o ۭjF@sddlZddlZddlZddlZddlZddlZddlm Z ddl m Z ddl mZmZmZejjddZejddZejdd Zejd d Zejd d ZejddZejddZejddZGddde jZddZddZddZ dS)N)base) JSONArray JSONDtype make_data UnhashablereasoncCstSN)rr r b/var/www/html/CropPilot/venv/lib/python3.10/site-packages/pandas/tests/extension/json/test_json.pydtyper cCsDt}t|dt|dkrt}t|dt|dkst|S)z*Length-100 PeriodArray for semantics test.r)rlenr)datar r r rs rcCstiddigS)zLength 2 array with [NA, Valid]a rr r r r data_missing,rcCstddiddidddgS)Nbrcrrrr r r r data_for_sorting2srcCstddiiddigS)Nrrrrrr r r r data_missing_for_sorting7srcCstjSr )operatoreqr r r r na_cmp<r r c Cs4tddiddiiiddddddddiddigS)Nrrrrrrrr r r r data_for_groupingAsr!cseZdZejjddfddZejjddfddZejjddfd d Zejjddfd d Z ejjd dfddZ ejjddfddZ ejjddfddZ ejjddfddZ ejjddfddZejddgdgdfdgdgdfdgdgd fdgd!gd"fd#gdgd$fd#gdgd$fd#gdgdfd#gd!gdfgfd%d&Zefd'd(Zefd)d*Zefd+d,Zejd-d.d/gfd0d1Zejd-d.d/gfd2d3Zejjd4dfd5d6Zejjd7d/ed8fd9d:Zejjd;dfddfd?d@Zejjd>dfdAdBZejdCfdDdEZfdFdGZejjdHdfdIdJZ efdKdLZ!efdMdNZ"efdOdPZ#efdQdRZ$fdSdTZ%fdUdVZ&ejjdWdfdXdYZ'ejjdWdfdZd[Z(ejjdWdfd\d]Z)ejjdWdfd^d_Z*ejjd`e+,gdae-j,gdadbdce-j,d.d.d.e-j.e-j.gdbdcggdddefdfdgZ/fdhdiZ0ejjdjdfdkdlZ1ejjdmgdne-j,gdndodce+,gdnggdpdefdqdrZ2ejjdsdejjdtdudvdwe-j.gd/fej3dudvdwe-j.gd.ejjdxddye-j,dudvdwe-j.gdodcd/fe-j,dudvdwe-j.gdodcd/fggdzdefd{d|Z4ejjd}dfd~dZ5fddZ6ejjddfddZ7ejjdjdejdddgfddZ8ejjddfddZ9ejjddfddZ:ejjddfddZ;ejjddfddZejjddejdddgfddZ?Z@S) TestJSONArrayz:comparison method not implemented for JSONArray (GH-37867)rct|dSr )super test_containsselfr __class__r r r%RszTestJSONArray.test_containsz¬ implemented constructor from dtypecr#r )r$test_from_dtyper&r(r r r*YrzTestJSONArray.test_from_dtypezRecursionError, GH-33900c >t}ztdt||Wt|dSt|wNd)sysgetrecursionlimitsetrecursionlimitr$*test_series_constructor_no_data_with_indexr'r na_value rec_limitr(r r r1^  z8TestJSONArray.test_series_constructor_no_data_with_indexc r+r,)r.r/r0r$,test_series_constructor_scalar_na_with_indexr2r(r r r6ir5z:TestJSONArray.test_series_constructor_scalar_na_with_indexzcollection as scalar, GH-33901c r+r,)r.r/r0r$)test_series_constructor_scalar_with_index)r'rr r4r(r r r7tr5z7TestJSONArray.test_series_constructor_scalar_with_indexzDifferent definitions of NActdS)z The test does .astype(object).stack(future_stack=True). If we happen to have any missing values in `data`, then we'll end up with different rows since we consider `{}` NA, but `.astype(object)` doesn't. N)r$ test_stackr'r(r r r9szTestJSONArray.test_stackz dict for NAcst||Sr )r$ test_unstack)r'rindexr(r r r;szTestJSONArray.test_unstackzSetting a dict as a scalarcr8z;We treat dictionaries as a mapping in fillna, not a scalar.N)r$test_fillna_seriesr:r(r r r>z TestJSONArray.test_fillna_seriescr8r=)r$test_fillna_framer:r(r r r@r?zTestJSONArray.test_fillna_framez'limit_area, input_ilocs, expected_ilocsoutside)rrrrr)rrrrr)rrrrr)rrrrr)rrrrr)rrrrrinside)rrrrrcsJd}tjt|dt||||WddS1swYdS)Nz'JSONArray does not implement limit_areamatch)pytestraisesNotImplementedErrorr$test_ffill_limit_area)r'r limit_area input_ilocsexpected_ilocsmsgr(r r rHs "z#TestJSONArray.test_ffill_limit_areact||dSr )r$test_value_counts)r'all_datadropnar(r r rNzTestJSONArray.test_value_countscr#r )r$ test_value_counts_with_normalizer&r(r r rRz.TestJSONArray.test_value_counts_with_normalizecstdSr )r$test_sort_values_framer:r(r r rTr?z$TestJSONArray.test_sort_values_frame ascendingTFct|||dSr )r$test_sort_values)r'rrU sort_by_keyr(r r rWzTestJSONArray.test_sort_valuescrVr )r$test_sort_values_missing)r'rrUrXr(r r rZsz&TestJSONArray.test_sort_values_missingz#combine for JSONArray not supportedcr#r )r$test_combine_le)r' data_repeatedr(r r r[rSzTestJSONArray.test_combine_lezGcombine for JSONArray not supported - may pass depending on random data)rstrictrFcr#r )r$test_combine_firstr&r(r r r^sz TestJSONArray.test_combine_firstzbroadcasting errorcrMr )r$test_where_series)r'rr3r(r r r_zTestJSONArray.test_where_serieszCan't compare dicts.cr#r )r$test_searchsorted)r'rr(r r rarSzTestJSONArray.test_searchsortedcrVr )r$ test_equals)r'rr3 as_seriesr(r r rbrYzTestJSONArray.test_equalsz-fill-value is interpreted as a dict of valuescr#r )r$test_fillna_copy_frame)r'rr(r r rdrSz$TestJSONArray.test_fillna_copy_framecs,|rtjjdd}||t|dS)NzFails with CoWr)rEmarkxfail applymarkerr$&test_equals_same_data_different_object)r'rusing_copy_on_writerequestrer(r r rhs z4TestJSONArray.test_equals_same_data_different_objectz$failing on np.array(self, dtype=str)cr8)zThis currently fails in NumPy on np.array(self, dtype=str) with *** ValueError: setting an array element with a sequence N)r$test_astype_strr:r(r r rkzTestJSONArray.test_astype_strcr8)a This currently fails in Series.name.setter, since the name must be hashable, but the value is a dictionary. I think this is what we want, i.e. `.name` should be the original values, and not the values for factorization. N)r$ test_groupby_extension_transformr:r(r r rmsz.TestJSONArray.test_groupby_extension_transformcr8)z This fails in Index._do_unique_check with > hash(val) E TypeError: unhashable type: 'UserDict' with I suspect that once we support Index[ExtensionArray], we'll be able to dispatch unique. N)r$test_groupby_extension_applyr:r(r r rns z*TestJSONArray.test_groupby_extension_applycr8z This fails when we get to tm.assert_series_equal when left.index contains dictionaries, which are not hashable. N)r$test_groupby_extension_aggr:r(r r rprlz(TestJSONArray.test_groupby_extension_aggcr8ro)r$test_groupby_extension_no_sortr:r(r r rqrlz,TestJSONArray.test_groupby_extension_no_sortcs:t|ddkrtjjdd}||t||dS)Nrrzraises in coercing to Seriesr)rrErerfrgr$test_arith_frame_with_scalar)r'rall_arithmetic_operatorsrjrer(r r rrs z*TestJSONArray.test_arith_frame_with_scalarcs4|jdvrtjjdd}||t||dS)N)rnez"Comparison methods not implementedr)__name__rErerfrgr$test_compare_array)r'r comparison_oprjrer(r r rv%s  z TestJSONArray.test_compare_arrayz.ValueError: Must have equal len keys and valuecr#r )r$test_setitem_loc_scalar_mixedr&r(r r rx+rSz+TestJSONArray.test_setitem_loc_scalar_mixedcr#r )r$,test_setitem_loc_scalar_multiple_homogoneousr&r(r r ry/rSz:TestJSONArray.test_setitem_loc_scalar_multiple_homogoneouscr#r )r$test_setitem_iloc_scalar_mixedr&r(r r rz3rSz,TestJSONArray.test_setitem_iloc_scalar_mixedcr#r )r$-test_setitem_iloc_scalar_multiple_homogoneousr&r(r r r{7rSz;TestJSONArray.test_setitem_iloc_scalar_multiple_homogoneousmask)TTTFFboolean)r ) numpy-arrayz boolean-arrayzboolean-array-na)idscsV|rtjjdd}||nt|tjs!tjjdd}||t|||dS)Nr@ parametrizerH unhashablerNrRrTrWrZr[AssertionErrorr^r_rarbskiprdrhrkrmrnrprqrrrvrxryrzr{rarraypdNArrrrparamrrrrrrrrrrrr __classcell__r r r(r r"Qs                           $          r"cOsz|jjdkr.|j|jksJtjt|jt|j|jd}tjt|jt|j|jd}t j ||g|Ri|dS)Njson)r<r) r rrSeriesrvaluesastypeobjectr<tmassert_series_equal)leftrightargskwargsr r r custom_assert_series_equals rc Os|dd}tj|j|j|dd|dd|dd|d d|d d |jd kj}|D]}t||||g|Ri|q/|j|d }|j|d }tj||g|Ri|dS)Nobj DataFramecheck_column_typeequiv check_namesT check_exactFcheck_categoricalz.columns)exactrrrrr)columns) getrassert_index_equalrdtypesr<rdropassert_frame_equal)rrrrobj_typejsonscolr r r custom_assert_frame_equals      "  rcCsttdditdditddig}t|}t||t||t|gd}d}t j t |d  t||Wdn1sLwYt j t |d t||WddS1smwYdS) Nrrrrrr)rrrzSeries are differentrC) r collectionsUserDictrrrrto_frametakerErFr)rrrrLr r r test_custom_assertss"      "r)!rrr.numpyrrEpandasrpandas._testing_testingrpandas.tests.extensionr!pandas.tests.extension.json.arrayrrrrerfrfixturer rrrrr r!ExtensionTestsr"rrrr r r r s<         _