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These indices are unlikely to cover corner cases, e.g. - no names - no NaTs/NaNs - no values near implementation bounds - ... )� indices_dictrE �copy)rF r r r r= � s c C s g | ]}t t| t�s|�qS r )� isinstancer� r )r} rr r r r r~ � s r~ c C s | j }t| �� S )z8 index fixture, but excluding MultiIndex cases. )rE r� r� )rF rr r r r � index_flat� s r� c C s& g | ] }|d krt t| t�s|�qS ))r� r� r� r� r� )r� r� r )r} rr r r r r~ s c C s� t | j jdd�}|j}| jdkrd|�� }d|d dd� |d< d|d dd� |d< t�|�S d|d< d|d< t|�|�S dS ) 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. T)�deep)r� zmi-with-dt64tz-levelr� )Nr r4 N���)r� rE r� �values�tolistr � from_tuplesr^ )rF �ind�valsr r r �index_with_missing� s r� c C s t g g tjd�S )N)r= �dtype)r r; �float64r r r r � empty_series# s r� c C s t �� } d| _| S )zC Fixture for Series of floats with Index of unique strings rc )r ZmakeStringSeriesr� )�sr r r � string_series( s r� c C s t �� } d| _| S )zI Fixture for Series of dtype object with Index of unique strings �objects)r ZmakeObjectSeriesr� )r� r r r � object_series2 s r� c C s t �� } d| _| S )z9 Fixture for Series of floats with DatetimeIndex �ts)r ZmakeTimeSeriesr� )r� r r r �datetime_series< s r� c C s" t | �}tj�|�}t|| dd�S )zHelper for the _series dictr� )r= r� )�lenr; r� r� r )r= �size�datar r r �_create_seriesF s r� c C s" i | ]\}}t |�d |� d��qS )z series-with-z-index)r� )r} Zindex_idr= r r r � <dictcomp>M s r� c C s t | �S )zE Fixture for tests on series with changing types of indices. )r� )r= r r r �series_with_simple_indexS s r� c C s` ddddddddgddddddddgg} t | � }t�|�}tj�d�}t||d�}tj|d < |S ) z: Fixture with a Series with a 2-level MultiIndex. r� r� r� r� r� r� � )r= r� )rS r r� r; r� r� r �NaN)Zarraysr� r= r� Zserr r r � series_with_multilevel_index[ s r� c C s( i | ] }t jd d��|�|j� d��qS )r� )r� z-series)r ZmakeFloatSeriesr| r_ )r} r� r r r r� v s c C s t | j �� S )z: Fixture for Series with low precision data types )�_narrow_seriesrE r� )rF r r r � narrow_series| s r� c C s t | j jdd�S )z| Fixture for tests on indexes, series and series with a narrow dtype copy to avoid mutation, e.g. setting .name T)r� )�_index_or_series_objsrE r� )rF r r r �index_or_series_obj� s r� c C s t � S )N)r r r r r � empty_frame� s r� c C s t t�� ��d�S )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)r r � getSeriesDatar| r r r r � int_frame� s r� c C s t t�� �S )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] )r r ZgetTimeSeriesDatar r r r �datetime_frame� s r� c C s t t�� �S )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] )r r r� r r r r � float_frame� s r� c C s> t dddtjdgd dd�tjdgd dd�d �t�d�d �S ) z� Fixture for DataFrame of float/int/string columns with RangeIndex Columns are ['a', 'b', 'c', 'float32', 'int32']. g �?r� r� r� �float32)r� r4 �int32)r� r� �cr� r� )r= )r r; re Zaranger r r r �mixed_type_frame� s r� c C s� t ddd�t ddd�t ddd�t ddd�t ddd�t ddd�t ddd�t ddd�t ddd�t ddd�g } ttj�t| ��| d�S )zF Fixture for Series with a DatetimeIndex that has duplicates. i� r4 r� r� � r3 )r= )r r r; r� r� r� )�datesr r r �(rand_series_with_duplicate_datetimeindex s r� )rM rN r� g�������?g �?r� z2012-01�M)�freqz period[M]z 2012-02-01�Dz period[D]z 2011-01-01z US/Eastern)�secondsztimedelta64[ns]c C s | j S )N)rE )rF r r r �ea_scalar_and_dtype s r� �__add__�__radd__�__sub__�__rsub__�__mul__�__rmul__� __floordiv__� __rfloordiv__� __truediv__� __rtruediv__�__pow__�__rpow__�__mod__�__rmod__c C s | j S )zD Fixture for dunder names for common arithmetic operations. )rE )rF r r r �all_arithmetic_operators@ s r� c C s | j S )zU Fixture for operator and roperator arithmetic, comparison, and logical ops. )rE )rF r r r �all_binary_operatorsH s "r� c C s | j S )z� Fixture for operator and roperator arithmetic functions. Notes ----- This includes divmod and rdivmod, whereas all_arithmetic_operators does not. )rE )rF r r r �all_arithmetic_functionsm s r� r� �max�minZmean�prodZstd�varZmedianZkurtZskewc C s | j S )z. Fixture for numeric reduction names. )rE )rF r r r �all_numeric_reductions� s r� �all�anyc C s | j S )z. Fixture for boolean reduction names. )rE )rF r r r �all_boolean_reductions� s r� c C s | j S )z> Fixture for all (boolean + numeric) reduction names. )rE )rF r r r �all_reductions� s r� �__eq__�__ne__�__le__�__lt__�__ge__�__gt__c C s | j S )zu Fixture for dunder names for common compare operations * >= * > * == * != * < * <= )rE )rF r r r �all_compare_operators� s r c C s | j S )zm Fixture for dunder names for compare operations except == and != * >= * > * < * <= )rE )rF r r r �compare_operators_no_eq_ne� s r �__and__�__rand__�__or__�__ror__�__xor__�__rxor__c C s | j S )zY Fixture for dunder names for common logical operations * | * & * ^ )rE )rF r r r �all_logical_operators� s r c C s | � d�S )zO Returns the configuration for the test setting `--strict-data-files`. z--strict-data-files)r$ )Z pytestconfigr r r �strict_data_files� s r c s( t j�t j�t�d�� � �fdd�}|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. �testsc sJ t jj� f| �� }t j�|�sF�r4td|� d���nt�d|� d�� |S )NzCould not find file z and --strict-data-files is set.zCould not find �.)�os�path�join�exists� ValueErrorr% r& )rj r )� BASE_PATHr r r �deco s zdatapath.<locals>.deco)r r r �dirname�__file__)r r r )r r r �datapath� s r c C s t �| dddd��S )z* The iris dataset as a DataFrame. �ior� �csvziris.csv)r9 Zread_csv)r r r r �iris s r �UTCz Asia/Tokyozdateutil/US/Pacificzdateutil/Asia/Singaporez+01:15z-02:15z UTC+01:15z UTC-02:15i, i���)�hoursr� )r� c C s g | ] }t |��qS r )r? )r} �ir r r r~ . s c C s | j S )zD Fixture for trying timezones including default (None): {0} )rE )rF r r r �tz_naive_fixture1 s r c C s | j S )z4 Fixture for trying explicit timezones: {0} )rE )rF r r r �tz_aware_fixture: s r r z dateutil/UTCc C s | j S )zQ Fixture to provide variants of UTC timezone strings and tzinfo objects. )rE )rF r r r � utc_fixtureG s r c C s | j S )zR Parametrized fixture for string dtypes. * str * 'str' * 'U' )rE )rF r r r � string_dtypeU s r zstring[python]zstring[pyarrow]Zpyarrowz1.0.0)� min_version)Zmarksc C s | j S )za Parametrized fixture for string dtypes. * 'string[python]' * 'string[pyarrow]' )rE )rF r r r �nullable_string_dtypea s r! �pythonc C s | j S )zb Parametrized fixture for pd.options.mode.string_storage. * 'python' * 'pyarrow' )rE )rF r r r �string_storages s r# c C s | j S )zK Parametrized fixture for bytes dtypes. * bytes * 'bytes' )rE )rF r r r � bytes_dtype� s r$ c C s | j S )zN Parametrized fixture for object dtypes. * object * 'object' )rE )rF r r r � object_dtype� s r% �objectc C s | j S )zo Parametrized fixture for string dtypes. * 'object' * 'string[python]' * 'string[pyarrow]' )rE )rF r r r �any_string_dtype� s r' c C s | j S )z\ Parametrized fixture for datetime64 dtypes. * 'datetime64[ns]' * 'M8[ns]' )rE )rF r r r �datetime64_dtype� s r( c C s | j S )z^ Parametrized fixture for timedelta64 dtypes. * 'timedelta64[ns]' * 'm8[ns]' )rE )rF r r r �timedelta64_dtype� s r) c C s | j S )z^ Parameterized fixture for float dtypes. * float * 'float32' * 'float64' )rE )rF r r r � float_dtype� s r* c C s | j S )zR Parameterized fixture for float dtypes. * 'Float32' * 'Float64' )rE )rF r r r �float_ea_dtype� s r+ c C s | j S )z~ Parameterized fixture for float dtypes. * float * 'float32' * 'float64' * 'Float32' * 'Float64' )rE )rF r r r � any_float_allowed_nullable_dtype� s r, c C s | j S )zg Parameterized fixture for complex dtypes. * complex * 'complex64' * 'complex128' )rE )rF r r r � complex_dtype� s r- c C s | j S )z| Parameterized fixture for signed integer dtypes. * int * 'int8' * 'int16' * 'int32' * 'int64' )rE )rF r r r � sint_dtype� s r. c C s | j S )zx Parameterized fixture for unsigned integer dtypes. * 'uint8' * 'uint16' * 'uint32' * 'uint64' )rE )rF r r r � uint_dtype s r/ c C s | j S )z� Parameterized fixture for any integer dtype. * int * 'int8' * 'uint8' * 'int16' * 'uint16' * 'int32' * 'uint32' * 'int64' * 'uint64' )rE )rF r r r � any_int_dtype s r0 c C s | j S )z� Parameterized fixture for any nullable integer dtype. * 'UInt8' * 'Int8' * 'UInt16' * 'Int16' * 'UInt32' * 'Int32' * 'UInt64' * 'Int64' )rE )rF r r r �any_nullable_int_dtype$ s r1 c C s | j S )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' )rE )rF r r r � any_int_or_nullable_int_dtype5 s r2 c C s | j S )z� Parameterized fixture for any nullable integer dtype and any float ea dtypes. * 'UInt8' * 'Int8' * 'UInt16' * 'Int16' * 'UInt32' * 'Int32' * 'UInt64' * 'Int64' * 'Float32' * 'Float64' )rE )rF r r r �any_nullable_numeric_dtypeO s r3 c C s | j S )z~ Parameterized fixture for any signed nullable integer dtype. * 'Int8' * 'Int16' * 'Int32' * 'Int64' )rE )rF r r r � any_signed_nullable_int_dtypec s r4 c C s | j S )z� Parameterized fixture for any (purely) real numeric dtype. * int * 'int8' * 'uint8' * 'int16' * 'uint16' * 'int32' * 'uint32' * 'int64' * 'uint64' * float * 'float32' * 'float64' )rE )rF r r r �any_real_dtypep s r5 c C s | j S )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' )rE )rF r r r �any_numpy_dtype� s "r6 r� r� r� �bytes� a� cr� z mixed-integer�mixedg @Zfloatingg �?�integerzmixed-integer-float�decimal�boolean� datetime64z 2013-01-01z 2018-01-01r r� Z20180101r i� i� r r r� r� c C s | 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� )rE r; re r& )rF Zinferred_dtyper� r r r �any_skipna_inferred_dtype� s ) r? c C s> t jddd� ddlm} ddlm} |� }d|j_| |d�S ) 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% � importorskipZ IPython.core.interactiveshellr@ Ztraitlets.configrA ZHistoryManagerZ hist_file)r@ rA r� r r r �ip� s rC ZbsrZcooZcscZcsrZdiaZdokZlilc C s ddl m} t|| jd �S )z- Yields scipy sparse matrix classes. r )�sparseZ_matrix)ZscipyrD �getattrrE )rF rD r r r �spmatrix s rF c C s. g | ]&}t ttj|�tjj�rttj|��qS r )� issubclassrE r9 �offsetsZTick)r} �or r r r~ s c C s | j S )zN Fixture for Tick based datetime offsets available for a time series. )rE )rF r r r � tick_classes s rJ c C s | S )Nr )r@ r r r rA & rB c C s | j S )zk Simple fixture for testing keys in sorting methods. Tests None (no key) and the identity key. )rE )rF r r r � sort_by_key& s rK c c sx t �d� ddlm} ddlm} ddlm} G dd� d|�}| d|d d � |� V |�dd � d |j d< |j � � d S ) N�fsspecr )�register_implementation)�MemoryFileSystem)� _registryc s& e Zd ZdZdgZ� fdd�Z� ZS )z fsspectest.<locals>.TestMemoryFS�testmemNc s$ |� dd �| jd< t� jf |� d S )N�testr )�poprQ �superrh )ri rk )� __class__r r rh : s z)fsspectest.<locals>.TestMemoryFS.__init__)r_ rl rm �protocolrQ rh � __classcell__r r )rT r � TestMemoryFS6 s rW rP T)�clobber) r% rB rL rM Z fsspec.implementations.memoryrN Zfsspec.registryrO rR rQ �store�clear)rM rN �registryrW r r r � fsspectest/ s r\ )r� NN)ZEgonZVenkmanN)�NCC1701Dr] r] c C s | j S )zP A 3-tuple of names, the first two for operands, the last for a result. )rE )rF r r r r� E s r� c C s | j S )zI Parametrize over __setitem__, loc.__setitem__, iloc.__setitem__ )rE )rF r r r � indexer_sliS s r^ c C s | j S )z8 Parametrize over __setitem__, iloc.__setitem__ )rE )rF r r r � indexer_si[ s r_ c C s | j S )z7 Parametrize over __setitem__, loc.__setitem__ )rE )rF r r r � indexer_slc s r` c C s | j S )z: Parametrize over at.__setitem__, loc.__setitem__ )rE )rF r r r � indexer_alk s ra c C s t jjjdkS )z> Fixture to check if the array manager is being used. re )r9 �options�modeZ data_manager)rF r r r �using_array_managers s rd ( �__doc__� collectionsr r r r r r r< r �operatorr Z dateutil.tzr r Z hypothesisr �st�numpyr; r% Zpytzr r Z pandas.util._test_decorators�utilZ_test_decorators�tdZpandas.core.dtypes.dtypesr r Zpandasr9 r r r r r r Zpandas._testingZ_testingr Z pandas.corer Zpandas.core.indexes.apir r r) �filterwarningsr* r r( r, �settingsZregister_profileZ HealthCheckZtoo_slowZ load_profile�splitr� rE ZtseriesrH �clsZregister_type_strategyZbuildsZintegersZbooleansZfixturer: r< rG Z axis_framerH rI rL rO rP rU rV rW rZ r] Z NULL_OBJECTSr` Znulls_fixture2�nanZNaTra Zunique_nulls_fixture2rb rd Zindex_or_series2re rf ro rw r� r� r� r� ZmakeUnicodeIndexZmakeStringIndexZ makeDateIndexZmakePeriodIndexZmakeTimedeltaIndexZ makeIntIndexZ makeUIntIndexZmakeRangeIndexZmakeFloatIndexZ makeBoolIndexZmakeCategoricalIndexZmakeIntervalIndexr� rS r� �keysr= Zindex_fixture2r� Z index_flat2r� r� r� r� r� r� r+ Z_seriesr� r� Zfloat16r� Zint8Zint16r� Zuint8Zuint16Zuint32Z_narrow_dtypesr� r� r� r� r� r� r� r� r� r� r� Z_all_arithmetic_operatorsr� �addZradd�subZrsub�mulZrmul�truedivZrtruediv�floordivZ rfloordiv�modZrmod�powZrpow�eq�ne�lt�le�gt�ge�and_Zrand_�xorZrxor�or_Zror_r� r� Z_all_numeric_reductionsr� Z_all_boolean_reductionsr� Z_all_reductionsr� r r r r r r Z TIMEZONESZ TIMEZONE_IDSZparametrize_fixture_doc�strr r Ztz_aware_fixture2r Z utc_fixture2Z STRING_DTYPESr rE Z skip_if_nor! r# Zstring_storage2Z BYTES_DTYPESr$ Z OBJECT_DTYPESr% r' ZDATETIME64_DTYPESr( ZTIMEDELTA64_DTYPESr) Z FLOAT_DTYPESr* ZFLOAT_EA_DTYPESr+ r, ZCOMPLEX_DTYPESr- ZSIGNED_INT_DTYPESr. ZUNSIGNED_INT_DTYPESr/ ZALL_INT_DTYPESr0 ZALL_EA_INT_DTYPESr1 r2 r3 ZSIGNED_EA_INT_DTYPESr4 ZALL_REAL_DTYPESr5 ZALL_NUMPY_DTYPESr6 ZNAr> Z_any_skipna_inferred_dtyperD �_r? rC rF �__all__rJ rK r\ r� �setitem�locZilocr^ r_ r` �atra rd r r r r �<module> sv & " $ " # , * 04 0 ' $ 34 " ($"$
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