理解common.count_not_none()||dedent||zsqrt

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我是靠谱客的博主传统嚓茶，这篇文章主要介绍理解common.count_not_none()||dedent||zsqrt，现在分享给大家，希望可以做个参考。

源代码

From ExponentialMovingWindow:

复制代码

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_agg_see_also_doc = dedent(
    """
    See Also
    --------
    pandas.DataFrame.rolling.aggregate
    """
)

@doc(
    _shared_docs["aggregate"],
    see_also=_agg_see_also_doc,
    examples=_agg_examples_doc,
    versionadded="",
    klass="Series/Dataframe",
    axis="",
)
def std():
    return zsqrt(...)

common

pandas/core/common.py
复制代码def count_not_none(*args) -> int: """ Returns the count of arguments that are not None """ return sum(x is not None for x in args)
```
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def count_not_none(*args) -> int:
	"""
	Returns the count of arguments that are not None
	"""
	return sum(x is not None for x in args)
```
From official API reference, cann’t find an explaination about the module of common.py. I think it is commonly used by the core develop, but it is really usefull.

Just like the header explaination :
复制代码""" Misc tools for implementing data structures Note : pandas.core.common is 'not' part of the public API """
```
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"""
Misc tools for implementing data structures
Note : pandas.core.common is 'not' part of the public API
"""
```
pandas/core/window/common.py

It is common utility functions for rolling oprations.
复制代码def zsqrt(x): with np.errstate(all="ignore"): result = np.sqrt(x) mask = x < 0 if isinstance(x, ABCDataFrame): if mask._values.any(): result[mask] = 0 else: if mask.any(): result[mask] = 0 return result
```
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def zsqrt(x):
    with np.errstate(all="ignore"):
        result = np.sqrt(x)
        mask = x < 0
    if isinstance(x, ABCDataFrame):
        if mask._values.any():
            result[mask] = 0
    else:
        if mask.any():
            result[mask] = 0
    return result
```
From textwrap import dedent

textwrap.py module provides some convenience functions, as well as TextWrapper, the class that does all the work.

textwrap.dedent(text)

Remove any common leanding whitespace from every line in text.

This can be used to make triple-quoted string line up with the left edge of the display, while still presenting them in the source code in indented form
from pandas.util._decorators import Appender, Substitution,