B x\ @sddlZddlZejddZejddZejddZejddgdd d Zejd d Zejd dZejddZ ejddZ ejddZ ejddZ ejddgdddZ dS)NcCstdS)z3A fixture providing the ExtensionDtype to validate.N)NotImplementedErrorrr>lib/python3.7/site-packages/pandas/tests/extension/conftest.pydtypesrcCstdS)zLength-100 array for this type. * data[0] and data[1] should both be non missing * data[0] and data[1] should not gbe equal N)rrrrrdata srcCstdS)zLength-2 array with [NA, Valid]N)rrrrr data_missingsr)ZparamscCs |jdkr|S|jdkr|SdS)z5Parametrized fixture giving 'data' and 'data_missing'rrN)param)requestrrrrrall_datas  r csfdd}|S)a  Generate many datasets. Parameters ---------- data : fixture implementing `data` Returns ------- Callable[[int], Generator]: A callable that takes a `count` argument and returns a generator yielding `count` datasets. c3sxt|D] }Vq WdS)N)range)count_)rrrgen4szdata_repeated..genr)rrr)rr data_repeated%s rcCstdS)ziLength-3 array with a known sort order. This should be three items [B, C, A] with A < B < C N)rrrrrdata_for_sorting:srcCstdS)zvLength-3 array with a known sort order. This should be three items [B, NA, A] with A < B and NA missing. N)rrrrrdata_missing_for_sortingDsrcCstjS)zBinary operator for comparing NA values. Should return a function of two arguments that returns True if both arguments are (scalar) NA for your type. By default, uses ``operator.is_`` )operatoris_rrrrna_cmpNs rcCsdS)z6The scalar missing value for this type. Default 'None'Nrrrrrna_valueZsrcCstdS)zData for factorization, grouping, and unique tests. Expected to be like [B, B, NA, NA, A, A, B, C] Where A < B < C and NA is missing N)rrrrrdata_for_grouping`srTFcCs|jS)z#Whether to box the data in a Series)r)r rrr box_in_seriesksr)rZpytestZfixturerrrr rrrrrrrrrrrs