4iu>SSKrSSKrSSKJr \RS5r\RS5r\RS5r\RS5r\R"SS/S 9S 5r \RS 5r \RS 5r \RS 5r \RS5r \RS5r\RS5r\R"SS/S 9S5r\R"SSSS//SQS9S5r\R"SS/S 9S5r\R"SS/S 9S5r\R"SS/S 9S5r\R"SS/S 9S 5r\R"SS/S 9S!5r\RS"5rg)#N)Seriesc[e)z3A fixture providing the ExtensionDtype to validate.NotImplementedErrora/var/www/html/dynamic-report/venv/lib/python3.13/site-packages/pandas/tests/extension/conftest.pydtyper   rc[e)z| Length-10 array for this type. * data[0] and data[1] should both be non missing * data[0] and data[1] should not be equal rrrr datar   rcUR(d)URS:Xd[R"US35 [e)z| Length-10 array in which all the elements are two. Call pytest.skip in your fixture if the dtype does not support divmod. mz is not a numeric dtype) _is_numerickindpytestskiprr s r data_for_twosrs4   s!2  ug456 rc[e)zLength-2 array with [NA, Valid]rrrr data_missingr(r rr r)paramscLURS:XaU$URS:XaU$g)z5Parametrized fixture giving 'data' and 'data_missing'r rNparam)requestr rs r all_datar.s,}} . ( )rc^U4SjnU$)z Generate many datasets. Parameters ---------- data : fixture implementing `data` Returns ------- Callable[[int], Generator]: A callable that takes a `count` argument and returns a generator yielding `count` datasets. c3:># [U5HnTv M g7fN)range)count_r s r gendata_repeated..genGsuAJsr)r r%s` r data_repeatedr'7s  Jrc[e)z Length-3 array with a known sort order. This should be three items [B, C, A] with A < B < C For boolean dtypes (for which there are only 2 values available), set B=C=True rrrr data_for_sortingr)Ns  rc[e)zk Length-3 array with a known sort order. This should be three items [B, NA, A] with A < B and NA missing. rrrr data_missing_for_sortingr+\rrc"[R$)z Binary 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_rrr na_cmpr/gs <<rcUR$)z The scalar missing value for this type. Default dtype.na_value. TODO: can be removed in 3.x (see https://github.com/pandas-dev/pandas/pull/54930) )na_valuers r r1r1ts >>rc[e)z Data for factorization, grouping, and unique tests. Expected to be like [B, B, NA, NA, A, A, B, C] Where A < B < C and NA is missing. If a dtype has _is_boolean = True, i.e. only 2 unique non-NA entries, then set C=B. rrrr data_for_groupingr3~s  rTFcUR$)z#Whether to box the data in a Seriesrrs r box_in_seriesr6s ==rcgNrxs r r<s!rc S/[U5-$r8)lenr:s r r<r<s1#A,rc2[S/[U5-5$r8)rr>r:s r r<r<s&!s1v&rcU$r!rr:s r r<r<s!r)scalarlistseriesobject)ridscUR$)z$ Functions to test groupby.apply(). rr5s r groupby_apply_oprGs ==rcUR$)zM Boolean fixture to support Series and Series.to_frame() comparison testing. rr5s r as_framerI ==rcUR$)zD Boolean fixture to support arr and Series(arr) comparison testing. rr5s r as_seriesrLrJrcUR$)zX Boolean fixture to support comparison testing of ExtensionDtype array and numpy array. rr5s r use_numpyrN ==rffillbfillcUR$)z` Parametrized fixture giving method parameters 'ffill' and 'bfill' for Series. testing. rr5s r fillna_methodrSrOrcUR$)zJ Boolean fixture to support ExtensionDtype _from_sequence method testing. rr5s r as_arrayrUrJrc4[R[5$)z A scalar that *cannot* be held by this ExtensionArray. The default should work for most subclasses, but is not guaranteed. If the array can hold any item (i.e. object dtype), then use pytest.skip. )rD__new__)r s r invalid_scalarrXs >>& !!r)r-rpandasrfixturer r rrrr'r)r+r/r1r3r6rGrIrLrNrSrUrXrrr r[s2     /01,      e}%& &   /e}%&e}%&e}%&)*+e}%&""r