tests/_devices_tests.py PASSED [ 33%]
>tests/test_device.py::TestDevices::test_from_device_number_invalid_type <- tests/_device_tests/_devices_tests.py PASSED [ 34%]
>tests/test_device.py::TestDevices::test_from_device_file <- tests/_device_tests/_devices_tests.py PASSED [ 34%]
>tests/test_device.py::TestDevices::test_from_device_file_links <- tests/_device_tests/_devices_tests.py SKIPPED [ 35%]
>tests/test_device.py::TestDevices::test_from_device_file_no_device_file <- tests/_device_tests/_devices_tests.py PASSED [ 35%]
>tests/test_device.py::TestDevices::test_from_device_file_non_existing <- tests/_device_tests/_devices_tests.py PASSED [ 36%]
>tests/test_device.py::TestDevices::test_from_environment <- tests/_device_tests/_devices_tests.py PASSED [ 36%]
>tests/test_device.py::TestTags::test_iteration_and_contains <- tests/_device_tests/_tags_tests.py PASSED [ 37%]
>tests/test_device.py::TestTags::test_iteration_mock <- tests/_device_tests/_tags_tests.py PASSED         [ 38%]
>tests/test_device.py::TestTags::test_contains_mock <- tests/_device_tests/_tags_tests.py PASSED          [ 38%]
>tests/test_device.py::test_garbage PASSED                                                                [ 39%]
>tests/test_discover.py::TestDiscovery::test_device_number PASSED                                         [ 39%]
>tests/test_discover.py::TestDiscovery::test_path PASSED                                                  [ 40%]
>tests/test_discover.py::TestDiscovery::test_name PASSED                                                  [ 40%]
>tests/test_discover.py::TestDiscovery::test_device_file SKIPPED                                          [ 41%]
>tests/test_discover.py::TestDiscovery::test_anything PASSED                                              [ 41%]
>tests/test_enumerate.py::TestEnumerator::test_match_subsystem_nomatch <- tests/utils/misc.py PASSED      [ 42%]
>tests/test_enumerate.py::TestEnumerator::test_match_attribute_nomatch_unfulfillable <- tests/utils/misc.py PASSED [ 42%]
>tests/test_enumerate.py::TestEnumerator::test_match_sys_name <- tests/utils/misc.py PASSED               [ 43%]
>tests/test_enumerate.py::TestEnumerator::test_match_subsystem_nomatch_unfulfillable <- tests/utils/misc.py PASSED [ 43%]
>tests/test_enumerate.py::TestEnumerator::test_match_attribute_int <- tests/utils/misc.py PASSED          [ 44%]
>tests/test_enumerate.py::TestEnumerator::test_match_attribute_bool <- tests/utils/misc.py PASSED         [ 44%]
>tests/test_enumerate.py::TestEnumerator::test_match_property_int <- tests/utils/misc.py PASSED           [ 45%]
>tests/test_enumerate.py::TestEnumerator::test_match_attribute_nomatch_complete <- tests/utils/misc.py PASSED [ 45%]
>tests/test_enumerate.py::TestEnumerator::test_match_attribute_nomatch <- tests/utils/misc.py PASSED      [ 46%]
>tests/test_enumerate.py::TestEnumerator::test_match_attribute_match <- tests/utils/misc.py PASSED        [ 46%]
>tests/test_enumerate.py::TestEnumerator::test_match_parent <- tests/utils/misc.py PASSED                 [ 47%]
>tests/test_enumerate.py::TestEnumerator::test_match_subsystem <- tests/utils/misc.py PASSED              [ 47%]
>tests/test_enumerate.py::TestEnumerator::test_match_property_bool <- tests/utils/misc.py SKIPPED         [ 48%]
>tests/test_enumerate.py::TestEnumerator::test_match_property_string <- tests/utils/misc.py PASSED        [ 48%]
>tests/test_enumerate.py::TestEnumerator::test_match_subsystem_nomatch_complete <- tests/utils/misc.py PASSED [ 49%]
>tests/test_enumerate.py::TestEnumerator::test_match_tag <- tests/utils/misc.py SKIPPED                   [ 50%]
>tests/test_enumerate.py::TestEnumerator::test_match_attribute_string <- tests/utils/misc.py PASSED       [ 50%]
>tests/test_enumerate.py::TestEnumeratorMatchCombinations::test_combined_property_matches PASSED          [ 51%]
>tests/test_enumerate.py::TestEnumeratorMatchCombinations::test_combined_attribute_matches PASSED         [ 51%]
>tests/test_enumerate.py::TestEnumeratorMatchCombinations::test_combined_matches_of_different_types PASSED [ 52%]
>tests/test_enumerate.py::TestEnumeratorMatchCombinations::test_match PASSED                              [ 52%]
>tests/test_enumerate.py::TestEnumeratorMatchMethod::test_match_passthrough_subsystem PASSED              [ 53%]
>tests/test_enumerate.py::TestEnumeratorMatchMethod::test_match_passthrough_sys_name PASSED               [ 53%]
>tests/test_enumerate.py::TestEnumeratorMatchMethod::test_match_passthrough_tag PASSED                    [ 54%]
>tests/test_enumerate.py::TestEnumeratorMatchMethod::test_match_passthrough_parent PASSED                 [ 54%]
>tests/test_enumerate.py::TestEnumeratorMatchMethod::test_match_passthrough_property PASSED               [ 55%]
>tests/test_monitor.py::TestMonitor::test_from_netlink_invalid_source PASSED                              [ 55%]
>tests/test_monitor.py::TestMonitor::test_from_netlink_source_udev PASSED                                 [ 56%]
>tests/test_monitor.py::TestMonitor::test_from_netlink_source_udev_mock PASSED                            [ 56%]
>tests/test_monitor.py::TestMonitor::test_from_netlink_source_kernel PASSED                               [ 57%]
>tests/test_monitor.py::TestMonitor::test_from_netlink_source_kernel_mock PASSED                          [ 57%]
>tests/test_monitor.py::TestMonitor::test_fileno PASSED                                                   [ 58%]
>tests/test_monitor.py::TestMonitor::test_fileno_mock PASSED                                              [ 58%]
>tests/test_monitor.py::TestMonitor::test_filter_by_no_subsystem PASSED                                   [ 59%]
>tests/test_monitor.py::TestMonitor::test_filter_by_subsystem_no_dev_type PASSED                          [ 59%]
>tests/test_monitor.py::TestMonitor::test_filter_by_subsystem_no_dev_type_mock PASSED                     [ 60%]
>tests/test_monitor.py::TestMonitor::test_filter_by_subsystem_dev_type PASSED                             [ 60%]
>tests/test_monitor.py::TestMonitor::test_filter_by_subsystem_dev_type_mock PASSED                        [ 61%]
>tests/test_monitor.py::TestMonitor::test_filter_by_tag PASSED                                            [ 61%]
>tests/test_monitor.py::TestMonitor::test_filter_by_tag_mock PASSED                                       [ 62%]
>tests/test_monitor.py::TestMonitor::test_remove_filter PASSED                                            [ 63%]
>tests/test_monitor.py::TestMonitor::test_remove_filter_mock PASSED                                       [ 63%]
>tests/test_monitor.py::TestMonitor::test_start_netlink_kernel_source PASSED                              [ 64%]
>tests/test_monitor.py::TestMonitor::test_start_mock PASSED                                               [ 64%]
>tests/test_monitor.py::TestMonitor::test_enable_receiving PASSED                                         [ 65%]
>tests/test_monitor.py::TestMonitor::test_set_receive_buffer_size_mock PASSED                             [ 65%]
>tests/test_monitor.py::TestMonitor::test_poll_timeout PASSED                                             [ 66%]
>tests/test_monitor.py::TestMonitor::test_poll SKIPPED                                                    [ 66%]
>tests/test_monitor.py::TestMonitor::test_receive_device PASSED                                           [ 67%]
>tests/test_monitor.py::TestMonitor::test_iter SKIPPED                                                    [ 67%]
>tests/test_monitor.py::TestMonitorObserver::test_deprecated_handler PASSED                               [ 68%]
>tests/test_monitor.py::TestMonitorObserver::test_fake PASSED                                             [ 68%]
>tests/test_monitor.py::TestMonitorObserver::test_real SKIPPED                                            [ 69%]
>tests/test_observer.py::test_fake_monitor PASSED                                                         [ 69%]
>tests/test_observer.py::TestPysideObserver::test_monitor SKIPPED                                         [ 70%]
>tests/test_observer.py::TestPysideObserver::test_events_fake_monitor SKIPPED                             [ 70%]
>tests/test_observer.py::TestPysideObserver::test_events_real SKIPPED                                     [ 71%]
>tests/test_observer.py::TestPyQt4Observer::test_monitor SKIPPED                                          [ 71%]
>tests/test_observer.py::TestPyQt4Observer::test_events_fake_monitor SKIPPED                              [ 72%]
>tests/test_observer.py::TestPyQt4Observer::test_events_real SKIPPED                                      [ 72%]
>tests/test_observer.py::TestPyQt5Observer::test_monitor PASSED                                           [ 73%]
>tests/test_observer.py::TestPyQt5Observer::test_events_fake_monitor PASSED                               [ 73%]
>tests/test_observer.py::TestPyQt5Observer::test_events_real SKIPPED                                      [ 74%]
>tests/test_observer.py::TestGlibObserver::test_monitor PASSED                                            [ 75%]
>tests/test_observer.py::TestGlibObserver::test_events_fake_monitor PASSED                                [ 75%]
>tests/test_observer.py::TestGlibObserver::test_events_real SKIPPED                                       [ 76%]
>tests/test_observer.py::TestWxObserver::test_monitor FAILED                                              [ 76%]
>tests/test_observer.py::TestWxObserver::test_events_fake_monitor FAILED                                  [ 77%]
>tests/test_observer.py::TestWxObserver::test_events_real SKIPPED                                         [ 77%]
>tests/test_observer_deprecated.py::TestDeprecatedPysideObserver::test_monitor SKIPPED                    [ 78%]
>tests/test_observer_deprecated.py::TestDeprecatedPysideObserver::test_events_fake_monitor[add] SKIPPED   [ 78%]
>tests/test_observer_deprecated.py::TestDeprecatedPysideObserver::test_events_fake_monitor[remove] SKIPPED [ 79%]
>tests/test_observer_deprecated.py::TestDeprecatedPysideObserver::test_events_fake_monitor[change] SKIPPED [ 79%]
>tests/test_observer_deprecated.py::TestDeprecatedPysideObserver::test_events_fake_monitor[move] SKIPPED  [ 80%]
>tests/test_observer_deprecated.py::TestDeprecatedPysideObserver::test_events_real SKIPPED                [ 80%]
>tests/test_observer_deprecated.py::TestDeprecatedPyQt4Observer::test_monitor SKIPPED                     [ 81%]
>tests/test_observer_deprecated.py::TestDeprecatedPyQt4Observer::test_events_fake_monitor[add] SKIPPED    [ 81%]
>tests/test_observer_deprecated.py::TestDeprecatedPyQt4Observer::test_events_fake_monitor[remove] SKIPPED [ 82%]
>tests/test_observer_deprecated.py::TestDeprecatedPyQt4Observer::test_events_fake_monitor[change] SKIPPED [ 82%]
>tests/test_observer_deprecated.py::TestDeprecatedPyQt4Observer::test_events_fake_monitor[move] SKIPPED   [ 83%]
>tests/test_observer_deprecated.py::TestDeprecatedPyQt4Observer::test_events_real SKIPPED                 [ 83%]
>tests/test_observer_deprecated.py::TestDeprecatedGlibObserver::test_monitor PASSED                       [ 84%]
>tests/test_observer_deprecated.py::TestDeprecatedGlibObserver::test_events_fake_monitor[add] PASSED      [ 84%]
>tests/test_observer_deprecated.py::TestDeprecatedGlibObserver::test_events_fake_monitor[remove] PASSED   [ 85%]
>tests/test_observer_deprecated.py::TestDeprecatedGlibObserver::test_events_fake_monitor[change] PASSED   [ 85%]
>tests/test_observer_deprecated.py::TestDeprecatedGlibObserver::test_events_fake_monitor[move] PASSED     [ 86%]
>tests/test_observer_deprecated.py::TestDeprecatedGlibObserver::test_events_real SKIPPED                  [ 86%]
>tests/test_observer_deprecated.py::TestDeprecatedWxObserver::test_monitor FAILED                         [ 87%]
>tests/test_observer_deprecated.py::TestDeprecatedWxObserver::test_events_fake_monitor[add] FAILED        [ 88%]
>tests/test_observer_deprecated.py::TestDeprecatedWxObserver::test_events_fake_monitor[remove] FAILED     [ 88%]
>tests/test_observer_deprecated.py::TestDeprecatedWxObserver::test_events_fake_monitor[change] FAILED     [ 89%]
>tests/test_observer_deprecated.py::TestDeprecatedWxObserver::test_events_fake_monitor[move] FAILED       [ 89%]
>tests/test_observer_deprecated.py::TestDeprecatedWxObserver::test_events_real SKIPPED                    [ 90%]
>tests/test_pypi.py::test_manifest_complete SKIPPED                                                       [ 90%]
>tests/test_pypi.py::test_description_rendering PASSED                                                    [ 91%]
>tests/test_util.py::test_ensure_byte_string PASSED                                                       [ 91%]
>tests/test_util.py::test_ensure_byte_string_none PASSED                                                  [ 92%]
>tests/test_util.py::test_ensure_unicode_string PASSED                                                    [ 92%]
>tests/test_util.py::test_ensure_unicode_string_none PASSED                                               [ 93%]
>tests/test_util.py::test_property_value_to_bytes_string PASSED                                           [ 93%]
>tests/test_util.py::test_property_value_to_bytes_int PASSED                                              [ 94%]
>tests/test_util.py::test_property_value_to_bytes_bool PASSED                                             [ 94%]
>tests/test_util.py::test_string_to_bool_true PASSED                                                      [ 95%]
>tests/test_util.py::test_string_to_bool_false PASSED                                                     [ 95%]
>tests/test_util.py::test_string_to_bool_invalid_value PASSED                                             [ 96%]
>tests/test_util.py::test_udev_list_iterate_no_entry PASSED                                               [ 96%]
>tests/test_util.py::test_udev_list_iterate_mock PASSED                                                   [ 97%]
>tests/test_util.py::test_get_device_type_character_device PASSED                                         [ 97%]
>tests/test_util.py::test_get_device_type_block_device PASSED                                             [ 98%]
>tests/test_util.py::test_get_device_type_no_device_file PASSED                                           [ 98%]
>tests/test_util.py::test_get_device_type_not_existing PASSED                                             [ 99%]
>tests/test_util.py::test_eintr_retry_call PASSED                                                         [100%]
>===Flaky Test Report===
>
>
>===End Flaky Test Report===
>
>=================================================== FAILURES ===================================================
>_________________________________________ TestWxObserver.test_monitor __________________________________________
>
>self = <tests.test_observer.TestWxObserver object at 0x7f4aec5b6190>
>fake_monitor = <tests.plugins.fake_monitor.FakeMonitor object at 0x7f4aebc9d2d0>
>
>    def test_monitor(self, fake_monitor):
>>       self.prepare_test(fake_monitor)
>
>tests/test_observer.py:93: 
>_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
>tests/test_observer.py:89: in prepare_test
>    self.create_event_loop(self_stop_timeout=5000)
>tests/test_observer.py:229: in create_event_loop
>    self.app = self.wx.App(False)
>_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
>
>self = <wx._core.App; proxy of <Swig Object of type 'wxPyApp *' at 0x55f4705a2650> >, redirect = False
>filename = None, useBestVisual = False, clearSigInt = True
>
>    def __init__(self,
>                 redirect=False,
>                 filename=None,
>                 useBestVisual=False,
>                 clearSigInt=True):
>        """
>            Construct a ``wx.App`` object.
>    
>            :param redirect: Should ``sys.stdout`` and ``sys.stderr`` be
>                redirected?  Defaults to False. If ``filename`` is None
>                then output will be redirected to a window that pops up
>                as needed.  (You can control what kind of window is created
>                for the output by resetting the class variable
>                ``outputWindowClass`` to a class of your choosing.)
>    
>            :param filename: The name of a file to redirect output to, if
>                redirect is True.
>    
>            :param useBestVisual: Should the app try to use the best
>                available visual provided by the system (only relevant on
>                systems that have more than one visual.)  This parameter
>                must be used instead of calling `SetUseBestVisual` later
>                on because it must be set before the underlying GUI
>                toolkit is initialized.
>    
>            :param clearSigInt: Should SIGINT be cleared?  This allows the
>                app to terminate upon a Ctrl-C in the console like other
>                GUI apps will.
>    
>            :note: You should override OnInit to do applicaition
>                initialization to ensure that the system, toolkit and
>                wxWidgets are fully initialized.
>            """
>    
>        wx.PyApp.__init__(self)
>    
>        # make sure we can create a GUI
>        if not self.IsDisplayAvailable():
>    
>            if wx.Platform == "__WXMAC__":
>                msg = """This program needs access to the screen.
>    Please run with a Framework build of python, and only when you are
>    logged in on the main display of your Mac."""
>    
>            elif wx.Platform == "__WXGTK__":
>                msg ="Unable to access the X Display, is $DISPLAY set properly?"
>    
>            else:
>                msg = "Unable to create GUI"
>                # TODO: more description is needed for wxMSW...
>    
>>           raise SystemExit(msg)
>E           SystemExit: Unable to access the X Display, is $DISPLAY set properly?
>
>/usr/lib64/python2.7/site-packages/wx-3.0-gtk2/wx/_core.py:8596: SystemExit
>--------------------------------------------- Captured stderr call ---------------------------------------------
>No protocol specified
>___________________________________ TestWxObserver.test_events_fake_monitor ____________________________________
>
>self = <tests.test_observer.TestWxObserver object at 0x7f4aebcd50d0>
>fake_monitor = <tests.plugins.fake_monitor.FakeMonitor object at 0x7f4af5bc98d0>
>fake_monitor_device = Device(u'/sys/devices/virtual/bdi/253:20')
>
>    def test_events_fake_monitor(self, fake_monitor, fake_monitor_device):
>>       self.prepare_test(fake_monitor)
>
>tests/test_observer.py:98: 
>_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
>tests/test_observer.py:89: in prepare_test
>    self.create_event_loop(self_stop_timeout=5000)
>tests/test_observer.py:229: in create_event_loop
>    self.app = self.wx.App(False)
>_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
>
>self = <wx._core.App; proxy of <Swig Object of type 'wxPyApp *' at 0x55f470cec6f0> >, redirect = False
>filename = None, useBestVisual = False, clearSigInt = True
>
>    def __init__(self,
>                 redirect=False,
>                 filename=None,
>                 useBestVisual=False,
>                 clearSigInt=True):
>        """
>            Construct a ``wx.App`` object.
>    
>            :param redirect: Should ``sys.stdout`` and ``sys.stderr`` be
>                redirected?  Defaults to False. If ``filename`` is None
>                then output will be redirected to a window that pops up
>                as needed.  (You can control what kind of window is created
>                for the output by resetting the class variable
>                ``outputWindowClass`` to a class of your choosing.)
>    
>            :param filename: The name of a file to redirect output to, if
>                redirect is True.
>    
>            :param useBestVisual: Should the app try to use the best
>                available visual provided by the system (only relevant on
>                systems that have more than one visual.)  This parameter
>                must be used instead of calling `SetUseBestVisual` later
>                on because it must be set before the underlying GUI
>                toolkit is initialized.
>    
>            :param clearSigInt: Should SIGINT be cleared?  This allows the
>                app to terminate upon a Ctrl-C in the console like other
>                GUI apps will.
>    
>            :note: You should override OnInit to do applicaition
>                initialization to ensure that the system, toolkit and
>                wxWidgets are fully initialized.
>            """
>    
>        wx.PyApp.__init__(self)
>    
>        # make sure we can create a GUI
>        if not self.IsDisplayAvailable():
>    
>            if wx.Platform == "__WXMAC__":
>                msg = """This program needs access to the screen.
>    Please run with a Framework build of python, and only when you are
>    logged in on the main display of your Mac."""
>    
>            elif wx.Platform == "__WXGTK__":
>                msg ="Unable to access the X Display, is $DISPLAY set properly?"
>    
>            else:
>                msg = "Unable to create GUI"
>                # TODO: more description is needed for wxMSW...
>    
>>           raise SystemExit(msg)
>E           SystemExit: Unable to access the X Display, is $DISPLAY set properly?
>
>/usr/lib64/python2.7/site-packages/wx-3.0-gtk2/wx/_core.py:8596: SystemExit
>--------------------------------------------- Captured stderr call ---------------------------------------------
>No protocol specified
>____________________________________ TestDeprecatedWxObserver.test_monitor _____________________________________
>
>self = <tests.test_observer_deprecated.TestDeprecatedWxObserver object at 0x7f4af5270950>
>fake_monitor = <tests.plugins.fake_monitor.FakeMonitor object at 0x7f4af52702d0>
>
>    def test_monitor(self, fake_monitor):
>>       self.prepare_test(fake_monitor)
>
>tests/test_observer_deprecated.py:87: 
>_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
>tests/test_observer_deprecated.py:83: in prepare_test
>    self.create_event_loop(self_stop_timeout=5000)
>tests/test_observer_deprecated.py:266: in create_event_loop
>    self.app = self.wx.App(False)
>_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
>
>self = <wx._core.App; proxy of <Swig Object of type 'wxPyApp *' at 0x55f46ea3ec80> >, redirect = False
>filename = None, useBestVisual = False, clearSigInt = True
>
>    def __init__(self,
>                 redirect=False,
>                 filename=None,
>                 useBestVisual=False,
>                 clearSigInt=True):
>        """
>            Construct a ``wx.App`` object.
>    
>            :param redirect: Should ``sys.stdout`` and ``sys.stderr`` be
>                redirected?  Defaults to False. If ``filename`` is None
>                then output will be redirected to a window that pops up
>                as needed.  (You can control what kind of window is created
>                for the output by resetting the class variable
>                ``outputWindowClass`` to a class of your choosing.)
>    
>            :param filename: The name of a file to redirect output to, if
>                redirect is True.
>    
>            :param useBestVisual: Should the app try to use the best
>                available visual provided by the system (only relevant on
>                systems that have more than one visual.)  This parameter
>                must be used instead of calling `SetUseBestVisual` later
>                on because it must be set before the underlying GUI
>                toolkit is initialized.
>    
>            :param clearSigInt: Should SIGINT be cleared?  This allows the
>                app to terminate upon a Ctrl-C in the console like other
>                GUI apps will.
>    
>            :note: You should override OnInit to do applicaition
>                initialization to ensure that the system, toolkit and
>                wxWidgets are fully initialized.
>            """
>    
>        wx.PyApp.__init__(self)
>    
>        # make sure we can create a GUI
>        if not self.IsDisplayAvailable():
>    
>            if wx.Platform == "__WXMAC__":
>                msg = """This program needs access to the screen.
>    Please run with a Framework build of python, and only when you are
>    logged in on the main display of your Mac."""
>    
>            elif wx.Platform == "__WXGTK__":
>                msg ="Unable to access the X Display, is $DISPLAY set properly?"
>    
>            else:
>                msg = "Unable to create GUI"
>                # TODO: more description is needed for wxMSW...
>    
>>           raise SystemExit(msg)
>E           SystemExit: Unable to access the X Display, is $DISPLAY set properly?
>
>/usr/lib64/python2.7/site-packages/wx-3.0-gtk2/wx/_core.py:8596: SystemExit
>--------------------------------------------- Captured stderr call ---------------------------------------------
>No protocol specified
>____________________________ TestDeprecatedWxObserver.test_events_fake_monitor[add] ____________________________
>
>self = <tests.test_observer_deprecated.TestDeprecatedWxObserver object at 0x7f4adff1dbd0>, action = 'add'
>fake_monitor = <tests.plugins.fake_monitor.FakeMonitor object at 0x7f4adff1dd50>
>fake_monitor_device = Device(u'/sys/devices/platform')
>
>    @pytest.mark.parametrize('action', ACTIONS, ids=ACTIONS)
>    def test_events_fake_monitor(self, action, fake_monitor,
>                                 fake_monitor_device):
>>       self.prepare_test(fake_monitor)
>
>tests/test_observer_deprecated.py:94: 
>_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
>tests/test_observer_deprecated.py:83: in prepare_test
>    self.create_event_loop(self_stop_timeout=5000)
>tests/test_observer_deprecated.py:266: in create_event_loop
>    self.app = self.wx.App(False)
>_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
>
>self = <wx._core.App; proxy of <Swig Object of type 'wxPyApp *' at 0x55f47085ed70> >, redirect = False
>filename = None, useBestVisual = False, clearSigInt = True
>
>    def __init__(self,
>                 redirect=False,
>                 filename=None,
>                 useBestVisual=False,
>                 clearSigInt=True):
>        """
>            Construct a ``wx.App`` object.
>    
>            :param redirect: Should ``sys.stdout`` and ``sys.stderr`` be
>                redirected?  Defaults to False. If ``filename`` is None
>                then output will be redirected to a window that pops up
>                as needed.  (You can control what kind of window is created
>                for the output by resetting the class variable
>                ``outputWindowClass`` to a class of your choosing.)
>    
>            :param filename: The name of a file to redirect output to, if
>                redirect is True.
>    
>            :param useBestVisual: Should the app try to use the best
>                available visual provided by the system (only relevant on
>                systems that have more than one visual.)  This parameter
>                must be used instead of calling `SetUseBestVisual` later
>                on because it must be set before the underlying GUI
>                toolkit is initialized.
>    
>            :param clearSigInt: Should SIGINT be cleared?  This allows the
>                app to terminate upon a Ctrl-C in the console like other
>                GUI apps will.
>    
>            :note: You should override OnInit to do applicaition
>                initialization to ensure that the system, toolkit and
>                wxWidgets are fully initialized.
>            """
>    
>        wx.PyApp.__init__(self)
>    
>        # make sure we can create a GUI
>        if not self.IsDisplayAvailable():
>    
>            if wx.Platform == "__WXMAC__":
>                msg = """This program needs access to the screen.
>    Please run with a Framework build of python, and only when you are
>    logged in on the main display of your Mac."""
>    
>            elif wx.Platform == "__WXGTK__":
>                msg ="Unable to access the X Display, is $DISPLAY set properly?"
>    
>            else:
>                msg = "Unable to create GUI"
>                # TODO: more description is needed for wxMSW...
>    
>>           raise SystemExit(msg)
>E           SystemExit: Unable to access the X Display, is $DISPLAY set properly?
>
>/usr/lib64/python2.7/site-packages/wx-3.0-gtk2/wx/_core.py:8596: SystemExit
>--------------------------------------------- Captured stderr call ---------------------------------------------
>No protocol specified
>__________________________ TestDeprecatedWxObserver.test_events_fake_monitor[remove] ___________________________
>
>self = <tests.test_observer_deprecated.TestDeprecatedWxObserver object at 0x7f4adff2cad0>, action = 'remove'
>fake_monitor = <tests.plugins.fake_monitor.FakeMonitor object at 0x7f4adf3e42d0>
>fake_monitor_device = Device(u'/sys/devices/platform')
>
>    @pytest.mark.parametrize('action', ACTIONS, ids=ACTIONS)
>    def test_events_fake_monitor(self, action, fake_monitor,
>                                 fake_monitor_device):
>>       self.prepare_test(fake_monitor)
>
>tests/test_observer_deprecated.py:94: 
>_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
>tests/test_observer_deprecated.py:83: in prepare_test
>    self.create_event_loop(self_stop_timeout=5000)
>tests/test_observer_deprecated.py:266: in create_event_loop
>    self.app = self.wx.App(False)
>_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
>
>self = <wx._core.App; proxy of <Swig Object of type 'wxPyApp *' at 0x55f470d19fa0> >, redirect = False
>filename = None, useBestVisual = False, clearSigInt = True
>
>    def __init__(self,
>                 redirect=False,
>                 filename=None,
>                 useBestVisual=False,
>                 clearSigInt=True):
>        """
>            Construct a ``wx.App`` object.
>    
>            :param redirect: Should ``sys.stdout`` and ``sys.stderr`` be
>                redirected?  Defaults to False. If ``filename`` is None
>                then output will be redirected to a window that pops up
>                as needed.  (You can control what kind of window is created
>                for the output by resetting the class variable
>                ``outputWindowClass`` to a class of your choosing.)
>    
>            :param filename: The name of a file to redirect output to, if
>                redirect is True.
>    
>            :param useBestVisual: Should the app try to use the best
>                available visual provided by the system (only relevant on
>                systems that have more than one visual.)  This parameter
>                must be used instead of calling `SetUseBestVisual` later
>                on because it must be set before the underlying GUI
>                toolkit is initialized.
>    
>            :param clearSigInt: Should SIGINT be cleared?  This allows the
>                app to terminate upon a Ctrl-C in the console like other
>                GUI apps will.
>    
>            :note: You should override OnInit to do applicaition
>                initialization to ensure that the system, toolkit and
>                wxWidgets are fully initialized.
>            """
>    
>        wx.PyApp.__init__(self)
>    
>        # make sure we can create a GUI
>        if not self.IsDisplayAvailable():
>    
>            if wx.Platform == "__WXMAC__":
>                msg = """This program needs access to the screen.
>    Please run with a Framework build of python, and only when you are
>    logged in on the main display of your Mac."""
>    
>            elif wx.Platform == "__WXGTK__":
>                msg ="Unable to access the X Display, is $DISPLAY set properly?"
>    
>            else:
>                msg = "Unable to create GUI"
>                # TODO: more description is needed for wxMSW...
>    
>>           raise SystemExit(msg)
>E           SystemExit: Unable to access the X Display, is $DISPLAY set properly?
>
>/usr/lib64/python2.7/site-packages/wx-3.0-gtk2/wx/_core.py:8596: SystemExit
>--------------------------------------------- Captured stderr call ---------------------------------------------
>No protocol specified
>__________________________ TestDeprecatedWxObserver.test_events_fake_monitor[change] ___________________________
>
>self = <tests.test_observer_deprecated.TestDeprecatedWxObserver object at 0x7f4adff2c950>, action = 'change'
>fake_monitor = <tests.plugins.fake_monitor.FakeMonitor object at 0x7f4adfeef290>
>fake_monitor_device = Device(u'/sys/devices/platform')
>
>    @pytest.mark.parametrize('action', ACTIONS, ids=ACTIONS)
>    def test_events_fake_monitor(self, action, fake_monitor,
>                                 fake_monitor_device):
>>       self.prepare_test(fake_monitor)
>
>tests/test_observer_deprecated.py:94: 
>_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
>tests/test_observer_deprecated.py:83: in prepare_test
>    self.create_event_loop(self_stop_timeout=5000)
>tests/test_observer_deprecated.py:266: in create_event_loop
>    self.app = self.wx.App(False)
>_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
>
>self = <wx._core.App; proxy of <Swig Object of type 'wxPyApp *' at 0x55f470f235b0> >, redirect = False
>filename = None, useBestVisual = False, clearSigInt = True
>
>    def __init__(self,
>                 redirect=False,
>                 filename=None,
>                 useBestVisual=False,
>                 clearSigInt=True):
>        """
>            Construct a ``wx.App`` object.
>    
>            :param redirect: Should ``sys.stdout`` and ``sys.stderr`` be
>                redirected?  Defaults to False. If ``filename`` is None
>                then output will be redirected to a window that pops up
>                as needed.  (You can control what kind of window is created
>                for the output by resetting the class variable
>                ``outputWindowClass`` to a class of your choosing.)
>    
>            :param filename: The name of a file to redirect output to, if
>                redirect is True.
>    
>            :param useBestVisual: Should the app try to use the best
>                available visual provided by the system (only relevant on
>                systems that have more than one visual.)  This parameter
>                must be used instead of calling `SetUseBestVisual` later
>                on because it must be set before the underlying GUI
>                toolkit is initialized.
>    
>            :param clearSigInt: Should SIGINT be cleared?  This allows the
>                app to terminate upon a Ctrl-C in the console like other
>                GUI apps will.
>    
>            :note: You should override OnInit to do applicaition
>                initialization to ensure that the system, toolkit and
>                wxWidgets are fully initialized.
>            """
>    
>        wx.PyApp.__init__(self)
>    
>        # make sure we can create a GUI
>        if not self.IsDisplayAvailable():
>    
>            if wx.Platform == "__WXMAC__":
>                msg = """This program needs access to the screen.
>    Please run with a Framework build of python, and only when you are
>    logged in on the main display of your Mac."""
>    
>            elif wx.Platform == "__WXGTK__":
>                msg ="Unable to access the X Display, is $DISPLAY set properly?"
>    
>            else:
>                msg = "Unable to create GUI"
>                # TODO: more description is needed for wxMSW...
>    
>>           raise SystemExit(msg)
>E           SystemExit: Unable to access the X Display, is $DISPLAY set properly?
>
>/usr/lib64/python2.7/site-packages/wx-3.0-gtk2/wx/_core.py:8596: SystemExit
>--------------------------------------------- Captured stderr call ---------------------------------------------
>No protocol specified
>___________________________ TestDeprecatedWxObserver.test_events_fake_monitor[move] ____________________________
>
>self = <tests.test_observer_deprecated.TestDeprecatedWxObserver object at 0x7f4adfeefad0>, action = 'move'
>fake_monitor = <tests.plugins.fake_monitor.FakeMonitor object at 0x7f4adf3e4310>
>fake_monitor_device = Device(u'/sys/devices/platform')
>
>    @pytest.mark.parametrize('action', ACTIONS, ids=ACTIONS)
>    def test_events_fake_monitor(self, action, fake_monitor,
>                                 fake_monitor_device):
>>       self.prepare_test(fake_monitor)
>
>tests/test_observer_deprecated.py:94: 
>_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
>tests/test_observer_deprecated.py:83: in prepare_test
>    self.create_event_loop(self_stop_timeout=5000)
>tests/test_observer_deprecated.py:266: in create_event_loop
>    self.app = self.wx.App(False)
>_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
>
>self = <wx._core.App; proxy of <Swig Object of type 'wxPyApp *' at 0x55f470d93680> >, redirect = False
>filename = None, useBestVisual = False, clearSigInt = True
>
>    def __init__(self,
>                 redirect=False,
>                 filename=None,
>                 useBestVisual=False,
>                 clearSigInt=True):
>        """
>            Construct a ``wx.App`` object.
>    
>            :param redirect: Should ``sys.stdout`` and ``sys.stderr`` be
>                redirected?  Defaults to False. If ``filename`` is None
>                then output will be redirected to a window that pops up
>                as needed.  (You can control what kind of window is created
>                for the output by resetting the class variable
>                ``outputWindowClass`` to a class of your choosing.)
>    
>            :param filename: The name of a file to redirect output to, if
>                redirect is True.
>    
>            :param useBestVisual: Should the app try to use the best
>                available visual provided by the system (only relevant on
>                systems that have more than one visual.)  This parameter
>                must be used instead of calling `SetUseBestVisual` later
>                on because it must be set before the underlying GUI
>                toolkit is initialized.
>    
>            :param clearSigInt: Should SIGINT be cleared?  This allows the
>                app to terminate upon a Ctrl-C in the console like other
>                GUI apps will.
>    
>            :note: You should override OnInit to do applicaition
>                initialization to ensure that the system, toolkit and
>                wxWidgets are fully initialized.
>            """
>    
>        wx.PyApp.__init__(self)
>    
>        # make sure we can create a GUI
>        if not self.IsDisplayAvailable():
>    
>            if wx.Platform == "__WXMAC__":
>                msg = """This program needs access to the screen.
>    Please run with a Framework build of python, and only when you are
>    logged in on the main display of your Mac."""
>    
>            elif wx.Platform == "__WXGTK__":
>                msg ="Unable to access the X Display, is $DISPLAY set properly?"
>    
>            else:
>                msg = "Unable to create GUI"
>                # TODO: more description is needed for wxMSW...
>    
>>           raise SystemExit(msg)
>E           SystemExit: Unable to access the X Display, is $DISPLAY set properly?
>
>/usr/lib64/python2.7/site-packages/wx-3.0-gtk2/wx/_core.py:8596: SystemExit
>--------------------------------------------- Captured stderr call ---------------------------------------------
>No protocol specified
>=============================================== warnings summary ===============================================
>None
>  [pytest] section in setup.cfg files is deprecated, use [tool:pytest] instead.
>
>tests/test_device.py::TestAttributes::()::test_getitem
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <tests.utils.udev.DeviceDatabase object at 0x7f4af98c5490>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>
>tests/test_device.py::TestDevice::()::test_getitem
>  hypothesis_temporary_module_c1c33a3dcff510661568e4e44b25574a60bfc0f9:361: HypothesisDeprecationWarning: Test took 494.81ms to run. In future the default deadline setting will be 200ms, which will make this an error. You can set deadline to an explicit value of e.g. 500 to turn tests slower than this into an error, or you can set it to None to disable this check entirely.
>
>tests/test_discover.py::TestDiscovery::()::test_device_number
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <pyudev.core.Enumerator object at 0x7f4af9259550>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>
>tests/test_enumerate.py::TestEnumerator::()::test_match_subsystem_nomatch
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <pyudev.core.Enumerator object at 0x7f4af931d090>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>
>tests/test_enumerate.py::TestEnumerator::()::test_match_attribute_nomatch_unfulfillable
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5d430f0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5d432d0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5d43410>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5d433c0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5d435a0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5d43640>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5d43730>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5d437d0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5d43be0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5d43e10>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5d43f00>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5bd2050>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5bd20f0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5bd2190>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5bd2230>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5bd22d0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5bd2370>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5bd2410>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5bd2500>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5bd24b0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5bd25a0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5bd2690>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5bd2730>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5bd27d0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>
>tests/test_enumerate.py::TestEnumerator::()::test_match_attribute_int
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5bd21e0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5bd23c0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5bd2320>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5bd28c0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5bd2910>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5bd2a00>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5bd2af0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5bd2d20>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5bd2e10>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5bd2eb0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5bd2c80>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5bd2f50>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5bd2be0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5b60050>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5b600f0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5b601e0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5b60280>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5b60370>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5b60460>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5b60500>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5b605a0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5b60640>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5b60780>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5b60870>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5b60960>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5b60a00>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5b60af0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5b605f0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5b60be0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5b60910>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5b60e10>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5b60f50>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5b60eb0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5b100f0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5b10190>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5b10230>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5b10320>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5b10460>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5b10550>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5b60d20>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5b106e0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5b10780>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5b10820>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5b108c0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5b10960>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5b10a50>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5b10b40>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5b10be0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5b10c80>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5b10e60>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5b10d20>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5b10d70>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5b10eb0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5ad8050>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5ad80f0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5ad8190>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5ad8230>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5ad8280>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5ad8320>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5ad8460>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5ad8640>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5ad8500>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5ad85a0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5ad8370>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5ad8730>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5ad87d0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5ad8870>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5ad8910>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5ad8a50>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5ad8aa0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5ad89b0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5ad8c30>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5ad8d20>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5ad8dc0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5ad8e60>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5ad8f50>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5a4f050>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5a4f190>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5a4f280>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5a4f320>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5a4f3c0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5a4f460>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5a4f550>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5a4f5f0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5a4f730>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5a4f6e0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5a4f870>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5a4fa50>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5a4faf0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5a4fb90>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5a4f0f0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5a4fcd0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5a4fdc0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5a4fe60>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5a4ff00>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>
>tests/test_enumerate.py::TestEnumerator::()::test_match_attribute_bool
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5b602d0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5b604b0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5b60140>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5b60cd0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5b100a0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5b101e0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5b105a0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5b10730>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5b104b0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5b10870>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5b109b0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5b10c30>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5b10e10>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5b10dc0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5d54690>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5d54dc0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5d542d0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5d43140>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5ad81e0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5ad8780>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5ad8960>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5ad8af0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5ad8e10>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5ad8b90>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5ad86e0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5ad8eb0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5a4f0a0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5a4f370>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5a4f5a0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5a4faa0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5a4fbe0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5a4fd20>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5a4feb0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5a4ff50>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5bb5050>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5bb50f0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5bb5190>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5bb5230>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5bb52d0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5bb5370>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5bb53c0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5bb5460>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5bb55a0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5bb5690>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5bb5730>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5bb5820>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5bb58c0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5bb5960>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5bb5a50>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5bb5b40>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5bb5910>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5bb5cd0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5bb5c30>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5bb5dc0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5bb5e60>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5bb5f00>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5bb5fa0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5a340a0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5a34140>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5a341e0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5a34280>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5a34370>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5a34460>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5a34550>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5a343c0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5a34320>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5a345a0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5a34640>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5a34780>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5a34820>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5a34960>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5a34a50>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5a34af0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5a34b40>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5a34c30>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5a34cd0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5a34d70>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5a34e10>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5a34f00>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5989050>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5989140>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af59891e0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5ed0b40>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5ed0c80>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5a34fa0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5989230>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af59892d0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af59893c0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5989460>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5989370>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af59895a0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5989640>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af59896e0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5989500>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af59897d0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5989870>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5989910>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af59899b0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5989aa0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5989be0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5989b90>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5989dc0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5989e60>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5989fa0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5973050>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af59730f0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5973280>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5973140>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af59733c0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5973460>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5973500>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af59735f0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5973690>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5973780>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af59737d0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5973870>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5973910>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af59739b0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5973aa0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5973af0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5973b90>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5973c30>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5973d20>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5973dc0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5973eb0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5937050>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5937140>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af59371e0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5937320>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5989cd0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5973fa0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>
>tests/test_enumerate.py::TestEnumerator::()::test_match_attribute_nomatch_complete
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5973b40>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  hypothesis_temporary_module_6ce7b66708270a94045696ab5708eac7e5bcd143:253: HypothesisDeprecationWarning: Test took 231.17ms to run. In future the default deadline setting will be 200ms, which will make this an error. You can set deadline to an explicit value of e.g. 300 to turn tests slower than this into an error, or you can set it to None to disable this check entirely.
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5a34190>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5a344b0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5a345f0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5a34730>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5a34c80>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5a34e60>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5a34dc0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5bd2a50>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5bb51e0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5ad80a0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5989190>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af59895f0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5989960>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5989f50>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>
>tests/test_enumerate.py::TestEnumerator::()::test_match_attribute_nomatch
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5b10690>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  hypothesis_temporary_module_66761eabec6311ba69e3dd50ee5da0696ac414f8:224: HypothesisDeprecationWarning: Test took 224.34ms to run. In future the default deadline setting will be 200ms, which will make this an error. You can set deadline to an explicit value of e.g. 300 to turn tests slower than this into an error, or you can set it to None to disable this check entirely.
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5989820>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af59375a0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5937cd0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5937820>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5876370>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af58765f0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5876a00>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5876a50>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5876be0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5876fa0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5937fa0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af57a1320>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>
>tests/test_enumerate.py::TestEnumerator::()::test_match_attribute_match
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5b609b0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af58765a0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5876af0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af57a1aa0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af57a1be0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5876230>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af57a1d70>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af58254b0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5825640>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5825f50>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5652500>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5652550>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af56525f0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af57a1f00>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5825870>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5652be0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5652e10>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5652f00>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>
>tests/test_enumerate.py::TestEnumerator::()::test_match_property_string
>  hypothesis_temporary_module_8ded927f73d9eab7d1e6331aa53dc4faea77bb76:159: HypothesisDeprecationWarning: Test took 207.00ms to run. In future the default deadline setting will be 200ms, which will make this an error. You can set deadline to an explicit value of e.g. 300 to turn tests slower than this into an error, or you can set it to None to disable this check entirely.
>
>tests/test_enumerate.py::TestEnumerator::()::test_match_tag
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <pyudev.device._device.Tags object at 0x7f4af5a84990>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <pyudev.device._device.Tags object at 0x7f4af5bc9790>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  hypothesis_temporary_module_a96ba4da354f29292c65febf74a90bd1ab0f3d00:317: HypothesisDeprecationWarning: Test took 227.82ms to run. In future the default deadline setting will be 200ms, which will make this an error. You can set deadline to an explicit value of e.g. 300 to turn tests slower than this into an error, or you can set it to None to disable this check entirely.
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <pyudev.device._device.Tags object at 0x7f4af5bc9c10>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <pyudev.device._device.Tags object at 0x7f4af5a66290>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <pyudev.device._device.Tags object at 0x7f4af5bc9e50>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <pyudev.device._device.Tags object at 0x7f4af5adab10>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>
>tests/test_enumerate.py::TestEnumerator::()::test_match_attribute_string
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5583a00>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5583be0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af55838c0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5583870>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5583f00>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5583e60>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af54e0050>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af54e00f0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af54e01e0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5583cd0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af54e0280>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af54e0410>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af54e0550>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af54e0500>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af54e0370>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af54e0690>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af54e06e0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af54e0820>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af54e08c0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af54e0910>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af54e0960>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af54e07d0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af54e0b40>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af54e0b90>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af54e0be0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af54e0d70>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af54e0e10>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>
>tests/test_enumerate.py::TestEnumeratorMatchCombinations::()::test_combined_property_matches
>  hypothesis_temporary_module_9665b4d63047daf1ca08e12d47aebad8e8d5f957:363: HypothesisDeprecationWarning: Test took 390.46ms to run. In future the default deadline setting will be 200ms, which will make this an error. You can set deadline to an explicit value of e.g. 400 to turn tests slower than this into an error, or you can set it to None to disable this check entirely.
>
>tests/test_enumerate.py::TestEnumeratorMatchCombinations::()::test_combined_attribute_matches
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af54e0af0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af54e0460>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af54e0d20>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af54e0f00>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af54e0fa0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  hypothesis_temporary_module_3eb2ad5a799315264a5ac26e5fcffe6a9c57013d:393: HypothesisDeprecationWarning: Test took 241.52ms to run. In future the default deadline setting will be 200ms, which will make this an error. You can set deadline to an explicit value of e.g. 300 to turn tests slower than this into an error, or you can set it to None to disable this check entirely.
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af55f5190>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af55f5280>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af55f5410>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af55f54b0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af55f5550>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af55f55f0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af55f5690>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af55f53c0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af55f5780>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af55f58c0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af55f59b0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af55f5aa0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af55f5c80>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af55f5d70>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af55f5e10>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af55f5f00>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af55f5fa0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5353140>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5353230>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5353410>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5353280>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>
>tests/test_enumerate.py::TestEnumeratorMatchCombinations::()::test_combined_matches_of_different_types
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af55f5050>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af55f5640>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af55f5500>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af55f5910>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af55f5e60>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af53530a0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af53531e0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5353460>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  hypothesis_temporary_module_9728d3e610389c4248e4bd996b4580c46a1ed212:423: HypothesisDeprecationWarning: Test took 207.49ms to run. In future the default deadline setting will be 200ms, which will make this an error. You can set deadline to an explicit value of e.g. 300 to turn tests slower than this into an error, or you can set it to None to disable this check entirely.
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af53535f0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5353820>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af53538c0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5353aa0>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5353d70>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>  /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from <generator object available_attributes at 0x7f4af5353d20>, not a sequence.  Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised.  To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation.  Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler.
>    values = check_sample(elements)
>
>tests/test_observer.py::TestGlibObserver::()::test_monitor
>  /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0/tests/test_observer.py:179: Warning: Source ID 6 was not found when attempting to remove it
>    self.glib.source_remove(source)
>
>tests/test_observer.py::TestGlibObserver::()::test_events_fake_monitor
>  /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0/tests/test_observer.py:179: Warning: Source ID 11 was not found when attempting to remove it
>    self.glib.source_remove(source)
>  /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0/tests/test_observer.py:179: Warning: Source ID 9 was not found when attempting to remove it
>    self.glib.source_remove(source)
>
>tests/test_observer_deprecated.py::TestDeprecatedGlibObserver::()::test_monitor
>  /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0/tests/test_observer_deprecated.py:205: Warning: Source ID 13 was not found when attempting to remove it
>    self.glib.source_remove(source)
>
>tests/test_observer_deprecated.py::TestDeprecatedGlibObserver::()::test_events_fake_monitor[add]
>  /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0/tests/test_observer_deprecated.py:205: Warning: Source ID 18 was not found when attempting to remove it
>    self.glib.source_remove(source)
>  /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0/tests/test_observer_deprecated.py:205: Warning: Source ID 16 was not found when attempting to remove it
>    self.glib.source_remove(source)
>
>tests/test_observer_deprecated.py::TestDeprecatedGlibObserver::()::test_events_fake_monitor[remove]
>  /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0/tests/test_observer_deprecated.py:205: Warning: Source ID 22 was not found when attempting to remove it
>    self.glib.source_remove(source)
>  /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0/tests/test_observer_deprecated.py:205: Warning: Source ID 20 was not found when attempting to remove it
>    self.glib.source_remove(source)
>
>tests/test_observer_deprecated.py::TestDeprecatedGlibObserver::()::test_events_fake_monitor[change]
>  /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0/tests/test_observer_deprecated.py:205: Warning: Source ID 26 was not found when attempting to remove it
>    self.glib.source_remove(source)
>  /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0/tests/test_observer_deprecated.py:205: Warning: Source ID 24 was not found when attempting to remove it
>    self.glib.source_remove(source)
>
>tests/test_observer_deprecated.py::TestDeprecatedGlibObserver::()::test_events_fake_monitor[move]
>  /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0/tests/test_observer_deprecated.py:205: Warning: Source ID 30 was not found when attempting to remove it
>    self.glib.source_remove(source)
>  /var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0/tests/test_observer_deprecated.py:205: Warning: Source ID 28 was not found when attempting to remove it
>    self.glib.source_remove(source)
>
>-- Docs: http://doc.pytest.org/en/latest/warnings.html
>======================= 7 failed, 148 passed, 37 skipped, 393 warnings in 146.61 seconds =======================
> * ERROR: dev-python/pyudev-0.21.0::gentoo failed (test phase):
> *   Tests fail with python2.7
> * 
> * Call stack:
> *     ebuild.sh, line  124:  Called src_test
> *   environment, line 2672:  Called distutils-r1_src_test
> *   environment, line  913:  Called _distutils-r1_run_foreach_impl 'python_test'
> *   environment, line  363:  Called python_foreach_impl 'distutils-r1_run_phase' 'python_test'
> *   environment, line 2209:  Called multibuild_foreach_variant '_python_multibuild_wrapper' 'distutils-r1_run_phase' 'python_test'
> *   environment, line 1567:  Called _multibuild_run '_python_multibuild_wrapper' 'distutils-r1_run_phase' 'python_test'
> *   environment, line 1565:  Called _python_multibuild_wrapper 'distutils-r1_run_phase' 'python_test'
> *   environment, line  587:  Called distutils-r1_run_phase 'python_test'
> *   environment, line  844:  Called python_test
> *   environment, line 2574:  Called die
> * The specific snippet of code:
> *       py.test -v || die "Tests fail with ${EPYTHON}"
> * 
> * If you need support, post the output of `emerge --info '=dev-python/pyudev-0.21.0::gentoo'`,
> * the complete build log and the output of `emerge -pqv '=dev-python/pyudev-0.21.0::gentoo'`.
> * The complete build log is located at '/var/log/portage/build/dev-python/pyudev-0.21.0:20180424-150811.log'.
> * For convenience, a symlink to the build log is located at '/var/tmp/portage/dev-python/pyudev-0.21.0/temp/build.log'.
> * The ebuild environment file is located at '/var/tmp/portage/dev-python/pyudev-0.21.0/temp/environment'.
> * Working directory: '/var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0'
> * S: '/var/tmp/portage/dev-python/pyudev-0.21.0/work/pyudev-0.21.0'

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Attachments on bug 653994: 528426