The default Python prompt of the interactive shell. Often seen for code examples which can be executed interactively in the interpreter.
The default Python prompt of the interactive shell when entering code for an indented code block or within a pair of matching left and right delimiters (parentheses, square brackets or curly braces).

A tool that tries to convert Python 2.x code to Python 3.x code by handling most of the incompatibilities which can be detected by parsing the source and traversing the parse tree.

2to3 is available in the standard library as lib2to3 ; a standalone entry point is provided as Tools/scripts/2to3 。见 2to3 - 自动 Python 2 到 3 代码翻译 .

Abstract base classes complement duck-typing by providing a way to define interfaces when other techniques like hasattr() would be clumsy or subtly wrong (for example with magic methods ). ABCs introduce virtual subclasses, which are classes that don’t inherit from a class but are still recognized by isinstance() and issubclass() ; see the abc module documentation. Python comes with many built-in ABCs for data structures (in the collections module), numbers (in the numbers module), and streams (in the io module). You can create your own ABCs with the abc 模块。

A value passed to a function (或 方法 ) when calling the function. There are two types of arguments:

  • 关键词自变量 : an argument preceded by an identifier (e.g. name= ) in a function call or passed as a value in a dictionary preceded by ** 。例如, 3 and 5 are both keyword arguments in the following calls to complex() :

    complex(real=3, imag=5)
    complex(**{'real': 3, 'imag': 5})
  • positional argument : an argument that is not a keyword argument. Positional arguments can appear at the beginning of an argument list and/or be passed as elements of an iterable preceded by * 。例如, 3 and 5 are both positional arguments in the following calls:

    complex(3, 5)
    complex(*(3, 5))

Arguments are assigned to the named local variables in a function body. See the 调用 section for the rules governing this assignment. Syntactically, any expression can be used to represent an argument; the evaluated value is assigned to the local variable.

另请参阅 parameter glossary entry and the FAQ question on the difference between arguments and parameters .

A value associated with an object which is referenced by name using dotted expressions. For example, if an object o has an attribute a it would be referenced as o.a .
仁慈的终生独裁者,也称为 Guido van Rossum ,Python 的创建者。
对象支持 缓冲协议 ,像 str , bytearray or memoryview . Bytes-like objects can be used for various operations that expect binary data, such as compression, saving to a binary file or sending over a socket. Some operations need the binary data to be mutable, in which case not all bytes-like objects can apply.

Python source code is compiled into bytecode, the internal representation of a Python program in the CPython interpreter. The bytecode is also cached in .pyc and .pyo files so that executing the same file is faster the second time (recompilation from source to bytecode can be avoided). This “intermediate language” is said to run on a 虚拟机 that executes the machine code corresponding to each bytecode. Do note that bytecodes are not expected to work between different Python virtual machines, nor to be stable between Python releases.

A list of bytecode instructions can be found in the documentation for dis 模块 .

A template for creating user-defined objects. Class definitions normally contain method definitions which operate on instances of the class.
classic class
Any class which does not inherit from object 。见 新样式类 . Classic classes have been removed in Python 3.
The implicit conversion of an instance of one type to another during an operation which involves two arguments of the same type. For example, int(3.15) converts the floating point number to the integer 3 , but in 3+4.5 , each argument is of a different type (one int, one float), and both must be converted to the same type before they can be added or it will raise a TypeError . Coercion between two operands can be performed with the coerce built-in function; thus, 3+4.5 is equivalent to calling operator.add(*coerce(3, 4.5)) and results in operator.add(3.0, 4.5) . Without coercion, all arguments of even compatible types would have to be normalized to the same value by the programmer, e.g., float(3)+4.5 rather than just 3+4.5 .
complex number
An extension of the familiar real number system in which all numbers are expressed as a sum of a real part and an imaginary part. Imaginary numbers are real multiples of the imaginary unit (the square root of -1 ), often written i in mathematics or j in engineering. Python has built-in support for complex numbers, which are written with this latter notation; the imaginary part is written with a j suffix, e.g., 3+1j . To get access to complex equivalents of the math module, use cmath . Use of complex numbers is a fairly advanced mathematical feature. If you’re not aware of a need for them, it’s almost certain you can safely ignore them.
控制所见环境的对象在 with 语句通过定义 __enter__() and __exit__() 方法。见 PEP 343 .
Python 编程语言的典型实现,作为分发在 python.org 。当有必要时使用 CPython 术语以区分这种实现与其它实现,譬如:Jython 或 IronPython。

返回另一函数的函数,通常作为函数变换运用,使用 @wrapper 句法。装饰器的常见范例是 classmethod() and staticmethod() .

装饰器句法只是句法糖,以下 2 函数定义在语义上是等效的:

def f(...):
f = staticmethod(f)
def f(...):

类存在同样的概念,但很少使用。见文档编制为 函数定义 and 类定义 为有关装饰器的更多信息。


Any new-style object which defines the methods __get__() , __set__() ,或 __delete__() . When a class attribute is a descriptor, its special binding behavior is triggered upon attribute lookup. Normally, using a.b to get, set or delete an attribute looks up the object named b in the class dictionary for a , but if b is a descriptor, the respective descriptor method gets called. Understanding descriptors is a key to a deep understanding of Python because they are the basis for many features including functions, methods, properties, class methods, static methods, and reference to super classes.

有关描述符方法的更多信息,见 实现描述符 .

An associative array, where arbitrary keys are mapped to values. The keys can be any object with __hash__() and __eq__() methods. Called a hash in Perl.
A string literal which appears as the first expression in a class, function or module. While ignored when the suite is executed, it is recognized by the compiler and put into the __doc__ attribute of the enclosing class, function or module. Since it is available via introspection, it is the canonical place for documentation of the object.
A programming style which does not look at an object’s type to determine if it has the right interface; instead, the method or attribute is simply called or used (“If it looks like a duck and quacks like a duck, it must be a duck.”) By emphasizing interfaces rather than specific types, well-designed code improves its flexibility by allowing polymorphic substitution. Duck-typing avoids tests using type() or isinstance() . (Note, however, that duck-typing can be complemented with 抽象基类 .) Instead, it typically employs hasattr() tests or EAFP programming.
Easier to ask for forgiveness than permission. This common Python coding style assumes the existence of valid keys or attributes and catches exceptions if the assumption proves false. This clean and fast style is characterized by the presence of many try and except statements. The technique contrasts with the LBYL style common to many other languages such as C.
A piece of syntax which can be evaluated to some value. In other words, an expression is an accumulation of expression elements like literals, names, attribute access, operators or function calls which all return a value. In contrast to many other languages, not all language constructs are expressions. There are also 语句 s which cannot be used as expressions, such as print or if . Assignments are also statements, not expressions.
A module written in C or C++, using Python’s C API to interact with the core and with user code.

An object exposing a file-oriented API (with methods such as read() or write() ) to an underlying resource. Depending on the way it was created, a file object can mediate access to a real on-disk file or to another type of storage or communication device (for example standard input/output, in-memory buffers, sockets, pipes, etc.). File objects are also called file-like objects or streams .

There are actually three categories of file objects: raw binary files, buffered binary files and text files. Their interfaces are defined in the io module. The canonical way to create a file object is by using the open() 函数。

同义词 文件对象 .
An object that tries to find the loader for a module. It must implement a method named find_module() 。见 PEP 302 了解细节。
floor division
Mathematical division that rounds down to nearest integer. The floor division operator is // . For example, the expression 11 // 4 evaluates to 2 in contrast to the 2.75 returned by float true division. Note that (-11) // 4 is -3 because that is -2.75 rounded downward 。见 PEP 238 .
A series of statements which returns some value to a caller. It can also be passed zero or more arguments which may be used in the execution of the body. See also parameter , 方法 ,和 函数定义 章节。

A pseudo-module which programmers can use to enable new language features which are not compatible with the current interpreter. For example, the expression 11/4 currently evaluates to 2 . If the module in which it is executed had enabled true division by executing:

from __future__ import division

the expression 11/4 would evaluate to 2.75 . By importing the __future__ module and evaluating its variables, you can see when a new feature was first added to the language and when it will become the default:

>>> import __future__
>>> __future__.division
_Feature((2, 2, 0, 'alpha', 2), (3, 0, 0, 'alpha', 0), 8192)
The process of freeing memory when it is not used anymore. Python performs garbage collection via reference counting and a cyclic garbage collector that is able to detect and break reference cycles.
A function which returns an iterator. It looks like a normal function except that it contains yield statements for producing a series a values usable in a for-loop or that can be retrieved one at a time with the next() function. Each yield temporarily suspends processing, remembering the location execution state (including local variables and pending try-statements). When the generator resumes, it picks-up where it left-off (in contrast to functions which start fresh on every invocation).

An expression that returns an iterator. It looks like a normal expression followed by a for expression defining a loop variable, range, and an optional if expression. The combined expression generates values for an enclosing function:

>>> sum(i*i for i in range(10))         # sum of squares 0, 1, 4, ... 81
全局解释器锁 .

机制用于 CPython 解释器担保只有一个线程执行 Python bytecode 每次。这简化 CPython 实现通过使对象模型 (包括关键内置类型,譬如 dict ) 隐含安全阻止并发访问。锁定整个解释器使解释器更易于多线程,以付出由多处理器机器提供的许多并行性为代价。

不管怎样,一些扩展模块 (标准或第 3 方) 被设计为在履行计算密集任务 (譬如:压缩或散列) 时释放 GIL。此外,当履行 I/O 时始终释放 GIL。

过去创建 "自由线程" 解释器 (以更细粒度锁定共享数据) 的努力并不成功,因为在常见单处理器情况下会损失性能。据信,克服此性能问题将使得实现更加复杂,因此维护更昂贵。


对象 hashable 若它拥有的哈希值在其寿命内从不改变 (它需要 __hash__() 方法),且可以比较其它对象 (它需要 __eq__() or __cmp__() 方法)。比较相等的可哈希对象必须拥有相同的哈希值。

可哈希性使对象可用作字典键和 set 成员,因为这些数据结构内部使用哈希值。

All of Python’s immutable built-in objects are hashable, while no mutable containers (such as lists or dictionaries) are. Objects which are instances of user-defined classes are hashable by default; they all compare unequal (except with themselves), and their hash value is their id() .

用于 Python 的集成开发环境。IDLE 是 Python 标准分发附带的基本编辑器和解释器环境。
具有固定值的对象。不可变对象包括数字、字符串及元组。这种对象不可以变更。必须创建新对象,若必须存储不同值。它们在需要常量哈希值 (例如:作为字典键) 的地方扮演重要角色。
integer division
Mathematical division discarding any remainder. For example, the expression 11/4 currently evaluates to 2 in contrast to the 2.75 returned by float division. Also called floor division . When dividing two integers the outcome will always be another integer (having the floor function applied to it). However, if one of the operands is another numeric type (such as a float ), the result will be coerced (see coercion ) to a common type. For example, an integer divided by a float will result in a float value, possibly with a decimal fraction. Integer division can be forced by using the // operator instead of the / operator. See also __future__ .
The process by which Python code in one module is made available to Python code in another module.
An object that both finds and loads a module; both a finder and loader 对象。
Python has an interactive interpreter which means you can enter statements and expressions at the interpreter prompt, immediately execute them and see their results. Just launch python with no arguments (possibly by selecting it from your computer’s main menu). It is a very powerful way to test out new ideas or inspect modules and packages (remember help(x) ).
Python is an interpreted language, as opposed to a compiled one, though the distinction can be blurry because of the presence of the bytecode compiler. This means that source files can be run directly without explicitly creating an executable which is then run. Interpreted languages typically have a shorter development/debug cycle than compiled ones, though their programs generally also run more slowly. See also interactive .
An object capable of returning its members one at a time. Examples of iterables include all sequence types (such as list , str ,和 tuple ) and some non-sequence types like dict and file and objects of any classes you define with an __iter__() or __getitem__() method. Iterables can be used in a for loop and in many other places where a sequence is needed ( zip() , map() , ...). When an iterable object is passed as an argument to the built-in function iter() , it returns an iterator for the object. This iterator is good for one pass over the set of values. When using iterables, it is usually not necessary to call iter() or deal with iterator objects yourself. The for statement does that automatically for you, creating a temporary unnamed variable to hold the iterator for the duration of the loop. See also iterator , sequence ,和 generator .

An object representing a stream of data. Repeated calls to the iterator’s next() method return successive items in the stream. When no more data are available a StopIteration exception is raised instead. At this point, the iterator object is exhausted and any further calls to its next() method just raise StopIteration again. Iterators are required to have an __iter__() method that returns the iterator object itself so every iterator is also iterable and may be used in most places where other iterables are accepted. One notable exception is code which attempts multiple iteration passes. A container object (such as a list ) produces a fresh new iterator each time you pass it to the iter() function or use it in a for loop. Attempting this with an iterator will just return the same exhausted iterator object used in the previous iteration pass, making it appear like an empty container.

可以找到更多信息在 迭代器类型 .

key function

A key function or collation function is a callable that returns a value used for sorting or ordering. For example, locale.strxfrm() is used to produce a sort key that is aware of locale specific sort conventions.

A number of tools in Python accept key functions to control how elements are ordered or grouped. They include min() , max() , sorted() , list.sort() , heapq.nsmallest() , heapq.nlargest() ,和 itertools.groupby() .

There are several ways to create a key function. For example. the str.lower() method can serve as a key function for case insensitive sorts. Alternatively, an ad-hoc key function can be built from a lambda expression such as lambda r: (r[0], r[2]) . Also, the operator module provides three key function constructors: attrgetter() , itemgetter() ,和 methodcaller() 。见 排序怎么样 for examples of how to create and use key functions.

argument .
An anonymous inline function consisting of a single expression which is evaluated when the function is called. The syntax to create a lambda function is lambda [arguments]: expression

Look before you leap. This coding style explicitly tests for pre-conditions before making calls or lookups. This style contrasts with the EAFP approach and is characterized by the presence of many if 语句。

In a multi-threaded environment, the LBYL approach can risk introducing a race condition between “the looking” and “the leaping”. For example, the code, if key in mapping: return mapping[key] can fail if another thread removes key from 映射 after the test, but before the lookup. This issue can be solved with locks or by using the EAFP approach.

A built-in Python sequence . Despite its name it is more akin to an array in other languages than to a linked list since access to elements are O(1).
A compact way to process all or part of the elements in a sequence and return a list with the results. result = ["0x%02x" % x for x in range(256) if x % 2 == 0] generates a list of strings containing even hex numbers (0x..) in the range from 0 to 255. The if clause is optional. If omitted, all elements in range(256) are processed.
An object that loads a module. It must define a method named load_module() . A loader is typically returned by a finder 。见 PEP 302 了解细节。
A container object that supports arbitrary key lookups and implements the methods specified in the Mapping or MutableMapping 抽象基类 . Examples include dict , collections.defaultdict , collections.OrderedDict and collections.Counter .

The class of a class. Class definitions create a class name, a class dictionary, and a list of base classes. The metaclass is responsible for taking those three arguments and creating the class. Most object oriented programming languages provide a default implementation. What makes Python special is that it is possible to create custom metaclasses. Most users never need this tool, but when the need arises, metaclasses can provide powerful, elegant solutions. They have been used for logging attribute access, adding thread-safety, tracking object creation, implementing singletons, and many other tasks.

可以找到更多信息在 定制类创建 .

A function which is defined inside a class body. If called as an attribute of an instance of that class, the method will get the instance object as its first argument (which is usually called self )。见 function and 嵌套作用域 .
Method Resolution Order is the order in which base classes are searched for a member during lookup. See Python 2.3 MRO (方法分辨次序) .

An object that serves as an organizational unit of Python code. Modules have a namespace containing arbitrary Python objects. Modules are loaded into Python by the process of importing .

另请参阅 package .

方法分辨次序 .
Mutable objects can change their value but keep their id() 。另请参阅 immutable .

Any tuple-like class whose indexable elements are also accessible using named attributes (for example, time.localtime() returns a tuple-like object where the year is accessible either with an index such as t[0] or with a named attribute like t.tm_year ).

A named tuple can be a built-in type such as time.struct_time , or it can be created with a regular class definition. A full featured named tuple can also be created with the factory function collections.namedtuple() . The latter approach automatically provides extra features such as a self-documenting representation like Employee(name='jones', title='programmer') .

The place where a variable is stored. Namespaces are implemented as dictionaries. There are the local, global and built-in namespaces as well as nested namespaces in objects (in methods). Namespaces support modularity by preventing naming conflicts. For instance, the functions __builtin__.open() and os.open() are distinguished by their namespaces. Namespaces also aid readability and maintainability by making it clear which module implements a function. For instance, writing random.seed() or itertools.izip() makes it clear that those functions are implemented by the random and itertools modules, respectively.
The ability to refer to a variable in an enclosing definition. For instance, a function defined inside another function can refer to variables in the outer function. Note that nested scopes work only for reference and not for assignment which will always write to the innermost scope. In contrast, local variables both read and write in the innermost scope. Likewise, global variables read and write to the global namespace.

Any class which inherits from object . This includes all built-in types like list and dict . Only new-style classes can use Python’s newer, versatile features like __slots__ , descriptors, properties, and __getattribute__() .

可以找到更多信息在 New-style and classic classes .

Any data with state (attributes or value) and defined behavior (methods). Also the ultimate base class of any 新样式类 .
Python 模块 which can contain submodules or recursively, subpackages. Technically, a package is a Python module with an __path__ 属性。

A named entity in a function (or method) definition that specifies an argument (or in some cases, arguments) that the function can accept. There are four types of parameters:

  • 位置或关键词 : specifies an argument that can be passed either positionally or as a 关键词自变量 . This is the default kind of parameter, for example foo and bar in the following:

    def func(foo, bar=None): ...
  • 仅位置 : specifies an argument that can be supplied only by position. Python has no syntax for defining positional-only parameters. However, some built-in functions have positional-only parameters (e.g. abs() ).

  • var-positional : specifies that an arbitrary sequence of positional arguments can be provided (in addition to any positional arguments already accepted by other parameters). Such a parameter can be defined by prepending the parameter name with * ,例如 args in the following:

    def func(*args, **kwargs): ...
  • var-keyword : specifies that arbitrarily many keyword arguments can be provided (in addition to any keyword arguments already accepted by other parameters). Such a parameter can be defined by prepending the parameter name with ** ,例如 kwargs in the example above.

Parameters can specify both optional and required arguments, as well as default values for some optional arguments.

另请参阅 argument glossary entry, the FAQ question on the difference between arguments and parameters ,和 函数定义 章节。

positional argument
argument .
Python 3000
Nickname for the Python 3.x release line (coined long ago when the release of version 3 was something in the distant future.) This is also abbreviated “Py3k”.

An idea or piece of code which closely follows the most common idioms of the Python language, rather than implementing code using concepts common to other languages. For example, a common idiom in Python is to loop over all elements of an iterable using a for statement. Many other languages don’t have this type of construct, so people unfamiliar with Python sometimes use a numerical counter instead:

for i in range(len(food)):
    print food[i]

As opposed to the cleaner, Pythonic method:

for piece in food:
    print piece
reference count
The number of references to an object. When the reference count of an object drops to zero, it is deallocated. Reference counting is generally not visible to Python code, but it is a key element of the CPython implementation. The sys module defines a getrefcount() function that programmers can call to return the reference count for a particular object.
A declaration inside a 新样式类 that saves memory by pre-declaring space for instance attributes and eliminating instance dictionaries. Though popular, the technique is somewhat tricky to get right and is best reserved for rare cases where there are large numbers of instances in a memory-critical application.
An iterable which supports efficient element access using integer indices via the __getitem__() special method and defines a len() method that returns the length of the sequence. Some built-in sequence types are list , str , tuple ,和 unicode 。注意, dict also supports __getitem__() and __len__() , but is considered a mapping rather than a sequence because the lookups use arbitrary immutable keys rather than integers.
An object usually containing a portion of a sequence . A slice is created using the subscript notation, [] with colons between numbers when several are given, such as in variable_name[1:3:5] . The bracket (subscript) notation uses slice objects internally (or in older versions, __getslice__() and __setslice__() ).
A method that is called implicitly by Python to execute a certain operation on a type, such as addition. Such methods have names starting and ending with double underscores. Special methods are documented in 特殊方法名称 .
A statement is part of a suite (a “block” of code). A statement is either an expression or one of several constructs with a keyword, such as if , while or for .
A tuple with named elements. Struct sequences expose an interface similiar to 命名元组 in that elements can either be accessed either by index or as an attribute. However, they do not have any of the named tuple methods like _make() or _asdict() . Examples of struct sequences include sys.float_info and the return value of os.stat() .
A string which is bound by three instances of either a quotation mark (”) or an apostrophe (‘). While they don’t provide any functionality not available with single-quoted strings, they are useful for a number of reasons. They allow you to include unescaped single and double quotes within a string and they can span multiple lines without the use of the continuation character, making them especially useful when writing docstrings.
The type of a Python object determines what kind of object it is; every object has a type. An object’s type is accessible as its __class__ attribute or can be retrieved with type(obj) .
A manner of interpreting text streams in which all of the following are recognized as ending a line: the Unix end-of-line convention '\n' , the Windows convention '\r\n' , and the old Macintosh convention '\r' 。见 PEP 278 and PEP 3116 ,及 str.splitlines() for an additional use.
The objects returned from dict.viewkeys() , dict.viewvalues() ,和 dict.viewitems() are called dictionary views. They are lazy sequences that will see changes in the underlying dictionary. To force the dictionary view to become a full list use list(dictview) 。见 字典视图对象 .
A cooperatively isolated runtime environment that allows Python users and applications to install and upgrade Python distribution packages without interfering with the behaviour of other Python applications running on the same system.
A computer defined entirely in software. Python’s virtual machine executes the bytecode 发射通过字节码编译器。
Python 禅宗
Listing of Python design principles and philosophies that are helpful in understanding and using the language. The listing can be found by typing “ import this ” at the interactive prompt.


FAQ:为什么要在我的计算机中安装 Python?