3种Python获取帮助的方式

梦里梦外; 2023-10-02 20:16 30阅读 0赞

### help() ###

help函数是Python的一个内置函数

>>> help()
    Welcome to Python 3.9's help utility!
    
    If this is your first time using Python, you should definitely check out
    the tutorial on the Internet at https://docs.python.org/3.9/tutorial/.
    
    Enter the name of any module, keyword, or topic to get help on writing

>>> help(sum)
    Help on built-in function sum in module builtins:
    
    sum(iterable, /, start=0)
        Return the sum of a 'start' value (default: 0) plus an iterable of numbers
        
        When the iterable is empty, return the start value.
        This function is intended specifically for use with numeric values and may
        reject non-numeric types.

### dir() ###

dir函数是Python的一个内置函数。

函数原型：dir(\[object\])

可以帮助我们获取该对象的大部分相关属性。

>>> dir(sum)
    ['__call__', '__class__', '__delattr__', '__dir__', '__doc__', '__eq__', '__format__', '__ge__', '__getattribute__', '__gt__', '__hash__', '__init__', '__init_subclass__', '__le__', '__lt__', '__module__', '__name__', '__ne__', '__new__', '__qualname__', '__reduce__', '__reduce_ex__', '__repr__', '__self__', '__setattr__', '__sizeof__', '__str__', '__subclasshook__', '__text_signature__']

### \_ doc\_ ###

在Python中有一个奇妙的特性，文档字符串，又称为DocStrings。

用它可以为我们的模块、类、函数等添加说明性的文字，使程序易读易懂，更重要的是可以通过Python自带的标准方法将这些描述性文字信息输出。

上面提到的自带的标准方法就是\_ doc \_。前后各两个下划线。

注：当不是函数、方法、模块等调用doc时，而是具体对象调用时，会显示此对象从属的类型的构造函数的文档字符串。

>>> import numpy
    >>> numpy.__doc__
    '\nNumPy\n=====\n\nProvides\n  1. An array object of arbitrary homogeneous items\n  2. Fast mathematical operations over arrays\n  3. Linear Algebra, Fourier Transforms, Random Number Generation\n\nHow to use the documentation\n----------------------------\nDocumentation is available in two forms: docstrings provided\nwith the code, and a loose standing reference guide, available from\n`the NumPy homepage <https://numpy.org>`_.\n\nWe recommend exploring the docstrings using\n`IPython <https://ipython.org>`_, an advanced Python shell with\nTAB-completion and introspection capabilities.  See below for further\ninstructions.\n\nThe docstring examples assume that `numpy` has been imported as `np`::\n\n  >>> import numpy as np\n\nCode snippets are indicated by three greater-than signs::\n\n  >>> x = 42\n  >>> x = x + 1\n\nUse the built-in ``help`` function to view a function\'s docstring::\n\n  >>> help(np.sort)\n  ... # doctest: +SKIP\n\nFor some objects, ``np.info(obj)`` may provide additional help.  This is\nparticularly true if you see the line "Help on ufunc object:" at the top\nof the help() page.  Ufuncs are implemented in C, not Python, for speed.\nThe native Python help() does not know how to view their help, but our\nnp.info() function does.\n\nTo search for documents containing a keyword, do::\n\n  >>> np.lookfor(\'keyword\')\n  ... # doctest: +SKIP\n\nGeneral-purpose documents like a glossary and help on the basic concepts\nof numpy are available under the ``doc`` sub-module::\n\n  >>> from numpy import doc\n  >>> help(doc)\n  ... # doctest: +SKIP\n\nAvailable subpackages\n---------------------\nlib\n    Basic functions used by several sub-packages.\nrandom\n    Core Random Tools\nlinalg\n    Core Linear Algebra Tools\nfft\n    Core FFT routines\npolynomial\n    Polynomial tools\ntesting\n    NumPy testing tools\ndistutils\n    Enhancements to distutils with support for\n    Fortran compilers support and more.\n\nUtilities\n---------\ntest\n    Run numpy unittests\nshow_config\n    Show numpy build configuration\ndual\n    Overwrite certain functions with high-performance SciPy tools.\n    Note: `numpy.dual` is deprecated.  Use the functions from NumPy or Scipy\n    directly instead of importing them from `numpy.dual`.\nmatlib\n    Make everything matrices.\n__version__\n    NumPy version string\n\nViewing documentation using IPython\n-----------------------------------\nStart IPython with the NumPy profile (``ipython -p numpy``), which will\nimport `numpy` under the alias `np`.  Then, use the ``cpaste`` command to\npaste examples into the shell.  To see which functions are available in\n`numpy`, type ``np.<TAB>`` (where ``<TAB>`` refers to the TAB key), or use\n``np.*cos*?<ENTER>`` (where ``<ENTER>`` refers to the ENTER key) to narrow\ndown the list.  To view the docstring for a function, use\n``np.cos?<ENTER>`` (to view the docstring) and ``np.cos??<ENTER>`` (to view\nthe source code).\n\nCopies vs. in-place operation\n-----------------------------\nMost of the functions in `numpy` return a copy of the array argument\n(e.g., `np.sort`).  In-place versions of these functions are often\navailable as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``.\nExceptions to this rule are documented.\n\n'