U f/eF@sdZddlmZddlmZmZmZmZmZddlm Z ddl Z ddl Z ddl m Z mZddlZddlmZddlZddlZddlmZmZddlmmZdd lmZmZddlZ dd lm!Z!m"Z"m#Z#m$Z$m%Z%m&Z&ddl'm(Z)dd l*m+Z+dd l,m-Z-m.Z.ej/0d Z1ddZ2ddZ3ddZ4ej5j6ddej7j8fdej59dd:D]8Z;ee;Z?e@e?ejAe?eBddeCdqNd:D]DZ;ee;Z?e@e?ejAe?eBddeCejBddd d!qd":D]DZ;ee;Z?e@e?ejAe?eBd#d$eCejBddd d%qejDd&d'd(d)ZEejDd&d'd*d+ZFejDddd,d-gd.d/d0d1d2ZGeGZHejDd&d3dgd4d5d6ZIejDd&d3dgd4d7d8ZJejDd9d:d3gd4d;d<ZKejDd=d>d?d@gd4dAdBZLejDd=d>d?d@gd4dCdDZMejDddEdFdGdHgd4dIdJZNejDdEdFdGdHgd4dKdLZOejDd&d3gd4dMdNZPejDdOdPd=d>gd4dQdRZQejDdSdTgd4dUdVZRejDe)jSdWd/d0dXdYZTeTZUejDdejVe jWgd4dZd[ZXeXZYejDe!e$gd4d\d]ZZejDe-e$gd,d^gd0d_d`Z[e[Z\ejDe-e$e j]gd,d^dagd0dbdcZ^ejDdddeZ_ejDdfdgZ`ejDdhdiZaejDdjdkZbdldmZcdndoZde)edpe)fdpe)gdpe)jgdpdqdre)hdpe)idpe)jdpe)kdpe)ldpe)mdpe)ndse)odpe)pdpe-ge.qerdtdudvgddwdxgedece-dddddwdwgdyZsejDestd4dzd,ZueuZvejDd{d|esDd4d}d~ZwewZxejDdd|esDd4ddZyejDddZzejDddZ{ejDddZ|ejDddZ}ddZ~ddesDZejDddZejDddZejejejejejejejejgZddeDZejDetd4ddZeseeZejDetd4ddZejDddZejDddZejDddZejDddZejDddZejDddZejDe"dddedd>fe"dddedd>fe#ddddfe#ddddfe&dddreddrfe%dddfgd4ddZddddddddddddddgZejDed4ddĄZejDe je+je je+je je+je je+je je+je je+je je+je je je je je je je je+je je+je je+jgd4ddƄZejDe je+je je+je je+je je+je je+je je+je je+jgd4ddȄZddddddddddg ZejDed4ddԄZddgZejDed4dd؄ZeeZejDed4ddڄZejDddddddgd4ddZejDddddgd4ddZejDddddddgd4ddZejDddZejDddZejDddZddddddddddee edededejeeddeedddtdgZdd|eDZeeeƒejDeed0ddZeeeddejDeddeddd0ddZeZejDddeeejgd4ddZeZejDe)jd4d d ZejDd ej̐d ej͐d dddgd4ddZejDdej̐d ej͐d dddgd4ddZeZejDe)jd4ddZejDe)jd4ddZejDdd ej̐d ej͐d dddgd4ddZejDe)jd4ddZejDe)jd4dd ZejDe)jd4d!d"ZejDe)jd4d#d$ZejDe)je)jd4d%d&ZejDe)jd4d'd(ZejDe)jd4d)d*ZejDe)jd4d+d,ZejDe)jd4d-d.ZejDe)jd4d/d0ZejDe)je)jd4d1d2ZejDe)je)jd4d3d4ZejDe)jd4d5d6ZejDe)jd4d7d8ZejDe)jd4d9d:Zd;dd?ejVd@gfdAejVejVejVgfdAgfdBdjDd4dfdgZejDddhd/gd4didjZeDdkdlZejDdmdndogd4dpdqZejDe)je)je)jgd4drdsZejDe)je)jgd4dtduZejDe)je)jgd4dvdwZejDe)je)jgd4dxdyZejDdzd{ZdS(|a This file is very long and growing, but it was decided to not split it yet, as it's still manageable (2020-03-17, ~1.1k LoC). See gh-31989 Instead of splitting it was decided to define sections here: - Configuration / Settings - Autouse fixtures - Common arguments - Missing values & co. - Classes - Indices - Series' - DataFrames - Operators & Operations - Data sets/files - Time zones - Dtypes - Misc )abc)datedatetimetime timedeltatimezone)DecimalN)tzlocaltzutc) strategies) FixedOffsetutc)DatetimeTZDtype IntervalDtype) DataFrameIntervalPeriodSeries Timedelta Timestamp)ops)Index MultiIndexz3ignore:Promotion of numbers and bools:FutureWarningcCsd|jdddd|jdddd|jdddd|jd dd d|jd dd d|jd ddddS)N --skip-slow store_truezskip slow tests)actionhelp--skip-networkzskip network tests --skip-dbz skip db tests--run-high-memoryzrun high memory tests --only-slowzrun only slow tests--strict-data-filesz0Fail if a test is skipped for missing data file.)Z addoption)parserr#3/tmp/pip-unpacked-wheel-tiezk1ph/pandas/conftest.pypytest_addoptionPsr%cCsd|jkr |jdr tdd|jkr@|jdr@tdd|jkr`|jdr`tdd |jkr|jd rtd d |jkr|jd stddS)NZslowrzskipping due to --skip-slowr zskipping due to --only-slownetworkrzskipping due to --skip-networkdbrzskipping due to --skip-dbZ high_memoryrz=skipping high memory test since --run-high-memory was not set)keywordsconfig getoptionpytestskip)itemr#r#r$pytest_runtest_setup_s    r.cCs0|D]&}d|jkr |tjj|tqdS)Nz/frame/)ZnodeidZ add_markerr+markZ arraymanager suppress_npdev_promotion_warning)itemsr-r#r#r$pytest_collection_modifyitemsrs r2cii)deadlineZsuppress_health_checkz)MonthBegin MonthEnd BMonthBegin BMonthEndic)n normalizez%YearBegin YearEnd BYearBegin BYearEnd )Z min_valueZ max_value)r6r7monthz1QuarterBegin QuarterEnd BQuarterBegin BQuarterEndi)r6r7Z startingMonthT)ZautousecCstdddS)z< Configure settings for all tests and test modules. Zchained_assignmentraiseN)pdZ set_optionr#r#r#r$configure_testssr@cCst|d<t|d<dS)z: Make `np` and `pd` names available for doctests. npr?N)rAr?)Zdoctest_namespacer#r#r$ add_importssrBindexcolumnscCsdt|S)Nzaxis=reprxr#r#r$rI)paramsidscCs|jS)z@ Fixture for returning the axis numbers of a DataFrame. paramrequestr#r#r$axissrQF)rKcCs|jS)a Pass in the observed keyword to groupby for [True, False] This indicates whether categoricals should return values for values which are not in the grouper [False / None], or only values which appear in the grouper [True]. [None] is supported for future compatibility if we decide to change the default (and would need to warn if this parameter is not passed). rMrOr#r#r$observeds rRcCs|jS)z6 Boolean 'ordered' parameter for Categorical. rMrOr#r#r$orderedsrSfirstlastcCs|jS)z[ Valid values for the 'keep' parameter used in .duplicated or .drop_duplicates rMrOr#r#r$keepsrVleftrightZbothZneithercCs|jS)z< Fixture for trying all interval closed parameters. rMrOr#r#r$closedsrYcCs|jS)zS Secondary closed fixture to allow parametrizing over all pairs of closed. rMrOr#r#r$ other_closedsrZgzipbz2zipxzcCs|jS)zK Fixture for trying common compression types in compression tests. rMrOr#r#r$ compressionsr_cCs|jS)zk Fixture for trying common compression types in compression tests excluding uncompressed case. rMrOr#r#r$compression_onlysr`cCs|jS)z, Fixture that an array is writable. rMrOr#r#r$writable srainneroutercCs|jS)z: Fixture for trying all types of join operations. rMrOr#r#r$ join_typesrdnlargest nsmallestcCs|jS)z1 Fixture for trying all nselect methods. rMrOr#r#r$nselect_methodsrgcCs t|jSN)type__name__rGr#r#r$rI%rJcCs|jS)z/ Fixture for each null type in pandas. rMrOr#r#r$ nulls_fixture%srkcCs|jS)zL Fixture for each null type in pandas, each null type exactly once. rMrOr#r#r$unique_nulls_fixture0srlcCs|jS)z; Fixture to parametrize over DataFrame and Series. rMrOr#r#r$frame_or_series@srmseriescCs|jS)z Fixture to parametrize over Index and Series, made necessary by a mypy bug, giving an error: List item 0 has incompatible type "Type[Series]"; expected "Type[PandasObject]" See GH#29725 rMrOr#r#r$index_or_seriesIs roarraycCs|jS)zG Fixture to parametrize over Index, Series, and ExtensionArray rMrOr#r#r$index_or_series_or_array\srqcCsGdddt}|S)z, Fixture for a dictionary subclass. c@seZdZddZdS)z"dict_subclass..TestSubDictc_stj|f||dSrh)dict__init__)selfargskwargsr#r#r$rsksz+dict_subclass..TestSubDict.__init__N)rj __module__ __qualname__rsr#r#r#r$ TestSubDictjsry)rr)ryr#r#r$ dict_subclassdsrzcCsGdddtj}|S)z8 Fixture for a non-mapping dictionary subclass. c@s,eZdZddZddZddZddZd S) z5non_dict_mapping_subclass..TestNonDictMappingcSs ||_dSrh)_data)rtZunderlying_dictr#r#r$rsxsz>non_dict_mapping_subclass..TestNonDictMapping.__init__cSs |j|Srh)r{ __getitem__)rtkeyr#r#r$r|{szAnon_dict_mapping_subclass..TestNonDictMapping.__getitem__cSs |jSrh)r{__iter__rtr#r#r$r~~sz>non_dict_mapping_subclass..TestNonDictMapping.__iter__cSs |jSrh)r{__len__rr#r#r$rsz=non_dict_mapping_subclass..TestNonDictMapping.__len__N)rjrwrxrsr|r~rr#r#r#r$TestNonDictMappingwsr)rMapping)rr#r#r$non_dict_mapping_subclassqs rcCs`td}|ddddddg}|jdd|jjD|_|jjdd d gd d |S) z DataFrame with 3 level MultiIndex (year, month, day) covering first 100 business days from 2000-01-01 with random data dcSs|jSrh)yearrGr#r#r$rIrJzAmultiindex_year_month_day_dataframe_random_data..cSs|jSrh)r<rGr#r#r$rIrJcSs|jSrh)dayrGr#r#r$rIrJcSsg|]}|dqS)i8)astype).0Zlevr#r#r$ szCmultiindex_year_month_day_dataframe_random_data..rr<rT)Zinplace)tmZmakeTimeDataFramegroupbysumrCZ set_levelslevelsZ set_names)ZtdfZymdr#r#r$/multiindex_year_month_day_dataframe_random_datas   rc Csvtddddgdddggdddd d d d d d d g dd d dd d d dd d g gd d gd}ttjdd |tdddgdddS)z2DataFrame with 2 level MultiIndex with random datafoobarbazquxonetwothreerr:rTsecond)rcodesnames ABCexpname)rCrD)rrrArandomrandnrrCr#r#r$ multiindex_dataframe_random_datas. rcCshtddddg}tddg}tdddd d d g}tddddddg}d d g}t||g||g|d dS)zJ MultiIndex used to test the general functionality of this object rrrrrrrr:rrrTrF)rrrZverify_integrity)rrArpr)Z major_axisZ minor_axisZ major_codesZ minor_codesZ index_namesr#r#r$_create_multiindexs rcCs.tjddgddgtjddddgd d d gd S) zB MultiIndex with a level that is a tzaware DatetimeIndex. r:rab20130101r US/Eastern)Zperiodstzrrr)r)rZ from_productr?Z date_ranger#r#r#r$_create_mi_with_dt64tz_levelsrrz US/Pacific)rrrrrrr)unicodestringrz datetime-tzperiodrintuintrangefloatboolZ categoricalintervalemptytuplesmi-with-dt64tz-levelmultirepeatscCst|jS)z Fixture for many "simple" kinds of indices. These indices are unlikely to cover corner cases, e.g. - no names - no NaTs/NaNs - no values near implementation bounds - ... ) indices_dictrNcopyrOr#r#r$rCs cCsg|]}tt|ts|qSr# isinstancerrrr}r#r#r$rsrcCs|j}t|S)z8 index fixture, but excluding MultiIndex cases. )rNrr)rPr}r#r#r$ index_flats rcCs&g|]}|dkrtt|ts|qS))rrrrrrrr#r#r$rscCst|jjdd}|j}|jdkrd|}d|ddd|d<d|ddd|d<t|Sd|d<d|d<t||SdS) z Fixture for indices with missing values. Integer-dtype and empty cases are excluded because they cannot hold missing values. MultiIndex is excluded because isna() is not defined for MultiIndex. Tdeep)rrrrhrr:N)rrNrvaluestolistr from_tuplesri)rPindvalsr#r#r$index_with_missings  rcCstggtjdS)N)rCdtype)rrAfloat64r#r#r#r$ empty_series#srcCst}d|_|S)zC Fixture for Series of floats with Index of unique strings rn)rZmakeStringSeriesrsr#r#r$ string_series(srcCst}d|_|S)zI Fixture for Series of dtype object with Index of unique strings Zobjects)rZmakeObjectSeriesrrr#r#r$ object_series2srcCst}d|_|S)z9 Fixture for Series of floats with DatetimeIndex ts)rZmakeTimeSeriesrrr#r#r$datetime_series<srcCs"t|}tj|}t||ddS)zHelper for the _series dictr)rCr)lenrArrr)rCsizedatar#r#r$_create_seriesFs rcCs"i|]\}}d|dt|qS)z series-with-z-indexr)rZindex_idrCr#r#r$ Ms rcCst|S)zE Fixture for tests on series with changing types of indices. rrr#r#r$series_with_simple_indexSsrc Cs`ddddddddgddddddddgg}t|}t|}tjd}t||d}tj|d <|S) z: Fixture with a Series with a 2-level MultiIndex. rrrrrrrr)r]rrrArrrNaN)ZarraysrrCrZserr#r#r$series_with_multilevel_index[s    rcCs(i|] }|jdtjdd|qS)z-seriesrr)rjrZmakeFloatSeriesr)rrr#r#r$rvs cCst|jS)z: Fixture for Series with low precision data types )_narrow_seriesrNrrOr#r#r$ narrow_series|srcCst|jjddS)z| Fixture for tests on indexes, series and series with a narrow dtype copy to avoid mutation, e.g. setting .name Tr)_index_or_series_objsrNrrOr#r#r$index_or_series_objsrcCstSrh)rr#r#r#r$ empty_framesrcCsttdS)a6 Fixture for DataFrame of ints with index of unique strings Columns are ['A', 'B', 'C', 'D'] A B C D vpBeWjM651 1 0 1 0 5JyxmrP1En -1 0 0 0 qEDaoD49U2 -1 1 0 0 m66TkTfsFe 0 0 0 0 EHPaNzEUFm -1 0 -1 0 fpRJCevQhi 2 0 0 0 OlQvnmfi3Q 0 0 -2 0 ... .. .. .. .. uB1FPlz4uP 0 0 0 1 EcSe6yNzCU 0 0 -1 0 L50VudaiI8 -1 1 -2 0 y3bpw4nwIp 0 -1 0 0 H0RdLLwrCT 1 1 0 0 rY82K0vMwm 0 0 0 0 1OPIUjnkjk 2 0 0 0 [30 rows x 4 columns] int64)rr getSeriesDatarr#r#r#r$ int_framesrcCs ttS)a Fixture for DataFrame of floats with DatetimeIndex Columns are ['A', 'B', 'C', 'D'] A B C D 2000-01-03 -1.122153 0.468535 0.122226 1.693711 2000-01-04 0.189378 0.486100 0.007864 -1.216052 2000-01-05 0.041401 -0.835752 -0.035279 -0.414357 2000-01-06 0.430050 0.894352 0.090719 0.036939 2000-01-07 -0.620982 -0.668211 -0.706153 1.466335 2000-01-10 -0.752633 0.328434 -0.815325 0.699674 2000-01-11 -2.236969 0.615737 -0.829076 -1.196106 ... ... ... ... ... 2000-02-03 1.642618 -0.579288 0.046005 1.385249 2000-02-04 -0.544873 -1.160962 -0.284071 -1.418351 2000-02-07 -2.656149 -0.601387 1.410148 0.444150 2000-02-08 -1.201881 -1.289040 0.772992 -1.445300 2000-02-09 1.377373 0.398619 1.008453 -0.928207 2000-02-10 0.473194 -0.636677 0.984058 0.511519 2000-02-11 -0.965556 0.408313 -1.312844 -0.381948 [30 rows x 4 columns] )rrZgetTimeSeriesDatar#r#r#r$datetime_framesrcCs ttS)a Fixture for DataFrame of floats with index of unique strings Columns are ['A', 'B', 'C', 'D']. A B C D P7GACiRnxd -0.465578 -0.361863 0.886172 -0.053465 qZKh6afn8n -0.466693 -0.373773 0.266873 1.673901 tkp0r6Qble 0.148691 -0.059051 0.174817 1.598433 wP70WOCtv8 0.133045 -0.581994 -0.992240 0.261651 M2AeYQMnCz -1.207959 -0.185775 0.588206 0.563938 QEPzyGDYDo -0.381843 -0.758281 0.502575 -0.565053 r78Jwns6dn -0.653707 0.883127 0.682199 0.206159 ... ... ... ... ... IHEGx9NO0T -0.277360 0.113021 -1.018314 0.196316 lPMj8K27FA -1.313667 -0.604776 -1.305618 -0.863999 qa66YMWQa5 1.110525 0.475310 -0.747865 0.032121 yOa0ATsmcE -0.431457 0.067094 0.096567 -0.264962 65znX3uRNG 1.528446 0.160416 -0.109635 -0.032987 eCOBvKqf3e 0.235281 1.622222 0.781255 0.392871 xSucinXxuV -1.263557 0.252799 -0.552247 0.400426 [30 rows x 4 columns] )rrrr#r#r#r$ float_framesrc Cs>tdddtjdgdddtjdgdddd tdd S) z Fixture for DataFrame of float/int/string columns with RangeIndex Columns are ['a', 'b', 'c', 'float32', 'int32']. ?rrrfloat32rr:int32)rrcrrr)rrArpZaranger#r#r#r$mixed_type_framesrc Cstdddtdddtdddtdddtdddtdddtdddtdddtdddtdddg }ttjt||dS)zF Fixture for Series with a DatetimeIndex that has duplicates. ir:rrr9r)rrrArrr)datesr#r#r$(rand_series_with_duplicate_datetimeindexs           r)rWrXrg?g?rz2012-01M)freqz period[M]z 2012-02-01Dz period[D]z 2011-01-01r)secondsztimedelta64[ns]cCs|jSrhrMrOr#r#r$ea_scalar_and_dtypesr__add____radd____sub____rsub____mul____rmul__ __floordiv__ __rfloordiv__ __truediv__ __rtruediv____pow____rpow____mod____rmod__cCs|jS)zD Fixture for dunder names for common arithmetic operations. rMrOr#r#r$all_arithmetic_operators@srcCs|jS)zU Fixture for operator and roperator arithmetic, comparison, and logical ops. rMrOr#r#r$all_binary_operatorsHs"rcCs|jS)z Fixture for operator and roperator arithmetic functions. Notes ----- This includes divmod and rdivmod, whereas all_arithmetic_operators does not. rMrOr#r#r$all_arithmetic_functionsmsrrmaxminZmeanprodZstdvarZmedianZkurtZskewcCs|jS)z. Fixture for numeric reduction names. rMrOr#r#r$all_numeric_reductionssr allanycCs|jS)z. Fixture for boolean reduction names. rMrOr#r#r$all_boolean_reductionssrcCs|jS)z> Fixture for all (boolean + numeric) reduction names. rMrOr#r#r$all_reductionssr__eq____ne____le____lt____ge____gt__cCs|jS)zu Fixture for dunder names for common compare operations * >= * > * == * != * < * <= rMrOr#r#r$all_compare_operatorss rcCs|jS)zm Fixture for dunder names for compare operations except == and != * >= * > * < * <= rMrOr#r#r$compare_operators_no_eq_nes r__and____rand____or____ror____xor____rxor__cCs|jS)zY Fixture for dunder names for common logical operations * | * & * ^ rMrOr#r#r$all_logical_operatorss rcCs |dS)zO Returns the configuration for the test setting `--strict-data-files`. r!)r*)Z pytestconfigr#r#r$strict_data_filessrcs(tjtjtdfdd}|S)a= Get the path to a data file. Parameters ---------- path : str Path to the file, relative to ``pandas/tests/`` Returns ------- path including ``pandas/tests``. Raises ------ ValueError If the path doesn't exist and the --strict-data-files option is set. testscsJtjjf|}tj|sFr4td|dntd|d|S)NzCould not find file z and --strict-data-files is set.zCould not find .)ospathjoinexists ValueErrorr+r,)rur#Z BASE_PATHrr#r$decos  zdatapath..deco)r"r#r$dirname__file__)rr(r#r'r$datapaths r+cCst|ddddS)z* The iris dataset as a DataFrame. iorcsvziris.csv)r?Zread_csv)r+r#r#r$irissr.UTCz Asia/Tokyozdateutil/US/Pacificzdateutil/Asia/Singaporez+01:15z-02:15z UTC+01:15z UTC-02:15i,i)hoursrrcCsg|] }t|qSr#rE)rir#r#r$r.scCs|jS)zD Fixture for trying timezones including default (None): {0} rMrOr#r#r$tz_naive_fixture1sr2cCs|jS)z4 Fixture for trying explicit timezones: {0} rMrOr#r#r$tz_aware_fixture:sr3r z dateutil/UTCcCs|jS)zQ Fixture to provide variants of UTC timezone strings and tzinfo objects. rMrOr#r#r$ utc_fixtureGsr4cCs|jS)zR Parametrized fixture for string dtypes. * str * 'str' * 'U' rMrOr#r#r$ string_dtypeUs r5zstring[python]zstring[pyarrow]Zpyarrowz1.0.0) min_version)ZmarkscCs|jS)za Parametrized fixture for string dtypes. * 'string[python]' * 'string[pyarrow]' rMrOr#r#r$nullable_string_dtypeasr7pythoncCs|jS)zb Parametrized fixture for pd.options.mode.string_storage. * 'python' * 'pyarrow' rMrOr#r#r$string_storagess r9cCs|jS)zK Parametrized fixture for bytes dtypes. * bytes * 'bytes' rMrOr#r#r$ bytes_dtypesr:cCs|jS)zN Parametrized fixture for object dtypes. * object * 'object' rMrOr#r#r$ object_dtypesr;objectcCs|jS)zo Parametrized fixture for string dtypes. * 'object' * 'string[python]' * 'string[pyarrow]' rMrOr#r#r$any_string_dtypesr=cCs|jS)z\ Parametrized fixture for datetime64 dtypes. * 'datetime64[ns]' * 'M8[ns]' rMrOr#r#r$datetime64_dtypesr>cCs|jS)z^ Parametrized fixture for timedelta64 dtypes. * 'timedelta64[ns]' * 'm8[ns]' rMrOr#r#r$timedelta64_dtypesr?cCs|jS)z^ Parameterized fixture for float dtypes. * float * 'float32' * 'float64' rMrOr#r#r$ float_dtypes r@cCs|jS)zR Parameterized fixture for float dtypes. * 'Float32' * 'Float64' rMrOr#r#r$float_ea_dtypesrAcCs|jS)z~ Parameterized fixture for float dtypes. * float * 'float32' * 'float64' * 'Float32' * 'Float64' rMrOr#r#r$ any_float_allowed_nullable_dtypes rBcCs|jS)zg Parameterized fixture for complex dtypes. * complex * 'complex64' * 'complex128' rMrOr#r#r$ complex_dtypes rCcCs|jS)z| Parameterized fixture for signed integer dtypes. * int * 'int8' * 'int16' * 'int32' * 'int64' rMrOr#r#r$ sint_dtypes rDcCs|jS)zx Parameterized fixture for unsigned integer dtypes. * 'uint8' * 'uint16' * 'uint32' * 'uint64' rMrOr#r#r$ uint_dtypes rEcCs|jS)z Parameterized fixture for any integer dtype. * int * 'int8' * 'uint8' * 'int16' * 'uint16' * 'int32' * 'uint32' * 'int64' * 'uint64' rMrOr#r#r$ any_int_dtypesrFcCs|jS)z Parameterized fixture for any nullable integer dtype. * 'UInt8' * 'Int8' * 'UInt16' * 'Int16' * 'UInt32' * 'Int32' * 'UInt64' * 'Int64' rMrOr#r#r$any_nullable_int_dtype$srGcCs|jS)a. Parameterized fixture for any nullable integer dtype. * int * 'int8' * 'uint8' * 'int16' * 'uint16' * 'int32' * 'uint32' * 'int64' * 'uint64' * 'UInt8' * 'Int8' * 'UInt16' * 'Int16' * 'UInt32' * 'Int32' * 'UInt64' * 'Int64' rMrOr#r#r$any_int_or_nullable_int_dtype5srHcCs|jS)z Parameterized fixture for any nullable integer dtype and any float ea dtypes. * 'UInt8' * 'Int8' * 'UInt16' * 'Int16' * 'UInt32' * 'Int32' * 'UInt64' * 'Int64' * 'Float32' * 'Float64' rMrOr#r#r$any_nullable_numeric_dtypeOsrIcCs|jS)z~ Parameterized fixture for any signed nullable integer dtype. * 'Int8' * 'Int16' * 'Int32' * 'Int64' rMrOr#r#r$any_signed_nullable_int_dtypecs rJcCs|jS)z Parameterized fixture for any (purely) real numeric dtype. * int * 'int8' * 'uint8' * 'int16' * 'uint16' * 'int32' * 'uint32' * 'int64' * 'uint64' * float * 'float32' * 'float64' rMrOr#r#r$any_real_dtypepsrKcCs|jS)a Parameterized fixture for all numpy dtypes. * bool * 'bool' * int * 'int8' * 'uint8' * 'int16' * 'uint16' * 'int32' * 'uint32' * 'int64' * 'uint64' * float * 'float32' * 'float64' * complex * 'complex64' * 'complex128' * str * 'str' * 'U' * bytes * 'bytes' * 'datetime64[ns]' * 'M8[ns]' * 'timedelta64[ns]' * 'm8[ns]' * object * 'object' rMrOr#r#r$any_numpy_dtypes"rLrrrbytesacrz mixed-integermixedg@Zfloatingrintegerzmixed-integer-floatdecimalboolean datetime64z 2013-01-01z 2018-01-01rrZ20180101riirrrrcCs |j\}}tj|td}||fS)a Fixture for all inferred dtypes from _libs.lib.infer_dtype The covered (inferred) types are: * 'string' * 'empty' * 'bytes' * 'mixed' * 'mixed-integer' * 'mixed-integer-float' * 'floating' * 'integer' * 'decimal' * 'boolean' * 'datetime64' * 'datetime' * 'date' * 'timedelta' * 'time' * 'period' * 'interval' Returns ------- inferred_dtype : str The string for the inferred dtype from _libs.lib.infer_dtype values : np.ndarray An array of object dtype that will be inferred to have `inferred_dtype` Examples -------- >>> import pandas._libs.lib as lib >>> >>> def test_something(any_skipna_inferred_dtype): ... inferred_dtype, values = any_skipna_inferred_dtype ... # will pass ... assert lib.infer_dtype(values, skipna=True) == inferred_dtype r)rNrArpr<)rPZinferred_dtyperr#r#r$any_skipna_inferred_dtypes) rUcCs>tjdddddlm}ddlm}|}d|j_||dS) zj Get an instance of IPython.InteractiveShell. Will raise a skip if IPython is not installed. ZIPythonz6.0.0)Z minversionr)InteractiveShell)Configz:memory:)r))r+ importorskipZIPython.core.interactiveshellrVZtraitlets.configrWZHistoryManagerZ hist_file)rVrWrr#r#r$ips   rYZbsrZcooZcscZcsrZdiaZdokZlilcCsddlm}t||jdS)z- Yields scipy sparse matrix classes. r)sparseZ_matrix)ZscipyrZgetattrrN)rPrZr#r#r$spmatrixs r\cCs.g|]&}tttj|tjjrttj|qSr#) issubclassr[r?offsetsZTick)ror#r#r$rscCs|jS)zN Fixture for Tick based datetime offsets available for a time series. rMrOr#r#r$ tick_classess r`cCs|Srhr#rGr#r#r$rI&rJcCs|jS)zk Simple fixture for testing keys in sorting methods. Tests None (no key) and the identity key. rMrOr#r#r$ sort_by_key&sraccsxtdddlm}ddlm}ddlm}Gddd|}|d|d d |V|ddd|j d<|j dS) Nfsspecr)register_implementation)MemoryFileSystem) _registrycs&eZdZdZdgZfddZZS)z fsspectest..TestMemoryFStestmemNcs$|dd|jd<tjf|dS)Ntestr)poprgsuperrs)rtrv __class__r#r$rs:sz)fsspectest..TestMemoryFS.__init__)rjrwrxprotocolrgrs __classcell__r#r#rjr$ TestMemoryFS6srnrfT)clobber) r+rXrbrcZfsspec.implementations.memoryrdZfsspec.registryrerhrgstoreclear)rcrdregistryrnr#r#r$ fsspectest/s      rs)rNN)ZEgonZVenkmanN)NCC1701DrtrtcCs|jS)zP A 3-tuple of names, the first two for operands, the last for a result. rMrOr#r#r$rEs rcCs|jS)zI Parametrize over __setitem__, loc.__setitem__, iloc.__setitem__ rMrOr#r#r$ indexer_sliSsrucCs|jS)z8 Parametrize over __setitem__, iloc.__setitem__ rMrOr#r#r$ indexer_si[srvcCs|jS)z7 Parametrize over __setitem__, loc.__setitem__ rMrOr#r#r$ indexer_slcsrwcCs|jS)z: Parametrize over at.__setitem__, loc.__setitem__ rMrOr#r#r$ indexer_alksrxcCstjjjdkS)z> Fixture to check if the array manager is being used. rp)r?optionsmodeZ data_managerrOr#r#r$using_array_managerssr{(__doc__ collectionsrrrrrrrRroperatorr"Z dateutil.tzr r Z hypothesisr stZnumpyrAr+Zpytzr r Zpandas.util._test_decoratorsutilZ_test_decoratorstdZpandas.core.dtypes.dtypesrrZpandasr?rrrrrrZpandas._testingZ_testingrZ pandas.corerZpandas.core.indexes.apirrr/filterwarningsr0r%r.r2settingsZregister_profileZ HealthCheckZtoo_slowZ load_profilesplitrr[Ztseriesr^clsZregister_type_strategyZbuildsZintegersZbooleansZfixturer@rBrQZ axis_framerRrSrVrYrZr_r`rardrgZ NULL_OBJECTSrkZnulls_fixture2nanZNaTrlZunique_nulls_fixture2rmroZindex_or_series2rprqrzrrrrrZmakeUnicodeIndexZmakeStringIndexZ makeDateIndexZmakePeriodIndexZmakeTimedeltaIndexZ makeIntIndexZ makeUIntIndexZmakeRangeIndexZmakeFloatIndexZ makeBoolIndexZmakeCategoricalIndexZmakeIntervalIndexrr]rkeysrCZindex_fixture2rZ index_flat2rrrrrrr1Z_seriesrrZfloat16rZint8Zint16rZuint8Zuint16Zuint32Z_narrow_dtypesrrrrrrrrrrrZ_all_arithmetic_operatorsraddZraddsubZrsubmulZrmultruedivZrtruedivfloordivZ rfloordivmodZrmodpowZrpoweqneltlegtgeand_Zrand_xorZrxoror_Zror_rrZ_all_numeric_reductionsr Z_all_boolean_reductionsrZ_all_reductionsrrrrrr+r.Z TIMEZONESZ TIMEZONE_IDSZparametrize_fixture_docstrr2r3Ztz_aware_fixture2r4Z utc_fixture2Z STRING_DTYPESr5rNZ skip_if_nor7r9Zstring_storage2Z BYTES_DTYPESr:Z OBJECT_DTYPESr;r=ZDATETIME64_DTYPESr>ZTIMEDELTA64_DTYPESr?Z FLOAT_DTYPESr@ZFLOAT_EA_DTYPESrArBZCOMPLEX_DTYPESrCZSIGNED_INT_DTYPESrDZUNSIGNED_INT_DTYPESrEZALL_INT_DTYPESrFZALL_EA_INT_DTYPESrGrHrIZSIGNED_EA_INT_DTYPESrJZALL_REAL_DTYPESrKZALL_NUMPY_DTYPESrLZNArTZ_any_skipna_inferred_dtyperL_rUrYr\__all__r`rarsrsetitemlocZilocrurvrwatrxr{r#r#r#r$s                                                                               "                          & $  2&