* 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 = fake_monitor = 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 = >, 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 = fake_monitor = 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 = >, 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 = fake_monitor = 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 = >, 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 = , action = 'add' fake_monitor = 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 = >, 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 = , action = 'remove' fake_monitor = 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 = >, 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 = , action = 'change' fake_monitor = 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 = >, 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 = , action = 'move' fake_monitor = 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 = >, 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 , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values 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 , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values 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 , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values 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 , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values 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 , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values 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 , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values 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 , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values 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 , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values 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 , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values 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 , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values 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 , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values 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 , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values 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 , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values 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 , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values 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 , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values 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 , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values 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 , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values 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 , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values such as math.nan require careful handling - and note that when simplifying an example, Hypothesis treats earlier values as simpler. values = check_sample(elements) /usr/lib64/python2.7/site-packages/hypothesis/strategies.py:483: HypothesisDeprecationWarning: Cannot sample from , not a sequence. Hypothesis goes to some length to ensure that sampling an element from a collection (with `sampled_from` or `choices`) is replayable and can be minimised. To replay a saved example, the sampled values must have the same iteration order on every run - ruling out sets, dicts, etc due to hash randomisation. Most cases can simply use `sorted(values)`, but mixed types or special values 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'