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 + 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
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 + 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
def make_signature(func):
"""
Returns a tuple containing the paramenter list with defaults
and parameter list.
Examples
--------
>>> def f(a, b, c=2):
>>> return a * b * c
>>> print(make_signature(f))
(['a', 'b', 'c=2'], ['a', 'b', 'c'])
"""
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 var, default in 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
def make_signature(func):
"""
Returns a tuple containing the paramenter list with defaults
and parameter list.
Examples
--------
>>> def f(a, b, c=2):
>>> return a * b * c
>>> print(make_signature(f))
(['a', 'b', 'c=2'], ['a', 'b', 'c'])
"""
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 var, default in 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
def _check_stat_op(self, name, alternate, string_series_,
check_objects=False, check_allna=False):
with pd.option_context('use_bottleneck', False):
f = getattr(Series, name)
# add some NaNs
string_series_[5:15] = np.NaN
# mean, idxmax, idxmin, min, and max are valid for dates
if name not in ['max', 'min', 'mean']:
ds = Series(pd.date_range('1/1/2001', periods=10))
with pytest.raises(TypeError):
f(ds)
# skipna or no
assert pd.notna(f(string_series_))
assert pd.isna(f(string_series_, skipna=False))
# check the result is correct
nona = string_series_.dropna()
tm.assert_almost_equal(f(nona), alternate(nona.values))
tm.assert_almost_equal(f(string_series_), alternate(nona.values))
allna = string_series_ * np.nan
if check_allna:
assert np.isnan(f(allna))
# dtype=object with None, it works!
s = Series([1, 2, 3, None, 5])
f(s)
# GH#2888
items = [0]
items.extend(lrange(2 ** 40, 2 ** 40 + 1000))
s = Series(items, dtype='int64')
tm.assert_almost_equal(float(f(s)), float(alternate(s.values)))
# check date range
if check_objects:
s = Series(pd.bdate_range('1/1/2000', periods=10))
res = f(s)
exp = alternate(s)
assert res == exp
# check on string data
if name not in ['sum', 'min', 'max']:
with pytest.raises(TypeError):
f(Series(list('abc')))
# Invalid axis.
with pytest.raises(ValueError):
f(string_series_, axis=1)
# Unimplemented numeric_only parameter.
if 'numeric_only' in compat.signature(f).args:
with pytest.raises(NotImplementedError, match=name):
f(string_series_, numeric_only=True)
def get_result(self):
""" compute the results """
# dispatch to agg
if is_list_like(self.f) or is_dict_like(self.f):
return self.obj.aggregate(self.f,
axis=self.axis,
*self.args,
**self.kwds)
# all empty
if len(self.columns) == 0 and len(self.index) == 0:
return self.apply_empty_result()
# string dispatch
if isinstance(self.f, str):
# Support for `frame.transform('method')`
# Some methods (shift, etc.) require the axis argument, others
# don't, so inspect and insert if necessary.
func = getattr(self.obj, self.f)
sig = compat.signature(func)
if 'axis' in sig.args:
self.kwds['axis'] = self.axis
return func(*self.args, **self.kwds)
# ufunc
elif isinstance(self.f, np.ufunc):
with np.errstate(all='ignore'):
results = self.obj._data.apply('apply', func=self.f)
return self.obj._constructor(data=results,
index=self.index,
columns=self.columns,
copy=False)
# broadcasting
if self.result_type == 'broadcast':
return self.apply_broadcast()
# one axis empty
elif not all(self.obj.shape):
return self.apply_empty_result()
# raw
elif self.raw and not self.obj._is_mixed_type:
return self.apply_raw()
return self.apply_standard()
def get_result(self):
""" compute the results """
# dispatch to agg
if is_list_like(self.f) or is_dict_like(self.f):
return self.obj.aggregate(self.f, axis=self.axis,
*self.args, **self.kwds)
# all empty
if len(self.columns) == 0 and len(self.index) == 0:
return self.apply_empty_result()
# string dispatch
if isinstance(self.f, compat.string_types):
# Support for `frame.transform('method')`
# Some methods (shift, etc.) require the axis argument, others
# don't, so inspect and insert if necessary.
func = getattr(self.obj, self.f)
sig = compat.signature(func)
if 'axis' in sig.args:
self.kwds['axis'] = self.axis
return func(*self.args, **self.kwds)
# ufunc
elif isinstance(self.f, np.ufunc):
with np.errstate(all='ignore'):
results = self.f(self.values)
return self.obj._constructor(data=results, index=self.index,
columns=self.columns, copy=False)
# broadcasting
if self.result_type == 'broadcast':
return self.apply_broadcast()
# one axis empty
elif not all(self.obj.shape):
return self.apply_empty_result()
# raw
elif self.raw and not self.obj._is_mixed_type:
return self.apply_raw()
return self.apply_standard()
def signature_parameters(self):
if inspect.isclass(self.obj):
if hasattr(self.obj, '_accessors') and (self.name.split('.')[-1]
in self.obj._accessors):
# accessor classes have a signature but don't want to show this
return tuple()
try:
sig = signature(self.obj)
except (TypeError, ValueError):
# Some objects, mainly in C extensions do not support introspection
# of the signature
return tuple()
params = sig.args
if sig.varargs:
params.append("*" + sig.varargs)
if sig.keywords:
params.append("**" + sig.keywords)
params = tuple(params)
if params and params[0] in ('self', 'cls'):
return params[1:]
return params
def signature_parameters(self):
if inspect.isclass(self.obj):
if hasattr(self.obj, '_accessors') and (
self.name.split('.')[-1] in
self.obj._accessors):
# accessor classes have a signature but don't want to show this
return tuple()
try:
sig = signature(self.obj)
except (TypeError, ValueError):
# Some objects, mainly in C extensions do not support introspection
# of the signature
return tuple()
params = sig.args
if sig.varargs:
params.append("*" + sig.varargs)
if sig.keywords:
params.append("**" + sig.keywords)
params = tuple(params)
if params and params[0] in ('self', 'cls'):
return params[1:]
return params