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Module that contains many useful utilities
for validating data or function arguments
� )�Iterable�UnionN)�is_boolc C sl |dk rt d��t|�t|�krht|�| }t|�| }|dkrDdnd}t| � d|� d|� d|� d ���d
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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� �argumentZ 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 �9/tmp/pip-build-5_djhm0z/pandas/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
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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
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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
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validate_argsG 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
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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|j� � ||� tt||��}x(|D ] }||kr.t| � d|� d���q.W |j|� 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# c C s0 t | �p| dks,td|� dt| �j� d���| S )z; Ensures that argument passed in arg_name is of type bool. NzFor argument "z$" expected type bool, received type �.)r r �type�__name__)�value�arg_namer r r �validate_bool_kwarg� s r) c sr i }d� kr0t � fdd�| jD ��r0d}t|��|� krr|rT|� d|� d�}t|��| j� jdd��}� | ||< x@� j� D ]4\}} y| j|�}
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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
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FutureWarning) �datar r r( � method_name�out�msgr* �k�vZaxr )r r �validate_axis_style_args� s@ %
r= Tc 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.missingr> r �
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rB )�q�returnc C sl t j| �}d}|jdkrDd| ko*dkn sht|j|d ���n$tdd� |D ��sht|j|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 )r+ �qsr r r r- } s z&validate_percentile.<locals>.<genexpr>)�npZasarray�ndimr �format�all)rC Zq_arrr: r r r �validate_percentile` s
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