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_decorators.py
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from pandas.compat import callable, signature, PY2
from pandas._libs.properties import cache_readonly # noqa
import inspect
import warnings
from textwrap import dedent, wrap
from functools import wraps, update_wrapper, WRAPPER_ASSIGNMENTS
def deprecate(name, alternative, version, alt_name=None,
klass=None, stacklevel=2, msg=None):
"""Return a new function that emits a deprecation warning on use.
To use this method for a deprecated function, another function
`alternative` with the same signature must exist. The deprecated
function will emit a deprecation warning, and in the docstring
it will contain the deprecation directive with the provided version
so it can be detected for future removal.
Parameters
----------
name : str
Name of function to deprecate.
alternative : func
Function to use instead.
version : str
Version of pandas in which the method has been deprecated.
alt_name : str, optional
Name to use in preference of alternative.__name__.
klass : Warning, default FutureWarning
stacklevel : int, default 2
msg : str
The message to display in the warning.
Default is '{name} is deprecated. Use {alt_name} instead.'
"""
alt_name = alt_name or alternative.__name__
klass = klass or FutureWarning
warning_msg = msg or '{} is deprecated, use {} instead'.format(name,
alt_name)
# adding deprecated directive to the docstring
msg = msg or 'Use `{alt_name}` instead.'.format(alt_name=alt_name)
msg = '\n '.join(wrap(msg, 70))
@Substitution(version=version, msg=msg)
@Appender(alternative.__doc__)
def wrapper(*args, **kwargs):
"""
.. deprecated:: %(version)s
%(msg)s
"""
warnings.warn(warning_msg, klass, stacklevel=stacklevel)
return alternative(*args, **kwargs)
# Since we are using Substitution to create the required docstring,
# remove that from the attributes that should be assigned to the wrapper
assignments = tuple(x for x in WRAPPER_ASSIGNMENTS if x != '__doc__')
update_wrapper(wrapper, alternative, assigned=assignments)
return wrapper
def deprecate_kwarg(old_arg_name, new_arg_name, mapping=None, stacklevel=2):
"""
Decorator to deprecate a keyword argument of a function.
Parameters
----------
old_arg_name : str
Name of argument in function to deprecate
new_arg_name : str or None
Name of preferred argument in function. Use None to raise warning that
``old_arg_name`` keyword is deprecated.
mapping : dict or callable
If mapping is present, use it to translate old arguments to
new arguments. A callable must do its own value checking;
values not found in a dict will be forwarded unchanged.
Examples
--------
The following deprecates 'cols', using 'columns' instead
>>> @deprecate_kwarg(old_arg_name='cols', new_arg_name='columns')
... def f(columns=''):
... print(columns)
...
>>> f(columns='should work ok')
should work ok
>>> f(cols='should raise warning')
FutureWarning: cols is deprecated, use columns instead
warnings.warn(msg, FutureWarning)
should raise warning
>>> f(cols='should error', columns="can\'t pass do both")
TypeError: Can only specify 'cols' or 'columns', not both
>>> @deprecate_kwarg('old', 'new', {'yes': True, 'no': False})
... def f(new=False):
... print('yes!' if new else 'no!')
...
>>> f(old='yes')
FutureWarning: old='yes' is deprecated, use new=True instead
warnings.warn(msg, FutureWarning)
yes!
To raise a warning that a keyword will be removed entirely in the future
>>> @deprecate_kwarg(old_arg_name='cols', new_arg_name=None)
... def f(cols='', another_param=''):
... print(cols)
...
>>> f(cols='should raise warning')
FutureWarning: the 'cols' keyword is deprecated and will be removed in a
future version please takes steps to stop use of 'cols'
should raise warning
>>> f(another_param='should not raise warning')
should not raise warning
>>> f(cols='should raise warning', another_param='')
FutureWarning: the 'cols' keyword is deprecated and will be removed in a
future version please takes steps to stop use of 'cols'
should raise warning
"""
if mapping is not None and not hasattr(mapping, 'get') and \
not callable(mapping):
raise TypeError("mapping from old to new argument values "
"must be dict or callable!")
def _deprecate_kwarg(func):
@wraps(func)
def wrapper(*args, **kwargs):
old_arg_value = kwargs.pop(old_arg_name, None)
if new_arg_name is None and old_arg_value is not None:
msg = (
"the '{old_name}' keyword is deprecated and will be "
"removed in a future version. "
"Please take steps to stop the use of '{old_name}'"
).format(old_name=old_arg_name)
warnings.warn(msg, FutureWarning, stacklevel=stacklevel)
kwargs[old_arg_name] = old_arg_value
return func(*args, **kwargs)
if old_arg_value is not None:
if mapping is not None:
if hasattr(mapping, 'get'):
new_arg_value = mapping.get(old_arg_value,
old_arg_value)
else:
new_arg_value = mapping(old_arg_value)
msg = ("the {old_name}={old_val!r} keyword is deprecated, "
"use {new_name}={new_val!r} instead"
).format(old_name=old_arg_name,
old_val=old_arg_value,
new_name=new_arg_name,
new_val=new_arg_value)
else:
new_arg_value = old_arg_value
msg = ("the '{old_name}' keyword is deprecated, "
"use '{new_name}' instead"
).format(old_name=old_arg_name,
new_name=new_arg_name)
warnings.warn(msg, FutureWarning, stacklevel=stacklevel)
if kwargs.get(new_arg_name, None) is not None:
msg = ("Can only specify '{old_name}' or '{new_name}', "
"not both").format(old_name=old_arg_name,
new_name=new_arg_name)
raise TypeError(msg)
else:
kwargs[new_arg_name] = new_arg_value
return func(*args, **kwargs)
return wrapper
return _deprecate_kwarg
def rewrite_axis_style_signature(name, extra_params):
def decorate(func):
@wraps(func)
def wrapper(*args, **kwargs):
return func(*args, **kwargs)
if not PY2:
kind = inspect.Parameter.POSITIONAL_OR_KEYWORD
params = [
inspect.Parameter('self', kind),
inspect.Parameter(name, kind, default=None),
inspect.Parameter('index', kind, default=None),
inspect.Parameter('columns', kind, default=None),
inspect.Parameter('axis', kind, default=None),
]
for pname, default in extra_params:
params.append(inspect.Parameter(pname, kind, default=default))
sig = inspect.Signature(params)
func.__signature__ = sig
return wrapper
return decorate
# Substitution and Appender are derived from matplotlib.docstring (1.1.0)
# module http://matplotlib.org/users/license.html
class Substitution(object):
"""
A decorator to take a function's docstring and perform string
substitution on it.
This decorator should be robust even if func.__doc__ is None
(for example, if -OO was passed to the interpreter)
Usage: construct a docstring.Substitution with a sequence or
dictionary suitable for performing substitution; then
decorate a suitable function with the constructed object. e.g.
sub_author_name = Substitution(author='Jason')
@sub_author_name
def some_function(x):
"%(author)s wrote this function"
# note that some_function.__doc__ is now "Jason wrote this function"
One can also use positional arguments.
sub_first_last_names = Substitution('Edgar Allen', 'Poe')
@sub_first_last_names
def some_function(x):
"%s %s wrote the Raven"
"""
def __init__(self, *args, **kwargs):
if (args and kwargs):
raise AssertionError("Only positional or keyword args are allowed")
self.params = args or kwargs
def __call__(self, func):
func.__doc__ = func.__doc__ and func.__doc__ % self.params
return func
def update(self, *args, **kwargs):
"""
Update self.params with supplied args.
If called, we assume self.params is a dict.
"""
self.params.update(*args, **kwargs)
@classmethod
def from_params(cls, params):
"""
In the case where the params is a mutable sequence (list or dictionary)
and it may change before this class is called, one may explicitly use a
reference to the params rather than using *args or **kwargs which will
copy the values and not reference them.
"""
result = cls()
result.params = params
return result
class Appender(object):
"""
A function decorator that will append an addendum to the docstring
of the target function.
This decorator should be robust even if func.__doc__ is None
(for example, if -OO was passed to the interpreter).
Usage: construct a docstring.Appender with a string to be joined to
the original docstring. An optional 'join' parameter may be supplied
which will be used to join the docstring and addendum. e.g.
add_copyright = Appender("Copyright (c) 2009", join='\n')
@add_copyright
def my_dog(has='fleas'):
"This docstring will have a copyright below"
pass
"""
def __init__(self, addendum, join='', indents=0):
if callable(addendum):
# allow for passing @Appender(func) instead of
# @Appender(func.__doc__), both more succinct and helpful when
# -oo optimization strips docstrings
addendum = addendum.__doc__ or ''
if indents > 0:
self.addendum = indent(addendum, indents=indents)
else:
self.addendum = addendum
self.join = join
def __call__(self, func):
func.__doc__ = func.__doc__ if func.__doc__ else ''
self.addendum = self.addendum if self.addendum else ''
docitems = [func.__doc__, self.addendum]
func.__doc__ = dedent(self.join.join(docitems))
return func
def indent(text, indents=1):
if not text or not isinstance(text, str):
return ''
jointext = ''.join(['\n'] + [' '] * indents)
return jointext.join(text.split('\n'))
def make_signature(func):
"""
Returns a string repr of the arg list of a func call, with any defaults.
Examples
--------
>>> def f(a,b,c=2) :
>>> return a*b*c
>>> print(_make_signature(f))
a,b,c=2
"""
spec = signature(func)
if spec.defaults is None:
n_wo_defaults = len(spec.args)
defaults = ('',) * n_wo_defaults
else:
n_wo_defaults = len(spec.args) - len(spec.defaults)
defaults = ('',) * n_wo_defaults + tuple(spec.defaults)
args = []
for i, (var, default) in enumerate(zip(spec.args, defaults)):
args.append(var if default == '' else var + '=' + repr(default))
if spec.varargs:
args.append('*' + spec.varargs)
if spec.keywords:
args.append('**' + spec.keywords)
return args, spec.args