a
    Pf                     @   s  d dl Z d dlZd dlmZ d dlmZmZ ejdd Zejdd Z	ejdd	 Z
ejd
d Zejddgddd Zejdd Zejdd Zejdd Zejdd Zejdd Zejdd Zejddgddd Zejdd  d!d  d"d  d#d  gg d$d%d&d' Zejddgdd(d) Zejddgdd*d+ Zejddgdd,d- Zejd.d/gdd0d1 Zejddgdd2d3 Zejd4d5 Zejed6d7d8ZdS )9    N)_get_option)Seriesoptionsc                   C   s   t dS )z3A fixture providing the ExtensionDtype to validate.NNotImplementedError r   r   X/var/www/ai-form-bot/venv/lib/python3.9/site-packages/pandas/tests/extension/conftest.pydtype   s    r	   c                   C   s   t dS )z
    Length-100 array for this type.

    * data[0] and data[1] should both be non missing
    * data[0] and data[1] should not be equal
    Nr   r   r   r   r   data   s    r
   c                 C   s(   | j s | jdks t|  d tdS )z
    Length-100 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 dtypeN)Z_is_numerickindpytestskipr   r	   r   r   r   data_for_twos   s    r   c                   C   s   t dS )zLength-2 array with [NA, Valid]Nr   r   r   r   r   data_missing-   s    r   )paramsc                 C   s    | j dkr|S | j dkr|S dS )z5Parametrized fixture giving 'data' and 'data_missing'r
   r   Nparam)requestr
   r   r   r   r   all_data3   s    

r   c                    s    fdd}|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.
    c                 3   s   t | D ]
} V  qd S N)range)count_r
   r   r   genL   s    zdata_repeated.<locals>.genr   )r
   r   r   r   r   data_repeated<   s    r   c                   C   s   t dS )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
    Nr   r   r   r   r   data_for_sortingS   s    r   c                   C   s   t dS )z{
    Length-3 array with a known sort order.

    This should be three items [B, NA, A] with
    A < B and NA missing.
    Nr   r   r   r   r   data_missing_for_sortinga   s    r   c                   C   s   t jS )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_``
    )operatoris_r   r   r   r   na_cmpl   s    
r"   c                 C   s   | j S )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_valuer   r   r   r   r#   y   s    r#   c                   C   s   t dS )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.
    Nr   r   r   r   r   data_for_grouping   s    r$   TFc                 C   s   | j S )z#Whether to box the data in a Seriesr   r   r   r   r   box_in_series   s    r&   c                 C   s   dS N   r   xr   r   r   <lambda>       r+   c                 C   s   dgt |  S r'   )lenr)   r   r   r   r+      r,   c                 C   s   t dgt|  S r'   )r   r-   r)   r   r   r   r+      r,   c                 C   s   | S r   r   r)   r   r   r   r+      r,   )ZscalarlistZseriesobject)r   Zidsc                 C   s   | j S )z,
    Functions to test groupby.apply().
    r   r%   r   r   r   groupby_apply_op   s    r0   c                 C   s   | j S )zU
    Boolean fixture to support Series and Series.to_frame() comparison testing.
    r   r%   r   r   r   as_frame   s    r1   c                 C   s   | j S )zL
    Boolean fixture to support arr and Series(arr) comparison testing.
    r   r%   r   r   r   	as_series   s    r2   c                 C   s   | j S )zd
    Boolean fixture to support comparison testing of ExtensionDtype array
    and numpy array.
    r   r%   r   r   r   	use_numpy   s    r3   ZffillZbfillc                 C   s   | j S )z{
    Parametrized fixture giving method parameters 'ffill' and 'bfill' for
    Series.fillna(method=<method>) testing.
    r   r%   r   r   r   fillna_method   s    r4   c                 C   s   | j S )zR
    Boolean fixture to support ExtensionDtype _from_sequence method testing.
    r   r%   r   r   r   as_array   s    r5   c                 C   s
   t t S )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.
    )r/   __new__r   r   r   r   invalid_scalar   s    	r7   )returnc                   C   s   t jjdu otddddkS )z7
    Fixture to check if Copy-on-Write is enabled.
    Tzmode.data_manager)Zsilentblock)r   modeZcopy_on_writer   r   r   r   r   using_copy_on_write   s    r;   )r    r   Zpandas._config.configr   Zpandasr   r   Zfixturer	   r
   r   r   r   r   r   r   r"   r#   r$   r&   r0   r1   r2   r3   r4   r5   r7   boolr;   r   r   r   r   <module>   sd   











	

	






