def test_configuration_error(self) -> None: """Test removing a locked package based on direct dependencies.""" # Default values should error, no adjustment to values. with pytest.raises(SieveError): VersionConstraintSieve().pre_run() unit = VersionConstraintSieve() unit.update_configuration({ "package_name": None, "version_specifier": None }) with pytest.raises(SieveError): unit.pre_run() unit = VersionConstraintSieve() unit.update_configuration({ "package_name": "tensorflow", "version_specifier": None, }) with pytest.raises(SieveError): unit.pre_run() unit = VersionConstraintSieve() unit.update_configuration({ "package_name": None, "version_specifier": ">2.0", }) with pytest.raises(SieveError): unit.pre_run()
def test_default_configuration(self) -> None: """Test obtaining default configuration.""" unit = VersionConstraintSieve() assert unit.configuration == { "package_name": None, "version_specifier": None }
def test_run_no_filter(self) -> None: """"Test not filtering a package based on version specifier.""" package_version = PackageVersion( name="tensorboard", version="==2.1.0", index=Source("https://pypi.org/simple"), develop=False, ) unit = VersionConstraintSieve() unit.update_configuration({ "package_name": "tensorboard", "version_specifier": ">2.0", }) unit.pre_run() assert list(unit.run([package_version])) == [package_version]
def test_super_pre_run(self, context: Context) -> None: """Make sure the pre-run method of the base is called.""" unit = VersionConstraintSieve() unit.update_configuration({ "package_name": "tensorflow", "version_specifier": "==2.3", }) assert unit.unit_run is False unit.unit_run = True with unit.assigned_context(context): unit.pre_run() assert ( unit.unit_run is False ), "Unit flag unit_run not reset, is super().pre_run() called in sources when providing pre_run method!?"