术语表¶
>>>
- Python默认的shell提示符。经常看到的代码示例,可以在解释器交互执行。
...
- 在输入缩进代码块的代码或一对匹配的左右分隔符(括号,方括号或花括号)时,交互式shell的默认Python提示。
- 2to3
尝试通过解析大多数不兼容性来尝试将Python 2.x代码转换为Python 3.x代码的工具,这些不兼容性可以通过解析源和遍历解析树来检测。
2to3 is available in the standard library as
lib2to3
; a standalone entry point is provided asTools/scripts/2to3
. See 2to3 - Automated Python 2 to 3 code translation.- abstract base class
- 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 byisinstance()
andissubclass()
; see theabc
module documentation. Python comes with many built-in ABCs for data structures (in thecollections.abc
module), numbers (in thenumbers
module), streams (in theio
module), import finders and loaders (in theimportlib.abc
module). You can create your own ABCs with theabc
module. - 参数
A value passed to a function (or method) when calling the function. There are two kinds of argument:
keyword argument: an argument preceded by an identifier (e.g.
name=
) in a function call or passed as a value in a dictionary preceded by**
. For example,3
and5
are both keyword arguments in the following calls tocomplex()
: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
*
. For example,3
and5
are both positional arguments in the following calls:complex(3, 5) complex(*(3, 5))
参数被分配给函数体中指定的局部变量。See the Calls 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.
See also the parameter glossary entry, the FAQ question on the difference between arguments and parameters, and PEP 362.
- 异步上下文管理器
- An object which controls the environment seen in an
async with
statement by defining__aenter__()
and__aexit__()
methods. Introduced by PEP 492. - 异步迭代
- An object, that can be used in an
async for
statement. Must return an asynchronous iterator from its__aiter__()
method. Introduced by PEP 492. - asynchronous iterator
- An object that implements
__aiter__()
and__anext__()
methods.__anext__
must return an awaitable object.async for
resolves awaitable returned from asynchronous iterator’s__anext__()
method until it raisesStopAsyncIteration
exception. Introduced by PEP 492. - attribute
- 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.
- awaitable
- An object that can be used in an
await
expression. Can be a coroutine or an object with an__await__()
method. See also PEP 492. - BDFL
- Benevolent Dictator For Life, a.k.a. Guido van Rossum, Python’s creator.
- 二进制文件
A file object able to read and write bytes-like objects.
- bytes-like object
An object that supports the Buffer Protocol and can export a C-contiguous buffer. This includes all
bytes
,bytearray
, andarray.array
objects, as well as many commonmemoryview
objects. Bytes-like objects can be used for various operations that work with binary data; these include compression, saving to a binary file, and sending over a socket.Some operations need the binary data to be mutable. The documentation often refers to these as “read-write bytes-like objects”. Example mutable buffer objects include
bytearray
and amemoryview
of abytearray
. Other operations require the binary data to be stored in immutable objects (“read-only bytes-like objects”); examples of these includebytes
and amemoryview
of abytes
object.- bytecode
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 virtual machine 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 the dis module.
- class
- A template for creating user-defined objects. Class definitions normally contain method definitions which operate on instances of the class.
- coercion
- 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 integer3
, but in3+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 aTypeError
. 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 just3+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 writteni
in mathematics orj
in engineering. Python has built-in support for complex numbers, which are written with this latter notation; the imaginary part is written with aj
suffix, e.g.,3+1j
. To get access to complex equivalents of themath
module, usecmath
. 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. - context manager
- 通过定义
__ enter __()
和__ exit __()
方法控制在中使用
语句看到的环境的对象。See PEP 343. - contiguous
A buffer is considered contiguous exactly if it is either C-contiguous or Fortran contiguous. Zero-dimensional buffers are C and Fortran contiguous. In one-dimensional arrays, the items must be laid out in memory next to each other, in order of increasing indexes starting from zero. In multidimensional C-contiguous arrays, the last index varies the fastest when visiting items in order of memory address. However, in Fortran contiguous arrays, the first index varies the fastest.
- coroutine
- Coroutines is a more generalized form of subroutines. Subroutines are entered at one point and exited at another point. Coroutines can be entered, exited, and resumed at many different points. They can be implemented with the
async def
statement. See also PEP 492. - coroutine function
- A function which returns a coroutine object. A coroutine function may be defined with the
async def
statement, and may containawait
,async for
, andasync with
keywords. These were introduced by PEP 492. - CPython
- The canonical implementation of the Python programming language, as distributed on python.org. The term “CPython” is used when necessary to distinguish this implementation from others such as Jython or IronPython.
- decorator
A function returning another function, usually applied as a function transformation using the
@wrapper
syntax. Common examples for decorators areclassmethod()
andstaticmethod()
.The decorator syntax is merely syntactic sugar, the following two function definitions are semantically equivalent:
def f(...): ... f = staticmethod(f) @staticmethod def f(...): ...
The same concept exists for classes, but is less commonly used there. See the documentation for function definitions and class definitions for more about decorators.
- descriptor
定义方法
__ get __()
,__ set __()
或__ delete __()
的任何对象。当类属性是描述符时,其特殊绑定行为在属性查找时触发。通常,使用a.b来获取,设置或删除属性会在a的类字典中查找名为b的对象,但如果b是一个描述器,相应的描述器方法被调用。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.For more information about descriptors’ methods, see Implementing Descriptors.
- dictionary
- 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. - dictionary view
- The objects returned from
dict.keys()
,dict.values()
, anddict.items()
are called dictionary views. They provide a dynamic view on the dictionary’s entries, which means that when the dictionary changes, the view reflects these changes. To force the dictionary view to become a full list uselist(dictview)
. See Dictionary view objects. - docstring
- 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. - 鸭子类型
- 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()
orisinstance()
. (Note, however, that duck-typing can be complemented with abstract base classes.) Instead, it typically employshasattr()
tests or EAFP programming. - EAFP
- 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
andexcept
statements. The technique contrasts with the LBYL style common to many other languages such as C. - 表达式
- 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 statements which cannot be used as expressions, such as
if
. Assignments are also statements, not expressions. - extension module
- A module written in C or C++, using Python’s C API to interact with the core and with user code.
- file object
An object exposing a file-oriented API (with methods such as
read()
orwrite()
) 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 theopen()
function.- file-like object
- A synonym for file object.
- finder
试图为正在导入的模块找到loader的对象。
Since Python 3.3, there are two types of finder: meta path finders for use with
sys.meta_path
, and path entry finders for use withsys.path_hooks
.- floor division
- Mathematical division that rounds down to nearest integer. The floor division operator is
//
. For example, the expression11 // 4
evaluates to2
in contrast to the2.75
returned by float true division. Note that(-11) // 4
is-3
because that is-2.75
rounded downward. See PEP 238. - function
- 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, method, and the Function definitions section.
- function annotation
An arbitrary metadata value associated with a function parameter or return value. Its syntax is explained in section Function definitions. Annotations may be accessed via the
__annotations__
special attribute of a function object.Python itself does not assign any particular meaning to function annotations. They are intended to be interpreted by third-party libraries or tools. See PEP 3107, which describes some of their potential uses.
- __future__
A pseudo-module which programmers can use to enable new language features which are not compatible with the current interpreter.
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 becomes the default:>>> import __future__ >>> __future__.division _Feature((2, 2, 0, 'alpha', 2), (3, 0, 0, 'alpha', 0), 8192)
- garbage collection
- 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.
- generator
返回一个 generator iterator 的函数。它看上去很像普通的函数,只是它包含
yield
表达式用于生成一系列的值,这些值可以用于 for 循环或通过next()
函数一次一个地取出来。通常是指一个 generator 函数,但在某些上下文中可能是指一个 generator iterator。如果意欲达到的含义不明确,则使用完整术语可避免含糊不清。
- generator iterator
由一个 generator 函数创建的对象。
每个
yield
临时挂起当前的运行,记住执行的位置和状态(包括局部变量和等待的 try 语句)。当 generator iterator 恢复时,它从离开的位置重新开始(与函数不同,函数每次调用从起始开始)。- generator expression
一个返回 iterator 的表达式。它看起来像一个普通的表达式后跟一个定义循环变量的
for
表达式、range和一个可选的if
表达式。这个组合表达式为闭包函数生成值:>>> sum(i*i for i in range(10)) # sum of squares 0, 1, 4, ... 81 285
- generic function
A function composed of multiple functions implementing the same operation for different types. Which implementation should be used during a call is determined by the dispatch algorithm.
See also the single dispatch glossary entry, the
functools.singledispatch()
decorator, and PEP 443.- GIL
- See global interpreter lock.
- global interpreter lock
The mechanism used by the CPython interpreter to assure that only one thread executes Python bytecode at a time. This simplifies the CPython implementation by making the object model (including critical built-in types such as
dict
) implicitly safe against concurrent access. Locking the entire interpreter makes it easier for the interpreter to be multi-threaded, at the expense of much of the parallelism afforded by multi-processor machines.However, some extension modules, either standard or third-party, are designed so as to release the GIL when doing computationally-intensive tasks such as compression or hashing. Also, the GIL is always released when doing I/O.
Past efforts to create a “free-threaded” interpreter (one which locks shared data at a much finer granularity) have not been successful because performance suffered in the common single-processor case. It is believed that overcoming this performance issue would make the implementation much more complicated and therefore costlier to maintain.
- hashable
如果对象具有hashable,则其哈希值在其生命周期内不会改变(它需要
__ hash __()
方法),并且可以与其他对象进行比较(它需要一个__ eq __()
方法)。比较相等的可哈希对象必须具有相同的哈希值。散列性使对象可用作字典键和set成员,因为这些数据结构在内部使用散列值。
Python的所有不可变内置对象都是可哈希的,而没有可变容器(例如列表或字典)是可哈希的。作为用户定义类实例的对象默认情况下可哈希化;它们都比较不相等(除了它们本身),并且其哈希值是从其
id()
派生的。- IDLE
- An Integrated Development Environment for Python. IDLE is a basic editor and interpreter environment which ships with the standard distribution of Python.
- immutable
- An object with a fixed value. Immutable objects include numbers, strings and tuples. Such an object cannot be altered. A new object has to be created if a different value has to be stored. They play an important role in places where a constant hash value is needed, for example as a key in a dictionary.
- import path
- A list of locations (or path entries) that are searched by the path based finder for modules to import. During import, this list of locations usually comes from
sys.path
, but for subpackages it may also come from the parent package’s__path__
attribute. - importing
- The process by which Python code in one module is made available to Python code in another module.
- importer
- An object that both finds and loads a module; both a finder and loader object.
- interactive
- 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 (rememberhelp(x)
). - interpreted
- 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.
- interpreter shutdown
When asked to shut down, the Python interpreter enters a special phase where it gradually releases all allocated resources, such as modules and various critical internal structures. It also makes several calls to the garbage collector. This can trigger the execution of code in user-defined destructors or weakref callbacks. Code executed during the shutdown phase can encounter various exceptions as the resources it relies on may not function anymore (common examples are library modules or the warnings machinery).
The main reason for interpreter shutdown is that the
__main__
module or the script being run has finished executing.- iterable
- 一个对象,能够一次返回其一个成员。Iterables 的例子包括所有的序列类型(例如
list
、str
和tuple
)以及一些非序列类型如dict
、file 对象 和任何定义了__iter__()
或__getitem__()
方法的对象。 Iterables 可用于for
循环以及其它许多需要序列的地方(zip()
、map()
,...)。当一个 iterable 对象作为参数传递给内置函数iter()
时,它返回该对象的一个 iterator。这个 iterator 适用于一组值的一次传递。使用iterables时,通常不需要自己调用iter()
或处理 iterator 对象。for
语句会自动为你执行此操作,它会创建一个临时的未命名变量以在循环期间保存 iterator。参见 iterator、sequence 和 generator。 - iterator
一个表示数据流的对象。对 iterator 的
__next__()
方法的调用(或者将它传递给内建的函数next()
)返回流中连续的条目。当没有更多数据时,会引发一个StopIteration
异常。此时,该 iterator 对象已耗尽,并且对其__next__()
方法的任何进一步调用再次引发StopIteration
。Iterator 需要有一个__iter__()
方法,该方法返回 iterator 对象本身,因此每个 iterator 也是可迭代的,并且可以在大多数接受其它可迭代对象的地方使用。一个值得注意的例外是尝试多次迭代传递的代码。容器对象(例如list
)在每次将它传递给iter()
函数或在for
循环中使用它时都会生成一个全新的 iterator。对 iterator 尝试这样的操作只会返回上一次迭代过程中使用的相同的已耗尽的 iterator 对象,使其看起来像一个空容器。更多信息可以在Iterator 类型中找到。
- 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.merge()
,heapq.nsmallest()
,heapq.nlargest()
, anditertools.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, a key function can be built from alambda
expression such aslambda r: (r[0], r[2])
. Also, theoperator
module provides three key function constructors:attrgetter()
,itemgetter()
, andmethodcaller()
. See the Sorting HOW TO for examples of how to create and use key functions.- keyword argument
- See argument.
- lambda
- 一个由单个表达式组成的匿名内联函数,当这个函数被调用时开始计算。创建 lambda 函数的语法是
lambda [arguments]: expression
- LBYL
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
statements.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 mapping after the test, but before the lookup. This issue can be solved with locks or by using the EAFP approach.- list
- A built-in Python sequence. 尽管它叫做列表,但它看上去更像是其它语言中的数组,而不是列表。它通过O(1)来访问子元素。
- list comprehension
- 处理序列中所有或部分元素并返回包含结果的列表的紧凑方法。
result = ['{:#04x}'.format(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. Theif
clause is optional. If omitted, all elements inrange(256)
are processed. - loader
- An object that loads a module. It must define a method named
load_module()
. A loader is typically returned by a finder. See PEP 302 for details andimportlib.abc.Loader
for an abstract base class. - mapping
- A container object that supports arbitrary key lookups and implements the methods specified in the
Mapping
orMutableMapping
abstract base classes. Examples includedict
,collections.defaultdict
,collections.OrderedDict
andcollections.Counter
. - meta path finder
A finder returned by a search of
sys.meta_path
. Meta path finders are related to, but different from path entry finders.See
importlib.abc.MetaPathFinder
for the methods that meta path finders implement.- metaclass
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.
More information can be found in Customizing class creation.
- method
- 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
). See function and nested scope. - method resolution order
- Method Resolution Order is the order in which base classes are searched for a member during lookup. See The Python 2.3 Method Resolution Order for details of the algorithm used by the Python interpreter since the 2.3 release.
- module
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.
See also package.
- module spec
- A namespace containing the import-related information used to load a module. An instance of
importlib.machinery.ModuleSpec
. - 方法解析顺序
- See method resolution order.
- 可变的
- Mutable objects can change their value but keep their
id()
. See also immutable. - named tuple
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 ast[0]
or with a named attribute liket.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 functioncollections.namedtuple()
. The latter approach automatically provides extra features such as a self-documenting representation likeEmployee(name='jones', title='programmer')
.- namespace
- 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
builtins.open
andos.open()
are distinguished by their namespaces. Namespaces also aid readability and maintainability by making it clear which module implements a function. For instance, writingrandom.seed()
oritertools.islice()
makes it clear that those functions are implemented by therandom
anditertools
modules, respectively. - namespace package
A PEP 420 package which serves only as a container for subpackages. Namespace packages may have no physical representation, and specifically are not like a regular package because they have no
__init__.py
file.See also module.
- nested scope
- 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 by default work only for reference and not for assignment. Local variables both read and write in the innermost scope. Likewise, global variables read and write to the global namespace. The
nonlocal
allows writing to outer scopes. - new-style class
- Old name for the flavor of classes now used for all class objects. In earlier Python versions, only new-style classes could use Python’s newer, versatile features like
__slots__
, descriptors, properties,__getattribute__()
, class methods, and static methods. - object
- 内存上的一块数据,具有我们赋予它的状态(又称属性、值)和行为(又称方法、函数),通常翻译成“对象”,这是编程中的一个通用性的概念。在Python中,这个词还有另一种用法,即特指任何new-style class的最终基类。
- package
A Python module which can contain submodules or recursively, subpackages. Technically, a package is a Python module with an
__path__
attribute.See also regular package and namespace package.
- parameter
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 five kinds of parameter:
positional-or-keyword: specifies an argument that can be passed either positionally or as a keyword argument. This is the default kind of parameter, for example foo and bar in the following:
def func(foo, bar=None): ...
positional-only: 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()
).
keyword-only: specifies an argument that can be supplied only by keyword. Keyword-only parameters can be defined by including a single var-positional parameter or bare
*
in the parameter list of the function definition before them, for example kw_only1 and kw_only2 in the following:def func(arg, *, kw_only1, kw_only2): ...
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
*
, for example 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
**
, for example kwargs in the example above.
Parameters can specify both optional and required arguments, as well as default values for some optional arguments.
See also the argument glossary entry, the FAQ question on the difference between arguments and parameters, the
inspect.Parameter
class, the Function definitions section, and PEP 362.- path entry
- A single location on the import path which the path based finder consults to find modules for importing.
- path entry finder
A finder returned by a callable on
sys.path_hooks
(i.e. a path entry hook) which knows how to locate modules given a path entry.See
importlib.abc.PathEntryFinder
for the methods that path entry finders implement.- path entry hook
- A callable on the
sys.path_hook
list which returns a path entry finder if it knows how to find modules on a specific path entry. - path based finder
- One of the default meta path finders which searches an import path for modules.
- portion
- A set of files in a single directory (possibly stored in a zip file) that contribute to a namespace package, as defined in PEP 420.
- positional argument
- See argument.
- provisional API
A provisional API is one which has been deliberately excluded from the standard library’s backwards compatibility guarantees. While major changes to such interfaces are not expected, as long as they are marked provisional, backwards incompatible changes (up to and including removal of the interface) may occur if deemed necessary by core developers. Such changes will not be made gratuitously – they will occur only if serious fundamental flaws are uncovered that were missed prior to the inclusion of the API.
Even for provisional APIs, backwards incompatible changes are seen as a “solution of last resort” - every attempt will still be made to find a backwards compatible resolution to any identified problems.
This process allows the standard library to continue to evolve over time, without locking in problematic design errors for extended periods of time. See PEP 411 for more details.
- provisional package
- See provisional API.
- 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”.
- Pythonic
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)
- qualified name
A dotted name showing the “path” from a module’s global scope to a class, function or method defined in that module, as defined in PEP 3155. For top-level functions and classes, the qualified name is the same as the object’s name:
>>> class C: ... class D: ... def meth(self): ... pass ... >>> C.__qualname__ 'C' >>> C.D.__qualname__ 'C.D' >>> C.D.meth.__qualname__ 'C.D.meth'
When used to refer to modules, the fully qualified name means the entire dotted path to the module, including any parent packages, e.g.
email.mime.text
:>>> import email.mime.text >>> email.mime.text.__name__ 'email.mime.text'
- 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 agetrefcount()
function that programmers can call to return the reference count for a particular object. - regular package
A traditional package, such as a directory containing an
__init__.py
file.See also namespace package.
- __slots__
- A declaration inside a class 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.
- sequence
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 arelist
,str
,tuple
, andbytes
. Note thatdict
also supports__getitem__()
and__len__()
, but is considered a mapping rather than a sequence because the lookups use arbitrary immutable keys rather than integers.The
collections.abc.Sequence
abstract base class defines a much richer interface that goes beyond just__getitem__()
and__len__()
, addingcount()
,index()
,__contains__()
, and__reversed__()
. Types that implement this expanded interface can be registered explicitly usingregister()
.- single dispatch
- A form of generic function dispatch where the implementation is chosen based on the type of a single argument.
- 切片
- 通常包含着 序列的一部分的对象. 切片是用下标符号,
[]
和给定的一些数字及冒号创建, 例如variable_name[1:3:5]
. 这个括号符号使用内部的slice
对象. - special method
- 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 Special method names.
- statement
- 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
orfor
. - struct sequence
- A tuple with named elements. Struct sequences expose an interface similar to named tuple 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 includesys.float_info
and the return value ofos.stat()
. - text encoding
- A codec which encodes Unicode strings to bytes.
- text file
A file object able to read and write
str
objects. Often, a text file actually accesses a byte-oriented datastream and handles the text encoding automatically.See also
A binary file reads and write
bytes
objects.- triple-quoted string
- 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.
- type
- 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 withtype(obj)
. - universal newlines
- 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'
. See PEP 278 and PEP 3116, as well asbytes.splitlines()
for an additional use. - virtual environment
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.
See also pyvenv - Creating virtual environments.
- virtual machine
- A computer defined entirely in software. Python’s virtual machine executes the bytecode emitted by the bytecode compiler.
- Python之禅
- Python设计原则和哲学的列表对于理解和使用Python语言有很大的帮助。通过在交互提示符下使用“import this”可以找到这个列表。The listing can be found by typing “
import this
” at the interactive prompt.