3. 数据模型
***********


3.1. 对象、值与类型
===================

*对象* 是 Python 中对数据的抽象。Python 程序中的所有数据都是由对象或对
象间关系来表示的。（从某种意义上说，按照冯·诺依曼的 “存储程序计算机”
模型，代码本身也是由对象来表示的。）

Every object has an identity, a type and a value.  An object’s
*identity* never changes once it has been created; you may think of it
as the object’s address in memory.  The ‘"is"’ operator compares the
identity of two objects; the "id()" function returns an integer
representing its identity (currently implemented as its address). An
object’s *type* is also unchangeable. [1] An object’s type determines
the operations that the object supports (e.g., “does it have a
length?”) and also defines the possible values for objects of that
type.  The "type()" function returns an object’s type (which is an
object itself).  The *value* of some objects can change.  Objects
whose value can change are said to be *mutable*; objects whose value
is unchangeable once they are created are called *immutable*. (The
value of an immutable container object that contains a reference to a
mutable object can change when the latter’s value is changed; however
the container is still considered immutable, because the collection of
objects it contains cannot be changed.  So, immutability is not
strictly the same as having an unchangeable value, it is more subtle.)
An object’s mutability is determined by its type; for instance,
numbers, strings and tuples are immutable, while dictionaries and
lists are mutable.

对象绝不会被显式地销毁；然而，当无法访问时它们可能会被作为垃圾回收。允
许具体的实现推迟垃圾回收或完全省略此机制 — 如何实现垃圾回收是实现的质
量问题，只要可访问的对象不会被回收即可。

**CPython implementation detail:** CPython currently uses a reference-
counting scheme with (optional) delayed detection of cyclically linked
garbage, which collects most objects as soon as they become
unreachable, but is not guaranteed to collect garbage containing
circular references.  See the documentation of the "gc" module for
information on controlling the collection of cyclic garbage. Other
implementations act differently and CPython may change. Do not depend
on immediate finalization of objects when they become unreachable (ex:
always close files).

注意：使用实现的跟踪或调试功能可能令正常情况下会被回收的对象继续存活。
还要注意通过 ‘"try"…"except"’ 语句捕捉异常也可能令对象保持存活。

Some objects contain references to “external” resources such as open
files or windows.  It is understood that these resources are freed
when the object is garbage-collected, but since garbage collection is
not guaranteed to happen, such objects also provide an explicit way to
release the external resource, usually a "close()" method. Programs
are strongly recommended to explicitly close such objects.  The
‘"try"…"finally"’ statement provides a convenient way to do this.

有些对象包含对其他对象的引用；它们被称为 *容器*。容器的例子有元组、列
表和字典等。这些引用是容器对象值的组成部分。在多数情况下，当谈论一个容
器的值时，我们是指所包含对象的值而不是其编号；但是，当我们谈论一个容器
的可变性时，则仅指其直接包含的对象的编号。因此，如果一个不可变容器 (例
如元组) 包含对一个可变对象的引用，则当该可变对象被改变时容器的值也会改
变。

类型会影响对象行为的几乎所有方面。甚至对象编号的重要性也在某种程度上受
到影响: 对于不可变类型，会得出新值的运算实际上会返回对相同类型和取值的
任一现有对象的引用，而对于可变类型来说这是不允许的。例如在 "a = 1; b =
1" 之后，"a" 和 "b" 可能会也可能不会指向同一个值为一的对象，这取决于具
体实现，但是在 "c = []; d = []" 之后，"c" 和 "d" 保证会指向两个不同、
单独的新建空列表。(请注意 "c = d = []" 则是将同一个对象赋值给 "c" 和
"d"。)


3.2. 标准类型层级结构
=====================

Below is a list of the types that are built into Python.  Extension
modules (written in C, Java, or other languages, depending on the
implementation) can define additional types.  Future versions of
Python may add types to the type hierarchy (e.g., rational numbers,
efficiently stored arrays of integers, etc.).

以下部分类型的描述中包含有 ‘特殊属性列表’ 段落。这些属性提供对具体实现
的访问而非通常使用。它们的定义在未来可能会改变。

None
   此类型只有一种取值。是一个具有此值的单独对象。此对象通过内置名称
   "None" 访问。在许多情况下它被用来表示空值，例如未显式指明返回值的函
   数将返回 None。它的逻辑值为假。

NotImplemented
   This type has a single value.  There is a single object with this
   value. This object is accessed through the built-in name
   "NotImplemented". Numeric methods and rich comparison methods may
   return this value if they do not implement the operation for the
   operands provided.  (The interpreter will then try the reflected
   operation, or some other fallback, depending on the operator.)  Its
   truth value is true.

Ellipsis
   This type has a single value.  There is a single object with this
   value. This object is accessed through the built-in name
   "Ellipsis". It is used to indicate the presence of the "..." syntax
   in a slice.  Its truth value is true.

"numbers.Number"
   此类对象由数字字面值创建，并会被作为算术运算符和算术内置函数的返回
   结果。数字对象是不可变的；一旦创建其值就不再改变。Python 中的数字当
   然非常类似数学中的数字，但也受限于计算机中的数字表示方法。

   Python 区分整型数、浮点型数和复数:

   "numbers.Integral"
      此类对象表示数学中整数集合的成员 (包括正数和负数)。

      There are three types of integers:

      Plain integers
         These represent numbers in the range -2147483648 through
         2147483647. (The range may be larger on machines with a
         larger natural word size, but not smaller.)  When the result
         of an operation would fall outside this range, the result is
         normally returned as a long integer (in some cases, the
         exception "OverflowError" is raised instead).  For the
         purpose of shift and mask operations, integers are assumed to
         have a binary, 2’s complement notation using 32 or more bits,
         and hiding no bits from the user (i.e., all 4294967296
         different bit patterns correspond to different values).

      Long integers
         此类对象表示任意大小的数字，仅受限于可用的内存 (包括虚拟内存)
         。在变换和掩码运算中会以二进制表示，负数会以 2 的补码表示，看
         起来像是符号位向左延伸补满空位。

      Booleans
         These represent the truth values False and True.  The two
         objects representing the values "False" and "True" are the
         only Boolean objects. The Boolean type is a subtype of plain
         integers, and Boolean values behave like the values 0 and 1,
         respectively, in almost all contexts, the exception being
         that when converted to a string, the strings ""False"" or
         ""True"" are returned, respectively.

      The rules for integer representation are intended to give the
      most meaningful interpretation of shift and mask operations
      involving negative integers and the least surprises when
      switching between the plain and long integer domains.  Any
      operation, if it yields a result in the plain integer domain,
      will yield the same result in the long integer domain or when
      using mixed operands.  The switch between domains is transparent
      to the programmer.

   "numbers.Real" ("float")
      此类对象表示机器级的双精度浮点数。其所接受的取值范围和溢出处理将
      受制于底层的机器架构 (以及 C 或 Java 实现)。Python 不支持单精度
      浮点数；支持后者通常的理由是节省处理器和内存消耗，但这会妨碍在
      Python 中使用对象，因此没有理由包含两种浮点数而令该语言变得复杂
      。

   "numbers.Complex"
      此类对象以一对机器级的双精度浮点数来表示复数值。有关浮点数的附带
      规则对其同样有效。一个复数值 "z" 的实部和虚部可通过只读属性
      "z.real" 和 "z.imag" 来获取。

序列
   此类对象表示以非负整数作为索引的有限有序集。内置函数 "len()" 可返回
   一个序列的条目数量。当一个序列的长度为 *n* 时，索引集包含数字 0, 1,
   …, *n*-1。序列 *a* 的条目 *i* 可通过 "a[i]" 选择。

   序列还支持切片: "a[i:j]" 选择索引号为 *k* 的所有条目，*i* "<=" *k*
   "<" *j*。当用作表达式时，序列的切片就是一个与序列类型相同的新序列。
   新序列的索引还是从 0 开始。

   有些序列还支持带有第三个 “step” 形参的 “扩展切片”: "a[i:j:k]" 选择
   *a* 中索引号为 *x* 的所有条目，"x = i + n*k", *n* ">=" "0" 且 *i*
   "<=" *x* "<" *j*。

   序列可根据其可变性来加以区分:

   不可变序列
      不可变序列类型的对象一旦创建就不能再改变。(如果对象包含对其他对
      象的引用，其中的可变对象就是可以改变的；但是，一个不可变对象所直
      接引用的对象集是不能改变的。)

      以下类型属于不可变对象:

      字符串
         The items of a string are characters.  There is no separate
         character type; a character is represented by a string of one
         item. Characters represent (at least) 8-bit bytes.  The
         built-in functions "chr()" and "ord()" convert between
         characters and nonnegative integers representing the byte
         values.  Bytes with the values 0–127 usually represent the
         corresponding ASCII values, but the interpretation of values
         is up to the program.  The string data type is also used to
         represent arrays of bytes, e.g., to hold data read from a
         file.

         (On systems whose native character set is not ASCII, strings
         may use EBCDIC in their internal representation, provided the
         functions "chr()" and "ord()" implement a mapping between
         ASCII and EBCDIC, and string comparison preserves the ASCII
         order. Or perhaps someone can propose a better rule?)

      Unicode
         The items of a Unicode object are Unicode code units.  A
         Unicode code unit is represented by a Unicode object of one
         item and can hold either a 16-bit or 32-bit value
         representing a Unicode ordinal (the maximum value for the
         ordinal is given in "sys.maxunicode", and depends on how
         Python is configured at compile time).  Surrogate pairs may
         be present in the Unicode object, and will be reported as two
         separate items.  The built-in functions "unichr()" and
         "ord()" convert between code units and nonnegative integers
         representing the Unicode ordinals as defined in the Unicode
         Standard 3.0. Conversion from and to other encodings are
         possible through the Unicode method "encode()" and the built-
         in function "unicode()".

      元组
         一个元组中的条目可以是任意 Python 对象。包含两个或以上条目的
         元组由逗号分隔的表达式构成。只有一个条目的元组 (‘单项元组’)
         可通过在表达式后加一个逗号来构成 (一个表达式本身不能创建为元
         组，因为圆括号要用来设置表达式分组)。一个空元组可通过一对内容
         为空的圆括号创建。

   可变序列
      可变序列在被创建后仍可被改变。下标和切片标注可被用作赋值和 "del"
      (删除) 语句的目标。

      目前有两种内生可变序列类型:

      列表
         列表中的条目可以是任意 Python 对象。列表由用方括号括起并由逗
         号分隔的多个表达式构成。(注意创建长度为 0 或 1 的列表无需使用
         特殊规则。)

      字节数组
         A bytearray object is a mutable array. They are created by
         the built-in "bytearray()" constructor.  Aside from being
         mutable (and hence unhashable), byte arrays otherwise provide
         the same interface and functionality as immutable bytes
         objects.

      The extension module "array" provides an additional example of a
      mutable sequence type.

集合类型
   此类对象表示由不重复且不可变对象组成的无序且有限的集合。因此它们不
   能通过下标来索引。但是它们可被迭代，也可用内置函数 "len()" 返回集合
   中的条目数。集合常见的用处是快速成员检测，去除序列中的重复项，以及
   进行交、并、差和对称差等数学运算。

   对于集合元素所采用的不可变规则与字典的键相同。注意数字类型遵循正常
   的数字比较规则: 如果两个数字相等 (例如 "1" 和 "1.0")，则同一集合中
   只能包含其中一个。

   目前有两种内生集合类型:

   集合
      此类对象表示可变集合。它们可通过内置的 "set()" 构造器创建，并且
      创建之后可以通过方法进行修改，例如 "add()"。

   冻结集合
      此类对象表示不可变集合。它们可通过内置的 "frozenset()" 构造器创
      建。由于 frozenset 对象不可变且 *hashable*，它可以被用作另一个集
      合的元素或是字典的键。

映射
   此类对象表示由任意索引集合所索引的对象的集合。通过下标 "a[k]" 可在
   映射 "a" 中选择索引为 "k" 的条目；这可以在表达式中使用，也可作为赋
   值或 "del" 语句的目标。内置函数 "len()" 可返回一个映射中的条目数。

   目前只有一种内生映射类型:

   字典
      此类对象表示由几乎任意值作为索引的有限个对象的集合。不可作为键的
      值类型只有包含列表或字典或其他可变类型，通过值而非对象编号进行比
      较的值，其原因在于高效的字典实现需要使用键的哈希值以保持一致性。
      用作键的数字类型遵循正常的数字比较规则: 如果两个数字相等 (例如
      "1" 和 "1.0") 则它们均可来用来索引同一个字典条目。

      字典是可变的；它们可通过 "{...}" 标注来创建 (参见 字典显示 小节)
      。

      The extension modules "dbm", "gdbm", and "bsddb" provide
      additional examples of mapping types.

可调用类型
   此类型可以被应用于函数调用操作 (参见 调用 小节):

   用户定义函数
      用户定义函数对象可通过函数定义来创建 (参见 函数定义 小节)。它被
      调用时应附带一个参数列表，其中包含的条目应与函数所定义的形参列表
      一致。

      特殊属性:

      +-------------------------+---------------------------------+-------------+
      | 属性                    | 意义                            |             |
      +=========================+=================================+=============+
      | "__doc__" "func_doc"    | The function’s documentation    | 可写        |
      |                         | string, or "None" if            |             |
      |                         | unavailable.                    |             |
      +-------------------------+---------------------------------+-------------+
      | "__name__" "func_name"  | 该函数的名称                    | 可写        |
      +-------------------------+---------------------------------+-------------+
      | "__module__"            | 该函数所属模块的名称，没有则为  | 可写        |
      |                         | "None"。                        |             |
      +-------------------------+---------------------------------+-------------+
      | "__defaults__"          | A tuple containing default      | 可写        |
      | "func_defaults"         | argument values for those       |             |
      |                         | arguments that have defaults,   |             |
      |                         | or "None" if no arguments have  |             |
      |                         | a default value.                |             |
      +-------------------------+---------------------------------+-------------+
      | "__code__" "func_code"  | 表示编译后的函数体的代码对象。  | 可写        |
      +-------------------------+---------------------------------+-------------+
      | "__globals__"           | 对存放该函数中全局变量的字典的  | 只读        |
      | "func_globals"          | 引用 — 函数所属模块的全局命名空 |             |
      |                         | 间 。                           |             |
      +-------------------------+---------------------------------+-------------+
      | "__dict__" "func_dict"  | 命名空间支持的函数属性。        | 可写        |
      +-------------------------+---------------------------------+-------------+
      | "__closure__"           | "None" or a tuple of cells that | 只读        |
      | "func_closure"          | contain bindings for the        |             |
      |                         | function’s free variables.      |             |
      +-------------------------+---------------------------------+-------------+

      大部分标有 “Writable” 的属性均会检查赋值的类型。

      在 2.4 版更改: "func_name" is now writable.

      在 2.6 版更改: The double-underscore attributes "__closure__",
      "__code__", "__defaults__", and "__globals__" were introduced as
      aliases for the corresponding "func_*" attributes for forwards
      compatibility with Python 3.

      函数对象也支持获取和设置任意属性，例如这可以被用来给函数附加元数
      据。使用正规的属性点号标注获取和设置此类属性。*注意当前实现仅支
      持用户定义函数属性。未来可能会增加支持内置函数属性。*

      有关函数定义的额外信息可以从其代码对象中提取；参见下文对内部类型
      的描述。

   User-defined methods
      A user-defined method object combines a class, a class instance
      (or "None") and any callable object (normally a user-defined
      function).

      Special read-only attributes: "im_self" is the class instance
      object, "im_func" is the function object; "im_class" is the
      class of "im_self" for bound methods or the class that asked for
      the method for unbound methods; "__doc__" is the method’s
      documentation (same as "im_func.__doc__"); "__name__" is the
      method name (same as "im_func.__name__"); "__module__" is the
      name of the module the method was defined in, or "None" if
      unavailable.

      在 2.2 版更改: "im_self" used to refer to the class that defined
      the method.

      在 2.6 版更改: For Python 3 forward-compatibility, "im_func" is
      also available as "__func__", and "im_self" as "__self__".

      方法还支持获取 (但不能设置) 下层函数对象的任意函数属性。

      User-defined method objects may be created when getting an
      attribute of a class (perhaps via an instance of that class), if
      that attribute is a user-defined function object, an unbound
      user-defined method object, or a class method object. When the
      attribute is a user-defined method object, a new method object
      is only created if the class from which it is being retrieved is
      the same as, or a derived class of, the class stored in the
      original method object; otherwise, the original method object is
      used as it is.

      When a user-defined method object is created by retrieving a
      user-defined function object from a class, its "im_self"
      attribute is "None" and the method object is said to be unbound.
      When one is created by retrieving a user-defined function object
      from a class via one of its instances, its "im_self" attribute
      is the instance, and the method object is said to be bound. In
      either case, the new method’s "im_class" attribute is the class
      from which the retrieval takes place, and its "im_func"
      attribute is the original function object.

      When a user-defined method object is created by retrieving
      another method object from a class or instance, the behaviour is
      the same as for a function object, except that the "im_func"
      attribute of the new instance is not the original method object
      but its "im_func" attribute.

      When a user-defined method object is created by retrieving a
      class method object from a class or instance, its "im_self"
      attribute is the class itself, and its "im_func" attribute is
      the function object underlying the class method.

      When an unbound user-defined method object is called, the
      underlying function ("im_func") is called, with the restriction
      that the first argument must be an instance of the proper class
      ("im_class") or of a derived class thereof.

      When a bound user-defined method object is called, the
      underlying function ("im_func") is called, inserting the class
      instance ("im_self") in front of the argument list.  For
      instance, when "C" is a class which contains a definition for a
      function "f()", and "x" is an instance of "C", calling "x.f(1)"
      is equivalent to calling "C.f(x, 1)".

      When a user-defined method object is derived from a class method
      object, the “class instance” stored in "im_self" will actually
      be the class itself, so that calling either "x.f(1)" or "C.f(1)"
      is equivalent to calling "f(C,1)" where "f" is the underlying
      function.

      Note that the transformation from function object to (unbound or
      bound) method object happens each time the attribute is
      retrieved from the class or instance. In some cases, a fruitful
      optimization is to assign the attribute to a local variable and
      call that local variable. Also notice that this transformation
      only happens for user-defined functions; other callable objects
      (and all non-callable objects) are retrieved without
      transformation.  It is also important to note that user-defined
      functions which are attributes of a class instance are not
      converted to bound methods; this *only* happens when the
      function is an attribute of the class.

   生成器函数
      A function or method which uses the "yield" statement (see
      section The yield statement) is called a *generator function*.
      Such a function, when called, always returns an iterator object
      which can be used to execute the body of the function:  calling
      the iterator’s "next()" method will cause the function to
      execute until it provides a value using the "yield" statement.
      When the function executes a "return" statement or falls off the
      end, a "StopIteration" exception is raised and the iterator will
      have reached the end of the set of values to be returned.

   内置函数
      内置函数对象是对于 C 函数的外部封装。内置函数的例子包括 "len()"
      和 "math.sin()"  ("math" 是一个标准内置模块)。内置函数参数的数量
      和类型由 C 函数决定。特殊的只读属性: "__doc__" 是函数的文档字符
      串，如果没有则为 "None"; "__name__" 是函数的名称; "__self__" 设
      定为 "None" (参见下一条目); "__module__" 是函数所属模块的名称，
      如果没有则为 "None"。

   内置方法
      此类型实际上是内置函数的另一种形式，只不过还包含了一个传入 C 函
      数的对象作为隐式的额外参数。内置方法的一个例子是
      "alist.append()"，其中 *alist* 为一个列表对象。在此示例中，特殊
      的只读属性 "__self__" 会被设为 *alist* 所标记的对象。

   Class Types
      Class types, or “new-style classes,” are callable.  These
      objects normally act as factories for new instances of
      themselves, but variations are possible for class types that
      override "__new__()".  The arguments of the call are passed to
      "__new__()" and, in the typical case, to "__init__()" to
      initialize the new instance.

   Classic Classes
      Class objects are described below.  When a class object is
      called, a new class instance (also described below) is created
      and returned.  This implies a call to the class’s "__init__()"
      method if it has one.  Any arguments are passed on to the
      "__init__()" method.  If there is no "__init__()" method, the
      class must be called without arguments.

   类实例
      Class instances are described below.  Class instances are
      callable only when the class has a "__call__()" method;
      "x(arguments)" is a shorthand for "x.__call__(arguments)".

模块
   Modules are imported by the "import" statement (see section The
   import statement). A module object has a namespace implemented by a
   dictionary object (this is the dictionary referenced by the
   func_globals attribute of functions defined in the module).
   Attribute references are translated to lookups in this dictionary,
   e.g., "m.x" is equivalent to "m.__dict__["x"]". A module object
   does not contain the code object used to initialize the module
   (since it isn’t needed once the initialization is done).

   属性赋值会更新模块的命名空间字典，例如 "m.x = 1" 等同于
   "m.__dict__["x"] = 1"。

   特殊的只读属性: "__dict__" 为以字典对象表示的模块命名空间。

   由于 CPython 清理模块字典的设定，当模块离开作用域时模块字典将会被清
   理，即使该字典还有活动的引用。想避免此问题，可复制该字典或保持模块
   状态以直接使用其字典。

   Predefined (writable) attributes: "__name__" is the module’s name;
   "__doc__" is the module’s documentation string, or "None" if
   unavailable; "__file__" is the pathname of the file from which the
   module was loaded, if it was loaded from a file. The "__file__"
   attribute is not present for C modules that are statically linked
   into the interpreter; for extension modules loaded dynamically from
   a shared library, it is the pathname of the shared library file.

类
   Both class types (new-style classes) and class objects (old-
   style/classic classes) are typically created by class definitions
   (see section 类定义).  A class has a namespace implemented by a
   dictionary object. Class attribute references are translated to
   lookups in this dictionary, e.g., "C.x" is translated to
   "C.__dict__["x"]" (although for new-style classes in particular
   there are a number of hooks which allow for other means of locating
   attributes). When the attribute name is not found there, the
   attribute search continues in the base classes.  For old-style
   classes, the search is depth-first, left-to-right in the order of
   occurrence in the base class list. New-style classes use the more
   complex C3 method resolution order which behaves correctly even in
   the presence of ‘diamond’ inheritance structures where there are
   multiple inheritance paths leading back to a common ancestor.
   Additional details on the C3 MRO used by new-style classes can be
   found in the documentation accompanying the 2.3 release at
   https://www.python.org/download/releases/2.3/mro/.

   When a class attribute reference (for class "C", say) would yield a
   user-defined function object or an unbound user-defined method
   object whose associated class is either "C" or one of its base
   classes, it is transformed into an unbound user-defined method
   object whose "im_class" attribute is "C". When it would yield a
   class method object, it is transformed into a bound user-defined
   method object whose "im_self" attribute is "C".  When it would
   yield a static method object, it is transformed into the object
   wrapped by the static method object. See section 实现描述器 for
   another way in which attributes retrieved from a class may differ
   from those actually contained in its "__dict__" (note that only
   new-style classes support descriptors).

   类属性赋值会更新类的字典，但不会更新基类的字典。

   类对象可被调用 (见上文) 以产生一个类实例 (见下文)。

   Special attributes: "__name__" is the class name; "__module__" is
   the module name in which the class was defined; "__dict__" is the
   dictionary containing the class’s namespace; "__bases__" is a tuple
   (possibly empty or a singleton) containing the base classes, in the
   order of their occurrence in the base class list; "__doc__" is the
   class’s documentation string, or "None" if undefined.

类实例
   A class instance is created by calling a class object (see above).
   A class instance has a namespace implemented as a dictionary which
   is the first place in which attribute references are searched.
   When an attribute is not found there, and the instance’s class has
   an attribute by that name, the search continues with the class
   attributes.  If a class attribute is found that is a user-defined
   function object or an unbound user-defined method object whose
   associated class is the class (call it "C") of the instance for
   which the attribute reference was initiated or one of its bases, it
   is transformed into a bound user-defined method object whose
   "im_class" attribute is "C" and whose "im_self" attribute is the
   instance. Static method and class method objects are also
   transformed, as if they had been retrieved from class "C"; see
   above under “Classes”. See section 实现描述器 for another way in
   which attributes of a class retrieved via its instances may differ
   from the objects actually stored in the class’s "__dict__". If no
   class attribute is found, and the object’s class has a
   "__getattr__()" method, that is called to satisfy the lookup.

   属性赋值和删除会更新实例的字典，但不会更新对应类的字典。如果类具有
   "__setattr__()" 或 "__delattr__()" 方法，则将调用方法而不再直接更新
   实例的字典。

   如果类实例具有某些特殊名称的方法，就可以伪装为数字、序列或映射。参
   见 特殊方法名称 一节。

   特殊属性: "__dict__" 为属性字典; "__class__" 为实例对应的类。

Files
   A file object represents an open file.  File objects are created by
   the "open()" built-in function, and also by "os.popen()",
   "os.fdopen()", and the "makefile()" method of socket objects (and
   perhaps by other functions or methods provided by extension
   modules).  The objects "sys.stdin", "sys.stdout" and "sys.stderr"
   are initialized to file objects corresponding to the interpreter’s
   standard input, output and error streams.  See File Objects for
   complete documentation of file objects.

内部类型
   某些由解释器内部使用的类型也被暴露给用户。它们的定义可能随未来解释
   器版本的更新而变化，为内容完整起见在此处一并介绍。

   代码对象
      代码对象表示 *编译为字节的* 可执行 Python 代码，或称 *bytecode*
      。代码对象和函数对象的区别在于函数对象包含对函数全局对象 (函数所
      属的模块) 的显式引用，而代码对象不包含上下文；而且默认参数值会存
      放于函数对象而不是代码对象内 (因为它们表示在运行时算出的值)。与
      函数对象不同，代码对象不可变，也不包含对可变对象的引用 (不论是直
      接还是间接)。

      特殊的只读属性: "co_name" 为函数名称; "co_argcount" 为位置参数的
      数量 (包括有默认值的参数); "co_nlocals" 为函数使用的本地变量数量
      (包括参数); "co_varnames" 为一个包含本地变量名称的元组 (以参数名
      打头); "co_cellvars" 为一个包含被嵌套函数所引用的本地变量名称的
      元组; "co_freevars" 为一个包含自由变量的元组; "co_code" 为一个表
      示字节码指令序列的字符串; "co_consts" 为一个包含字节码所使用的字
      面值的元组; "co_names" 为一个包含字节码所使用的名称的元组;
      "co_filename" 为被编译代码所在的文件名; "co_firstlineno" 为函数
      首行的行号; "co_lnotab" 为一个以编码表示的从字节码偏移量到行号的
      映射的字符串 (详情参见解释器的源码); "co_stacksize" 为要求的栈大
      小 (包括本地变量); "co_flags" 为一个以编码表示的多个解释器所用标
      志的整型数。

      以下是可用于 "co_flags" 的标志位定义: 如果函数使用 "*arguments"
      语法来接受任意数量的位置参数则设置 "0x04" 位;  如果函数使用
      "**keywords" 语法来接受任意数量的关键字参数则设置 "0x08``位; 如
      果函数是一个生成器则设置 ``0x20" 位。

      未来特性声明 ("from __future__ import division") 也使用
      "co_flags" 中的标志位来指明代码对象的编译是否启用特定的特性: 如
      果函数编译时启用未来除法特性则设置 "0x2000" 位; 在更早的 Python
      版本中则使用 "0x10" 和 "0x1000" 位。

      "co_flags" 中的其他位被保留为内部使用。

      如果代码对象表示一个函数，"co_consts" 中的第一项将是函数的文档字
      符串，如果未定义则为 "None"。

   帧对象
      Frame objects represent execution frames.  They may occur in
      traceback objects (see below).

      Special read-only attributes: "f_back" is to the previous stack
      frame (towards the caller), or "None" if this is the bottom
      stack frame; "f_code" is the code object being executed in this
      frame; "f_locals" is the dictionary used to look up local
      variables; "f_globals" is used for global variables;
      "f_builtins" is used for built-in (intrinsic) names;
      "f_restricted" is a flag indicating whether the function is
      executing in restricted execution mode; "f_lasti" gives the
      precise instruction (this is an index into the bytecode string
      of the code object).

      Special writable attributes: "f_trace", if not "None", is a
      function called at the start of each source code line (this is
      used by the debugger); "f_exc_type", "f_exc_value",
      "f_exc_traceback" represent the last exception raised in the
      parent frame provided another exception was ever raised in the
      current frame (in all other cases they are "None"); "f_lineno"
      is the current line number of the frame — writing to this from
      within a trace function jumps to the given line (only for the
      bottom-most frame).  A debugger can implement a Jump command
      (aka Set Next Statement) by writing to f_lineno.

   回溯对象
      Traceback objects represent a stack trace of an exception.  A
      traceback object is created when an exception occurs.  When the
      search for an exception handler unwinds the execution stack, at
      each unwound level a traceback object is inserted in front of
      the current traceback.  When an exception handler is entered,
      the stack trace is made available to the program. (See section
      The try statement.) It is accessible as "sys.exc_traceback", and
      also as the third item of the tuple returned by
      "sys.exc_info()".  The latter is the preferred interface, since
      it works correctly when the program is using multiple threads.
      When the program contains no suitable handler, the stack trace
      is written (nicely formatted) to the standard error stream; if
      the interpreter is interactive, it is also made available to the
      user as "sys.last_traceback".

      Special read-only attributes: "tb_next" is the next level in the
      stack trace (towards the frame where the exception occurred), or
      "None" if there is no next level; "tb_frame" points to the
      execution frame of the current level; "tb_lineno" gives the line
      number where the exception occurred; "tb_lasti" indicates the
      precise instruction.  The line number and last instruction in
      the traceback may differ from the line number of its frame
      object if the exception occurred in a "try" statement with no
      matching except clause or with a finally clause.

   切片对象
      Slice objects are used to represent slices when *extended slice
      syntax* is used. This is a slice using two colons, or multiple
      slices or ellipses separated by commas, e.g., "a[i:j:step]",
      "a[i:j, k:l]", or "a[..., i:j]".  They are also created by the
      built-in "slice()" function.

      特殊的只读属性: "start" 为下界; "stop" 为上界; "step" 为步长值;
      各值如省略则为 "None"。这些属性可具有任意类型。

      切片对象支持一个方法:

      slice.indices(self, length)

         This method takes a single integer argument *length* and
         computes information about the extended slice that the slice
         object would describe if applied to a sequence of *length*
         items.  It returns a tuple of three integers; respectively
         these are the *start* and *stop* indices and the *step* or
         stride length of the slice. Missing or out-of-bounds indices
         are handled in a manner consistent with regular slices.

         2.3 新版功能.

   静态方法对象
      静态方法对象提供了一种避免上文所述将函数对象转换为方法对象的方式
      。静态方法对象为对任意其他对象的封装，通常用来封装用户定义方法对
      象。当从类或类实例获取一个静态方法对象时，实际返回的对象是封装的
      对象，它不会被进一步转换。静态方法对象自身不是可调用的，但它们所
      封装的对象通常都是可调用的。静态方法对象可通过内置的
      "staticmethod()" 构造器来创建。

   类方法对象
      类方法对象和静态方法一样是对其他对象的封装，会改变从类或类实例获
      取该对象的方式。类方法对象在此类获取操作中的行为已在上文  “用户
      定义方法” 一节中描述。类方法对象可通过内置的 "classmethod()" 构
      造器来创建。


3.3. New-style and classic classes
==================================

Classes and instances come in two flavors: old-style (or classic) and
new-style.

Up to Python 2.1 the concept of "class" was unrelated to the concept
of "type", and old-style classes were the only flavor available.  For
an old-style class, the statement "x.__class__" provides the class of
*x*, but "type(x)" is always "<type 'instance'>".  This reflects the
fact that all old-style instances, independent of their class, are
implemented with a single built-in type, called "instance".

New-style classes were introduced in Python 2.2 to unify the concepts
of "class" and "type".  A new-style class is simply a user-defined
type, no more, no less.  If *x* is an instance of a new-style class,
then "type(x)" is typically the same as "x.__class__" (although this
is not guaranteed – a new-style class instance is permitted to
override the value returned for "x.__class__").

The major motivation for introducing new-style classes is to provide a
unified object model with a full meta-model.  It also has a number of
practical benefits, like the ability to subclass most built-in types,
or the introduction of “descriptors”, which enable computed
properties.

For compatibility reasons, classes are still old-style by default.
New-style classes are created by specifying another new-style class
(i.e. a type) as a parent class, or the “top-level type” "object" if
no other parent is needed.  The behaviour of new-style classes differs
from that of old-style classes in a number of important details in
addition to what "type()" returns.  Some of these changes are
fundamental to the new object model, like the way special methods are
invoked.  Others are “fixes” that could not be implemented before for
compatibility concerns, like the method resolution order in case of
multiple inheritance.

While this manual aims to provide comprehensive coverage of Python’s
class mechanics, it may still be lacking in some areas when it comes
to its coverage of new-style classes. Please see
https://www.python.org/doc/newstyle/ for sources of additional
information.

Old-style classes are removed in Python 3, leaving only new-style
classes.


3.4. 特殊方法名称
=================

A class can implement certain operations that are invoked by special
syntax (such as arithmetic operations or subscripting and slicing) by
defining methods with special names. This is Python’s approach to
*operator overloading*, allowing classes to define their own behavior
with respect to language operators.  For instance, if a class defines
a method named "__getitem__()", and "x" is an instance of this class,
then "x[i]" is roughly equivalent to "x.__getitem__(i)" for old-style
classes and "type(x).__getitem__(x, i)" for new-style classes.  Except
where mentioned, attempts to execute an operation raise an exception
when no appropriate method is defined (typically "AttributeError" or
"TypeError").

在实现模拟任何内置类型的类时，很重要的一点是模拟的实现程度对于被模拟对
象来说应当是有意义的。例如，提取单个元素的操作对于某些序列来说是适宜的
，但提取切片可能就没有意义。(这种情况的一个实例是 W3C 的文档对象模型中
的 "NodeList" 接口。)


3.4.1. 基本定制
---------------

object.__new__(cls[, ...])

   调用以创建一个 *cls* 类的新实例。"__new__()" 是一个静态方法 (因为是
   特例所以你不需要显式地声明)，它会将所请求实例所属的类作为第一个参数
   。其余的参数会被传递给对象构造器表达式 (对类的调用)。"__new__()" 的
   返回值应为新对象实例 (通常是 *cls* 的实例)。

   Typical implementations create a new instance of the class by
   invoking the superclass’s "__new__()" method using
   "super(currentclass, cls).__new__(cls[, ...])" with appropriate
   arguments and then modifying the newly-created instance as
   necessary before returning it.

   如果 "__new__()" 返回一个 *cls* 的实例，则新实例的 "__init__()" 方
   法会在之后被执行，例如 "__init__(self[, ...])"，其中 *self* 为新实
   例，其余的参数与被传递给 "__new__()" 的相同。

   如果 "__new__()" 未返回一个 *cls* 的实例，则新实例的 "__init__()"
   方法就不会被执行。

   "__new__()" 的目的主要是允许不可变类型的子类 (例如 int, str 或
   tuple) 定制实例创建过程。它也常会在自定义元类中被重载以便定制类创建
   过程。

object.__init__(self[, ...])

   Called after the instance has been created (by "__new__()"), but
   before it is returned to the caller.  The arguments are those
   passed to the class constructor expression.  If a base class has an
   "__init__()" method, the derived class’s "__init__()" method, if
   any, must explicitly call it to ensure proper initialization of the
   base class part of the instance; for example:
   "BaseClass.__init__(self, [args...])".

   Because "__new__()" and "__init__()" work together in constructing
   objects ("__new__()" to create it, and "__init__()" to customise
   it), no non-"None" value may be returned by "__init__()"; doing so
   will cause a "TypeError" to be raised at runtime.

object.__del__(self)

   Called when the instance is about to be destroyed.  This is also
   called a destructor.  If a base class has a "__del__()" method, the
   derived class’s "__del__()" method, if any, must explicitly call it
   to ensure proper deletion of the base class part of the instance.
   Note that it is possible (though not recommended!) for the
   "__del__()" method to postpone destruction of the instance by
   creating a new reference to it.  It may then be called at a later
   time when this new reference is deleted.  It is not guaranteed that
   "__del__()" methods are called for objects that still exist when
   the interpreter exits.

   注解: "del x" doesn’t directly call "x.__del__()" — the former
     decrements the reference count for "x" by one, and the latter is
     only called when "x"’s reference count reaches zero.  Some common
     situations that may prevent the reference count of an object from
     going to zero include: circular references between objects (e.g.,
     a doubly-linked list or a tree data structure with parent and
     child pointers); a reference to the object on the stack frame of
     a function that caught an exception (the traceback stored in
     "sys.exc_traceback" keeps the stack frame alive); or a reference
     to the object on the stack frame that raised an unhandled
     exception in interactive mode (the traceback stored in
     "sys.last_traceback" keeps the stack frame alive).  The first
     situation can only be remedied by explicitly breaking the cycles;
     the latter two situations can be resolved by storing "None" in
     "sys.exc_traceback" or "sys.last_traceback".  Circular references
     which are garbage are detected when the option cycle detector is
     enabled (it’s on by default), but can only be cleaned up if there
     are no Python-level "__del__()" methods involved. Refer to the
     documentation for the "gc" module for more information about how
     "__del__()" methods are handled by the cycle detector,
     particularly the description of the "garbage" value.

   警告: Due to the precarious circumstances under which "__del__()"
     methods are invoked, exceptions that occur during their execution
     are ignored, and a warning is printed to "sys.stderr" instead.
     Also, when "__del__()" is invoked in response to a module being
     deleted (e.g., when execution of the program is done), other
     globals referenced by the "__del__()" method may already have
     been deleted or in the process of being torn down (e.g. the
     import machinery shutting down).  For this reason, "__del__()"
     methods should do the absolute minimum needed to maintain
     external invariants.  Starting with version 1.5, Python
     guarantees that globals whose name begins with a single
     underscore are deleted from their module before other globals are
     deleted; if no other references to such globals exist, this may
     help in assuring that imported modules are still available at the
     time when the "__del__()" method is called.

   See also the "-R" command-line option.

object.__repr__(self)

   Called by the "repr()" built-in function and by string conversions
   (reverse quotes) to compute the “official” string representation of
   an object.  If at all possible, this should look like a valid
   Python expression that could be used to recreate an object with the
   same value (given an appropriate environment).  If this is not
   possible, a string of the form "<...some useful description...>"
   should be returned.  The return value must be a string object. If a
   class defines "__repr__()" but not "__str__()", then "__repr__()"
   is also used when an “informal” string representation of instances
   of that class is required.

   此方法通常被用于调试，因此确保其表示的内容包含丰富信息且无歧义是很
   重要的。

object.__str__(self)

   Called by the "str()" built-in function and by the "print"
   statement to compute the “informal” string representation of an
   object.  This differs from "__repr__()" in that it does not have to
   be a valid Python expression: a more convenient or concise
   representation may be used instead. The return value must be a
   string object.

object.__lt__(self, other)
object.__le__(self, other)
object.__eq__(self, other)
object.__ne__(self, other)
object.__gt__(self, other)
object.__ge__(self, other)

   2.1 新版功能.

   These are the so-called “rich comparison” methods, and are called
   for comparison operators in preference to "__cmp__()" below. The
   correspondence between operator symbols and method names is as
   follows: "x<y" calls "x.__lt__(y)", "x<=y" calls "x.__le__(y)",
   "x==y" calls "x.__eq__(y)", "x!=y" and "x<>y" call "x.__ne__(y)",
   "x>y" calls "x.__gt__(y)", and "x>=y" calls "x.__ge__(y)".

   如果指定的参数对没有相应的实现，富比较方法可能会返回单例对象
   "NotImplemented"。按照惯例，成功的比较会返回 "False" 或 "True"。不
   过实际上这些方法可以返回任意值，因此如果比较运算符是要用于布尔值判
   断（例如作为 "if" 语句的条件），Python 会对返回值调用 "bool()" 以确
   定结果为真还是假。

   There are no implied relationships among the comparison operators.
   The truth of "x==y" does not imply that "x!=y" is false.
   Accordingly, when defining "__eq__()", one should also define
   "__ne__()" so that the operators will behave as expected.  See the
   paragraph on "__hash__()" for some important notes on creating
   *hashable* objects which support custom comparison operations and
   are usable as dictionary keys.

   There are no swapped-argument versions of these methods (to be used
   when the left argument does not support the operation but the right
   argument does); rather, "__lt__()" and "__gt__()" are each other’s
   reflection, "__le__()" and "__ge__()" are each other’s reflection,
   and "__eq__()" and "__ne__()" are their own reflection.

   Arguments to rich comparison methods are never coerced.

   To automatically generate ordering operations from a single root
   operation, see "functools.total_ordering()".

object.__cmp__(self, other)

   Called by comparison operations if rich comparison (see above) is
   not defined.  Should return a negative integer if "self < other",
   zero if "self == other", a positive integer if "self > other".  If
   no "__cmp__()", "__eq__()" or "__ne__()" operation is defined,
   class instances are compared by object identity (“address”).  See
   also the description of "__hash__()" for some important notes on
   creating *hashable* objects which support custom comparison
   operations and are usable as dictionary keys. (Note: the
   restriction that exceptions are not propagated by "__cmp__()" has
   been removed since Python 1.5.)

object.__rcmp__(self, other)

   在 2.1 版更改: No longer supported.

object.__hash__(self)

   Called by built-in function "hash()" and for operations on members
   of hashed collections including "set", "frozenset", and "dict".
   "__hash__()" should return an integer.  The only required property
   is that objects which compare equal have the same hash value; it is
   advised to mix together the hash values of the components of the
   object that also play a part in comparison of objects by packing
   them into a tuple and hashing the tuple. Example:

      def __hash__(self):
          return hash((self.name, self.nick, self.color))

   If a class does not define a "__cmp__()" or "__eq__()" method it
   should not define a "__hash__()" operation either; if it defines
   "__cmp__()" or "__eq__()" but not "__hash__()", its instances will
   not be usable in hashed collections.  If a class defines mutable
   objects and implements a "__cmp__()" or "__eq__()" method, it
   should not implement "__hash__()", since hashable collection
   implementations require that an object’s hash value is immutable
   (if the object’s hash value changes, it will be in the wrong hash
   bucket).

   User-defined classes have "__cmp__()" and "__hash__()" methods by
   default; with them, all objects compare unequal (except with
   themselves) and "x.__hash__()" returns a result derived from
   "id(x)".

   Classes which inherit a "__hash__()" method from a parent class but
   change the meaning of "__cmp__()" or "__eq__()" such that the hash
   value returned is no longer appropriate (e.g. by switching to a
   value-based concept of equality instead of the default identity
   based equality) can explicitly flag themselves as being unhashable
   by setting "__hash__ = None" in the class definition. Doing so
   means that not only will instances of the class raise an
   appropriate "TypeError" when a program attempts to retrieve their
   hash value, but they will also be correctly identified as
   unhashable when checking "isinstance(obj, collections.Hashable)"
   (unlike classes which define their own "__hash__()" to explicitly
   raise "TypeError").

   在 2.5 版更改: "__hash__()" may now also return a long integer
   object; the 32-bit integer is then derived from the hash of that
   object.

   在 2.6 版更改: "__hash__" may now be set to "None" to explicitly
   flag instances of a class as unhashable.

object.__nonzero__(self)

   Called to implement truth value testing and the built-in operation
   "bool()"; should return "False" or "True", or their integer
   equivalents "0" or "1".  When this method is not defined,
   "__len__()" is called, if it is defined, and the object is
   considered true if its result is nonzero. If a class defines
   neither "__len__()" nor "__nonzero__()", all its instances are
   considered true.

object.__unicode__(self)

   Called to implement "unicode()" built-in; should return a Unicode
   object. When this method is not defined, string conversion is
   attempted, and the result of string conversion is converted to
   Unicode using the system default encoding.


3.4.2. 自定义属性访问
---------------------

可以定义下列方法来自定义对类实例属性访问（"x.name" 的使用、赋值或删除
）的具体含义.

object.__getattr__(self, name)

   Called when an attribute lookup has not found the attribute in the
   usual places (i.e. it is not an instance attribute nor is it found
   in the class tree for "self").  "name" is the attribute name. This
   method should return the (computed) attribute value or raise an
   "AttributeError" exception.

   Note that if the attribute is found through the normal mechanism,
   "__getattr__()" is not called.  (This is an intentional asymmetry
   between "__getattr__()" and "__setattr__()".) This is done both for
   efficiency reasons and because otherwise "__getattr__()" would have
   no way to access other attributes of the instance.  Note that at
   least for instance variables, you can fake total control by not
   inserting any values in the instance attribute dictionary (but
   instead inserting them in another object).  See the
   "__getattribute__()" method below for a way to actually get total
   control in new-style classes.

object.__setattr__(self, name, value)

   Called when an attribute assignment is attempted.  This is called
   instead of the normal mechanism (i.e. store the value in the
   instance dictionary).  *name* is the attribute name, *value* is the
   value to be assigned to it.

   If "__setattr__()" wants to assign to an instance attribute, it
   should not simply execute "self.name = value" — this would cause a
   recursive call to itself.  Instead, it should insert the value in
   the dictionary of instance attributes, e.g., "self.__dict__[name] =
   value".  For new-style classes, rather than accessing the instance
   dictionary, it should call the base class method with the same
   name, for example, "object.__setattr__(self, name, value)".

object.__delattr__(self, name)

   类似于 "__setattr__()" 但其作用为删除而非赋值。此方法应该仅在 "del
   obj.name" 对于该对象有意义时才被实现。


3.4.2.1. More attribute access for new-style classes
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The following methods only apply to new-style classes.

object.__getattribute__(self, name)

   此方法会无条件地被调用以实现对类实例属性的访问。如果类还定义了
   "__getattr__()"，则后者不会被调用，除非 "__getattribute__()" 显式地
   调用它或是引发了 "AttributeError"。此方法应当返回（找到的）属性值或
   是引发一个 "AttributeError" 异常。为了避免此方法中的无限递归，其实
   现应该总是调用具有相同名称的基类方法来访问它所需要的任何属性，例如
   "object.__getattribute__(self, name)"。

   注解: This method may still be bypassed when looking up special
     methods as the result of implicit invocation via language syntax
     or built-in functions. See Special method lookup for new-style
     classes.


3.4.2.2. 实现描述器
~~~~~~~~~~~~~~~~~~~

以下方法仅当一个包含该方法的类（称为 *描述器* 类）的实例出现于一个 *所
有者* 类中的时候才会起作用（该描述器必须在所有者类或其某个上级类的字典
中）。在以下示例中，“属性”指的是名称为所有者类 "__dict__" 中的特征属性
的键名的属性。

object.__get__(self, instance, owner)

   调用此方法以获取所有者类的属性（类属性访问）或该类的实例的属性（实
   例属性访问）。*所有者* 是指所有者类，而 *实例* 是指被用来访问属性的
   实例，如果是 *所有者* 被用来访问属性时则为 "None"。此方法应当返回（
   计算出的）属性值或是引发一个 "AttributeError" 异常。

object.__set__(self, instance, value)

   调用此方法以设置 *instance* 指定的所有者类的实例的属性为新值
   *value*。

object.__delete__(self, instance)

   调用此方法以删除 *instance* 指定的所有者类的实例的属性。


3.4.2.3. 发起调用描述器
~~~~~~~~~~~~~~~~~~~~~~~

总的说来，描述器就是具有“绑定行为”的对象属性，其属性访问已被描述器协议
中的方法所重载，包括 "__get__()", "__set__()" 和 "__delete__()"。如果
一个对象定义了以上方法中的任意一个，它就被称为描述器。

属性访问的默认行为是从一个对象的字典中获取、设置或删除属性。例如，
"a.x" 的查找顺序会从 "a.__dict__['x']" 开始，然后是
"type(a).__dict__['x']"，接下来依次查找 "type(a)" 的上级基类，不包括元
类。

However, if the looked-up value is an object defining one of the
descriptor methods, then Python may override the default behavior and
invoke the descriptor method instead.  Where this occurs in the
precedence chain depends on which descriptor methods were defined and
how they were called.  Note that descriptors are only invoked for new
style objects or classes (ones that subclass "object()" or "type()").

描述器发起调用的开始点是一个绑定 "a.x"。参数的组合方式依 "a" 而定:

直接调用
   最简单但最不常见的调用方式是用户代码直接发起调用一个描述器方法:
   "x.__get__(a)"。

实例绑定
   If binding to a new-style object instance, "a.x" is transformed
   into the call: "type(a).__dict__['x'].__get__(a, type(a))".

类绑定
   If binding to a new-style class, "A.x" is transformed into the
   call: "A.__dict__['x'].__get__(None, A)".

超绑定
   如果 "a" 是 "super" 的一个实例，则绑定 "super(B, obj).m()" 会在
   "obj.__class__.__mro__" 中搜索 "B" 的直接上级基类 "A" 然后通过以下
   调用发起调用描述器: "A.__dict__['m'].__get__(obj, obj.__class__)"。

对于实例绑定，发起描述器调用的优先级取决于定义了哪些描述器方法。一个描
述器可以定义 "__get__()"、"__set__()" 和 "__delete__()" 的任意组合。如
果它没有定义 "__get__()"，则访问属性会返回描述器对象自身，除非对象的实
例字典中有相应属性值。如果描述器定义了 "__set__()" 和/或
"__delete__()"，则它是一个数据描述器；如果以上两个都未定义，则它是一个
非数据描述器。通常，数据描述器会同时定义 "__get__()" 和 "__set__()"，
而非数据描述器只有 "__get__()" 方法。定义了 "__set__()" 和 "__get__()"
的数据描述器总是会重载实例字典中的定义。与之相对的，非数据描述器可被实
例所重载。

Python 方法 (包括 "staticmethod()" 和 "classmethod()") 都是作为非描述
器来实现的。因此实例可以重定义并重载方法。这允许单个实例获得与相同类的
其他实例不一样的行为。

"property()" 函数是作为数据描述器来实现的。因此实例不能重载特性属性的
行为。


3.4.2.4. __slots__
~~~~~~~~~~~~~~~~~~

By default, instances of both old and new-style classes have a
dictionary for attribute storage.  This wastes space for objects
having very few instance variables.  The space consumption can become
acute when creating large numbers of instances.

The default can be overridden by defining *__slots__* in a new-style
class definition.  The *__slots__* declaration takes a sequence of
instance variables and reserves just enough space in each instance to
hold a value for each variable.  Space is saved because *__dict__* is
not created for each instance.

__slots__

   This class variable can be assigned a string, iterable, or sequence
   of strings with variable names used by instances.  If defined in a
   new-style class, *__slots__* reserves space for the declared
   variables and prevents the automatic creation of *__dict__* and
   *__weakref__* for each instance.

   2.2 新版功能.

使用 *__slots__* 的注意事项

* When inheriting from a class without *__slots__*, the *__dict__*
  attribute of that class will always be accessible, so a *__slots__*
  definition in the subclass is meaningless.

* 没有 *__dict__* 变量，实例就不能给未在 *__slots__* 定义中列出的新
  变 量赋值。尝试给一个未列出的变量名赋值将引发 "AttributeError"。新变
  量 需要动态赋值，就要将 "'__dict__'" 加入到 *__slots__* 声明的字符串
  序 列中。

  在 2.3 版更改: Previously, adding "'__dict__'" to the *__slots__*
  declaration would not enable the assignment of new attributes not
  specifically listed in the sequence of instance variable names.

* 如果未给每个实例设置 *__weakref__* 变量，定义了 *__slots__* 的类就
  不 支持对其实际的弱引用。如果需要弱引用支持，就要将 "'__weakref__'"
  加 入到 *__slots__* 声明的字符串序列中。

  在 2.3 版更改: Previously, adding "'__weakref__'" to the *__slots__*
  declaration would not enable support for weak references.

* *__slots__* 是通过为每个变量名创建描述器 (实现描述器) 在类层级上实
  现 的。因此，类属性不能被用来为通过 *__slots__* 定义的实例变量设置默
  认 值；否则，类属性就会覆盖描述器赋值。

* The action of a *__slots__* declaration is limited to the class
  where it is defined.  As a result, subclasses will have a *__dict__*
  unless they also define *__slots__* (which must only contain names
  of any *additional* slots).

* 如果一个类定义的位置在某个基类中也有定义，则由基类位置定义的实例变
  量 将不可访问（除非通过直接从基类获取其描述器的方式）。这会使得程序
  的含 义变成未定义。未来可能会添加一个防止此情况的检查。

* Nonempty *__slots__* does not work for classes derived from
  “variable-length” built-in types such as "long", "str" and "tuple".

* 任何非字符串可迭代对象都可以被赋值给 *__slots__*。映射也可以被使用
  ； 不过，未来可能会分别赋给每个键具有特殊含义的值。

* *__class__* 赋值仅在两个类具有相同的 *__slots__* 时才会起作用。

  在 2.6 版更改: Previously, *__class__* assignment raised an error if
  either new or old class had *__slots__*.


3.4.3. 自定义类创建
-------------------

By default, new-style classes are constructed using "type()". A class
definition is read into a separate namespace and the value of class
name is bound to the result of "type(name, bases, dict)".

When the class definition is read, if *__metaclass__* is defined then
the callable assigned to it will be called instead of "type()". This
allows classes or functions to be written which monitor or alter the
class creation process:

* Modifying the class dictionary prior to the class being created.

* Returning an instance of another class – essentially performing
  the role of a factory function.

These steps will have to be performed in the metaclass’s "__new__()"
method – "type.__new__()" can then be called from this method to
create a class with different properties.  This example adds a new
element to the class dictionary before creating the class:

   class metacls(type):
       def __new__(mcs, name, bases, dict):
           dict['foo'] = 'metacls was here'
           return type.__new__(mcs, name, bases, dict)

You can of course also override other class methods (or add new
methods); for example defining a custom "__call__()" method in the
metaclass allows custom behavior when the class is called, e.g. not
always creating a new instance.

__metaclass__

   This variable can be any callable accepting arguments for "name",
   "bases", and "dict".  Upon class creation, the callable is used
   instead of the built-in "type()".

   2.2 新版功能.

The appropriate metaclass is determined by the following precedence
rules:

* If "dict['__metaclass__']" exists, it is used.

* Otherwise, if there is at least one base class, its metaclass is
  used (this looks for a *__class__* attribute first and if not found,
  uses its type).

* Otherwise, if a global variable named __metaclass__ exists, it is
  used.

* Otherwise, the old-style, classic metaclass (types.ClassType) is
  used.

The potential uses for metaclasses are boundless. Some ideas that have
been explored including logging, interface checking, automatic
delegation, automatic property creation, proxies, frameworks, and
automatic resource locking/synchronization.


3.4.4. 自定义实例及子类检查
---------------------------

2.6 新版功能.

以下方法被用来重载 "isinstance()" 和 "issubclass()" 内置函数的默认行为
。

特别地，元类 "abc.ABCMeta" 实现了这些方法以便允许将抽象基类（ABC）作为
“虚拟基类”添加到任何类或类型（包括内置类型），包括其他 ABC 之中。

class.__instancecheck__(self, instance)

   如果 *instance* 应被视为 *class* 的一个（直接或间接）实例则返回真值
   。如果定义了此方法，则会被调用以实现 "isinstance(instance, class)"
   。

class.__subclasscheck__(self, subclass)

   Return true 如果 *subclass* 应被视为 *class* 的一个（直接或间接）子
   类则返回真值。如果定义了此方法，则会被调用以实现
   "issubclass(subclass, class)"。

请注意这些方法的查找是基于类的类型（元类）。它们不能作为类方法在实际的
类中被定义。这与基于实例被调用的特殊方法的查找是一致的，只有在此情况下
实例本身被当作是类。

参见:

  **PEP 3119** - 引入抽象基类
     新增功能描述，通过 "__instancecheck__()" 和 "__subclasscheck__()"
     来定制 "isinstance()" 和 "issubclass()" 行为，加入此功能的动机是
     出于向该语言添加抽象基类的内容（参见 "abc" 模块）。


3.4.5. 模拟可调用对象
---------------------

object.__call__(self[, args...])

   此方法会在实例作为一个函数被“调用”时被调用；如果定义了此方法，则
   "x(arg1, arg2, ...)" 就相当于 "x.__call__(arg1, arg2, ...)" 的快捷
   方式。


3.4.6. 模拟容器类型
-------------------

The following methods can be defined to implement container objects.
Containers usually are sequences (such as lists or tuples) or mappings
(like dictionaries), but can represent other containers as well.  The
first set of methods is used either to emulate a sequence or to
emulate a mapping; the difference is that for a sequence, the
allowable keys should be the integers *k* for which "0 <= k < N" where
*N* is the length of the sequence, or slice objects, which define a
range of items. (For backwards compatibility, the method
"__getslice__()" (see below) can also be defined to handle simple, but
not extended slices.) It is also recommended that mappings provide the
methods "keys()", "values()", "items()", "has_key()", "get()",
"clear()", "setdefault()", "iterkeys()", "itervalues()",
"iteritems()", "pop()", "popitem()", "copy()", and "update()" behaving
similar to those for Python’s standard dictionary objects.  The
"UserDict" module provides a "DictMixin" class to help create those
methods from a base set of "__getitem__()", "__setitem__()",
"__delitem__()", and "keys()". Mutable sequences should provide
methods "append()", "count()", "index()", "extend()", "insert()",
"pop()", "remove()", "reverse()" and "sort()", like Python standard
list objects.  Finally, sequence types should implement addition
(meaning concatenation) and multiplication (meaning repetition) by
defining the methods "__add__()", "__radd__()", "__iadd__()",
"__mul__()", "__rmul__()" and "__imul__()" described below; they
should not define "__coerce__()" or other numerical operators.  It is
recommended that both mappings and sequences implement the
"__contains__()" method to allow efficient use of the "in" operator;
for mappings, "in" should be equivalent of "has_key()"; for sequences,
it should search through the values.  It is further recommended that
both mappings and sequences implement the "__iter__()" method to allow
efficient iteration through the container; for mappings, "__iter__()"
should be the same as "iterkeys()"; for sequences, it should iterate
through the values.

object.__len__(self)

   Called to implement the built-in function "len()".  Should return
   the length of the object, an integer ">=" 0.  Also, an object that
   doesn’t define a "__nonzero__()" method and whose "__len__()"
   method returns zero is considered to be false in a Boolean context.

   **CPython implementation detail:** In CPython, the length is
   required to be at most "sys.maxsize". If the length is larger than
   "sys.maxsize" some features (such as "len()") may raise
   "OverflowError".  To prevent raising "OverflowError" by truth value
   testing, an object must define a "__nonzero__()" method.

object.__getitem__(self, key)

   调用此方法以实现 "self[key]" 的求值。对于序列类型，接受的键应为整数
   和切片对象。请注意负数索引（如果类想要模拟序列类型）的特殊解读是取
   决于 "__getitem__()" 方法。如果 *key* 的类型不正确则会引发
   "TypeError" 异常；如果为序列索引集范围以外的值（在进行任何负数索引
   的特殊解读之后）则应引发 "IndexError" 异常。对于映射类型，如果
   *key* 找不到（不在容器中）则应引发 "KeyError" 异常。

   注解: "for" 循环在有不合法索引时会期待捕获 "IndexError" 以便正确
     地检测 到序列的结束。

object.__setitem__(self, key, value)

   调用此方法以实现向 "self[key]" 赋值。注意事项与 "__getitem__()" 相
   同。为对象实现此方法应该仅限于需要映射允许基于键修改值或添加键，或
   是序列允许元素被替换时。不正确的 *key* 值所引发的异常应与
   "__getitem__()" 方法的情况相同。

object.__delitem__(self, key)

   调用此方法以实现 "self[key]" 的删除。注意事项与 "__getitem__()" 相
   同。为对象实现此方法应该权限于需要映射允许移除键，或是序列允许移除
   元素时。不正确的 *key* 值所引发的异常应与 "__getitem__()" 方法的情
   况相同。

object.__missing__(self, key)

   此方法由 "dict"."__getitem__()" 在找不到字典中的键时调用以实现 dict
   子类的 "self[key]"。

object.__iter__(self)

   This method is called when an iterator is required for a container.
   This method should return a new iterator object that can iterate
   over all the objects in the container.  For mappings, it should
   iterate over the keys of the container, and should also be made
   available as the method "iterkeys()".

   迭代器对象也需要实现此方法；它们需要返回对象自身。有关迭代器对象的
   详情请参看 Iterator Types 一节。

object.__reversed__(self)

   此方法（如果存在）会被 "reversed()" 内置函数调用以实现逆向迭代。它
   应当返回一个新的以逆序逐个迭代容器内所有对象的迭代器对象。

   如果未提供 "__reversed__()" 方法，则 "reversed()" 内置函数将回退到
   使用序列协议 ("__len__()" 和 "__getitem__()")。支持序列协议的对象应
   当仅在能够提供比 "reversed()" 所提供的实现更高效的实现时才提供
   "__reversed__()" 方法。

   2.6 新版功能.

成员检测运算符 ("in" 和 "not in") 通常以在序列中逐个迭代的方式来实现。
不过，容器对象可以提供以下特殊方法并采用更有效率的实现，这样也不要求对
象必须属于序列。

object.__contains__(self, item)

   调用此方法以实现成员检测运算符。如果 *item* 是 *self* 的成员则应返
   回真，否则返回假。对于映射类型，此检测应基于映射的键而不是值或者键
   值对。

   对于未定义 "__contains__()" 的对象，成员检测将首先尝试通过
   "__iter__()" 进行迭代，然后再使用 "__getitem__()" 的旧式序列迭代协
   议，参看 语言参考中的相应部分。


3.4.7. Additional methods for emulation of sequence types
---------------------------------------------------------

The following optional methods can be defined to further emulate
sequence objects.  Immutable sequences methods should at most only
define "__getslice__()"; mutable sequences might define all three
methods.

object.__getslice__(self, i, j)

   2.0 版后已移除: Support slice objects as parameters to the
   "__getitem__()" method. (However, built-in types in CPython
   currently still implement "__getslice__()".  Therefore, you have to
   override it in derived classes when implementing slicing.)

   Called to implement evaluation of "self[i:j]". The returned object
   should be of the same type as *self*.  Note that missing *i* or *j*
   in the slice expression are replaced by zero or "sys.maxsize",
   respectively.  If negative indexes are used in the slice, the
   length of the sequence is added to that index. If the instance does
   not implement the "__len__()" method, an "AttributeError" is
   raised. No guarantee is made that indexes adjusted this way are not
   still negative.  Indexes which are greater than the length of the
   sequence are not modified. If no "__getslice__()" is found, a slice
   object is created instead, and passed to "__getitem__()" instead.

object.__setslice__(self, i, j, sequence)

   Called to implement assignment to "self[i:j]". Same notes for *i*
   and *j* as for "__getslice__()".

   This method is deprecated. If no "__setslice__()" is found, or for
   extended slicing of the form "self[i:j:k]", a slice object is
   created, and passed to "__setitem__()", instead of "__setslice__()"
   being called.

object.__delslice__(self, i, j)

   Called to implement deletion of "self[i:j]". Same notes for *i* and
   *j* as for "__getslice__()". This method is deprecated. If no
   "__delslice__()" is found, or for extended slicing of the form
   "self[i:j:k]", a slice object is created, and passed to
   "__delitem__()", instead of "__delslice__()" being called.

Notice that these methods are only invoked when a single slice with a
single colon is used, and the slice method is available.  For slice
operations involving extended slice notation, or in absence of the
slice methods, "__getitem__()", "__setitem__()" or "__delitem__()" is
called with a slice object as argument.

The following example demonstrate how to make your program or module
compatible with earlier versions of Python (assuming that methods
"__getitem__()", "__setitem__()" and "__delitem__()" support slice
objects as arguments):

   class MyClass:
       ...
       def __getitem__(self, index):
           ...
       def __setitem__(self, index, value):
           ...
       def __delitem__(self, index):
           ...

       if sys.version_info < (2, 0):
           # They won't be defined if version is at least 2.0 final

           def __getslice__(self, i, j):
               return self[max(0, i):max(0, j):]
           def __setslice__(self, i, j, seq):
               self[max(0, i):max(0, j):] = seq
           def __delslice__(self, i, j):
               del self[max(0, i):max(0, j):]
       ...

Note the calls to "max()"; these are necessary because of the handling
of negative indices before the "__*slice__()" methods are called.
When negative indexes are used, the "__*item__()" methods receive them
as provided, but the "__*slice__()" methods get a “cooked” form of the
index values.  For each negative index value, the length of the
sequence is added to the index before calling the method (which may
still result in a negative index); this is the customary handling of
negative indexes by the built-in sequence types, and the "__*item__()"
methods are expected to do this as well.  However, since they should
already be doing that, negative indexes cannot be passed in; they must
be constrained to the bounds of the sequence before being passed to
the "__*item__()" methods. Calling "max(0, i)" conveniently returns
the proper value.


3.4.8. 模拟数字类型
-------------------

定义以下方法即可模拟数字类型。特定种类的数字不支持的运算（例如非整数不
能进行位运算）所对应的方法应当保持未定义状态。

object.__add__(self, other)
object.__sub__(self, other)
object.__mul__(self, other)
object.__floordiv__(self, other)
object.__mod__(self, other)
object.__divmod__(self, other)
object.__pow__(self, other[, modulo])
object.__lshift__(self, other)
object.__rshift__(self, other)
object.__and__(self, other)
object.__xor__(self, other)
object.__or__(self, other)

   These methods are called to implement the binary arithmetic
   operations ("+", "-", "*", "//", "%", "divmod()", "pow()", "**",
   "<<", ">>", "&", "^", "|").  For instance, to evaluate the
   expression "x + y", where *x* is an instance of a class that has an
   "__add__()" method, "x.__add__(y)" is called.  The "__divmod__()"
   method should be the equivalent to using "__floordiv__()" and
   "__mod__()"; it should not be related to "__truediv__()" (described
   below).  Note that "__pow__()" should be defined to accept an
   optional third argument if the ternary version of the built-in
   "pow()" function is to be supported.

   如果这些方法中的某一个不支持与所提供参数进行运算，它应该返回
   "NotImplemented"。

object.__div__(self, other)
object.__truediv__(self, other)

   The division operator ("/") is implemented by these methods.  The
   "__truediv__()" method is used when "__future__.division" is in
   effect, otherwise "__div__()" is used.  If only one of these two
   methods is defined, the object will not support division in the
   alternate context; "TypeError" will be raised instead.

object.__radd__(self, other)
object.__rsub__(self, other)
object.__rmul__(self, other)
object.__rdiv__(self, other)
object.__rtruediv__(self, other)
object.__rfloordiv__(self, other)
object.__rmod__(self, other)
object.__rdivmod__(self, other)
object.__rpow__(self, other)
object.__rlshift__(self, other)
object.__rrshift__(self, other)
object.__rand__(self, other)
object.__rxor__(self, other)
object.__ror__(self, other)

   These methods are called to implement the binary arithmetic
   operations ("+", "-", "*", "/", "%", "divmod()", "pow()", "**",
   "<<", ">>", "&", "^", "|") with reflected (swapped) operands.
   These functions are only called if the left operand does not
   support the corresponding operation and the operands are of
   different types. [2] For instance, to evaluate the expression "x -
   y", where *y* is an instance of a class that has an "__rsub__()"
   method, "y.__rsub__(x)" is called if "x.__sub__(y)" returns
   *NotImplemented*.

   请注意三元版的 "pow()" 并不会尝试调用 "__rpow__()" (因为强制转换规
   则会太过复杂)。

   注解: 如果右操作数类型为左操作数类型的一个子类，且该子类提供了指
     定运算 的反射方法，则此方法会先于左操作数的非反射方法被调用。此行
     为可允 许子类重载其祖先类的运算符。

object.__iadd__(self, other)
object.__isub__(self, other)
object.__imul__(self, other)
object.__idiv__(self, other)
object.__itruediv__(self, other)
object.__ifloordiv__(self, other)
object.__imod__(self, other)
object.__ipow__(self, other[, modulo])
object.__ilshift__(self, other)
object.__irshift__(self, other)
object.__iand__(self, other)
object.__ixor__(self, other)
object.__ior__(self, other)

   These methods are called to implement the augmented arithmetic
   assignments ("+=", "-=", "*=", "/=", "//=", "%=", "**=", "<<=",
   ">>=", "&=", "^=", "|=").  These methods should attempt to do the
   operation in-place (modifying *self*) and return the result (which
   could be, but does not have to be, *self*).  If a specific method
   is not defined, the augmented assignment falls back to the normal
   methods.  For instance, to execute the statement "x += y", where
   *x* is an instance of a class that has an "__iadd__()" method,
   "x.__iadd__(y)" is called.  If *x* is an instance of a class that
   does not define a "__iadd__()" method, "x.__add__(y)" and
   "y.__radd__(x)" are considered, as with the evaluation of "x + y".

object.__neg__(self)
object.__pos__(self)
object.__abs__(self)
object.__invert__(self)

   调用此方法以实现一元算术运算 ("-", "+", "abs()" 和 "~")。

object.__complex__(self)
object.__int__(self)
object.__long__(self)
object.__float__(self)

   Called to implement the built-in functions "complex()", "int()",
   "long()", and "float()".  Should return a value of the appropriate
   type.

object.__oct__(self)
object.__hex__(self)

   Called to implement the built-in functions "oct()" and "hex()".
   Should return a string value.

object.__index__(self)

   Called to implement "operator.index()".  Also called whenever
   Python needs an integer object (such as in slicing).  Must return
   an integer (int or long).

   2.5 新版功能.

object.__coerce__(self, other)

   Called to implement “mixed-mode” numeric arithmetic.  Should either
   return a 2-tuple containing *self* and *other* converted to a
   common numeric type, or "None" if conversion is impossible.  When
   the common type would be the type of "other", it is sufficient to
   return "None", since the interpreter will also ask the other object
   to attempt a coercion (but sometimes, if the implementation of the
   other type cannot be changed, it is useful to do the conversion to
   the other type here).  A return value of "NotImplemented" is
   equivalent to returning "None".


3.4.9. Coercion rules
---------------------

This section used to document the rules for coercion.  As the language
has evolved, the coercion rules have become hard to document
precisely; documenting what one version of one particular
implementation does is undesirable.  Instead, here are some informal
guidelines regarding coercion.  In Python 3, coercion will not be
supported.

* If the left operand of a % operator is a string or Unicode object,
  no coercion takes place and the string formatting operation is
  invoked instead.

* It is no longer recommended to define a coercion operation. Mixed-
  mode operations on types that don’t define coercion pass the
  original arguments to the operation.

* New-style classes (those derived from "object") never invoke the
  "__coerce__()" method in response to a binary operator; the only
  time "__coerce__()" is invoked is when the built-in function
  "coerce()" is called.

* For most intents and purposes, an operator that returns
  "NotImplemented" is treated the same as one that is not implemented
  at all.

* Below, "__op__()" and "__rop__()" are used to signify the generic
  method names corresponding to an operator; "__iop__()" is used for
  the corresponding in-place operator.  For example, for the operator
  ‘"+"’, "__add__()" and "__radd__()" are used for the left and right
  variant of the binary operator, and "__iadd__()" for the in-place
  variant.

* For objects *x* and *y*, first "x.__op__(y)" is tried.  If this is
  not implemented or returns "NotImplemented", "y.__rop__(x)" is
  tried.  If this is also not implemented or returns "NotImplemented",
  a "TypeError" exception is raised.  But see the following exception:

* Exception to the previous item: if the left operand is an instance
  of a built-in type or a new-style class, and the right operand is an
  instance of a proper subclass of that type or class and overrides
  the base’s "__rop__()" method, the right operand’s "__rop__()"
  method is tried *before* the left operand’s "__op__()" method.

  This is done so that a subclass can completely override binary
  operators. Otherwise, the left operand’s "__op__()" method would
  always accept the right operand: when an instance of a given class
  is expected, an instance of a subclass of that class is always
  acceptable.

* When either operand type defines a coercion, this coercion is
  called before that type’s "__op__()" or "__rop__()" method is
  called, but no sooner.  If the coercion returns an object of a
  different type for the operand whose coercion is invoked, part of
  the process is redone using the new object.

* When an in-place operator (like ‘"+="’) is used, if the left
  operand implements "__iop__()", it is invoked without any coercion.
  When the operation falls back to "__op__()" and/or "__rop__()", the
  normal coercion rules apply.

* In "x + y", if *x* is a sequence that implements sequence
  concatenation, sequence concatenation is invoked.

* In "x * y", if one operand is a sequence that implements sequence
  repetition, and the other is an integer ("int" or "long"), sequence
  repetition is invoked.

* Rich comparisons (implemented by methods "__eq__()" and so on)
  never use coercion.  Three-way comparison (implemented by
  "__cmp__()") does use coercion under the same conditions as other
  binary operations use it.

* In the current implementation, the built-in numeric types "int",
  "long", "float", and "complex" do not use coercion. All these types
  implement a "__coerce__()" method, for use by the built-in
  "coerce()" function.

  在 2.7 版更改: The complex type no longer makes implicit calls to
  the "__coerce__()" method for mixed-type binary arithmetic
  operations.


3.4.10. with 语句上下文管理器
-----------------------------

2.5 新版功能.

A *context manager* is an object that defines the runtime context to
be established when executing a "with" statement. The context manager
handles the entry into, and the exit from, the desired runtime context
for the execution of the block of code.  Context managers are normally
invoked using the "with" statement (described in section The with
statement), but can also be used by directly invoking their methods.

上下文管理器的典型用法包括保存和恢复各种全局状态，锁定和解锁资源，关闭
打开的文件等等。

要了解上下文管理器的更多信息，请参阅 Context Manager Types。

object.__enter__(self)

   Enter the runtime context related to this object. The "with"
   statement will bind this method’s return value to the target(s)
   specified in the "as" clause of the statement, if any.

object.__exit__(self, exc_type, exc_value, traceback)

   退出关联到此对象的运行时上下文。 各个参数描述了导致上下文退出的异常
   。 如果上下文是无异常地退出的，三个参数都将为 "None"。

   如果提供了异常，并且希望方法屏蔽此异常（即避免其被传播），则应当返
   回真值。 否则的话，异常将在退出此方法时按正常流程处理。

   请注意 "__exit__()" 方法不应该重新引发被传入的异常，这是调用者的责
   任。

参见:

  **PEP 343** - “with” 语句
     Python "with" 语句的规范描述、背景和示例。


3.4.11. Special method lookup for old-style classes
---------------------------------------------------

For old-style classes, special methods are always looked up in exactly
the same way as any other method or attribute. This is the case
regardless of whether the method is being looked up explicitly as in
"x.__getitem__(i)" or implicitly as in "x[i]".

This behaviour means that special methods may exhibit different
behaviour for different instances of a single old-style class if the
appropriate special attributes are set differently:

   >>> class C:
   ...     pass
   ...
   >>> c1 = C()
   >>> c2 = C()
   >>> c1.__len__ = lambda: 5
   >>> c2.__len__ = lambda: 9
   >>> len(c1)
   5
   >>> len(c2)
   9


3.4.12. Special method lookup for new-style classes
---------------------------------------------------

For new-style classes, implicit invocations of special methods are
only guaranteed to work correctly if defined on an object’s type, not
in the object’s instance dictionary.  That behaviour is the reason why
the following code raises an exception (unlike the equivalent example
with old-style classes):

   >>> class C(object):
   ...     pass
   ...
   >>> c = C()
   >>> c.__len__ = lambda: 5
   >>> len(c)
   Traceback (most recent call last):
     File "<stdin>", line 1, in <module>
   TypeError: object of type 'C' has no len()

此行为背后的原理在于包括类型对象在内的所有对象都会实现的几个特殊方法，
例如 "__hash__()" 和 "__repr__()"。 如果这些方法的隐式查找使用了传统的
查找过程，它们会在对类型对象本身发起调用时失败:

   >>> 1 .__hash__() == hash(1)
   True
   >>> int.__hash__() == hash(int)
   Traceback (most recent call last):
     File "<stdin>", line 1, in <module>
   TypeError: descriptor '__hash__' of 'int' object needs an argument

以这种方式不正确地尝试发起调用一个类的未绑定方法有时被称为‘元类混淆’，
可以通过在查找特殊方法时绕过实例的方式来避免:

   >>> type(1).__hash__(1) == hash(1)
   True
   >>> type(int).__hash__(int) == hash(int)
   True

除了为了正确性而绕过任何实例属性之外，隐式特殊方法查找通常也会绕过
"__getattribute__()" 方法，甚至包括对象的元类:

   >>> class Meta(type):
   ...    def __getattribute__(*args):
   ...       print "Metaclass getattribute invoked"
   ...       return type.__getattribute__(*args)
   ...
   >>> class C(object):
   ...     __metaclass__ = Meta
   ...     def __len__(self):
   ...         return 10
   ...     def __getattribute__(*args):
   ...         print "Class getattribute invoked"
   ...         return object.__getattribute__(*args)
   ...
   >>> c = C()
   >>> c.__len__()                 # Explicit lookup via instance
   Class getattribute invoked
   10
   >>> type(c).__len__(c)          # Explicit lookup via type
   Metaclass getattribute invoked
   10
   >>> len(c)                      # Implicit lookup
   10

以这种方式绕过 "__getattribute__()" 机制为解析器内部的速度优化提供了显
著的空间，其代价则是牺牲了处理特殊方法时的一些灵活性（特殊方法 *必须*
设置在类对象本身上以便始终一致地由解释器发起调用）。

-[ 脚注 ]-

[1] 在某些情况下 *有可能* 基于可控的条件改变一个对象的类型。 但这
    通常 不是个好主意，因为如果处理不当会导致一些非常怪异的行为。

[2] 对于相同类型的操作数，如果非反射方法 (例如 "__add__()") 失败则
    会认 为相应运算不被支持，这就是反射方法未被调用的原因。
