[英]How to document kwargs according to Numpy style docstring?
So, I've found posts related to other styles and I am aware of this NumPy page about the documentation but I am confused.所以,我找到了与其他 styles 相关的帖子,我知道这个NumPy 页面关于文档,但我很困惑。 I didn't understand how to add each kwargs to the parameters section of a method.
我不明白如何将每个 kwargs 添加到方法的参数部分。 This is from the given web page:
这是来自给定的 web 页面:
def foo(var1, var2, *args, long_var_name='hi', **kwargs):
r"""Summarize the function in one line.
Several sentences providing an extended description. Refer to
variables using back-ticks, e.g. `var`.
Parameters
----------
var1 : array_like
Array_like means all those objects -- lists, nested lists, etc. --
that can be converted to an array. We can also refer to
variables like `var1`.
var2 : int
The type above can either refer to an actual Python type
(e.g. ``int``), or describe the type of the variable in more
detail, e.g. ``(N,) ndarray`` or ``array_like``.
*args : iterable
Other arguments.
long_var_name : {'hi', 'ho'}, optional
Choices in brackets, default first when optional.
**kwargs : dict
Keyword arguments.
It is not clear how to add each kwargs here.目前尚不清楚如何在此处添加每个 kwargs。 I also saw this sphinx page "Example NumPy Style Python Docstring" , here is the section about the kwargs:
我还看到了这个 sphinx 页面“Example NumPy Style Python Docstring” ,这里是关于 kwargs 的部分:
def module_level_function(param1, param2=None, *args, **kwargs):
"""This is an example of a module level function.
Function parameters should be documented in the ``Parameters`` section.
The name of each parameter is required. The type and description of each
parameter is optional, but should be included if not obvious.
If \*args or \*\*kwargs are accepted,
they should be listed as ``*args`` and ``**kwargs``.
The format for a parameter is::
name : type
description
The description may span multiple lines. Following lines
should be indented to match the first line of the description.
The ": type" is optional.
Multiple paragraphs are supported in parameter
descriptions.
Parameters
----------
param1 : int
The first parameter.
param2 : :obj:`str`, optional
The second parameter.
*args
Variable length argument list.
**kwargs
Arbitrary keyword arguments.
Nope, I am still confused.不,我仍然很困惑。 Is it something like this?
是这样的吗?
"""
Dummy docstring.
Parameters
----------
**kwargs: dict
first_kwarg: int
This is an integer
second_kwarg: str
This is a string
"""
The **kwargs
are not typically listed in the function, but instead the final destination of the **kwargs
is mentioned. **kwargs
通常不会在 function 中列出,而是会提到**kwargs
的最终目的地。 For example:例如:
**kwargs
Instructions on how to decorate your plots.
The keyword arguments are passed to `matplotlib.axes.Axes.plot()`
**kwargs
for the convenience of the end users.**kwargs
中列出可能的关键字 arguments 以方便最终用户。 This kind of approach is used in matplotlib, for example.**kwargs
(Numpydoc)**kwargs
(Numpydoc)**kwargs
? **kwargs
? First thing to note here is that **kwargs
should be used to pass arguments to underlying functions and methods .这里首先要注意的是,应该使用
**kwargs
将 arguments 传递给底层函数和方法。 If the argument inside **kwargs
would be used in the function (and not passed down), it should be written out as normal keyword argument, instead.如果
**kwargs
中的参数将在 function 中使用(而不是向下传递),则应将其写为普通关键字参数。
**kwargs
decription? **kwargs
描述放在哪里? The location of **kwargs
description is in the Parameters
section. **kwargs
描述的位置在Parameters
部分。 Sometimes it is appropriate to list them in the Other Parameters
section, but remember: Other Parameters should only be used if a function has a large number of keyword parameters, to prevent cluttering the Parameters section.有时将它们列在“
Other Parameters
”部分是合适的,但请记住:只有在 function 具有大量关键字参数时才应使用“其他参数”,以防止使“参数”部分混乱。
matplotlib.axes.Axes.grid
has **kwargs
in Parameters
section. matplotlib.axes.Axes.grid
在Parameters
部分有**kwargs
。matplotlib.axes.Axes.plot
has **kwargs
in Other Parameters
section (reasoning probably to large number of keyword arguments). matplotlib.axes.Axes.plot
在Other Parameters
部分有**kwargs
(推理可能是大量关键字参数)。**kwargs
decription **kwargs
描述的语法The syntax for the description for the **kwargs
is, following Numpydoc styleguide **kwargs
描述的语法是,遵循Numpydoc styleguide
Parameters
----------
... (other lines)
**kwargs : sometype
Some description on what the kwargs are
used for.
or或者
Parameters
----------
... (other lines)
**kwargs
Some description on what the kwargs are
used for.
The one describing the type is more appropriate, as [ source ].描述类型的那个更合适,如 [ source ]。
For the parameter types, be as precise as possible
对于参数类型,尽可能精确
One exception for this is for example when the **kwargs
could be passed to one of many functions based on other parameter values , as in seaborn.kdeplot .例如,当
**kwargs
可以根据其他参数值传递给许多函数之一时,例如seaborn.kdeplot 就是一个例外。 Then, the line for the type would become too long for describing all the types and it would be cleaner to use a bullet point list, which also describes the conditions on when the **kwargs
are forwarded to where.然后,类型的行会变得太长而无法描述所有类型,使用项目符号列表会更清晰,它还描述了何时将
**kwargs
转发到何处的条件。 Eg.:例如。:
Parameters
----------
fill: bool or None
If True, fill in the area under univariate density curves or between
bivariate contours. If None, the default depends on multiple.
**kwargs
Other keyword arguments are passed to one of the following matplotlib
functions:
* matplotlib.axes.Axes.plot() (univariate, fill=False),
* matplotlib.axes.Axes.fill_between() (univariate, fill=True),
* matplotlib.axes.Axes.contour() (bivariate, fill=False),
* matplotlib.axes.contourf() (bivariate, fill=True).
You may also add listing of the valid keyword arguments in **kwargs
like in matplotlib.axes.Axes.grid
.您还可以在
**kwargs
中添加有效关键字 arguments 的列表,例如matplotlib.axes.Axes.grid
。 Here is the interpolated python doc/text version:这是内插的 python 文档/文本版本:
Parameters
----------
... (other lines)
**kwargs : `.Line2D` properties
Define the line properties of the grid, e.g.::
grid(color='r', linestyle='-', linewidth=2)
Valid keyword arguments are:
Properties:
agg_filter: a filter function, which takes a (m, n, 3) float array and a dpi value, and returns a (m, n, 3) array
alpha: float or None
animated: bool
antialiased or aa: bool
clip_box: `.Bbox`
clip_on: bool
clip_path: Patch or (Path, Transform) or None
color or c: color
contains: unknown
dash_capstyle: {'butt', 'round', 'projecting'}
dash_joinstyle: {'miter', '
... (more lines)
This is convenient for the user, but challenging for the developer.这对用户来说很方便,但对开发人员来说具有挑战性。 In matplotlib this kind of luxury is made possible with the automatization using some special documentation decorators and linking 1 .
在 matplotlib 中,这种奢侈是通过使用一些特殊的文档装饰器和链接1的自动化实现的。 Manual writing of allowed kwargs will surely become a code maintenance nightmare.
手动编写允许的 kwargs 肯定会成为代码维护的噩梦。
**kwargs
/ Extended help **kwargs
相关的注释/扩展帮助Some additional info about the **kwargs
could be included in the Notes
section.关于
**kwargs
的一些附加信息可以包含在Notes
部分中。 For example matplotlib.axes.Axes.plot
discusses marker styles, line styles and colors in the Notes
section.例如
matplotlib.axes.Axes.plot
在Notes
部分讨论了标记 styles、行 styles 和 colors。 [2] [2]
[1] They use a @docstring.dedent_interpd
decorator which pulls the meaning of the kwargs to the final docs. [1]他们使用
@docstring.dedent_interpd
装饰器将 kwargs 的含义提取到最终文档中。 So that is happening in place of %(Line2D:kwdoc)s
, for example.例如,这代替了
%(Line2D:kwdoc)s
。
[2] See: help(ax.plot)
where ax
is instance of matplotlib.axes.Axes
. [2]请参阅:
help(ax.plot)
,其中ax
是matplotlib.axes.Axes
的实例。
Usually kwargs that need to be described in the Parameters
section would typically be handled like other named arguments and the **kwargs
is left unexpanded.通常需要在
Parameters
部分描述的 kwargs 通常会像其他命名的 arguments 一样处理,并且**kwargs
保持未扩展。 However, the numpy style guide also has an Other Parameters
section than can be used for providing descriptions of kwargs without cluttering the Parameters
section.但是,numpy 样式指南也有一个
Other Parameters
部分,可用于提供 kwargs 的描述,而不会使Parameters
部分混乱。 The style guide describes it as: 风格指南将其描述为:
An optional section used to describe infrequently used parameters.
用于描述不经常使用的参数的可选部分。 It should only be used if a function has a large number of keyword parameters, to prevent cluttering the Parameters section.
仅当 function 具有大量关键字参数时才应使用它,以防止参数部分混乱。
The numpydoc repo gives this example : numpydoc repo 给出了这个例子:
"""
Other Parameters
----------------
only_seldom_used_keyword : int, optional
Infrequently used parameters can be described under this optional
section to prevent cluttering the Parameters section.
**kwargs : dict
Other infrequently used keyword arguments. Note that all keyword
arguments appearing after the first parameter specified under the
Other Parameters section, should also be described under this
section.
"""
So, the additional kwargs could be added as因此,额外的 kwargs 可以添加为
"""
Other Parameters
----------------
first_kwarg: int
This is an integer
second_kwarg: str
This is a string
**kwargs : dict
Other infrequently used keyword arguments.
"""
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