.iunddlZddlZddlmZejdZejdZejdZejdZejddg d Z ejd Z ejd Z ejd Z ejdZ ejdZejdZejddg dZejddddggddZejddg dZejddg dZejddg dZejddg d Zejddg d!Zejd"Zy)#N)Seriesct)z3A fixture providing the ExtensionDtype to validate.NotImplementedError]/var/www/app/trading-bot/venv/lib/python3.12/site-packages/pandas/tests/extension/conftest.pydtyper   rct)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   rct|js'|jdk(stj|dt)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 rct)zLength-2 array with [NA, Valid]rrrr data_missingr(r rr r)paramscH|jdk(r|S|jdk(r|Sy)z5Parametrized fixture giving 'data' and 'data_missing'r rNparam)requestr rs r all_datar.s,}} . ( )rcfd}|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. c36Kt|D]}ywN)range)count_r s r genzdata_repeated..genGsu AJ sr)r r%s` r data_repeatedr&7s  Jrct)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  rct)z{ 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"tjS)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 <<rc|jS)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 r0r0ts >>rct)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_groupingr2~s  rTFc|jS)z#Whether to box the data in a Seriesrrs r box_in_seriesr5s ==rcyNrxs r r;src dgt|zSr7)lenr9s r r;r;s1#A,rc2tdgt|zSr7)rr=r9s r r;r;s&!s1v&rc|Sr!rr9s r r;r;s!r)scalarlistseriesobject)ridsc|jS)z, Functions to test groupby.apply(). rr4s r groupby_apply_oprFs ==rc|jS)zU Boolean fixture to support Series and Series.to_frame() comparison testing. rr4s r as_framerH ==rc|jS)zL Boolean fixture to support arr and Series(arr) comparison testing. rr4s r as_seriesrKrIrc|jS)zd Boolean fixture to support comparison testing of ExtensionDtype array and numpy array. rr4s r use_numpyrM ==rffillbfillc|jS)zl Parametrized fixture giving method parameters 'ffill' and 'bfill' for Series. testing. rr4s r fillna_methodrRrNrc|jS)zR Boolean fixture to support ExtensionDtype _from_sequence method testing. rr4s r as_arrayrTrIrc4tjtS)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. )rC__new__)r s r invalid_scalarrWs >>& !!r)r,rpandasrfixturer r rrrr&r(r*r.r0r2r5rFrHrKrMrRrTrWrrr rZsB     /01,      e}%& &   /e}%&e}%&e}%&)*+e}%&""r