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# [`functools`](#module-functools "functools: Higher-order functions and operations on callable objects.") --- 高階函數和可調用對象上的操作
**源代碼:** [Lib/functools.py](https://github.com/python/cpython/tree/3.7/Lib/functools.py) \[https://github.com/python/cpython/tree/3.7/Lib/functools.py\]
- - - - - -
[`functools`](#module-functools "functools: Higher-order functions and operations on callable objects.") 模塊應用于高階函數，即——參數或（和）返回值為其他函數的函數。通常來說，此模塊的功能適用于所有可調用對象。
[`functools`](#module-functools "functools: Higher-order functions and operations on callable objects.") 模塊定義了以下函數:
`functools.``cmp_to_key`(*func*)將(舊式的)比較函數轉換為新式的 [key function](../glossary.xhtml#term-key-function) . 在類似于 [`sorted()`](functions.xhtml#sorted "sorted") ， [`min()`](functions.xhtml#min "min") ， [`max()`](functions.xhtml#max "max") ， [`heapq.nlargest()`](heapq.xhtml#heapq.nlargest "heapq.nlargest") ， [`heapq.nsmallest()`](heapq.xhtml#heapq.nsmallest "heapq.nsmallest") ， [`itertools.groupby()`](itertools.xhtml#itertools.groupby "itertools.groupby") 等函數的 key 參數中使用。此函數主要用作將 Python 2 程序轉換至新版的轉換工具，以保持對比較函數的兼容。
比較函數意為一個可調用對象，該對象接受兩個參數并比較它們，結果為小于則返回一個負數，相等則返回零，大于則返回一個正數。key function則是一個接受一個參數，并返回另一個用以排序的值的可調用對象。
示例:
```
sorted(iterable, key=cmp_to_key(locale.strcoll)) # locale-aware sort order
```
有關排序示例和簡要排序教程，請參閱 [排序指南](../howto/sorting.xhtml#sortinghowto) 。
3\.2 新版功能.
`@``functools.``lru_cache`(*maxsize=128*, *typed=False*)一個提供緩存功能的裝飾器，包裝一個函數，緩存其\*maxsize\*組傳入參數，在下次以相同參數調用時直接返回上一次的結果。用以節約高開銷或I/O函數的調用時間。
由于使用了字典存儲緩存，所以該函數的固定參數和關鍵字參數必須是可哈希的。
不同模式的參數可能被視為不同從而產生多個緩存項，例如, f(a=1, b=2) 和 f(b=2, a=1) 因其參數順序不同，可能會被緩存兩次。
如果 *maxsize* 設置為 `None` ，LRU功能將被禁用且緩存數量無上限。 *maxsize* 設置為2的冪時可獲得最佳性能。
如果 *typed* 設置為true，不同類型的函數參數將被分別緩存。例如， `f(3)` 和 `f(3.0)` 將被視為不同而分別緩存。
To help measure the effectiveness of the cache and tune the *maxsize*parameter, the wrapped function is instrumented with a `cache_info()`function that returns a [named tuple](../glossary.xhtml#term-named-tuple) showing *hits*, *misses*, *maxsize* and *currsize*. In a multi-threaded environment, the hits and misses are approximate.
該裝飾器也提供了一個用于清理/使緩存失效的函數 `cache_clear()` 。
The original underlying function is accessible through the `__wrapped__` attribute. This is useful for introspection, for bypassing the cache, or for rewrapping the function with a different cache.
“最久未使用算法”（LRU） 緩存 算法鏈接：<[https://en.wikipedia.org/wiki/Cache\_algorithms#Examples](https://en.wikipedia.org/wiki/Cache_algorithms#Examples)> 這個緩存在“最近的調用是即將到來的調用的最佳預測因子”時性能最好，（比如，新聞服務器上最受歡迎的文章傾向于每天更改）。“緩存大小限制”參數保證緩存不會在長時間運行的進程比如說網站服務器上無限制的增加自身的大小。
一般來說，LRU緩存只在當你想要重用之前計算的結果時使用。因此，用它緩存具有副作用的函數、需要在每次調用時創建不同、易變的對象的函數或者諸如time（）或random（）之類的不純函數是沒有意義的。
靜態 Web 內容的 LRU 緩存示例:
```
@lru_cache(maxsize=32)
def get_pep(num):
'Retrieve text of a Python Enhancement Proposal'
resource = 'http://www.python.org/dev/peps/pep-%04d/' % num
try:
with urllib.request.urlopen(resource) as s:
return s.read()
except urllib.error.HTTPError:
return 'Not Found'
>>> for n in 8, 290, 308, 320, 8, 218, 320, 279, 289, 320, 9991:
... pep = get_pep(n)
... print(n, len(pep))
>>> get_pep.cache_info()
CacheInfo(hits=3, misses=8, maxsize=32, currsize=8)
```
Example of efficiently computing [Fibonacci numbers](https://en.wikipedia.org/wiki/Fibonacci_number) \[https://en.wikipedia.org/wiki/Fibonacci\_number\]using a cache to implement a [dynamic programming](https://en.wikipedia.org/wiki/Dynamic_programming) \[https://en.wikipedia.org/wiki/Dynamic\_programming\]technique:
```
@lru_cache(maxsize=None)
def fib(n):
if n < 2:
return n
return fib(n-1) + fib(n-2)
>>> [fib(n) for n in range(16)]
[0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, 233, 377, 610]
>>> fib.cache_info()
CacheInfo(hits=28, misses=16, maxsize=None, currsize=16)
```
3\.2 新版功能.
在 3.3 版更改: 添加 *typed* 選項。
`@``functools.``total_ordering`Given a class defining one or more rich comparison ordering methods, this class decorator supplies the rest. This simplifies the effort involved in specifying all of the possible rich comparison operations:
The class must define one of [`__lt__()`](../reference/datamodel.xhtml#object.__lt__ "object.__lt__"), [`__le__()`](../reference/datamodel.xhtml#object.__le__ "object.__le__"), [`__gt__()`](../reference/datamodel.xhtml#object.__gt__ "object.__gt__"), or [`__ge__()`](../reference/datamodel.xhtml#object.__ge__ "object.__ge__"). In addition, the class should supply an [`__eq__()`](../reference/datamodel.xhtml#object.__eq__ "object.__eq__") method.
例如:
```
@total_ordering
class Student:
def _is_valid_operand(self, other):
return (hasattr(other, "lastname") and
hasattr(other, "firstname"))
def __eq__(self, other):
if not self._is_valid_operand(other):
return NotImplemented
return ((self.lastname.lower(), self.firstname.lower()) ==
(other.lastname.lower(), other.firstname.lower()))
def __lt__(self, other):
if not self._is_valid_operand(other):
return NotImplemented
return ((self.lastname.lower(), self.firstname.lower()) <
(other.lastname.lower(), other.firstname.lower()))
```
注解
While this decorator makes it easy to create well behaved totally ordered types, it *does* come at the cost of slower execution and more complex stack traces for the derived comparison methods. If performance benchmarking indicates this is a bottleneck for a given application, implementing all six rich comparison methods instead is likely to provide an easy speed boost.
3\.2 新版功能.
在 3.4 版更改: Returning NotImplemented from the underlying comparison function for unrecognised types is now supported.
`functools.``partial`(*func*, *\*args*, *\*\*keywords*)Return a new [partial object](#partial-objects) which when called will behave like *func* called with the positional arguments *args*and keyword arguments *keywords*. If more arguments are supplied to the call, they are appended to *args*. If additional keyword arguments are supplied, they extend and override *keywords*. Roughly equivalent to:
```
def partial(func, *args, **keywords):
def newfunc(*fargs, **fkeywords):
newkeywords = keywords.copy()
newkeywords.update(fkeywords)
return func(*args, *fargs, **newkeywords)
newfunc.func = func
newfunc.args = args
newfunc.keywords = keywords
return newfunc
```
The [`partial()`](#functools.partial "functools.partial") is used for partial function application which "freezes" some portion of a function's arguments and/or keywords resulting in a new object with a simplified signature. For example, [`partial()`](#functools.partial "functools.partial") can be used to create a callable that behaves like the [`int()`](functions.xhtml#int "int") function where the *base* argument defaults to two:
```
>>> from functools import partial
>>> basetwo = partial(int, base=2)
>>> basetwo.__doc__ = 'Convert base 2 string to an int.'
>>> basetwo('10010')
18
```
*class* `functools.``partialmethod`(*func*, *\*args*, *\*\*keywords*)Return a new [`partialmethod`](#functools.partialmethod "functools.partialmethod") descriptor which behaves like [`partial`](#functools.partial "functools.partial") except that it is designed to be used as a method definition rather than being directly callable.
*func* must be a [descriptor](../glossary.xhtml#term-descriptor) or a callable (objects which are both, like normal functions, are handled as descriptors).
When *func* is a descriptor (such as a normal Python function, [`classmethod()`](functions.xhtml#classmethod "classmethod"), [`staticmethod()`](functions.xhtml#staticmethod "staticmethod"), `abstractmethod()` or another instance of [`partialmethod`](#functools.partialmethod "functools.partialmethod")), calls to `__get__` are delegated to the underlying descriptor, and an appropriate [partial object](#partial-objects) returned as the result.
When *func* is a non-descriptor callable, an appropriate bound method is created dynamically. This behaves like a normal Python function when used as a method: the *self* argument will be inserted as the first positional argument, even before the *args* and *keywords* supplied to the [`partialmethod`](#functools.partialmethod "functools.partialmethod") constructor.
示例:
```
>>> class Cell(object):
... def __init__(self):
... self._alive = False
... @property
... def alive(self):
... return self._alive
... def set_state(self, state):
... self._alive = bool(state)
... set_alive = partialmethod(set_state, True)
... set_dead = partialmethod(set_state, False)
...
>>> c = Cell()
>>> c.alive
False
>>> c.set_alive()
>>> c.alive
True
```
3\.4 新版功能.
`functools.``reduce`(*function*, *iterable*\[, *initializer*\])Apply *function* of two arguments cumulatively to the items of *sequence*, from left to right, so as to reduce the sequence to a single value. For example, `reduce(lambda x, y: x+y, [1, 2, 3, 4, 5])` calculates `((((1+2)+3)+4)+5)`. The left argument, *x*, is the accumulated value and the right argument, *y*, is the update value from the *sequence*. If the optional *initializer* is present, it is placed before the items of the sequence in the calculation, and serves as a default when the sequence is empty. If *initializer* is not given and *sequence* contains only one item, the first item is returned.
大致相當于：
```
def reduce(function, iterable, initializer=None):
it = iter(iterable)
if initializer is None:
value = next(it)
else:
value = initializer
for element in it:
value = function(value, element)
return value
```
`@``functools.``singledispatch`Transform a function into a [single-dispatch](../glossary.xhtml#term-single-dispatch) [generic function](../glossary.xhtml#term-generic-function).
To define a generic function, decorate it with the `@singledispatch`decorator. Note that the dispatch happens on the type of the first argument, create your function accordingly:
```
>>> from functools import singledispatch
>>> @singledispatch
... def fun(arg, verbose=False):
... if verbose:
... print("Let me just say,", end=" ")
... print(arg)
```
To add overloaded implementations to the function, use the `register()`attribute of the generic function. It is a decorator. For functions annotated with types, the decorator will infer the type of the first argument automatically:
```
>>> @fun.register
... def _(arg: int, verbose=False):
... if verbose:
... print("Strength in numbers, eh?", end=" ")
... print(arg)
...
>>> @fun.register
... def _(arg: list, verbose=False):
... if verbose:
... print("Enumerate this:")
... for i, elem in enumerate(arg):
... print(i, elem)
```
For code which doesn't use type annotations, the appropriate type argument can be passed explicitly to the decorator itself:
```
>>> @fun.register(complex)
... def _(arg, verbose=False):
... if verbose:
... print("Better than complicated.", end=" ")
... print(arg.real, arg.imag)
...
```
To enable registering lambdas and pre-existing functions, the `register()` attribute can be used in a functional form:
```
>>> def nothing(arg, verbose=False):
... print("Nothing.")
...
>>> fun.register(type(None), nothing)
```
The `register()` attribute returns the undecorated function which enables decorator stacking, pickling, as well as creating unit tests for each variant independently:
```
>>> @fun.register(float)
... @fun.register(Decimal)
... def fun_num(arg, verbose=False):
... if verbose:
... print("Half of your number:", end=" ")
... print(arg / 2)
...
>>> fun_num is fun
False
```
When called, the generic function dispatches on the type of the first argument:
```
>>> fun("Hello, world.")
Hello, world.
>>> fun("test.", verbose=True)
Let me just say, test.
>>> fun(42, verbose=True)
Strength in numbers, eh? 42
>>> fun(['spam', 'spam', 'eggs', 'spam'], verbose=True)
Enumerate this:
0 spam
1 spam
2 eggs
3 spam
>>> fun(None)
Nothing.
>>> fun(1.23)
0.615
```
Where there is no registered implementation for a specific type, its method resolution order is used to find a more generic implementation. The original function decorated with `@singledispatch` is registered for the base `object` type, which means it is used if no better implementation is found.
To check which implementation will the generic function choose for a given type, use the `dispatch()` attribute:
```
>>> fun.dispatch(float)
<function fun_num at 0x1035a2840>
>>> fun.dispatch(dict) # note: default implementation
<function fun at 0x103fe0000>
```
To access all registered implementations, use the read-only `registry`attribute:
```
>>> fun.registry.keys()
dict_keys([<class 'NoneType'>, <class 'int'>, <class 'object'>,
<class 'decimal.Decimal'>, <class 'list'>,
<class 'float'>])
>>> fun.registry[float]
<function fun_num at 0x1035a2840>
>>> fun.registry[object]
<function fun at 0x103fe0000>
```
3\.4 新版功能.
在 3.7 版更改: The `register()` attribute supports using type annotations.
`functools.``update_wrapper`(*wrapper*, *wrapped*, *assigned=WRAPPER\_ASSIGNMENTS*, *updated=WRAPPER\_UPDATES*)Update a *wrapper* function to look like the *wrapped* function. The optional arguments are tuples to specify which attributes of the original function are assigned directly to the matching attributes on the wrapper function and which attributes of the wrapper function are updated with the corresponding attributes from the original function. The default values for these arguments are the module level constants `WRAPPER_ASSIGNMENTS` (which assigns to the wrapper function's `__module__`, `__name__`, `__qualname__`, `__annotations__`and `__doc__`, the documentation string) and `WRAPPER_UPDATES` (which updates the wrapper function's `__dict__`, i.e. the instance dictionary).
To allow access to the original function for introspection and other purposes (e.g. bypassing a caching decorator such as [`lru_cache()`](#functools.lru_cache "functools.lru_cache")), this function automatically adds a `__wrapped__` attribute to the wrapper that refers to the function being wrapped.
The main intended use for this function is in [decorator](../glossary.xhtml#term-decorator) functions which wrap the decorated function and return the wrapper. If the wrapper function is not updated, the metadata of the returned function will reflect the wrapper definition rather than the original function definition, which is typically less than helpful.
[`update_wrapper()`](#functools.update_wrapper "functools.update_wrapper") may be used with callables other than functions. Any attributes named in *assigned* or *updated* that are missing from the object being wrapped are ignored (i.e. this function will not attempt to set them on the wrapper function). [`AttributeError`](exceptions.xhtml#AttributeError "AttributeError") is still raised if the wrapper function itself is missing any attributes named in *updated*.
3\.2 新版功能: Automatic addition of the `__wrapped__` attribute.
3\.2 新版功能: Copying of the `__annotations__` attribute by default.
在 3.2 版更改: Missing attributes no longer trigger an [`AttributeError`](exceptions.xhtml#AttributeError "AttributeError").
在 3.4 版更改: The `__wrapped__` attribute now always refers to the wrapped function, even if that function defined a `__wrapped__` attribute. (see [bpo-17482](https://bugs.python.org/issue17482) \[https://bugs.python.org/issue17482\])
`@``functools.``wraps`(*wrapped*, *assigned=WRAPPER\_ASSIGNMENTS*, *updated=WRAPPER\_UPDATES*)This is a convenience function for invoking [`update_wrapper()`](#functools.update_wrapper "functools.update_wrapper") as a function decorator when defining a wrapper function. It is equivalent to `partial(update_wrapper, wrapped=wrapped, assigned=assigned, updated=updated)`. For example:
```
>>> from functools import wraps
>>> def my_decorator(f):
... @wraps(f)
... def wrapper(*args, **kwds):
... print('Calling decorated function')
... return f(*args, **kwds)
... return wrapper
...
>>> @my_decorator
... def example():
... """Docstring"""
... print('Called example function')
...
>>> example()
Calling decorated function
Called example function
>>> example.__name__
'example'
>>> example.__doc__
'Docstring'
```
Without the use of this decorator factory, the name of the example function would have been `'wrapper'`, and the docstring of the original `example()`would have been lost.
## [`partial`](#functools.partial "functools.partial") Objects
[`partial`](#functools.partial "functools.partial") objects are callable objects created by [`partial()`](#functools.partial "functools.partial"). They have three read-only attributes:
`partial.``func`A callable object or function. Calls to the [`partial`](#functools.partial "functools.partial") object will be forwarded to [`func`](#functools.partial.func "functools.partial.func") with new arguments and keywords.
`partial.``args`The leftmost positional arguments that will be prepended to the positional arguments provided to a [`partial`](#functools.partial "functools.partial") object call.
`partial.``keywords`The keyword arguments that will be supplied when the [`partial`](#functools.partial "functools.partial") object is called.
[`partial`](#functools.partial "functools.partial") objects are like `function` objects in that they are callable, weak referencable, and can have attributes. There are some important differences. For instance, the [`__name__`](stdtypes.xhtml#definition.__name__ "definition.__name__") and `__doc__` attributes are not created automatically. Also, [`partial`](#functools.partial "functools.partial") objects defined in classes behave like static methods and do not transform into bound methods during instance attribute look-up.
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- Python文檔內容
- Python 有什么新變化？
- Python 3.7 有什么新變化
- 摘要 - 發布重點
- 新的特性
- 其他語言特性修改
- 新增模塊
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- C API 的改變
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- 平臺支持的移除
- API 與特性的移除
- 移除的模塊
- Windows 專屬的改變
- 移植到 Python 3.7
- Python 3.7.1 中的重要變化
- Python 3.7.2 中的重要變化
- Python 3.6 有什么新變化A
- 摘要 - 發布重點
- 新的特性
- 其他語言特性修改
- 新增模塊
- 改進的模塊
- 性能優化
- Build and C API Changes
- 其他改進
- 棄用
- 移除
- 移植到Python 3.6
- Python 3.6.2 中的重要變化
- Python 3.6.4 中的重要變化
- Python 3.6.5 中的重要變化
- Python 3.6.7 中的重要變化
- Python 3.5 有什么新變化
- 摘要 - 發布重點
- 新的特性
- 其他語言特性修改
- 新增模塊
- 改進的模塊
- Other module-level changes
- 性能優化
- Build and C API Changes
- 棄用
- 移除
- Porting to Python 3.5
- Notable changes in Python 3.5.4
- What's New In Python 3.4
- 摘要 - 發布重點
- 新的特性
- 新增模塊
- 改進的模塊
- CPython Implementation Changes
- 棄用
- 移除
- Porting to Python 3.4
- Changed in 3.4.3
- What's New In Python 3.3
- 摘要 - 發布重點
- PEP 405: Virtual Environments
- PEP 420: Implicit Namespace Packages
- PEP 3118: New memoryview implementation and buffer protocol documentation
- PEP 393: Flexible String Representation
- PEP 397: Python Launcher for Windows
- PEP 3151: Reworking the OS and IO exception hierarchy
- PEP 380: Syntax for Delegating to a Subgenerator
- PEP 409: Suppressing exception context
- PEP 414: Explicit Unicode literals
- PEP 3155: Qualified name for classes and functions
- PEP 412: Key-Sharing Dictionary
- PEP 362: Function Signature Object
- PEP 421: Adding sys.implementation
- Using importlib as the Implementation of Import
- 其他語言特性修改
- A Finer-Grained Import Lock
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- 新增模塊
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- Build and C API Changes
- 棄用
- Porting to Python 3.3
- What's New In Python 3.2
- PEP 384: Defining a Stable ABI
- PEP 389: Argparse Command Line Parsing Module
- PEP 391: Dictionary Based Configuration for Logging
- PEP 3148: The concurrent.futures module
- PEP 3147: PYC Repository Directories
- PEP 3149: ABI Version Tagged .so Files
- PEP 3333: Python Web Server Gateway Interface v1.0.1
- 其他語言特性修改
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- 多線程
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- Unicode
- Codecs
- 文檔
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- Build and C API Changes
- Porting to Python 3.2
- What's New In Python 3.1
- PEP 372: Ordered Dictionaries
- PEP 378: Format Specifier for Thousands Separator
- 其他語言特性修改
- New, Improved, and Deprecated Modules
- 性能優化
- IDLE
- Build and C API Changes
- Porting to Python 3.1
- What's New In Python 3.0
- Common Stumbling Blocks
- Overview Of Syntax Changes
- Changes Already Present In Python 2.6
- Library Changes
- PEP 3101: A New Approach To String Formatting
- Changes To Exceptions
- Miscellaneous Other Changes
- Build and C API Changes
- 性能
- Porting To Python 3.0
- What's New in Python 2.7
- The Future for Python 2.x
- Changes to the Handling of Deprecation Warnings
- Python 3.1 Features
- PEP 372: Adding an Ordered Dictionary to collections
- PEP 378: Format Specifier for Thousands Separator
- PEP 389: The argparse Module for Parsing Command Lines
- PEP 391: Dictionary-Based Configuration For Logging
- PEP 3106: Dictionary Views
- PEP 3137: The memoryview Object
- 其他語言特性修改
- New and Improved Modules
- Build and C API Changes
- Other Changes and Fixes
- Porting to Python 2.7
- New Features Added to Python 2.7 Maintenance Releases
- Acknowledgements
- Python 2.6 有什么新變化
- Python 3.0
- Changes to the Development Process
- PEP 343: The 'with' statement
- PEP 366: Explicit Relative Imports From a Main Module
- PEP 370: Per-user site-packages Directory
- PEP 371: The multiprocessing Package
- PEP 3101: Advanced String Formatting
- PEP 3105: print As a Function
- PEP 3110: Exception-Handling Changes
- PEP 3112: Byte Literals
- PEP 3116: New I/O Library
- PEP 3118: Revised Buffer Protocol
- PEP 3119: Abstract Base Classes
- PEP 3127: Integer Literal Support and Syntax
- PEP 3129: Class Decorators
- PEP 3141: A Type Hierarchy for Numbers
- 其他語言特性修改
- New and Improved Modules
- Deprecations and Removals
- Build and C API Changes
- Porting to Python 2.6
- Acknowledgements
- What's New in Python 2.5
- PEP 308: Conditional Expressions
- PEP 309: Partial Function Application
- PEP 314: Metadata for Python Software Packages v1.1
- PEP 328: Absolute and Relative Imports
- PEP 338: Executing Modules as Scripts
- PEP 341: Unified try/except/finally
- PEP 342: New Generator Features
- PEP 343: The 'with' statement
- PEP 352: Exceptions as New-Style Classes
- PEP 353: Using ssize_t as the index type
- PEP 357: The 'index' method
- 其他語言特性修改
- New, Improved, and Removed Modules
- Build and C API Changes
- Porting to Python 2.5
- Acknowledgements
- What's New in Python 2.4
- PEP 218: Built-In Set Objects
- PEP 237: Unifying Long Integers and Integers
- PEP 289: Generator Expressions
- PEP 292: Simpler String Substitutions
- PEP 318: Decorators for Functions and Methods
- PEP 322: Reverse Iteration
- PEP 324: New subprocess Module
- PEP 327: Decimal Data Type
- PEP 328: Multi-line Imports
- PEP 331: Locale-Independent Float/String Conversions
- 其他語言特性修改
- New, Improved, and Deprecated Modules
- Build and C API Changes
- Porting to Python 2.4
- Acknowledgements
- What's New in Python 2.3
- PEP 218: A Standard Set Datatype
- PEP 255: Simple Generators
- PEP 263: Source Code Encodings
- PEP 273: Importing Modules from ZIP Archives
- PEP 277: Unicode file name support for Windows NT
- PEP 278: Universal Newline Support
- PEP 279: enumerate()
- PEP 282: The logging Package
- PEP 285: A Boolean Type
- PEP 293: Codec Error Handling Callbacks
- PEP 301: Package Index and Metadata for Distutils
- PEP 302: New Import Hooks
- PEP 305: Comma-separated Files
- PEP 307: Pickle Enhancements
- Extended Slices
- 其他語言特性修改
- New, Improved, and Deprecated Modules
- Pymalloc: A Specialized Object Allocator
- Build and C API Changes
- Other Changes and Fixes
- Porting to Python 2.3
- Acknowledgements
- What's New in Python 2.2
- 概述
- PEPs 252 and 253: Type and Class Changes
- PEP 234: Iterators
- PEP 255: Simple Generators
- PEP 237: Unifying Long Integers and Integers
- PEP 238: Changing the Division Operator
- Unicode Changes
- PEP 227: Nested Scopes
- New and Improved Modules
- Interpreter Changes and Fixes
- Other Changes and Fixes
- Acknowledgements
- What's New in Python 2.1
- 概述
- PEP 227: Nested Scopes
- PEP 236: future Directives
- PEP 207: Rich Comparisons
- PEP 230: Warning Framework
- PEP 229: New Build System
- PEP 205: Weak References
- PEP 232: Function Attributes
- PEP 235: Importing Modules on Case-Insensitive Platforms
- PEP 217: Interactive Display Hook
- PEP 208: New Coercion Model
- PEP 241: Metadata in Python Packages
- New and Improved Modules
- Other Changes and Fixes
- Acknowledgements
- What's New in Python 2.0
- 概述
- What About Python 1.6?
- New Development Process
- Unicode
- 列表推導式
- Augmented Assignment
- 字符串的方法
- Garbage Collection of Cycles
- Other Core Changes
- Porting to 2.0
- Extending/Embedding Changes
- Distutils: Making Modules Easy to Install
- XML Modules
- Module changes
- New modules
- IDLE Improvements
- Deleted and Deprecated Modules
- Acknowledgements
- 更新日志
- Python 下一版
- Python 3.7.3 最終版
- Python 3.7.3 發布候選版 1
- Python 3.7.2 最終版
- Python 3.7.2 發布候選版 1
- Python 3.7.1 最終版
- Python 3.7.1 RC 2版本
- Python 3.7.1 發布候選版 1
- Python 3.7.0 正式版
- Python 3.7.0 release candidate 1
- Python 3.7.0 beta 5
- Python 3.7.0 beta 4
- Python 3.7.0 beta 3
- Python 3.7.0 beta 2
- Python 3.7.0 beta 1
- Python 3.7.0 alpha 4
- Python 3.7.0 alpha 3
- Python 3.7.0 alpha 2
- Python 3.7.0 alpha 1
- Python 3.6.6 final
- Python 3.6.6 RC 1
- Python 3.6.5 final
- Python 3.6.5 release candidate 1
- Python 3.6.4 final
- Python 3.6.4 release candidate 1
- Python 3.6.3 final
- Python 3.6.3 release candidate 1
- Python 3.6.2 final
- Python 3.6.2 release candidate 2
- Python 3.6.2 release candidate 1
- Python 3.6.1 final
- Python 3.6.1 release candidate 1
- Python 3.6.0 final
- Python 3.6.0 release candidate 2
- Python 3.6.0 release candidate 1
- Python 3.6.0 beta 4
- Python 3.6.0 beta 3
- Python 3.6.0 beta 2
- Python 3.6.0 beta 1
- Python 3.6.0 alpha 4
- Python 3.6.0 alpha 3
- Python 3.6.0 alpha 2
- Python 3.6.0 alpha 1
- Python 3.5.5 final
- Python 3.5.5 release candidate 1
- Python 3.5.4 final
- Python 3.5.4 release candidate 1
- Python 3.5.3 final
- Python 3.5.3 release candidate 1
- Python 3.5.2 final
- Python 3.5.2 release candidate 1
- Python 3.5.1 final
- Python 3.5.1 release candidate 1
- Python 3.5.0 final
- Python 3.5.0 release candidate 4
- Python 3.5.0 release candidate 3
- Python 3.5.0 release candidate 2
- Python 3.5.0 release candidate 1
- Python 3.5.0 beta 4
- Python 3.5.0 beta 3
- Python 3.5.0 beta 2
- Python 3.5.0 beta 1
- Python 3.5.0 alpha 4
- Python 3.5.0 alpha 3
- Python 3.5.0 alpha 2
- Python 3.5.0 alpha 1
- Python 教程
- 課前甜點
- 使用 Python 解釋器
- 調用解釋器
- 解釋器的運行環境
- Python 的非正式介紹
- Python 作為計算器使用
- 走向編程的第一步
- 其他流程控制工具
- if 語句
- for 語句
- range() 函數
- break 和 continue 語句，以及循環中的 else 子句
- pass 語句
- 定義函數
- 函數定義的更多形式
- 小插曲：編碼風格
- 數據結構
- 列表的更多特性
- del 語句
- 元組和序列
- 集合
- 字典
- 循環的技巧
- 深入條件控制
- 序列和其它類型的比較
- 模塊
- 有關模塊的更多信息
- 標準模塊
- dir() 函數
- 包
- 輸入輸出
- 更漂亮的輸出格式
- 讀寫文件
- 錯誤和異常
- 語法錯誤
- 異常
- 處理異常
- 拋出異常
- 用戶自定義異常
- 定義清理操作
- 預定義的清理操作
- 類
- 名稱和對象
- Python 作用域和命名空間
- 初探類
- 補充說明
- 繼承
- 私有變量
- 雜項說明
- 迭代器
- 生成器
- 生成器表達式
- 標準庫簡介
- 操作系統接口
- 文件通配符
- 命令行參數
- 錯誤輸出重定向和程序終止
- 字符串模式匹配
- 數學
- 互聯網訪問
- 日期和時間
- 數據壓縮
- 性能測量
- 質量控制
- 自帶電池
- 標準庫簡介 —— 第二部分
- 格式化輸出
- 模板
- 使用二進制數據記錄格式
- 多線程
- 日志
- 弱引用
- 用于操作列表的工具
- 十進制浮點運算
- 虛擬環境和包
- 概述
- 創建虛擬環境
- 使用pip管理包
- 接下來？
- 交互式編輯和編輯歷史
- Tab 補全和編輯歷史
- 默認交互式解釋器的替代品
- 浮點算術：爭議和限制
- 表示性錯誤
- 附錄
- 交互模式
- 安裝和使用 Python
- 命令行與環境
- 命令行
- 環境變量
- 在Unix平臺中使用Python
- 獲取最新版本的Python
- 構建Python
- 與Python相關的路徑和文件
- 雜項
- 編輯器和集成開發環境
- 在Windows上使用 Python
- 完整安裝程序
- Microsoft Store包
- nuget.org 安裝包
- 可嵌入的包
- 替代捆綁包
- 配置Python
- 適用于Windows的Python啟動器
- 查找模塊
- 附加模塊
- 在Windows上編譯Python
- 其他平臺
- 在蘋果系統上使用 Python
- 獲取和安裝 MacPython
- IDE
- 安裝額外的 Python 包
- Mac 上的圖形界面編程
- 在 Mac 上分發 Python 應用程序
- 其他資源
- Python 語言參考
- 概述
- 其他實現
- 標注
- 詞法分析
- 行結構
- 其他形符
- 標識符和關鍵字
- 字面值
- 運算符
- 分隔符
- 數據模型
- 對象、值與類型
- 標準類型層級結構
- 特殊方法名稱
- 協程
- 執行模型
- 程序的結構
- 命名與綁定
- 異常
- 導入系統
- importlib
- 包
- 搜索
- 加載
- 基于路徑的查找器
- 替換標準導入系統
- Package Relative Imports
- 有關 main 的特殊事項
- 開放問題項
- 參考文獻
- 表達式
- 算術轉換
- 原子
- 原型
- await 表達式
- 冪運算符
- 一元算術和位運算
- 二元算術運算符
- 移位運算
- 二元位運算
- 比較運算
- 布爾運算
- 條件表達式
- lambda 表達式
- 表達式列表
- 求值順序
- 運算符優先級
- 簡單語句
- 表達式語句
- 賦值語句
- assert 語句
- pass 語句
- del 語句
- return 語句
- yield 語句
- raise 語句
- break 語句
- continue 語句
- import 語句
- global 語句
- nonlocal 語句
- 復合語句
- if 語句
- while 語句
- for 語句
- try 語句
- with 語句
- 函數定義
- 類定義
- 協程
- 最高層級組件
- 完整的 Python 程序
- 文件輸入
- 交互式輸入
- 表達式輸入
- 完整的語法規范
- Python 標準庫
- 概述
- 可用性注釋
- 內置函數
- 內置常量
- 由 site 模塊添加的常量
- 內置類型
- 邏輯值檢測
- 布爾運算 — and, or, not
- 比較
- 數字類型 — int, float, complex
- 迭代器類型
- 序列類型 — list, tuple, range
- 文本序列類型 — str
- 二進制序列類型 — bytes, bytearray, memoryview
- 集合類型 — set, frozenset
- 映射類型 — dict
- 上下文管理器類型
- 其他內置類型
- 特殊屬性
- 內置異常
- 基類
- 具體異常
- 警告
- 異常層次結構
- 文本處理服務
- string — 常見的字符串操作
- re — 正則表達式操作
- 模塊 difflib 是一個計算差異的助手
- textwrap — Text wrapping and filling
- unicodedata — Unicode 數據庫
- stringprep — Internet String Preparation
- readline — GNU readline interface
- rlcompleter — GNU readline的完成函數
- 二進制數據服務
- struct — Interpret bytes as packed binary data
- codecs — Codec registry and base classes
- 數據類型
- datetime — 基礎日期/時間數據類型
- calendar — General calendar-related functions
- collections — 容器數據類型
- collections.abc — 容器的抽象基類
- heapq — 堆隊列算法
- bisect — Array bisection algorithm
- array — Efficient arrays of numeric values
- weakref — 弱引用
- types — Dynamic type creation and names for built-in types
- copy — 淺層 (shallow) 和深層 (deep) 復制操作
- pprint — 數據美化輸出
- reprlib — Alternate repr() implementation
- enum — Support for enumerations
- 數字和數學模塊
- numbers — 數字的抽象基類
- math — 數學函數
- cmath — Mathematical functions for complex numbers
- decimal — 十進制定點和浮點運算
- fractions — 分數
- random — 生成偽隨機數
- statistics — Mathematical statistics functions
- 函數式編程模塊
- itertools — 為高效循環而創建迭代器的函數
- functools — 高階函數和可調用對象上的操作
- operator — 標準運算符替代函數
- 文件和目錄訪問
- pathlib — 面向對象的文件系統路徑
- os.path — 常見路徑操作
- fileinput — Iterate over lines from multiple input streams
- stat — Interpreting stat() results
- filecmp — File and Directory Comparisons
- tempfile — Generate temporary files and directories
- glob — Unix style pathname pattern expansion
- fnmatch — Unix filename pattern matching
- linecache — Random access to text lines
- shutil — High-level file operations
- macpath — Mac OS 9 路徑操作函數
- 數據持久化
- pickle —— Python 對象序列化
- copyreg — Register pickle support functions
- shelve — Python object persistence
- marshal — Internal Python object serialization
- dbm — Interfaces to Unix “databases”
- sqlite3 — SQLite 數據庫 DB-API 2.0 接口模塊
- 數據壓縮和存檔
- zlib — 與 gzip 兼容的壓縮
- gzip — 對 gzip 格式的支持
- bz2 — 對 bzip2 壓縮算法的支持
- lzma — 用 LZMA 算法壓縮
- zipfile — 在 ZIP 歸檔中工作
- tarfile — Read and write tar archive files
- 文件格式
- csv — CSV 文件讀寫
- configparser — Configuration file parser
- netrc — netrc file processing
- xdrlib — Encode and decode XDR data
- plistlib — Generate and parse Mac OS X .plist files
- 加密服務
- hashlib — 安全哈希與消息摘要
- hmac — 基于密鑰的消息驗證
- secrets — Generate secure random numbers for managing secrets
- 通用操作系統服務
- os — 操作系統接口模塊
- io — 處理流的核心工具
- time — 時間的訪問和轉換
- argparse — 命令行選項、參數和子命令解析器
- getopt — C-style parser for command line options
- 模塊 logging — Python 的日志記錄工具
- logging.config — 日志記錄配置
- logging.handlers — Logging handlers
- getpass — 便攜式密碼輸入工具
- curses — 終端字符單元顯示的處理
- curses.textpad — Text input widget for curses programs
- curses.ascii — Utilities for ASCII characters
- curses.panel — A panel stack extension for curses
- platform — Access to underlying platform's identifying data
- errno — Standard errno system symbols
- ctypes — Python 的外部函數庫
- 并發執行
- threading — 基于線程的并行
- multiprocessing — 基于進程的并行
- concurrent 包
- concurrent.futures — 啟動并行任務
- subprocess — 子進程管理
- sched — 事件調度器
- queue — 一個同步的隊列類
- _thread — 底層多線程 API
- _dummy_thread — _thread 的替代模塊
- dummy_threading — 可直接替代 threading 模塊。
- contextvars — Context Variables
- Context Variables
- Manual Context Management
- asyncio support
- 網絡和進程間通信
- asyncio — 異步 I/O
- socket — 底層網絡接口
- ssl — TLS/SSL wrapper for socket objects
- select — Waiting for I/O completion
- selectors — 高級 I/O 復用庫
- asyncore — 異步socket處理器
- asynchat — 異步 socket 指令/響應 處理器
- signal — Set handlers for asynchronous events
- mmap — Memory-mapped file support
- 互聯網數據處理
- email — 電子郵件與 MIME 處理包
- json — JSON 編碼和解碼器
- mailcap — Mailcap file handling
- mailbox — Manipulate mailboxes in various formats
- mimetypes — Map filenames to MIME types
- base64 — Base16, Base32, Base64, Base85 數據編碼
- binhex — 對binhex4文件進行編碼和解碼
- binascii — 二進制和 ASCII 碼互轉
- quopri — Encode and decode MIME quoted-printable data
- uu — Encode and decode uuencode files
- 結構化標記處理工具
- html — 超文本標記語言支持
- html.parser — 簡單的 HTML 和 XHTML 解析器
- html.entities — HTML 一般實體的定義
- XML處理模塊
- xml.etree.ElementTree — The ElementTree XML API
- xml.dom — The Document Object Model API
- xml.dom.minidom — Minimal DOM implementation
- xml.dom.pulldom — Support for building partial DOM trees
- xml.sax — Support for SAX2 parsers
- xml.sax.handler — Base classes for SAX handlers
- xml.sax.saxutils — SAX Utilities
- xml.sax.xmlreader — Interface for XML parsers
- xml.parsers.expat — Fast XML parsing using Expat
- 互聯網協議和支持
- webbrowser — 方便的Web瀏覽器控制器
- cgi — Common Gateway Interface support
- cgitb — Traceback manager for CGI scripts
- wsgiref — WSGI Utilities and Reference Implementation
- urllib — URL 處理模塊
- urllib.request — 用于打開 URL 的可擴展庫
- urllib.response — Response classes used by urllib
- urllib.parse — Parse URLs into components
- urllib.error — Exception classes raised by urllib.request
- urllib.robotparser — Parser for robots.txt
- http — HTTP 模塊
- http.client — HTTP協議客戶端
- ftplib — FTP protocol client
- poplib — POP3 protocol client
- imaplib — IMAP4 protocol client
- nntplib — NNTP protocol client
- smtplib —SMTP協議客戶端
- smtpd — SMTP Server
- telnetlib — Telnet client
- uuid — UUID objects according to RFC 4122
- socketserver — A framework for network servers
- http.server — HTTP 服務器
- http.cookies — HTTP state management
- http.cookiejar — Cookie handling for HTTP clients
- xmlrpc — XMLRPC 服務端與客戶端模塊
- xmlrpc.client — XML-RPC client access
- xmlrpc.server — Basic XML-RPC servers
- ipaddress — IPv4/IPv6 manipulation library
- 多媒體服務
- audioop — Manipulate raw audio data
- aifc — Read and write AIFF and AIFC files
- sunau — 讀寫 Sun AU 文件
- wave — 讀寫WAV格式文件
- chunk — Read IFF chunked data
- colorsys — Conversions between color systems
- imghdr — 推測圖像類型
- sndhdr — 推測聲音文件的類型
- ossaudiodev — Access to OSS-compatible audio devices
- 國際化
- gettext — 多語種國際化服務
- locale — 國際化服務
- 程序框架
- turtle — 海龜繪圖
- cmd — 支持面向行的命令解釋器
- shlex — Simple lexical analysis
- Tk圖形用戶界面(GUI)
- tkinter — Tcl/Tk的Python接口
- tkinter.ttk — Tk themed widgets
- tkinter.tix — Extension widgets for Tk
- tkinter.scrolledtext — 滾動文字控件
- IDLE
- 其他圖形用戶界面（GUI）包
- 開發工具
- typing — 類型標注支持
- pydoc — Documentation generator and online help system
- doctest — Test interactive Python examples
- unittest — 單元測試框架
- unittest.mock — mock object library
- unittest.mock 上手指南
- 2to3 - 自動將 Python 2 代碼轉為 Python 3 代碼
- test — Regression tests package for Python
- test.support — Utilities for the Python test suite
- test.support.script_helper — Utilities for the Python execution tests
- 調試和分析
- bdb — Debugger framework
- faulthandler — Dump the Python traceback
- pdb — The Python Debugger
- The Python Profilers
- timeit — 測量小代碼片段的執行時間
- trace — Trace or track Python statement execution
- tracemalloc — Trace memory allocations
- 軟件打包和分發
- distutils — 構建和安裝 Python 模塊
- ensurepip — Bootstrapping the pip installer
- venv — 創建虛擬環境
- zipapp — Manage executable Python zip archives
- Python運行時服務
- sys — 系統相關的參數和函數
- sysconfig — Provide access to Python's configuration information
- builtins — 內建對象
- main — 頂層腳本環境
- warnings — Warning control
- dataclasses — 數據類
- contextlib — Utilities for with-statement contexts
- abc — 抽象基類
- atexit — 退出處理器
- traceback — Print or retrieve a stack traceback
- future — Future 語句定義
- gc — 垃圾回收器接口
- inspect — 檢查對象
- site — Site-specific configuration hook
- 自定義 Python 解釋器
- code — Interpreter base classes
- codeop — Compile Python code
- 導入模塊
- zipimport — Import modules from Zip archives
- pkgutil — Package extension utility
- modulefinder — 查找腳本使用的模塊
- runpy — Locating and executing Python modules
- importlib — The implementation of import
- Python 語言服務
- parser — Access Python parse trees
- ast — 抽象語法樹
- symtable — Access to the compiler's symbol tables
- symbol — 與 Python 解析樹一起使用的常量
- token — 與Python解析樹一起使用的常量
- keyword — 檢驗Python關鍵字
- tokenize — Tokenizer for Python source
- tabnanny — 模糊縮進檢測
- pyclbr — Python class browser support
- py_compile — Compile Python source files
- compileall — Byte-compile Python libraries
- dis — Python 字節碼反匯編器
- pickletools — Tools for pickle developers
- 雜項服務
- formatter — Generic output formatting
- Windows系統相關模塊
- msilib — Read and write Microsoft Installer files
- msvcrt — Useful routines from the MS VC++ runtime
- winreg — Windows 注冊表訪問
- winsound — Sound-playing interface for Windows
- Unix 專有服務
- posix — The most common POSIX system calls
- pwd — 用戶密碼數據庫
- spwd — The shadow password database
- grp — The group database
- crypt — Function to check Unix passwords
- termios — POSIX style tty control
- tty — 終端控制功能
- pty — Pseudo-terminal utilities
- fcntl — The fcntl and ioctl system calls
- pipes — Interface to shell pipelines
- resource — Resource usage information
- nis — Interface to Sun's NIS (Yellow Pages)
- Unix syslog 庫例程
- 被取代的模塊
- optparse — Parser for command line options
- imp — Access the import internals
- 未創建文檔的模塊
- 平臺特定模塊
- 擴展和嵌入 Python 解釋器
- 推薦的第三方工具
- 不使用第三方工具創建擴展
- 使用 C 或 C++ 擴展 Python
- 自定義擴展類型：教程
- 定義擴展類型：已分類主題
- 構建C/C++擴展
- 在Windows平臺編譯C和C++擴展
- 在更大的應用程序中嵌入 CPython 運行時
- Embedding Python in Another Application
- Python/C API 參考手冊
- 概述
- 代碼標準
- 包含文件
- 有用的宏
- 對象、類型和引用計數
- 異常
- 嵌入Python
- 調試構建
- 穩定的應用程序二進制接口
- The Very High Level Layer
- Reference Counting
- 異常處理
- Printing and clearing
- 拋出異常
- Issuing warnings
- Querying the error indicator
- Signal Handling
- Exception Classes
- Exception Objects
- Unicode Exception Objects
- Recursion Control
- 標準異常
- 標準警告類別
- 工具
- 操作系統實用程序
- 系統功能
- 過程控制
- 導入模塊
- Data marshalling support
- 語句解釋及變量編譯
- 字符串轉換與格式化
- 反射
- 編解碼器注冊與支持功能
- 抽象對象層
- Object Protocol
- 數字協議
- Sequence Protocol
- Mapping Protocol
- 迭代器協議
- 緩沖協議
- Old Buffer Protocol
- 具體的對象層
- 基本對象
- 數值對象
- 序列對象
- 容器對象
- 函數對象
- 其他對象
- Initialization, Finalization, and Threads
- 在Python初始化之前
- 全局配置變量
- Initializing and finalizing the interpreter
- Process-wide parameters
- Thread State and the Global Interpreter Lock
- Sub-interpreter support
- Asynchronous Notifications
- Profiling and Tracing
- Advanced Debugger Support
- Thread Local Storage Support
- 內存管理
- 概述
- 原始內存接口
- Memory Interface
- 對象分配器
- 默認內存分配器
- Customize Memory Allocators
- The pymalloc allocator
- tracemalloc C API
- 示例
- 對象實現支持
- 在堆中分配對象
- Common Object Structures
- Type 對象
- Number Object Structures
- Mapping Object Structures
- Sequence Object Structures
- Buffer Object Structures
- Async Object Structures
- 使對象類型支持循環垃圾回收
- API 和 ABI 版本管理
- 分發 Python 模塊
- 關鍵術語
- 開源許可與協作
- 安裝工具
- 閱讀指南
- 我該如何...？
- ...為我的項目選擇一個名字？
- ...創建和分發二進制擴展？
- 安裝 Python 模塊
- 關鍵術語
- 基本使用
- 我應如何 ...？
- ... 在 Python 3.4 之前的 Python 版本中安裝 pip ？
- ... 只為當前用戶安裝軟件包？
- ... 安裝科學計算類 Python 軟件包？
- ... 使用并行安裝的多個 Python 版本？
- 常見的安裝問題
- 在 Linux 的系統 Python 版本上安裝
- 未安裝 pip
- 安裝二進制編譯擴展
- Python 常用指引
- 將 Python 2 代碼遷移到 Python 3
- 簡要說明
- 詳情
- 將擴展模塊移植到 Python 3
- 條件編譯
- 對象API的更改
- 模塊初始化和狀態
- CObject 替換為 Capsule
- 其他選項
- Curses Programming with Python
- What is curses?
- Starting and ending a curses application
- Windows and Pads
- Displaying Text
- User Input
- For More Information
- 實現描述器
- 摘要
- 定義和簡介
- 描述器協議
- 發起調用描述符
- 描述符示例
- Properties
- 函數和方法
- Static Methods and Class Methods
- 函數式編程指引
- 概述
- 迭代器
- 生成器表達式和列表推導式
- 生成器
- 內置函數
- itertools 模塊
- The functools module
- Small functions and the lambda expression
- Revision History and Acknowledgements
- 引用文獻
- 日志 HOWTO
- 日志基礎教程
- 進階日志教程
- 日志級別
- 有用的處理程序
- 記錄日志中引發的異常
- 使用任意對象作為消息
- 優化
- 日志操作手冊
- 在多個模塊中使用日志
- 在多線程中使用日志
- 使用多個日志處理器和多種格式化
- 在多個地方記錄日志
- 日志服務器配置示例
- 處理日志處理器的阻塞
- Sending and receiving logging events across a network
- Adding contextual information to your logging output
- Logging to a single file from multiple processes
- Using file rotation
- Use of alternative formatting styles
- Customizing LogRecord
- Subclassing QueueHandler - a ZeroMQ example
- Subclassing QueueListener - a ZeroMQ example
- An example dictionary-based configuration
- Using a rotator and namer to customize log rotation processing
- A more elaborate multiprocessing example
- Inserting a BOM into messages sent to a SysLogHandler
- Implementing structured logging
- Customizing handlers with dictConfig()
- Using particular formatting styles throughout your application
- Configuring filters with dictConfig()
- Customized exception formatting
- Speaking logging messages
- Buffering logging messages and outputting them conditionally
- Formatting times using UTC (GMT) via configuration
- Using a context manager for selective logging
- 正則表達式HOWTO
- 概述
- 簡單模式
- 使用正則表達式
- 更多模式能力
- 修改字符串
- 常見問題
- 反饋
- 套接字編程指南
- 套接字
- 創建套接字
- 使用一個套接字
- 斷開連接
- 非阻塞的套接字
- 排序指南
- 基本排序
- 關鍵函數
- Operator 模塊函數
- 升序和降序
- 排序穩定性和排序復雜度
- 使用裝飾-排序-去裝飾的舊方法
- 使用 cmp 參數的舊方法
- 其它
- Unicode 指南
- Unicode 概述
- Python's Unicode Support
- Reading and Writing Unicode Data
- Acknowledgements
- 如何使用urllib包獲取網絡資源
- 概述
- Fetching URLs
- 處理異常
- info and geturl
- Openers and Handlers
- Basic Authentication
- Proxies
- Sockets and Layers
- 腳注
- Argparse 教程
- 概念
- 基礎
- 位置參數介紹
- Introducing Optional arguments
- Combining Positional and Optional arguments
- Getting a little more advanced
- Conclusion
- ipaddress模塊介紹
- 創建 Address/Network/Interface 對象
- 審查 Address/Network/Interface 對象
- Network 作為 Address 列表
- 比較
- 將IP地址與其他模塊一起使用
- 實例創建失敗時獲取更多詳細信息
- Argument Clinic How-To
- The Goals Of Argument Clinic
- Basic Concepts And Usage
- Converting Your First Function
- Advanced Topics
- 使用 DTrace 和 SystemTap 檢測CPython
- Enabling the static markers
- Static DTrace probes
- Static SystemTap markers
- Available static markers
- SystemTap Tapsets
- 示例
- Python 常見問題
- Python常見問題
- 一般信息
- 現實世界中的 Python
- 編程常見問題
- 一般問題
- 核心語言
- 數字和字符串
- 性能
- 序列（元組/列表）
- 對象
- 模塊
- 設計和歷史常見問題
- 為什么Python使用縮進來分組語句？
- 為什么簡單的算術運算得到奇怪的結果？
- 為什么浮點計算不準確？
- 為什么Python字符串是不可變的？
- 為什么必須在方法定義和調用中顯式使用“self”？
- 為什么不能在表達式中賦值？
- 為什么Python對某些功能（例如list.index()）使用方法來實現，而其他功能（例如len(List)）使用函數實現？
- 為什么 join()是一個字符串方法而不是列表或元組方法？
- 異常有多快？
- 為什么Python中沒有switch或case語句？
- 難道不能在解釋器中模擬線程，而非得依賴特定于操作系統的線程實現嗎？
- 為什么lambda表達式不能包含語句？
- 可以將Python編譯為機器代碼，C或其他語言嗎？
- Python如何管理內存？
- 為什么CPython不使用更傳統的垃圾回收方案？
- CPython退出時為什么不釋放所有內存？
- 為什么有單獨的元組和列表數據類型？
- 列表是如何在CPython中實現的？
- 字典是如何在CPython中實現的？
- 為什么字典key必須是不可變的？
- 為什么 list.sort() 沒有返回排序列表？
- 如何在Python中指定和實施接口規范？
- 為什么沒有goto？
- 為什么原始字符串（r-strings）不能以反斜杠結尾？
- 為什么Python沒有屬性賦值的“with”語句？
- 為什么 if/while/def/class語句需要冒號？
- 為什么Python在列表和元組的末尾允許使用逗號？
- 代碼庫和插件 FAQ
- 通用的代碼庫問題
- 通用任務
- 線程相關
- 輸入輸出
- 網絡 / Internet 編程
- 數據庫
- 數學和數字
- 擴展/嵌入常見問題
- 可以使用C語言中創建自己的函數嗎？
- 可以使用C++語言中創建自己的函數嗎？
- C很難寫，有沒有其他選擇？
- 如何從C執行任意Python語句？
- 如何從C中評估任意Python表達式？
- 如何從Python對象中提取C的值？
- 如何使用Py_BuildValue()創建任意長度的元組？
- 如何從C調用對象的方法？
- 如何捕獲PyErr_Print()（或打印到stdout / stderr的任何內容）的輸出？
- 如何從C訪問用Python編寫的模塊？
- 如何從Python接口到C ++對象？
- 我使用Setup文件添加了一個模塊，為什么make失敗了？
- 如何調試擴展？
- 我想在Linux系統上編譯一個Python模塊，但是缺少一些文件。為什么?
- 如何區分“輸入不完整”和“輸入無效”？
- 如何找到未定義的g++符號__builtin_new或__pure_virtual？
- 能否創建一個對象類，其中部分方法在C中實現，而其他方法在Python中實現（例如通過繼承）？
- Python在Windows上的常見問題
- 我怎樣在Windows下運行一個Python程序？
- 我怎么讓 Python 腳本可執行？
- 為什么有時候 Python 程序會啟動緩慢？
- 我怎樣使用Python腳本制作可執行文件？
- *.pyd 文件和DLL文件相同嗎？
- 我怎樣將Python嵌入一個Windows程序？
- 如何讓編輯器不要在我的 Python 源代碼中插入 tab ？
- 如何在不阻塞的情況下檢查按鍵？
- 圖形用戶界面（GUI）常見問題
- 圖形界面常見問題
- Python 是否有平臺無關的圖形界面工具包？
- 有哪些Python的GUI工具是某個平臺專用的？
- 有關Tkinter的問題
- “為什么我的電腦上安裝了 Python ？”
- 什么是Python？
- 為什么我的電腦上安裝了 Python ？
- 我能刪除 Python 嗎？
- 術語對照表
- 文檔說明
- Python 文檔貢獻者
- 解決 Bug
- 文檔錯誤
- 使用 Python 的錯誤追蹤系統
- 開始為 Python 貢獻您的知識
- 版權
- 歷史和許可證
- 軟件歷史
- 訪問Python或以其他方式使用Python的條款和條件
- Python 3.7.3 的 PSF 許可協議
- Python 2.0 的 BeOpen.com 許可協議
- Python 1.6.1 的 CNRI 許可協議
- Python 0.9.0 至 1.2 的 CWI 許可協議
- 集成軟件的許可和認可
- Mersenne Twister
- 套接字
- Asynchronous socket services
- Cookie management
- Execution tracing
- UUencode and UUdecode functions
- XML Remote Procedure Calls
- test_epoll
- Select kqueue
- SipHash24
- strtod and dtoa
- OpenSSL
- expat
- libffi
- zlib
- cfuhash
- libmpdec