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B �5�g09 � @ s� d Z ddlmZ ddlmZmZ ddlZddlZddl m Z dd� Z dd � Z d d � Z d d � Zdd� Zdd� Zd#dd�Zdd� Zd$dd�Zddd �d d �Zd%d d �d!d"�ZdS )&zV Module that contains many useful utilities for validating data or function arguments � )� annotations)�Iterable�SequenceN)�is_boolc C sl |dk rt d��t|�t|�krht|�| }t|�| }|dkrDdnd}t| � d|� d|� d|� d ���d S ) z� Checks whether 'args' has length of at most 'compat_args'. Raises a TypeError if that is not the case, similar to in Python when a function is called with too many arguments. r z*'max_fname_arg_count' must be non-negative� �argument� argumentsz() takes at most � z (z given)N)� ValueError�len� TypeError)�fname�args�max_fname_arg_count� compat_argsZ max_arg_countZactual_arg_countr � r �M/home/digitalm-up/venv/lib/python3.7/site-packages/pandas/util/_validators.py�_check_arg_length s r c C s� x�|D ]�}yR|| }|| }|dk r,|dks<|dkrB|dk rBd}n||k}t |�sZtd��W n$ tk r� || || k}Y nX |std|� d| � d���qW dS )z� Check that the keys in `arg_val_dict` are mapped to their default values as specified in `compat_args`. Note that this function is to be called only when it has been checked that arg_val_dict.keys() is a subset of compat_args NFz'match' is not a booleanzthe 'z=' parameter is not supported in the pandas implementation of z())r r )r Z arg_val_dictr �keyZv1Zv2�matchr r r �_check_for_default_values& s r c C s, t | |||� tt||��}t| ||� dS )a Checks whether the length of the `*args` argument passed into a function has at most `len(compat_args)` arguments and whether or not all of these elements in `args` are set to their default values. Parameters ---------- fname : str The name of the function being passed the `*args` parameter args : tuple The `*args` parameter passed into a function max_fname_arg_count : int The maximum number of arguments that the function `fname` can accept, excluding those in `args`. Used for displaying appropriate error messages. Must be non-negative. compat_args : dict A dictionary of keys and their associated default values. In order to accommodate buggy behaviour in some versions of `numpy`, where a signature displayed keyword arguments but then passed those arguments **positionally** internally when calling downstream implementations, a dict ensures that the original order of the keyword arguments is enforced. Raises ------ TypeError If `args` contains more values than there are `compat_args` ValueError If `args` contains values that do not correspond to those of the default values specified in `compat_args` N)r �dict�zipr )r r r r �kwargsr r r � validate_argsL s r c C s8 t |�t |� }|r4t|�d }t| � d|� d���dS )z} Checks whether 'kwargs' contains any keys that are not in 'compat_args' and raises a TypeError if there is one. r z'() got an unexpected keyword argument '�'N)�set�listr )r r r �diffZbad_argr r r �_check_for_invalid_keysu s r c C s$ |� � }t| ||� t| ||� dS )a� Checks whether parameters passed to the **kwargs argument in a function `fname` are valid parameters as specified in `*compat_args` and whether or not they are set to their default values. Parameters ---------- fname : str The name of the function being passed the `**kwargs` parameter kwargs : dict The `**kwargs` parameter passed into `fname` compat_args: dict A dictionary of keys that `kwargs` is allowed to have and their associated default values Raises ------ TypeError if `kwargs` contains keys not in `compat_args` ValueError if `kwargs` contains keys in `compat_args` that do not map to the default values specified in `compat_args` N)�copyr r )r r r �kwdsr r r �validate_kwargs� s r" c C sl t | |t|�� � ||� tt||��}x(|D ] }||kr.t| � d|� d���q.W |�|� t| ||� dS )a� Checks whether parameters passed to the *args and **kwargs argument in a function `fname` are valid parameters as specified in `*compat_args` and whether or not they are set to their default values. Parameters ---------- fname: str The name of the function being passed the `**kwargs` parameter args: tuple The `*args` parameter passed into a function kwargs: dict The `**kwargs` parameter passed into `fname` max_fname_arg_count: int The minimum number of arguments that the function `fname` requires, excluding those in `args`. Used for displaying appropriate error messages. Must be non-negative. compat_args: dict A dictionary of keys that `kwargs` is allowed to have and their associated default values. Raises ------ TypeError if `args` contains more values than there are `compat_args` OR `kwargs` contains keys not in `compat_args` ValueError if `args` contains values not at the default value (`None`) `kwargs` contains keys in `compat_args` that do not map to the default value as specified in `compat_args` See Also -------- validate_args : Purely args validation. validate_kwargs : Purely kwargs validation. z-() got multiple values for keyword argument 'r N)r �tuple�valuesr r r �updater" )r r r r r Z args_dictr r r r �validate_args_and_kwargs� s & r& TFc C sN t | �}|r|p| dk}|r*|p(t| t�}|sJtd|� dt| �j� d���| S )aR Ensure that argument passed in arg_name can be interpreted as boolean. Parameters ---------- value : bool Value to be validated. arg_name : str Name of the argument. To be reflected in the error message. none_allowed : bool, default True Whether to consider None to be a valid boolean. int_allowed : bool, default False Whether to consider integer value to be a valid boolean. Returns ------- value The same value as input. Raises ------ ValueError If the value is not a valid boolean. NzFor argument "z$" expected type bool, received type �.)r � isinstance�intr �type�__name__)�value�arg_name� none_allowed� int_allowedZ good_valuer r r �validate_bool_kwarg� s r0 c sr i }d� kr0t � fdd�| jD ��r0d}t|��|� krr|rT|� d|� d�}t|��| �� �dd��}� | ||< x@� �� D ]4\}} y| �|�} W n tk r� Y q|X | || < q|W t|�dkr�n�t|�dkr�| �� �dd��}|d ||< n�t|�d k�rZd� k�rd }t|��d |� d |� d �}tj |t dd� |d || �d�< |d || �d�< nd|� d�}t|��|S )aw Argument handler for mixed index, columns / axis functions In an attempt to handle both `.method(index, columns)`, and `.method(arg, axis=.)`, we have to do some bad things to argument parsing. This translates all arguments to `{index=., columns=.}` style. Parameters ---------- data : DataFrame args : tuple All positional arguments from the user kwargs : dict All keyword arguments from the user arg_name, method_name : str Used for better error messages Returns ------- kwargs : dict A dictionary of keyword arguments. Doesn't modify ``kwargs`` inplace, so update them with the return value here. Examples -------- >>> df._validate_axis_style_args((str.upper,), {'columns': id}, ... 'mapper', 'rename') {'columns': <function id>, 'index': <method 'upper' of 'str' objects>} This emits a warning >>> df._validate_axis_style_args((str.upper, id), {}, ... 'mapper', 'rename') {'columns': <function id>, 'index': <method 'upper' of 'str' objects>} �axisc 3 s | ]}|� kV qd S )Nr )�.0�x)r r r � <genexpr>' s z+validate_axis_style_args.<locals>.<genexpr>z;Cannot specify both 'axis' and any of 'index' or 'columns'.z# got multiple values for argument 'r r r � z:Cannot specify both 'axis' and any of 'index' or 'columns'zInterpreting call '.z(a, b)' as '.z�(index=a, columns=b)'. Use named arguments to remove any ambiguity. In the future, using positional arguments for 'index' or 'columns' will raise a 'TypeError'.� )� stacklevelzCannot specify all of 'z', 'index', 'columns'.) �anyZ_AXIS_TO_AXIS_NUMBERr Z_get_axis_name�get�itemsr r �warnings�warn� FutureWarning) �datar r r- � method_name�out�msgr1 �k�vZaxr )r r �validate_axis_style_args� s@ % rD c C s� ddl m} | dkr&|dkr&td��nl| dkr@|dk r@||�}nR| dk rz|dkrz|r�t| ttf�r�tdt| �j� d���n| dk r�|dk r�td��| |fS )a$ Validate the keyword arguments to 'fillna'. This checks that exactly one of 'value' and 'method' is specified. If 'method' is specified, this validates that it's a valid method. Parameters ---------- value, method : object The 'value' and 'method' keyword arguments for 'fillna'. validate_scalar_dict_value : bool, default True Whether to validate that 'value' is a scalar or dict. Specifically, validate that it is not a list or tuple. Returns ------- value, method : object r )�clean_fill_methodNz(Must specify a fill 'value' or 'method'.z>"value" parameter must be a scalar or dict, but you passed a "�"z)Cannot specify both 'value' and 'method'.) Zpandas.core.missingrE r r( r r# r r* r+ )r, �methodZvalidate_scalar_dict_valuerE r r r �validate_fillna_kwargs\ s rH zfloat | Iterable[float]z np.ndarray)�q�returnc C sj t �| �}d}|jdkrBd| kr,dksfn t|�|d ���n$tdd� |D ��sft|�|d ���|S )a� Validate percentiles (used by describe and quantile). This function checks if the given float or iterable of floats is a valid percentile otherwise raises a ValueError. Parameters ---------- q: float or iterable of floats A single percentile or an iterable of percentiles. Returns ------- ndarray An ndarray of the percentiles if valid. Raises ------ ValueError if percentiles are not in given interval([0, 1]). zApercentiles should all be in the interval [0, 1]. Try {} instead.r r g Y@c s s& | ] }d | kodkn V qdS )r r Nr )r2 �qsr r r r4 � s z&validate_percentile.<locals>.<genexpr>)�npZasarray�ndimr �format�all)rI Zq_arrrA r r r �validate_percentile� s rP z!bool | int | Sequence[bool | int])� ascendingc s8 ddd�� t | ttf�s&t| df� �S � fdd�| D �S )z8Validate ``ascending`` kwargs for ``sort_index`` method.FT)r. r/ rQ c s g | ]}t |d f� ��qS )rQ )r0 )r2 �item)r r r � <listcomp>� s z&validate_ascending.<locals>.<listcomp>)r( r r# r0 )rQ r )r r �validate_ascending� s rT )TF)T)T)�__doc__� __future__r �typingr r r; �numpyrL Zpandas.core.dtypes.commonr r r r r r" r& r0 rD rH rP rT r r r r �<module> s &) 8 (_ '#
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