o g09@sdZddlmZddlmZmZddlZddlZddl m Z ddZ dd Z d d Z d d ZddZddZd$ddZddZd%ddZd&ddZ d%d'd"d#ZdS)(zV Module that contains many useful utilities for validating data or function arguments ) annotations)IterableSequenceN)is_boolc Csl|dkrtdt|t|kr4t||}t||}|dkr"dnd}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_args max_arg_countactual_arg_countrrU/home/ubuntu/cloudmapper/venv/lib/python3.10/site-packages/pandas/util/_validators.py_check_arg_lengths  rc Cs|D]J}z)||}||}|dur|dus|dur |dur d}n||k}t|s,tdWnty>||||u}Ynw|sLtd|d|dqdS)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 arg_val_dictrkeyv1v2matchrrr_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|}|rt|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 rrdiffbad_argrrr_check_for_invalid_keysus  r%cCs$|}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 rrkwdsrrrvalidate_kwargss r(cCsht||t|||tt||}|D]}||vr&t|d|dq||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)rtuplevaluesrrr updater()r rrrr args_dictrrrrvalidate_args_and_kwargss& r-TFcCsNt|}|r |p |du}|r|pt|t}|s%td|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$" expected type bool, received type .)r isinstanceintr type__name__)valuearg_name none_allowed int_allowed good_valuerrrvalidate_bool_kwargs r8c sli}dvrtfdd|jDrd}t||vr9|r*|d|d}t||dd}|||<D]\}} z||} Wn tyQYq=w| || <q=t|dkr` |St|dkrw|dd}|d||<|St|d krdvrd }t|d |d |d }tj |t dd|d||d<|d||d<|Sd|d}t|)aw Argument handler for mixed index, columns / axis functions In an attempt to handle both `.method(index, columns)`, and `.method(arg, axis=.)`, we have to do some bad things to argument parsing. This translates all arguments to `{index=., columns=.}` style. Parameters ---------- data : DataFrame args : tuple All positional arguments from the user kwargs : dict All keyword arguments from the user arg_name, method_name : str Used for better error messages Returns ------- kwargs : dict A dictionary of keyword arguments. Doesn't modify ``kwargs`` inplace, so update them with the return value here. Examples -------- >>> df._validate_axis_style_args((str.upper,), {'columns': id}, ... 'mapper', 'rename') {'columns': , 'index': } This emits a warning >>> df._validate_axis_style_args((str.upper, id), {}, ... 'mapper', 'rename') {'columns': , 'index': } axisc3s|]}|vVqdS)Nr).0xrrr 'sz+validate_axis_style_args..z;Cannot specify both 'axis' and any of 'index' or 'columns'.z# got multiple values for argument 'r rrz:Cannot specify both 'axis' and any of 'index' or 'columns'zInterpreting call '.z(a, b)' as '.z(index=a, columns=b)'. Use named arguments to remove any ambiguity. In the future, using positional arguments for 'index' or 'columns' will raise a 'TypeError'.) stacklevelzCannot specify all of 'z', 'index', 'columns'.) any_AXIS_TO_AXIS_NUMBERr _get_axis_namegetitemsr r warningswarn FutureWarning) datarrr4 method_nameoutmsgr9kvaxrr<rvalidate_axis_style_argssL%         rPcCsddlm}|dur|durtd|dur"|dur"||}||fS|durB|durB|r>t|ttfr>tdt|jd||fS|durN|durNtd||fS)a$ 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'.) pandas.core.missingrQr r/r"r)r r1r2)r3methodvalidate_scalar_dict_valuerQrrrvalidate_fillna_kwargs\s"  rVqfloat | Iterable[float]return np.ndarraycCslt|}d}|jdkr"d|krdks nt||d|Stdd|Ds4t||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|ko dknVqdS)rrNr)r:qsrrrr=s&z&validate_percentile..)npasarrayndimr formatall)rWq_arrrLrrrvalidate_percentiles  rb ascending!bool | int | Sequence[bool | int]cs<dddt|ttfst|dfiSfdd|DS)z8Validate ``ascending`` kwargs for ``sort_index`` method.FT)r5r6rccsg|] }t|dfiqSrc)r8)r:itemr<rr sz&validate_ascending..)r/r"r)r8rerr<rvalidate_ascendings rh)TF)T)rWrXrYrZ)rcrd)__doc__ __future__rtypingrrrFnumpyr\pandas.core.dtypes.commonrrrrr%r(r-r8rPrVrbrhrrrrs$  &)  8( _ '#