B Y0d09@sdZddlmZddlmZmZddlZddlZddl m Z ddZ dd Z d d Z d d ZddZddZd#ddZddZd$ddZdddddZd%dd d!d"ZdS)&zV Module that contains many useful utilities for validating data or function arguments ) annotations)IterableSequenceN)is_boolc Csl|dkrtdt|t|krht||}t||}|dkrDdnd}t|d|d|d|d d S) z Checks whether 'args' has length of at most 'compat_args'. Raises a TypeError if that is not the case, similar to in Python when a function is called with too many arguments. rz*'max_fname_arg_count' must be non-negativeargument argumentsz() takes at most  z (z given)N) ValueErrorlen TypeError)fnameargsmax_fname_arg_count compat_argsZ max_arg_countZactual_arg_countrrI/var/www/html/venv/lib/python3.7/site-packages/pandas/util/_validators.py_check_arg_lengths  rc Csx|D]}yR||}||}|dk r,|dks<|dkrB|dk rBd}n||k}t|sZtdWn$tk r||||k}YnX|std|d|dqWdS)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())rr )r Z arg_val_dictrkeyZv1Zv2matchrrr_check_for_default_values&s   rcCs,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)rdictzipr)r rrrkwargsrrr validate_argsLs rcCs8t|t|}|r4t|d}t|d|ddS)z} Checks whether 'kwargs' contains any keys that are not in 'compat_args' and raises a TypeError if there is one. rz'() got an unexpected keyword argument ''N)setlistr )r rrdiffZbad_argrrr_check_for_invalid_keysus rcCs$|}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)copyrr)r rrkwdsrrrvalidate_kwargss r"cCslt||t|||tt||}x(|D] }||kr.t|d|dq.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 'rN)rtuplevaluesrrr updater")r rrrrZ args_dictrrrrvalidate_args_and_kwargss&  r&TFcCsNt|}|r|p|dk}|r*|p(t|t}|sJtd|dt|jd|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 isinstanceintr type__name__)valuearg_name none_allowed int_allowedZ good_valuerrrvalidate_bool_kwargs r0c sri}dkr0tfdd|jDr0d}t||krr|rT|d|d}t||dd}|||<x@D]4\}} y||} Wntk rYq|X| || <q|Wt|dkrnt|dkr|dd}|d||<nt|d krZdkrd }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': , 'index': } This emits a warning >>> df._validate_axis_style_args((str.upper, id), {}, ... 'mapper', 'rename') {'columns': , 'index': } axisc3s|]}|kVqdS)Nr).0x)rrr 'sz+validate_axis_style_args..z;Cannot specify both 'axis' and any of 'index' or 'columns'.z# got multiple values for argument 'rrrz: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_namegetitemsr r warningswarn FutureWarning) datarrr- method_nameoutmsgr1kvZaxr)rrvalidate_axis_style_argss@%       rDcCsddlm}|dkr&|dkr&tdnl|dkr@|dk r@||}nR|dk rz|dkrz|rt|ttfrtdt|jdn|dk r|dk rtd||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.missingrEr r(rr#r r*r+)r,methodZvalidate_scalar_dict_valuerErrrvalidate_fillna_kwargs\s   rHzfloat | Iterable[float]z np.ndarray)qreturncCsjt|}d}|jdkrBd|kr,dksfnt||dn$tdd|Dsft||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.rrgY@css&|]}d|kodknVqdS)rrNr)r2qsrrrr4sz&validate_percentile..)npZasarrayndimr formatall)rIZq_arrrArrrvalidate_percentiles  rPz!bool | int | Sequence[bool | int]) ascendingcs8dddt|ttfs&t|dfSfdd|DS)z8Validate ``ascending`` kwargs for ``sort_index`` method.FT)r.r/rQcsg|]}t|dfqS)rQ)r0)r2item)rrr sz&validate_ascending..)r(rr#r0)rQr)rrvalidate_ascendings rT)TF)T)T)__doc__ __future__rtypingrrr;numpyrLZpandas.core.dtypes.commonrrrrrr"r&r0rDrHrPrTrrrrs   &) 8 (_ '#