Module Assign NameStore Dict Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str Str
N/A N/A topics N/A assert assignment atom-identifiers atom-literals attribute-access attribute-references augassign binary bitwise bltin-code-objects bltin-ellipsis-object bltin-file-objects bltin-null-object bltin-type-objects booleans break callable-types calls class coercion-rules comparisons compound context-managers continue conversions customization debugger del dict dynamic-features else exceptions exec execmodel exprlists floating for formatstrings function global id-classes identifiers if imaginary import in integers lambda lists naming numbers numeric-types objects operator-summary pass power print raise return sequence-methods sequence-types shifting slicings specialattrs specialnames string-conversions string-methods strings subscriptions truth try types typesfunctions typesmapping typesmethods typesmodules typesseq typesseq-mutable unary while with yield 
The ``assert`` statement
************************

Assert statements are a convenient way to insert debugging assertions
into a program:

   assert_stmt ::= "assert" expression ["," expression]

The simple form, ``assert expression``, is equivalent to

   if __debug__:
      if not expression: raise AssertionError

The extended form, ``assert expression1, expression2``, is equivalent
to

   if __debug__:
      if not expression1: raise AssertionError, expression2

These equivalences assume that ``__debug__`` and ``AssertionError``
refer to the built-in variables with those names.  In the current
implementation, the built-in variable ``__debug__`` is ``True`` under
normal circumstances, ``False`` when optimization is requested
(command line option -O).  The current code generator emits no code
for an assert statement when optimization is requested at compile
time.  Note that it is unnecessary to include the source code for the
expression that failed in the error message; it will be displayed as
part of the stack trace.

Assignments to ``__debug__`` are illegal.  The value for the built-in
variable is determined when the interpreter starts.
 
Assignment statements
*********************

Assignment statements are used to (re)bind names to values and to
modify attributes or items of mutable objects:

   assignment_stmt ::= (target_list "=")+ (expression_list | yield_expression)
   target_list     ::= target ("," target)* [","]
   target          ::= identifier
              | "(" target_list ")"
              | "[" target_list "]"
              | attributeref
              | subscription
              | slicing

(See section *Primaries* for the syntax definitions for the last three
symbols.)

An assignment statement evaluates the expression list (remember that
this can be a single expression or a comma-separated list, the latter
yielding a tuple) and assigns the single resulting object to each of
the target lists, from left to right.

Assignment is defined recursively depending on the form of the target
(list). When a target is part of a mutable object (an attribute
reference, subscription or slicing), the mutable object must
ultimately perform the assignment and decide about its validity, and
may raise an exception if the assignment is unacceptable.  The rules
observed by various types and the exceptions raised are given with the
definition of the object types (see section *The standard type
hierarchy*).

Assignment of an object to a target list is recursively defined as
follows.

* If the target list is a single target: The object is assigned to
  that target.

* If the target list is a comma-separated list of targets: The object
  must be a sequence with the same number of items as there are
  targets in the target list, and the items are assigned, from left to
  right, to the corresponding targets. (This rule is relaxed as of
  Python 1.5; in earlier versions, the object had to be a tuple.
  Since strings are sequences, an assignment like ``a, b = "xy"`` is
  now legal as long as the string has the right length.)

Assignment of an object to a single target is recursively defined as
follows.

* If the target is an identifier (name):

  * If the name does not occur in a ``global`` statement in the
    current code block: the name is bound to the object in the current
    local namespace.

  * Otherwise: the name is bound to the object in the current global
    namespace.

  The name is rebound if it was already bound.  This may cause the
  reference count for the object previously bound to the name to reach
  zero, causing the object to be deallocated and its destructor (if it
  has one) to be called.

* If the target is a target list enclosed in parentheses or in square
  brackets: The object must be a sequence with the same number of
  items as there are targets in the target list, and its items are
  assigned, from left to right, to the corresponding targets.

* If the target is an attribute reference: The primary expression in
  the reference is evaluated.  It should yield an object with
  assignable attributes; if this is not the case, ``TypeError`` is
  raised.  That object is then asked to assign the assigned object to
  the given attribute; if it cannot perform the assignment, it raises
  an exception (usually but not necessarily ``AttributeError``).

* If the target is a subscription: The primary expression in the
  reference is evaluated.  It should yield either a mutable sequence
  object (such as a list) or a mapping object (such as a dictionary).
  Next, the subscript expression is evaluated.

  If the primary is a mutable sequence object (such as a list), the
  subscript must yield a plain integer.  If it is negative, the
  sequence's length is added to it. The resulting value must be a
  nonnegative integer less than the sequence's length, and the
  sequence is asked to assign the assigned object to its item with
  that index.  If the index is out of range, ``IndexError`` is raised
  (assignment to a subscripted sequence cannot add new items to a
  list).

  If the primary is a mapping object (such as a dictionary), the
  subscript must have a type compatible with the mapping's key type,
  and the mapping is then asked to create a key/datum pair which maps
  the subscript to the assigned object.  This can either replace an
  existing key/value pair with the same key value, or insert a new
  key/value pair (if no key with the same value existed).

* If the target is a slicing: The primary expression in the reference
  is evaluated.  It should yield a mutable sequence object (such as a
  list).  The assigned object should be a sequence object of the same
  type.  Next, the lower and upper bound expressions are evaluated,
  insofar they are present; defaults are zero and the sequence's
  length.  The bounds should evaluate to (small) integers.  If either
  bound is negative, the sequence's length is added to it. The
  resulting bounds are clipped to lie between zero and the sequence's
  length, inclusive.  Finally, the sequence object is asked to replace
  the slice with the items of the assigned sequence.  The length of
  the slice may be different from the length of the assigned sequence,
  thus changing the length of the target sequence, if the object
  allows it.

(In the current implementation, the syntax for targets is taken to be
the same as for expressions, and invalid syntax is rejected during the
code generation phase, causing less detailed error messages.)

WARNING: Although the definition of assignment implies that overlaps
between the left-hand side and the right-hand side are 'safe' (for
example ``a, b = b, a`` swaps two variables), overlaps *within* the
collection of assigned-to variables are not safe!  For instance, the
following program prints ``[0, 2]``:

   x = [0, 1]
   i = 0
   i, x[i] = 1, 2
   print x


Augmented assignment statements
===============================

Augmented assignment is the combination, in a single statement, of a
binary operation and an assignment statement:

   augmented_assignment_stmt ::= target augop (expression_list | yield_expression)
   augop                     ::= "+=" | "-=" | "*=" | "/=" | "//=" | "%=" | "**="
             | ">>=" | "<<=" | "&=" | "^=" | "|="

(See section *Primaries* for the syntax definitions for the last three
symbols.)

An augmented assignment evaluates the target (which, unlike normal
assignment statements, cannot be an unpacking) and the expression
list, performs the binary operation specific to the type of assignment
on the two operands, and assigns the result to the original target.
The target is only evaluated once.

An augmented assignment expression like ``x += 1`` can be rewritten as
``x = x + 1`` to achieve a similar, but not exactly equal effect. In
the augmented version, ``x`` is only evaluated once. Also, when
possible, the actual operation is performed *in-place*, meaning that
rather than creating a new object and assigning that to the target,
the old object is modified instead.

With the exception of assigning to tuples and multiple targets in a
single statement, the assignment done by augmented assignment
statements is handled the same way as normal assignments. Similarly,
with the exception of the possible *in-place* behavior, the binary
operation performed by augmented assignment is the same as the normal
binary operations.

For targets which are attribute references, the initial value is
retrieved with a ``getattr()`` and the result is assigned with a
``setattr()``.  Notice that the two methods do not necessarily refer
to the same variable.  When ``getattr()`` refers to a class variable,
``setattr()`` still writes to an instance variable. For example:

   class A:
       x = 3    # class variable
   a = A()
   a.x += 1     # writes a.x as 4 leaving A.x as 3
 
Identifiers (Names)
*******************

An identifier occurring as an atom is a name.  See section
*Identifiers and keywords* for lexical definition and section *Naming
and binding* for documentation of naming and binding.

When the name is bound to an object, evaluation of the atom yields
that object. When a name is not bound, an attempt to evaluate it
raises a ``NameError`` exception.

**Private name mangling:** When an identifier that textually occurs in
a class definition begins with two or more underscore characters and
does not end in two or more underscores, it is considered a *private
name* of that class. Private names are transformed to a longer form
before code is generated for them.  The transformation inserts the
class name in front of the name, with leading underscores removed, and
a single underscore inserted in front of the class name.  For example,
the identifier ``__spam`` occurring in a class named ``Ham`` will be
transformed to ``_Ham__spam``.  This transformation is independent of
the syntactical context in which the identifier is used.  If the
transformed name is extremely long (longer than 255 characters),
implementation defined truncation may happen.  If the class name
consists only of underscores, no transformation is done.
 
Literals
********

Python supports string literals and various numeric literals:

   literal ::= stringliteral | integer | longinteger
               | floatnumber | imagnumber

Evaluation of a literal yields an object of the given type (string,
integer, long integer, floating point number, complex number) with the
given value.  The value may be approximated in the case of floating
point and imaginary (complex) literals.  See section *Literals* for
details.

All literals correspond to immutable data types, and hence the
object's identity is less important than its value.  Multiple
evaluations of literals with the same value (either the same
occurrence in the program text or a different occurrence) may obtain
the same object or a different object with the same value.
 
Customizing attribute access
****************************

The following methods can be defined to customize the meaning of
attribute access (use of, assignment to, or deletion of ``x.name``)
for class instances.

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)

   Like ``__setattr__()`` but for attribute deletion instead of
   assignment.  This should only be implemented if ``del obj.name`` is
   meaningful for the object.


More attribute access for new-style classes
===========================================

The following methods only apply to new-style classes.

object.__getattribute__(self, name)

   Called unconditionally to implement attribute accesses for
   instances of the class. If the class also defines
   ``__getattr__()``, the latter will not be called unless
   ``__getattribute__()`` either calls it explicitly or raises an
   ``AttributeError``. This method should return the (computed)
   attribute value or raise an ``AttributeError`` exception. In order
   to avoid infinite recursion in this method, its implementation
   should always call the base class method with the same name to
   access any attributes it needs, for example,
   ``object.__getattribute__(self, name)``.

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


Implementing Descriptors
========================

The following methods only apply when an instance of the class
containing the method (a so-called *descriptor* class) appears in the
class dictionary of another new-style class, known as the *owner*
class. In the examples below, "the attribute" refers to the attribute
whose name is the key of the property in the owner class'
``__dict__``.  Descriptors can only be implemented as new-style
classes themselves.

object.__get__(self, instance, owner)

   Called to get the attribute of the owner class (class attribute
   access) or of an instance of that class (instance attribute
   access). *owner* is always the owner class, while *instance* is the
   instance that the attribute was accessed through, or ``None`` when
   the attribute is accessed through the *owner*.  This method should
   return the (computed) attribute value or raise an
   ``AttributeError`` exception.

object.__set__(self, instance, value)

   Called to set the attribute on an instance *instance* of the owner
   class to a new value, *value*.

object.__delete__(self, instance)

   Called to delete the attribute on an instance *instance* of the
   owner class.


Invoking Descriptors
====================

In general, a descriptor is an object attribute with "binding
behavior", one whose attribute access has been overridden by methods
in the descriptor protocol:  ``__get__()``, ``__set__()``, and
``__delete__()``. If any of those methods are defined for an object,
it is said to be a descriptor.

The default behavior for attribute access is to get, set, or delete
the attribute from an object's dictionary. For instance, ``a.x`` has a
lookup chain starting with ``a.__dict__['x']``, then
``type(a).__dict__['x']``, and continuing through the base classes of
``type(a)`` excluding metaclasses.

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()``).

The starting point for descriptor invocation is a binding, ``a.x``.
How the arguments are assembled depends on ``a``:

Direct Call
   The simplest and least common call is when user code directly
   invokes a descriptor method:    ``x.__get__(a)``.

Instance Binding
   If binding to a new-style object instance, ``a.x`` is transformed
   into the call: ``type(a).__dict__['x'].__get__(a, type(a))``.

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

Super Binding
   If ``a`` is an instance of ``super``, then the binding ``super(B,
   obj).m()`` searches ``obj.__class__.__mro__`` for the base class
   ``A`` immediately preceding ``B`` and then invokes the descriptor
   with the call: ``A.__dict__['m'].__get__(obj, A)``.

For instance bindings, the precedence of descriptor invocation depends
on the which descriptor methods are defined.  Normally, data
descriptors define both ``__get__()`` and ``__set__()``, while non-
data descriptors have just the ``__get__()`` method.  Data descriptors
always override a redefinition in an instance dictionary.  In
contrast, non-data descriptors can be overridden by instances. [2]

Python methods (including ``staticmethod()`` and ``classmethod()``)
are implemented as non-data descriptors.  Accordingly, instances can
redefine and override methods.  This allows individual instances to
acquire behaviors that differ from other instances of the same class.

The ``property()`` function is implemented as a data descriptor.
Accordingly, instances cannot override the behavior of a property.


__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.

   New in version 2.2.

Notes on using *__slots__*

* 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.

* Without a *__dict__* variable, instances cannot be assigned new
  variables not listed in the *__slots__* definition.  Attempts to
  assign to an unlisted variable name raises ``AttributeError``. If
  dynamic assignment of new variables is desired, then add
  ``'__dict__'`` to the sequence of strings in the *__slots__*
  declaration.

  Changed in version 2.3: 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.

* Without a *__weakref__* variable for each instance, classes defining
  *__slots__* do not support weak references to its instances. If weak
  reference support is needed, then add ``'__weakref__'`` to the
  sequence of strings in the *__slots__* declaration.

  Changed in version 2.3: Previously, adding ``'__weakref__'`` to the
  *__slots__* declaration would not enable support for weak
  references.

* *__slots__* are implemented at the class level by creating
  descriptors (*Implementing Descriptors*) for each variable name.  As
  a result, class attributes cannot be used to set default values for
  instance variables defined by *__slots__*; otherwise, the class
  attribute would overwrite the descriptor assignment.

* If a class defines a slot also defined in a base class, the instance
  variable defined by the base class slot is inaccessible (except by
  retrieving its descriptor directly from the base class). This
  renders the meaning of the program undefined.  In the future, a
  check may be added to prevent this.

* 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__*.

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

* Any non-string iterable may be assigned to *__slots__*. Mappings may
  also be used; however, in the future, special meaning may be
  assigned to the values corresponding to each key.

* *__class__* assignment works only if both classes have the same
  *__slots__*.

  Changed in version 2.6: Previously, *__class__* assignment raised an
  error if either new or old class had *__slots__*.
 
Attribute references
********************

An attribute reference is a primary followed by a period and a name:

   attributeref ::= primary "." identifier

The primary must evaluate to an object of a type that supports
attribute references, e.g., a module, list, or an instance.  This
object is then asked to produce the attribute whose name is the
identifier.  If this attribute is not available, the exception
``AttributeError`` is raised. Otherwise, the type and value of the
object produced is determined by the object.  Multiple evaluations of
the same attribute reference may yield different objects.
 
Augmented assignment statements
*******************************

Augmented assignment is the combination, in a single statement, of a
binary operation and an assignment statement:

   augmented_assignment_stmt ::= target augop (expression_list | yield_expression)
   augop                     ::= "+=" | "-=" | "*=" | "/=" | "//=" | "%=" | "**="
             | ">>=" | "<<=" | "&=" | "^=" | "|="

(See section *Primaries* for the syntax definitions for the last three
symbols.)

An augmented assignment evaluates the target (which, unlike normal
assignment statements, cannot be an unpacking) and the expression
list, performs the binary operation specific to the type of assignment
on the two operands, and assigns the result to the original target.
The target is only evaluated once.

An augmented assignment expression like ``x += 1`` can be rewritten as
``x = x + 1`` to achieve a similar, but not exactly equal effect. In
the augmented version, ``x`` is only evaluated once. Also, when
possible, the actual operation is performed *in-place*, meaning that
rather than creating a new object and assigning that to the target,
the old object is modified instead.

With the exception of assigning to tuples and multiple targets in a
single statement, the assignment done by augmented assignment
statements is handled the same way as normal assignments. Similarly,
with the exception of the possible *in-place* behavior, the binary
operation performed by augmented assignment is the same as the normal
binary operations.

For targets which are attribute references, the initial value is
retrieved with a ``getattr()`` and the result is assigned with a
``setattr()``.  Notice that the two methods do not necessarily refer
to the same variable.  When ``getattr()`` refers to a class variable,
``setattr()`` still writes to an instance variable. For example:

   class A:
       x = 3    # class variable
   a = A()
   a.x += 1     # writes a.x as 4 leaving A.x as 3
 
Binary arithmetic operations
****************************

The binary arithmetic operations have the conventional priority
levels.  Note that some of these operations also apply to certain non-
numeric types.  Apart from the power operator, there are only two
levels, one for multiplicative operators and one for additive
operators:

   m_expr ::= u_expr | m_expr "*" u_expr | m_expr "//" u_expr | m_expr "/" u_expr
              | m_expr "%" u_expr
   a_expr ::= m_expr | a_expr "+" m_expr | a_expr "-" m_expr

The ``*`` (multiplication) operator yields the product of its
arguments.  The arguments must either both be numbers, or one argument
must be an integer (plain or long) and the other must be a sequence.
In the former case, the numbers are converted to a common type and
then multiplied together.  In the latter case, sequence repetition is
performed; a negative repetition factor yields an empty sequence.

The ``/`` (division) and ``//`` (floor division) operators yield the
quotient of their arguments.  The numeric arguments are first
converted to a common type. Plain or long integer division yields an
integer of the same type; the result is that of mathematical division
with the 'floor' function applied to the result. Division by zero
raises the ``ZeroDivisionError`` exception.

The ``%`` (modulo) operator yields the remainder from the division of
the first argument by the second.  The numeric arguments are first
converted to a common type.  A zero right argument raises the
``ZeroDivisionError`` exception.  The arguments may be floating point
numbers, e.g., ``3.14%0.7`` equals ``0.34`` (since ``3.14`` equals
``4*0.7 + 0.34``.)  The modulo operator always yields a result with
the same sign as its second operand (or zero); the absolute value of
the result is strictly smaller than the absolute value of the second
operand [2].

The integer division and modulo operators are connected by the
following identity: ``x == (x/y)*y + (x%y)``.  Integer division and
modulo are also connected with the built-in function ``divmod()``:
``divmod(x, y) == (x/y, x%y)``.  These identities don't hold for
floating point numbers; there similar identities hold approximately
where ``x/y`` is replaced by ``floor(x/y)`` or ``floor(x/y) - 1`` [3].

In addition to performing the modulo operation on numbers, the ``%``
operator is also overloaded by string and unicode objects to perform
string formatting (also known as interpolation). The syntax for string
formatting is described in the Python Library Reference, section
*String Formatting Operations*.

Deprecated since version 2.3: The floor division operator, the modulo
operator, and the ``divmod()`` function are no longer defined for
complex numbers.  Instead, convert to a floating point number using
the ``abs()`` function if appropriate.

The ``+`` (addition) operator yields the sum of its arguments. The
arguments must either both be numbers or both sequences of the same
type.  In the former case, the numbers are converted to a common type
and then added together.  In the latter case, the sequences are
concatenated.

The ``-`` (subtraction) operator yields the difference of its
arguments.  The numeric arguments are first converted to a common
type.
 
Binary bitwise operations
*************************

Each of the three bitwise operations has a different priority level:

   and_expr ::= shift_expr | and_expr "&" shift_expr
   xor_expr ::= and_expr | xor_expr "^" and_expr
   or_expr  ::= xor_expr | or_expr "|" xor_expr

The ``&`` operator yields the bitwise AND of its arguments, which must
be plain or long integers.  The arguments are converted to a common
type.

The ``^`` operator yields the bitwise XOR (exclusive OR) of its
arguments, which must be plain or long integers.  The arguments are
converted to a common type.

The ``|`` operator yields the bitwise (inclusive) OR of its arguments,
which must be plain or long integers.  The arguments are converted to
a common type.
 
Code Objects
************

Code objects are used by the implementation to represent "pseudo-
compiled" executable Python code such as a function body. They differ
from function objects because they don't contain a reference to their
global execution environment.  Code objects are returned by the built-
in ``compile()`` function and can be extracted from function objects
through their ``func_code`` attribute. See also the ``code`` module.

A code object can be executed or evaluated by passing it (instead of a
source string) to the ``exec`` statement or the built-in ``eval()``
function.

See *The standard type hierarchy* for more information.
 
The Ellipsis Object
*******************

This object is used by extended slice notation (see *Slicings*).  It
supports no special operations.  There is exactly one ellipsis object,
named ``Ellipsis`` (a built-in name).

It is written as ``Ellipsis``.
 
File Objects
************

File objects are implemented using C's ``stdio`` package and can be
created with the built-in ``open()`` function.  File objects are also
returned by some other built-in functions and methods, such as
``os.popen()`` and ``os.fdopen()`` and the ``makefile()`` method of
socket objects. Temporary files can be created using the ``tempfile``
module, and high-level file operations such as copying, moving, and
deleting files and directories can be achieved with the ``shutil``
module.

When a file operation fails for an I/O-related reason, the exception
``IOError`` is raised.  This includes situations where the operation
is not defined for some reason, like ``seek()`` on a tty device or
writing a file opened for reading.

Files have the following methods:

file.close()

   Close the file.  A closed file cannot be read or written any more.
   Any operation which requires that the file be open will raise a
   ``ValueError`` after the file has been closed.  Calling ``close()``
   more than once is allowed.

   As of Python 2.5, you can avoid having to call this method
   explicitly if you use the ``with`` statement.  For example, the
   following code will automatically close *f* when the ``with`` block
   is exited:

      from __future__ import with_statement # This isn't required in Python 2.6

      with open("hello.txt") as f:
          for line in f:
              print line

   In older versions of Python, you would have needed to do this to
   get the same effect:

      f = open("hello.txt")
      try:
          for line in f:
              print line
      finally:
          f.close()

   Note: Not all "file-like" types in Python support use as a context
     manager for the ``with`` statement.  If your code is intended to
     work with any file-like object, you can use the function
     ``contextlib.closing()`` instead of using the object directly.

file.flush()

   Flush the internal buffer, like ``stdio``'s ``fflush``.  This may
   be a no-op on some file-like objects.

file.fileno()

   Return the integer "file descriptor" that is used by the underlying
   implementation to request I/O operations from the operating system.
   This can be useful for other, lower level interfaces that use file
   descriptors, such as the ``fcntl`` module or ``os.read()`` and
   friends.

   Note: File-like objects which do not have a real file descriptor should
     *not* provide this method!

file.isatty()

   Return ``True`` if the file is connected to a tty(-like) device,
   else ``False``.

   Note: If a file-like object is not associated with a real file, this
     method should *not* be implemented.

file.next()

   A file object is its own iterator, for example ``iter(f)`` returns
   *f* (unless *f* is closed).  When a file is used as an iterator,
   typically in a ``for`` loop (for example, ``for line in f: print
   line``), the ``next()`` method is called repeatedly.  This method
   returns the next input line, or raises ``StopIteration`` when EOF
   is hit when the file is open for reading (behavior is undefined
   when the file is open for writing).  In order to make a ``for``
   loop the most efficient way of looping over the lines of a file (a
   very common operation), the ``next()`` method uses a hidden read-
   ahead buffer.  As a consequence of using a read-ahead buffer,
   combining ``next()`` with other file methods (like ``readline()``)
   does not work right.  However, using ``seek()`` to reposition the
   file to an absolute position will flush the read-ahead buffer.

   New in version 2.3.

file.read([size])

   Read at most *size* bytes from the file (less if the read hits EOF
   before obtaining *size* bytes).  If the *size* argument is negative
   or omitted, read all data until EOF is reached.  The bytes are
   returned as a string object.  An empty string is returned when EOF
   is encountered immediately.  (For certain files, like ttys, it
   makes sense to continue reading after an EOF is hit.)  Note that
   this method may call the underlying C function ``fread`` more than
   once in an effort to acquire as close to *size* bytes as possible.
   Also note that when in non-blocking mode, less data than was
   requested may be returned, even if no *size* parameter was given.

   Note: This function is simply a wrapper for the underlying ``fread`` C
     function, and will behave the same in corner cases, such as
     whether the EOF value is cached.

file.readline([size])

   Read one entire line from the file.  A trailing newline character
   is kept in the string (but may be absent when a file ends with an
   incomplete line). [6]  If the *size* argument is present and non-
   negative, it is a maximum byte count (including the trailing
   newline) and an incomplete line may be returned. An empty string is
   returned *only* when EOF is encountered immediately.

   Note: Unlike ``stdio``'s ``fgets``, the returned string contains null
     characters (``'\0'``) if they occurred in the input.

file.readlines([sizehint])

   Read until EOF using ``readline()`` and return a list containing
   the lines thus read.  If the optional *sizehint* argument is
   present, instead of reading up to EOF, whole lines totalling
   approximately *sizehint* bytes (possibly after rounding up to an
   internal buffer size) are read.  Objects implementing a file-like
   interface may choose to ignore *sizehint* if it cannot be
   implemented, or cannot be implemented efficiently.

file.xreadlines()

   This method returns the same thing as ``iter(f)``.

   New in version 2.1.

   Deprecated since version 2.3: Use ``for line in file`` instead.

file.seek(offset[, whence])

   Set the file's current position, like ``stdio``'s ``fseek``. The
   *whence* argument is optional and defaults to  ``os.SEEK_SET`` or
   ``0`` (absolute file positioning); other values are ``os.SEEK_CUR``
   or ``1`` (seek relative to the current position) and
   ``os.SEEK_END`` or ``2``  (seek relative to the file's end).  There
   is no return value.

   For example, ``f.seek(2, os.SEEK_CUR)`` advances the position by
   two and ``f.seek(-3, os.SEEK_END)`` sets the position to the third
   to last.

   Note that if the file is opened for appending (mode ``'a'`` or
   ``'a+'``), any ``seek()`` operations will be undone at the next
   write.  If the file is only opened for writing in append mode (mode
   ``'a'``), this method is essentially a no-op, but it remains useful
   for files opened in append mode with reading enabled (mode
   ``'a+'``).  If the file is opened in text mode (without ``'b'``),
   only offsets returned by ``tell()`` are legal.  Use of other
   offsets causes undefined behavior.

   Note that not all file objects are seekable.

   Changed in version 2.6: Passing float values as offset has been
   deprecated.

file.tell()

   Return the file's current position, like ``stdio``'s ``ftell``.

   Note: On Windows, ``tell()`` can return illegal values (after an
     ``fgets``) when reading files with Unix-style line-endings. Use
     binary mode (``'rb'``) to circumvent this problem.

file.truncate([size])

   Truncate the file's size.  If the optional *size* argument is
   present, the file is truncated to (at most) that size.  The size
   defaults to the current position. The current file position is not
   changed.  Note that if a specified size exceeds the file's current
   size, the result is platform-dependent:  possibilities include that
   the file may remain unchanged, increase to the specified size as if
   zero-filled, or increase to the specified size with undefined new
   content. Availability:  Windows, many Unix variants.

file.write(str)

   Write a string to the file.  There is no return value.  Due to
   buffering, the string may not actually show up in the file until
   the ``flush()`` or ``close()`` method is called.

file.writelines(sequence)

   Write a sequence of strings to the file.  The sequence can be any
   iterable object producing strings, typically a list of strings.
   There is no return value. (The name is intended to match
   ``readlines()``; ``writelines()`` does not add line separators.)

Files support the iterator protocol.  Each iteration returns the same
result as ``file.readline()``, and iteration ends when the
``readline()`` method returns an empty string.

File objects also offer a number of other interesting attributes.
These are not required for file-like objects, but should be
implemented if they make sense for the particular object.

file.closed

   bool indicating the current state of the file object.  This is a
   read-only attribute; the ``close()`` method changes the value. It
   may not be available on all file-like objects.

file.encoding

   The encoding that this file uses. When Unicode strings are written
   to a file, they will be converted to byte strings using this
   encoding. In addition, when the file is connected to a terminal,
   the attribute gives the encoding that the terminal is likely to use
   (that  information might be incorrect if the user has misconfigured
   the  terminal). The attribute is read-only and may not be present
   on all file-like objects. It may also be ``None``, in which case
   the file uses the system default encoding for converting Unicode
   strings.

   New in version 2.3.

file.errors

   The Unicode error handler used along with the encoding.

   New in version 2.6.

file.mode

   The I/O mode for the file.  If the file was created using the
   ``open()`` built-in function, this will be the value of the *mode*
   parameter.  This is a read-only attribute and may not be present on
   all file-like objects.

file.name

   If the file object was created using ``open()``, the name of the
   file. Otherwise, some string that indicates the source of the file
   object, of the form ``<...>``.  This is a read-only attribute and
   may not be present on all file-like objects.

file.newlines

   If Python was built with the *--with-universal-newlines* option to
   **configure** (the default) this read-only attribute exists, and
   for files opened in universal newline read mode it keeps track of
   the types of newlines encountered while reading the file. The
   values it can take are ``'\r'``, ``'\n'``, ``'\r\n'``, ``None``
   (unknown, no newlines read yet) or a tuple containing all the
   newline types seen, to indicate that multiple newline conventions
   were encountered. For files not opened in universal newline read
   mode the value of this attribute will be ``None``.

file.softspace

   Boolean that indicates whether a space character needs to be
   printed before another value when using the ``print`` statement.
   Classes that are trying to simulate a file object should also have
   a writable ``softspace`` attribute, which should be initialized to
   zero.  This will be automatic for most classes implemented in
   Python (care may be needed for objects that override attribute
   access); types implemented in C will have to provide a writable
   ``softspace`` attribute.

   Note: This attribute is not used to control the ``print`` statement,
     but to allow the implementation of ``print`` to keep track of its
     internal state.
 
The Null Object
***************

This object is returned by functions that don't explicitly return a
value.  It supports no special operations.  There is exactly one null
object, named ``None`` (a built-in name).

It is written as ``None``.
 
Type Objects
************

Type objects represent the various object types.  An object's type is
accessed by the built-in function ``type()``.  There are no special
operations on types.  The standard module ``types`` defines names for
all standard built-in types.

Types are written like this: ``<type 'int'>``.
 
Boolean operations
******************

Boolean operations have the lowest priority of all Python operations:

   expression             ::= conditional_expression | lambda_form
   old_expression         ::= or_test | old_lambda_form
   conditional_expression ::= or_test ["if" or_test "else" expression]
   or_test                ::= and_test | or_test "or" and_test
   and_test               ::= not_test | and_test "and" not_test
   not_test               ::= comparison | "not" not_test

In the context of Boolean operations, and also when expressions are
used by control flow statements, the following values are interpreted
as false: ``False``, ``None``, numeric zero of all types, and empty
strings and containers (including strings, tuples, lists,
dictionaries, sets and frozensets).  All other values are interpreted
as true.  (See the ``__nonzero__()`` special method for a way to
change this.)

The operator ``not`` yields ``True`` if its argument is false,
``False`` otherwise.

The expression ``x if C else y`` first evaluates *C* (*not* *x*); if
*C* is true, *x* is evaluated and its value is returned; otherwise,
*y* is evaluated and its value is returned.

New in version 2.5.

The expression ``x and y`` first evaluates *x*; if *x* is false, its
value is returned; otherwise, *y* is evaluated and the resulting value
is returned.

The expression ``x or y`` first evaluates *x*; if *x* is true, its
value is returned; otherwise, *y* is evaluated and the resulting value
is returned.

(Note that neither ``and`` nor ``or`` restrict the value and type they
return to ``False`` and ``True``, but rather return the last evaluated
argument. This is sometimes useful, e.g., if ``s`` is a string that
should be replaced by a default value if it is empty, the expression
``s or 'foo'`` yields the desired value.  Because ``not`` has to
invent a value anyway, it does not bother to return a value of the
same type as its argument, so e.g., ``not 'foo'`` yields ``False``,
not ``''``.)
 
The ``break`` statement
***********************

   break_stmt ::= "break"

``break`` may only occur syntactically nested in a ``for`` or
``while`` loop, but not nested in a function or class definition
within that loop.

It terminates the nearest enclosing loop, skipping the optional
``else`` clause if the loop has one.

If a ``for`` loop is terminated by ``break``, the loop control target
keeps its current value.

When ``break`` passes control out of a ``try`` statement with a
``finally`` clause, that ``finally`` clause is executed before really
leaving the loop.
 
Emulating callable objects
**************************

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

   Called when the instance is "called" as a function; if this method
   is defined, ``x(arg1, arg2, ...)`` is a shorthand for
   ``x.__call__(arg1, arg2, ...)``.
 
Calls
*****

A call calls a callable object (e.g., a function) with a possibly
empty series of arguments:

   call                 ::= primary "(" [argument_list [","]
            | expression genexpr_for] ")"
   argument_list        ::= positional_arguments ["," keyword_arguments]
                       ["," "*" expression] ["," keyword_arguments]
                       ["," "**" expression]
                     | keyword_arguments ["," "*" expression]
                       ["," "**" expression]
                     | "*" expression ["," "*" expression] ["," "**" expression]
                     | "**" expression
   positional_arguments ::= expression ("," expression)*
   keyword_arguments    ::= keyword_item ("," keyword_item)*
   keyword_item         ::= identifier "=" expression

A trailing comma may be present after the positional and keyword
arguments but does not affect the semantics.

The primary must evaluate to a callable object (user-defined
functions, built-in functions, methods of built-in objects, class
objects, methods of class instances, and certain class instances
themselves are callable; extensions may define additional callable
object types).  All argument expressions are evaluated before the call
is attempted.  Please refer to section *Function definitions* for the
syntax of formal parameter lists.

If keyword arguments are present, they are first converted to
positional arguments, as follows.  First, a list of unfilled slots is
created for the formal parameters.  If there are N positional
arguments, they are placed in the first N slots.  Next, for each
keyword argument, the identifier is used to determine the
corresponding slot (if the identifier is the same as the first formal
parameter name, the first slot is used, and so on).  If the slot is
already filled, a ``TypeError`` exception is raised. Otherwise, the
value of the argument is placed in the slot, filling it (even if the
expression is ``None``, it fills the slot).  When all arguments have
been processed, the slots that are still unfilled are filled with the
corresponding default value from the function definition.  (Default
values are calculated, once, when the function is defined; thus, a
mutable object such as a list or dictionary used as default value will
be shared by all calls that don't specify an argument value for the
corresponding slot; this should usually be avoided.)  If there are any
unfilled slots for which no default value is specified, a
``TypeError`` exception is raised.  Otherwise, the list of filled
slots is used as the argument list for the call.

Note: An implementation may provide builtin functions whose positional
  parameters do not have names, even if they are 'named' for the
  purpose of documentation, and which therefore cannot be supplied by
  keyword.  In CPython, this is the case for functions implemented in
  C that use ``PyArg_ParseTuple`` to parse their arguments.

If there are more positional arguments than there are formal parameter
slots, a ``TypeError`` exception is raised, unless a formal parameter
using the syntax ``*identifier`` is present; in this case, that formal
parameter receives a tuple containing the excess positional arguments
(or an empty tuple if there were no excess positional arguments).

If any keyword argument does not correspond to a formal parameter
name, a ``TypeError`` exception is raised, unless a formal parameter
using the syntax ``**identifier`` is present; in this case, that
formal parameter receives a dictionary containing the excess keyword
arguments (using the keywords as keys and the argument values as
corresponding values), or a (new) empty dictionary if there were no
excess keyword arguments.

If the syntax ``*expression`` appears in the function call,
``expression`` must evaluate to a sequence.  Elements from this
sequence are treated as if they were additional positional arguments;
if there are positional arguments *x1*,..., *xN*, and ``expression``
evaluates to a sequence *y1*, ..., *yM*, this is equivalent to a call
with M+N positional arguments *x1*, ..., *xN*, *y1*, ..., *yM*.

A consequence of this is that although the ``*expression`` syntax may
appear *after* some keyword arguments, it is processed *before* the
keyword arguments (and the ``**expression`` argument, if any -- see
below).  So:

   >>> def f(a, b):
   ...  print a, b
   ...
   >>> f(b=1, *(2,))
   2 1
   >>> f(a=1, *(2,))
   Traceback (most recent call last):
     File "<stdin>", line 1, in ?
   TypeError: f() got multiple values for keyword argument 'a'
   >>> f(1, *(2,))
   1 2

It is unusual for both keyword arguments and the ``*expression``
syntax to be used in the same call, so in practice this confusion does
not arise.

If the syntax ``**expression`` appears in the function call,
``expression`` must evaluate to a mapping, the contents of which are
treated as additional keyword arguments.  In the case of a keyword
appearing in both ``expression`` and as an explicit keyword argument,
a ``TypeError`` exception is raised.

Formal parameters using the syntax ``*identifier`` or ``**identifier``
cannot be used as positional argument slots or as keyword argument
names.  Formal parameters using the syntax ``(sublist)`` cannot be
used as keyword argument names; the outermost sublist corresponds to a
single unnamed argument slot, and the argument value is assigned to
the sublist using the usual tuple assignment rules after all other
parameter processing is done.

A call always returns some value, possibly ``None``, unless it raises
an exception.  How this value is computed depends on the type of the
callable object.

If it is---

a user-defined function:
   The code block for the function is executed, passing it the
   argument list.  The first thing the code block will do is bind the
   formal parameters to the arguments; this is described in section
   *Function definitions*.  When the code block executes a ``return``
   statement, this specifies the return value of the function call.

a built-in function or method:
   The result is up to the interpreter; see *Built-in Functions* for
   the descriptions of built-in functions and methods.

a class object:
   A new instance of that class is returned.

a class instance method:
   The corresponding user-defined function is called, with an argument
   list that is one longer than the argument list of the call: the
   instance becomes the first argument.

a class instance:
   The class must define a ``__call__()`` method; the effect is then
   the same as if that method was called.
 
Class definitions
*****************

A class definition defines a class object (see section *The standard
type hierarchy*):

   classdef    ::= "class" classname [inheritance] ":" suite
   inheritance ::= "(" [expression_list] ")"
   classname   ::= identifier

A class definition is an executable statement.  It first evaluates the
inheritance list, if present.  Each item in the inheritance list
should evaluate to a class object or class type which allows
subclassing.  The class's suite is then executed in a new execution
frame (see section *Naming and binding*), using a newly created local
namespace and the original global namespace. (Usually, the suite
contains only function definitions.)  When the class's suite finishes
execution, its execution frame is discarded but its local namespace is
saved. [4] A class object is then created using the inheritance list
for the base classes and the saved local namespace for the attribute
dictionary.  The class name is bound to this class object in the
original local namespace.

**Programmer's note:** Variables defined in the class definition are
class variables; they are shared by all instances.  To create instance
variables, they can be set in a method with ``self.name = value``.
Both class and instance variables are accessible through the notation
"``self.name``", and an instance variable hides a class variable with
the same name when accessed in this way. Class variables can be used
as defaults for instance variables, but using mutable values there can
lead to unexpected results.  For *new-style class*es, descriptors can
be used to create instance variables with different implementation
details.

Class definitions, like function definitions, may be wrapped by one or
more *decorator* expressions.  The evaluation rules for the decorator
expressions are the same as for functions.  The result must be a class
object, which is then bound to the class name.

-[ Footnotes ]-

[1] The exception is propagated to the invocation stack only if there
    is no ``finally`` clause that negates the exception.

[2] Currently, control "flows off the end" except in the case of an
    exception or the execution of a ``return``, ``continue``, or
    ``break`` statement.

[3] A string literal appearing as the first statement in the function
    body is transformed into the function's ``__doc__`` attribute and
    therefore the function's *docstring*.

[4] A string literal appearing as the first statement in the class
    body is transformed into the namespace's ``__doc__`` item and
    therefore the class's *docstring*.
 
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 3.0, 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 operator 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`` and ``float`` do not use coercion; the type ``complex``
  however does use it.  The difference can become apparent when
  subclassing these types.  Over time, the type ``complex`` may be
  fixed to avoid coercion. All these types implement a
  ``__coerce__()`` method, for use by the built-in ``coerce()``
  function.
 
Comparisons
***********

Unlike C, all comparison operations in Python have the same priority,
which is lower than that of any arithmetic, shifting or bitwise
operation.  Also unlike C, expressions like ``a < b < c`` have the
interpretation that is conventional in mathematics:

   comparison    ::= or_expr ( comp_operator or_expr )*
   comp_operator ::= "<" | ">" | "==" | ">=" | "<=" | "<>" | "!="
                     | "is" ["not"] | ["not"] "in"

Comparisons yield boolean values: ``True`` or ``False``.

Comparisons can be chained arbitrarily, e.g., ``x < y <= z`` is
equivalent to ``x < y and y <= z``, except that ``y`` is evaluated
only once (but in both cases ``z`` is not evaluated at all when ``x <
y`` is found to be false).

Formally, if *a*, *b*, *c*, ..., *y*, *z* are expressions and *op1*,
*op2*, ..., *opN* are comparison operators, then ``a op1 b op2 c ... y
opN z`` is equivalent to ``a op1 b and b op2 c and ... y opN z``,
except that each expression is evaluated at most once.

Note that ``a op1 b op2 c`` doesn't imply any kind of comparison
between *a* and *c*, so that, e.g., ``x < y > z`` is perfectly legal
(though perhaps not pretty).

The forms ``<>`` and ``!=`` are equivalent; for consistency with C,
``!=`` is preferred; where ``!=`` is mentioned below ``<>`` is also
accepted.  The ``<>`` spelling is considered obsolescent.

The operators ``<``, ``>``, ``==``, ``>=``, ``<=``, and ``!=`` compare
the values of two objects.  The objects need not have the same type.
If both are numbers, they are converted to a common type.  Otherwise,
objects of different types *always* compare unequal, and are ordered
consistently but arbitrarily. You can control comparison behavior of
objects of non-builtin types by defining a ``__cmp__`` method or rich
comparison methods like ``__gt__``, described in section *Special
method names*.

(This unusual definition of comparison was used to simplify the
definition of operations like sorting and the ``in`` and ``not in``
operators. In the future, the comparison rules for objects of
different types are likely to change.)

Comparison of objects of the same type depends on the type:

* Numbers are compared arithmetically.

* Strings are compared lexicographically using the numeric equivalents
  (the result of the built-in function ``ord()``) of their characters.
  Unicode and 8-bit strings are fully interoperable in this behavior.
  [4]

* Tuples and lists are compared lexicographically using comparison of
  corresponding elements.  This means that to compare equal, each
  element must compare equal and the two sequences must be of the same
  type and have the same length.

  If not equal, the sequences are ordered the same as their first
  differing elements.  For example, ``cmp([1,2,x], [1,2,y])`` returns
  the same as ``cmp(x,y)``.  If the corresponding element does not
  exist, the shorter sequence is ordered first (for example, ``[1,2] <
  [1,2,3]``).

* Mappings (dictionaries) compare equal if and only if their sorted
  (key, value) lists compare equal. [5] Outcomes other than equality
  are resolved consistently, but are not otherwise defined. [6]

* Most other objects of builtin types compare unequal unless they are
  the same object; the choice whether one object is considered smaller
  or larger than another one is made arbitrarily but consistently
  within one execution of a program.

The operators ``in`` and ``not in`` test for collection membership.
``x in s`` evaluates to true if *x* is a member of the collection *s*,
and false otherwise.  ``x not in s`` returns the negation of ``x in
s``. The collection membership test has traditionally been bound to
sequences; an object is a member of a collection if the collection is
a sequence and contains an element equal to that object.  However, it
make sense for many other object types to support membership tests
without being a sequence.  In particular, dictionaries (for keys) and
sets support membership testing.

For the list and tuple types, ``x in y`` is true if and only if there
exists an index *i* such that ``x == y[i]`` is true.

For the Unicode and string types, ``x in y`` is true if and only if
*x* is a substring of *y*.  An equivalent test is ``y.find(x) != -1``.
Note, *x* and *y* need not be the same type; consequently, ``u'ab' in
'abc'`` will return ``True``. Empty strings are always considered to
be a substring of any other string, so ``"" in "abc"`` will return
``True``.

Changed in version 2.3: Previously, *x* was required to be a string of
length ``1``.

For user-defined classes which define the ``__contains__()`` method,
``x in y`` is true if and only if ``y.__contains__(x)`` is true.

For user-defined classes which do not define ``__contains__()`` and do
define ``__getitem__()``, ``x in y`` is true if and only if there is a
non-negative integer index *i* such that ``x == y[i]``, and all lower
integer indices do not raise ``IndexError`` exception. (If any other
exception is raised, it is as if ``in`` raised that exception).

The operator ``not in`` is defined to have the inverse true value of
``in``.

The operators ``is`` and ``is not`` test for object identity: ``x is
y`` is true if and only if *x* and *y* are the same object.  ``x is
not y`` yields the inverse truth value. [7]
 
Compound statements
*******************

Compound statements contain (groups of) other statements; they affect
or control the execution of those other statements in some way.  In
general, compound statements span multiple lines, although in simple
incarnations a whole compound statement may be contained in one line.

The ``if``, ``while`` and ``for`` statements implement traditional
control flow constructs.  ``try`` specifies exception handlers and/or
cleanup code for a group of statements.  Function and class
definitions are also syntactically compound statements.

Compound statements consist of one or more 'clauses.'  A clause
consists of a header and a 'suite.'  The clause headers of a
particular compound statement are all at the same indentation level.
Each clause header begins with a uniquely identifying keyword and ends
with a colon.  A suite is a group of statements controlled by a
clause.  A suite can be one or more semicolon-separated simple
statements on the same line as the header, following the header's
colon, or it can be one or more indented statements on subsequent
lines.  Only the latter form of suite can contain nested compound
statements; the following is illegal, mostly because it wouldn't be
clear to which ``if`` clause a following ``else`` clause would belong:

   if test1: if test2: print x

Also note that the semicolon binds tighter than the colon in this
context, so that in the following example, either all or none of the
``print`` statements are executed:

   if x < y < z: print x; print y; print z

Summarizing:

   compound_stmt ::= if_stmt
                     | while_stmt
                     | for_stmt
                     | try_stmt
                     | with_stmt
                     | funcdef
                     | classdef
                     | decorated
   suite         ::= stmt_list NEWLINE | NEWLINE INDENT statement+ DEDENT
   statement     ::= stmt_list NEWLINE | compound_stmt
   stmt_list     ::= simple_stmt (";" simple_stmt)* [";"]

Note that statements always end in a ``NEWLINE`` possibly followed by
a ``DEDENT``. Also note that optional continuation clauses always
begin with a keyword that cannot start a statement, thus there are no
ambiguities (the 'dangling ``else``' problem is solved in Python by
requiring nested ``if`` statements to be indented).

The formatting of the grammar rules in the following sections places
each clause on a separate line for clarity.


The ``if`` statement
====================

The ``if`` statement is used for conditional execution:

   if_stmt ::= "if" expression ":" suite
               ( "elif" expression ":" suite )*
               ["else" ":" suite]

It selects exactly one of the suites by evaluating the expressions one
by one until one is found to be true (see section *Boolean operations*
for the definition of true and false); then that suite is executed
(and no other part of the ``if`` statement is executed or evaluated).
If all expressions are false, the suite of the ``else`` clause, if
present, is executed.


The ``while`` statement
=======================

The ``while`` statement is used for repeated execution as long as an
expression is true:

   while_stmt ::= "while" expression ":" suite
                  ["else" ":" suite]

This repeatedly tests the expression and, if it is true, executes the
first suite; if the expression is false (which may be the first time
it is tested) the suite of the ``else`` clause, if present, is
executed and the loop terminates.

A ``break`` statement executed in the first suite terminates the loop
without executing the ``else`` clause's suite.  A ``continue``
statement executed in the first suite skips the rest of the suite and
goes back to testing the expression.


The ``for`` statement
=====================

The ``for`` statement is used to iterate over the elements of a
sequence (such as a string, tuple or list) or other iterable object:

   for_stmt ::= "for" target_list "in" expression_list ":" suite
                ["else" ":" suite]

The expression list is evaluated once; it should yield an iterable
object.  An iterator is created for the result of the
``expression_list``.  The suite is then executed once for each item
provided by the iterator, in the order of ascending indices.  Each
item in turn is assigned to the target list using the standard rules
for assignments, and then the suite is executed.  When the items are
exhausted (which is immediately when the sequence is empty), the suite
in the ``else`` clause, if present, is executed, and the loop
terminates.

A ``break`` statement executed in the first suite terminates the loop
without executing the ``else`` clause's suite.  A ``continue``
statement executed in the first suite skips the rest of the suite and
continues with the next item, or with the ``else`` clause if there was
no next item.

The suite may assign to the variable(s) in the target list; this does
not affect the next item assigned to it.

The target list is not deleted when the loop is finished, but if the
sequence is empty, it will not have been assigned to at all by the
loop.  Hint: the built-in function ``range()`` returns a sequence of
integers suitable to emulate the effect of Pascal's ``for i := a to b
do``; e.g., ``range(3)`` returns the list ``[0, 1, 2]``.

Warning: There is a subtlety when the sequence is being modified by the loop
  (this can only occur for mutable sequences, i.e. lists). An internal
  counter is used to keep track of which item is used next, and this
  is incremented on each iteration.  When this counter has reached the
  length of the sequence the loop terminates.  This means that if the
  suite deletes the current (or a previous) item from the sequence,
  the next item will be skipped (since it gets the index of the
  current item which has already been treated).  Likewise, if the
  suite inserts an item in the sequence before the current item, the
  current item will be treated again the next time through the loop.
  This can lead to nasty bugs that can be avoided by making a
  temporary copy using a slice of the whole sequence, e.g.,

   for x in a[:]:
       if x < 0: a.remove(x)


The ``try`` statement
=====================

The ``try`` statement specifies exception handlers and/or cleanup code
for a group of statements:

   try_stmt  ::= try1_stmt | try2_stmt
   try1_stmt ::= "try" ":" suite
                 ("except" [expression [("as" | ",") target]] ":" suite)+
                 ["else" ":" suite]
                 ["finally" ":" suite]
   try2_stmt ::= "try" ":" suite
                 "finally" ":" suite

Changed in version 2.5: In previous versions of Python,
``try``...``except``...``finally`` did not work. ``try``...``except``
had to be nested in ``try``...``finally``.

The ``except`` clause(s) specify one or more exception handlers. When
no exception occurs in the ``try`` clause, no exception handler is
executed. When an exception occurs in the ``try`` suite, a search for
an exception handler is started.  This search inspects the except
clauses in turn until one is found that matches the exception.  An
expression-less except clause, if present, must be last; it matches
any exception.  For an except clause with an expression, that
expression is evaluated, and the clause matches the exception if the
resulting object is "compatible" with the exception.  An object is
compatible with an exception if it is the class or a base class of the
exception object, a tuple containing an item compatible with the
exception, or, in the (deprecated) case of string exceptions, is the
raised string itself (note that the object identities must match, i.e.
it must be the same string object, not just a string with the same
value).

If no except clause matches the exception, the search for an exception
handler continues in the surrounding code and on the invocation stack.
[1]

If the evaluation of an expression in the header of an except clause
raises an exception, the original search for a handler is canceled and
a search starts for the new exception in the surrounding code and on
the call stack (it is treated as if the entire ``try`` statement
raised the exception).

When a matching except clause is found, the exception is assigned to
the target specified in that except clause, if present, and the except
clause's suite is executed.  All except clauses must have an
executable block.  When the end of this block is reached, execution
continues normally after the entire try statement.  (This means that
if two nested handlers exist for the same exception, and the exception
occurs in the try clause of the inner handler, the outer handler will
not handle the exception.)

Before an except clause's suite is executed, details about the
exception are assigned to three variables in the ``sys`` module:
``sys.exc_type`` receives the object identifying the exception;
``sys.exc_value`` receives the exception's parameter;
``sys.exc_traceback`` receives a traceback object (see section *The
standard type hierarchy*) identifying the point in the program where
the exception occurred. These details are also available through the
``sys.exc_info()`` function, which returns a tuple ``(exc_type,
exc_value, exc_traceback)``.  Use of the corresponding variables is
deprecated in favor of this function, since their use is unsafe in a
threaded program.  As of Python 1.5, the variables are restored to
their previous values (before the call) when returning from a function
that handled an exception.

The optional ``else`` clause is executed if and when control flows off
the end of the ``try`` clause. [2] Exceptions in the ``else`` clause
are not handled by the preceding ``except`` clauses.

If ``finally`` is present, it specifies a 'cleanup' handler.  The
``try`` clause is executed, including any ``except`` and ``else``
clauses.  If an exception occurs in any of the clauses and is not
handled, the exception is temporarily saved. The ``finally`` clause is
executed.  If there is a saved exception, it is re-raised at the end
of the ``finally`` clause. If the ``finally`` clause raises another
exception or executes a ``return`` or ``break`` statement, the saved
exception is lost.  The exception information is not available to the
program during execution of the ``finally`` clause.

When a ``return``, ``break`` or ``continue`` statement is executed in
the ``try`` suite of a ``try``...``finally`` statement, the
``finally`` clause is also executed 'on the way out.' A ``continue``
statement is illegal in the ``finally`` clause. (The reason is a
problem with the current implementation --- this restriction may be
lifted in the future).

Additional information on exceptions can be found in section
*Exceptions*, and information on using the ``raise`` statement to
generate exceptions may be found in section *The raise statement*.


The ``with`` statement
======================

New in version 2.5.

The ``with`` statement is used to wrap the execution of a block with
methods defined by a context manager (see section *With Statement
Context Managers*). This allows common
``try``...``except``...``finally`` usage patterns to be encapsulated
for convenient reuse.

   with_stmt ::= "with" expression ["as" target] ":" suite

The execution of the ``with`` statement proceeds as follows:

1. The context expression is evaluated to obtain a context manager.

2. The context manager's ``__enter__()`` method is invoked.

3. If a target was included in the ``with`` statement, the return
   value from ``__enter__()`` is assigned to it.

   Note: The ``with`` statement guarantees that if the ``__enter__()``
     method returns without an error, then ``__exit__()`` will always
     be called. Thus, if an error occurs during the assignment to the
     target list, it will be treated the same as an error occurring
     within the suite would be. See step 5 below.

4. The suite is executed.

5. The context manager's ``__exit__()`` method is invoked. If an
   exception caused the suite to be exited, its type, value, and
   traceback are passed as arguments to ``__exit__()``. Otherwise,
   three ``None`` arguments are supplied.

   If the suite was exited due to an exception, and the return value
   from the ``__exit__()`` method was false, the exception is
   reraised. If the return value was true, the exception is
   suppressed, and execution continues with the statement following
   the ``with`` statement.

   If the suite was exited for any reason other than an exception, the
   return value from ``__exit__()`` is ignored, and execution proceeds
   at the normal location for the kind of exit that was taken.

Note: In Python 2.5, the ``with`` statement is only allowed when the
  ``with_statement`` feature has been enabled.  It is always enabled
  in Python 2.6.

See also:

   **PEP 0343** - The "with" statement
      The specification, background, and examples for the Python
      ``with`` statement.


Function definitions
====================

A function definition defines a user-defined function object (see
section *The standard type hierarchy*):

   decorated      ::= decorators (classdef | funcdef)
   decorators     ::= decorator+
   decorator      ::= "@" dotted_name ["(" [argument_list [","]] ")"] NEWLINE
   funcdef        ::= "def" funcname "(" [parameter_list] ")" ":" suite
   dotted_name    ::= identifier ("." identifier)*
   parameter_list ::= (defparameter ",")*
                      (  "*" identifier [, "**" identifier]
                      | "**" identifier
                      | defparameter [","] )
   defparameter   ::= parameter ["=" expression]
   sublist        ::= parameter ("," parameter)* [","]
   parameter      ::= identifier | "(" sublist ")"
   funcname       ::= identifier

A function definition is an executable statement.  Its execution binds
the function name in the current local namespace to a function object
(a wrapper around the executable code for the function).  This
function object contains a reference to the current global namespace
as the global namespace to be used when the function is called.

The function definition does not execute the function body; this gets
executed only when the function is called. [3]

A function definition may be wrapped by one or more *decorator*
expressions. Decorator expressions are evaluated when the function is
defined, in the scope that contains the function definition.  The
result must be a callable, which is invoked with the function object
as the only argument. The returned value is bound to the function name
instead of the function object.  Multiple decorators are applied in
nested fashion. For example, the following code:

   @f1(arg)
   @f2
   def func(): pass

is equivalent to:

   def func(): pass
   func = f1(arg)(f2(func))

When one or more top-level parameters have the form *parameter* ``=``
*expression*, the function is said to have "default parameter values."
For a parameter with a default value, the corresponding argument may
be omitted from a call, in which case the parameter's default value is
substituted.  If a parameter has a default value, all following
parameters must also have a default value --- this is a syntactic
restriction that is not expressed by the grammar.

**Default parameter values are evaluated when the function definition
is executed.**  This means that the expression is evaluated once, when
the function is defined, and that that same "pre-computed" value is
used for each call.  This is especially important to understand when a
default parameter is a mutable object, such as a list or a dictionary:
if the function modifies the object (e.g. by appending an item to a
list), the default value is in effect modified. This is generally not
what was intended.  A way around this  is to use ``None`` as the
default, and explicitly test for it in the body of the function, e.g.:

   def whats_on_the_telly(penguin=None):
       if penguin is None:
           penguin = []
       penguin.append("property of the zoo")
       return penguin

Function call semantics are described in more detail in section
*Calls*. A function call always assigns values to all parameters
mentioned in the parameter list, either from position arguments, from
keyword arguments, or from default values.  If the form
"``*identifier``" is present, it is initialized to a tuple receiving
any excess positional parameters, defaulting to the empty tuple.  If
the form "``**identifier``" is present, it is initialized to a new
dictionary receiving any excess keyword arguments, defaulting to a new
empty dictionary.

It is also possible to create anonymous functions (functions not bound
to a name), for immediate use in expressions.  This uses lambda forms,
described in section *Expression lists*.  Note that the lambda form is
merely a shorthand for a simplified function definition; a function
defined in a "``def``" statement can be passed around or assigned to
another name just like a function defined by a lambda form.  The
"``def``" form is actually more powerful since it allows the execution
of multiple statements.

**Programmer's note:** Functions are first-class objects.  A "``def``"
form executed inside a function definition defines a local function
that can be returned or passed around.  Free variables used in the
nested function can access the local variables of the function
containing the def.  See section *Naming and binding* for details.


Class definitions
=================

A class definition defines a class object (see section *The standard
type hierarchy*):

   classdef    ::= "class" classname [inheritance] ":" suite
   inheritance ::= "(" [expression_list] ")"
   classname   ::= identifier

A class definition is an executable statement.  It first evaluates the
inheritance list, if present.  Each item in the inheritance list
should evaluate to a class object or class type which allows
subclassing.  The class's suite is then executed in a new execution
frame (see section *Naming and binding*), using a newly created local
namespace and the original global namespace. (Usually, the suite
contains only function definitions.)  When the class's suite finishes
execution, its execution frame is discarded but its local namespace is
saved. [4] A class object is then created using the inheritance list
for the base classes and the saved local namespace for the attribute
dictionary.  The class name is bound to this class object in the
original local namespace.

**Programmer's note:** Variables defined in the class definition are
class variables; they are shared by all instances.  To create instance
variables, they can be set in a method with ``self.name = value``.
Both class and instance variables are accessible through the notation
"``self.name``", and an instance variable hides a class variable with
the same name when accessed in this way. Class variables can be used
as defaults for instance variables, but using mutable values there can
lead to unexpected results.  For *new-style class*es, descriptors can
be used to create instance variables with different implementation
details.

Class definitions, like function definitions, may be wrapped by one or
more *decorator* expressions.  The evaluation rules for the decorator
expressions are the same as for functions.  The result must be a class
object, which is then bound to the class name.

-[ Footnotes ]-

[1] The exception is propagated to the invocation stack only if there
    is no ``finally`` clause that negates the exception.

[2] Currently, control "flows off the end" except in the case of an
    exception or the execution of a ``return``, ``continue``, or
    ``break`` statement.

[3] A string literal appearing as the first statement in the function
    body is transformed into the function's ``__doc__`` attribute and
    therefore the function's *docstring*.

[4] A string literal appearing as the first statement in the class
    body is transformed into the namespace's ``__doc__`` item and
    therefore the class's *docstring*.
 
With Statement Context Managers
*******************************

New in version 2.5.

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.

Typical uses of context managers include saving and restoring various
kinds of global state, locking and unlocking resources, closing opened
files, etc.

For more information on context managers, see *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)

   Exit the runtime context related to this object. The parameters
   describe the exception that caused the context to be exited. If the
   context was exited without an exception, all three arguments will
   be ``None``.

   If an exception is supplied, and the method wishes to suppress the
   exception (i.e., prevent it from being propagated), it should
   return a true value. Otherwise, the exception will be processed
   normally upon exit from this method.

   Note that ``__exit__()`` methods should not reraise the passed-in
   exception; this is the caller's responsibility.

See also:

   **PEP 0343** - The "with" statement
      The specification, background, and examples for the Python
      ``with`` statement.
 
The ``continue`` statement
**************************

   continue_stmt ::= "continue"

``continue`` may only occur syntactically nested in a ``for`` or
``while`` loop, but not nested in a function or class definition or
``finally`` clause within that loop.  It continues with the next cycle
of the nearest enclosing loop.

When ``continue`` passes control out of a ``try`` statement with a
``finally`` clause, that ``finally`` clause is executed before really
starting the next loop cycle.
 
Arithmetic conversions
**********************

When a description of an arithmetic operator below uses the phrase
"the numeric arguments are converted to a common type," the arguments
are coerced using the coercion rules listed at  *Coercion rules*.  If
both arguments are standard numeric types, the following coercions are
applied:

* If either argument is a complex number, the other is converted to
  complex;

* otherwise, if either argument is a floating point number, the other
  is converted to floating point;

* otherwise, if either argument is a long integer, the other is
  converted to long integer;

* otherwise, both must be plain integers and no conversion is
  necessary.

Some additional rules apply for certain operators (e.g., a string left
argument to the '%' operator). Extensions can define their own
coercions.
 
Basic customization
*******************

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

   Called to create a new instance of class *cls*.  ``__new__()`` is a
   static method (special-cased so you need not declare it as such)
   that takes the class of which an instance was requested as its
   first argument.  The remaining arguments are those passed to the
   object constructor expression (the call to the class).  The return
   value of ``__new__()`` should be the new object instance (usually
   an instance of *cls*).

   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.

   If ``__new__()`` returns an instance of *cls*, then the new
   instance's ``__init__()`` method will be invoked like
   ``__init__(self[, ...])``, where *self* is the new instance and the
   remaining arguments are the same as were passed to ``__new__()``.

   If ``__new__()`` does not return an instance of *cls*, then the new
   instance's ``__init__()`` method will not be invoked.

   ``__new__()`` is intended mainly to allow subclasses of immutable
   types (like int, str, or tuple) to customize instance creation.  It
   is also commonly overridden in custom metaclasses in order to
   customize class creation.

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

   Called when the instance is created.  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...])``.  As a special constraint
   on constructors, no value may be returned; 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.

   Note: ``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.

   Warning: 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.  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.

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.

   This is typically used for debugging, so it is important that the
   representation is information-rich and unambiguous.

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)

   New in version 2.1.

   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)``.

   A rich comparison method may return the singleton
   ``NotImplemented`` if it does not implement the operation for a
   given pair of arguments. By convention, ``False`` and ``True`` are
   returned for a successful comparison. However, these methods can
   return any value, so if the comparison operator is used in a
   Boolean context (e.g., in the condition of an ``if`` statement),
   Python will call ``bool()`` on the value to determine if the result
   is true or false.

   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.

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)

   Changed in version 2.1: No longer supported.

object.__hash__(self)

   Called for the key object for dictionary operations, and by the
   built-in function ``hash()``.  Should return an integer usable as a
   hash value for dictionary operations.  The only required property
   is that objects which compare equal have the same hash value; it is
   advised to somehow mix together (e.g., using exclusive or) the hash
   values for the components of the object that also play a part in
   comparison of objects.

   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 as dictionary keys.  If a class
   defines mutable objects and implements a ``__cmp__()`` or
   ``__eq__()`` method, it should not implement ``__hash__()``, since
   the dictionary implementation requires that a key'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 ``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``).

   Changed in version 2.5: ``__hash__()`` may now also return a long
   integer object; the 32-bit integer is then derived from the hash of
   that object.

   Changed in version 2.6: ``__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 (see below).  If a class
   defines neither ``__len__()`` nor ``__nonzero__()``, all its
   instances are considered true.

object.__unicode__(self)

   Called to implement ``unicode()`` builtin; 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.
 
``pdb`` --- The Python Debugger
*******************************

The module ``pdb`` defines an interactive source code debugger for
Python programs.  It supports setting (conditional) breakpoints and
single stepping at the source line level, inspection of stack frames,
source code listing, and evaluation of arbitrary Python code in the
context of any stack frame.  It also supports post-mortem debugging
and can be called under program control.

The debugger is extensible --- it is actually defined as the class
``Pdb``. This is currently undocumented but easily understood by
reading the source.  The extension interface uses the modules ``bdb``
(undocumented) and ``cmd``.

The debugger's prompt is ``(Pdb)``. Typical usage to run a program
under control of the debugger is:

   >>> import pdb
   >>> import mymodule
   >>> pdb.run('mymodule.test()')
   > <string>(0)?()
   (Pdb) continue
   > <string>(1)?()
   (Pdb) continue
   NameError: 'spam'
   > <string>(1)?()
   (Pdb)

``pdb.py`` can also be invoked as a script to debug other scripts.
For example:

   python -m pdb myscript.py

When invoked as a script, pdb will automatically enter post-mortem
debugging if the program being debugged exits abnormally. After post-
mortem debugging (or after normal exit of the program), pdb will
restart the program. Automatic restarting preserves pdb's state (such
as breakpoints) and in most cases is more useful than quitting the
debugger upon program's exit.

New in version 2.4: Restarting post-mortem behavior added.

Typical usage to inspect a crashed program is:

   >>> import pdb
   >>> import mymodule
   >>> mymodule.test()
   Traceback (most recent call last):
     File "<stdin>", line 1, in ?
     File "./mymodule.py", line 4, in test
       test2()
     File "./mymodule.py", line 3, in test2
       print spam
   NameError: spam
   >>> pdb.pm()
   > ./mymodule.py(3)test2()
   -> print spam
   (Pdb)

The module defines the following functions; each enters the debugger
in a slightly different way:

pdb.run(statement[, globals[, locals]])

   Execute the *statement* (given as a string) under debugger control.
   The debugger prompt appears before any code is executed; you can
   set breakpoints and type ``continue``, or you can step through the
   statement using ``step`` or ``next`` (all these commands are
   explained below).  The optional *globals* and *locals* arguments
   specify the environment in which the code is executed; by default
   the dictionary of the module ``__main__`` is used.  (See the
   explanation of the ``exec`` statement or the ``eval()`` built-in
   function.)

pdb.runeval(expression[, globals[, locals]])

   Evaluate the *expression* (given as a string) under debugger
   control.  When ``runeval()`` returns, it returns the value of the
   expression.  Otherwise this function is similar to ``run()``.

pdb.runcall(function[, argument, ...])

   Call the *function* (a function or method object, not a string)
   with the given arguments.  When ``runcall()`` returns, it returns
   whatever the function call returned.  The debugger prompt appears
   as soon as the function is entered.

pdb.set_trace()

   Enter the debugger at the calling stack frame.  This is useful to
   hard-code a breakpoint at a given point in a program, even if the
   code is not otherwise being debugged (e.g. when an assertion
   fails).

pdb.post_mortem([traceback])

   Enter post-mortem debugging of the given *traceback* object.  If no
   *traceback* is given, it uses the one of the exception that is
   currently being handled (an exception must be being handled if the
   default is to be used).

pdb.pm()

   Enter post-mortem debugging of the traceback found in
   ``sys.last_traceback``.
 
The ``del`` statement
*********************

   del_stmt ::= "del" target_list

Deletion is recursively defined very similar to the way assignment is
defined. Rather that spelling it out in full details, here are some
hints.

Deletion of a target list recursively deletes each target, from left
to right.

Deletion of a name removes the binding of that name  from the local or
global namespace, depending on whether the name occurs in a ``global``
statement in the same code block.  If the name is unbound, a
``NameError`` exception will be raised.

It is illegal to delete a name from the local namespace if it occurs
as a free variable in a nested block.

Deletion of attribute references, subscriptions and slicings is passed
to the primary object involved; deletion of a slicing is in general
equivalent to assignment of an empty slice of the right type (but even
this is determined by the sliced object).
 
Dictionary displays
*******************

A dictionary display is a possibly empty series of key/datum pairs
enclosed in curly braces:

   dict_display   ::= "{" [key_datum_list] "}"
   key_datum_list ::= key_datum ("," key_datum)* [","]
   key_datum      ::= expression ":" expression

A dictionary display yields a new dictionary object.

The key/datum pairs are evaluated from left to right to define the
entries of the dictionary: each key object is used as a key into the
dictionary to store the corresponding datum.

Restrictions on the types of the key values are listed earlier in
section *The standard type hierarchy*.  (To summarize, the key type
should be *hashable*, which excludes all mutable objects.)  Clashes
between duplicate keys are not detected; the last datum (textually
rightmost in the display) stored for a given key value prevails.
 
Interaction with dynamic features
*********************************

There are several cases where Python statements are illegal when used
in conjunction with nested scopes that contain free variables.

If a variable is referenced in an enclosing scope, it is illegal to
delete the name.  An error will be reported at compile time.

If the wild card form of import --- ``import *`` --- is used in a
function and the function contains or is a nested block with free
variables, the compiler will raise a ``SyntaxError``.

If ``exec`` is used in a function and the function contains or is a
nested block with free variables, the compiler will raise a
``SyntaxError`` unless the exec explicitly specifies the local
namespace for the ``exec``.  (In other words, ``exec obj`` would be
illegal, but ``exec obj in ns`` would be legal.)

The ``eval()``, ``execfile()``, and ``input()`` functions and the
``exec`` statement do not have access to the full environment for
resolving names.  Names may be resolved in the local and global
namespaces of the caller.  Free variables are not resolved in the
nearest enclosing namespace, but in the global namespace. [1] The
``exec`` statement and the ``eval()`` and ``execfile()`` functions
have optional arguments to override the global and local namespace.
If only one namespace is specified, it is used for both.
 
The ``if`` statement
********************

The ``if`` statement is used for conditional execution:

   if_stmt ::= "if" expression ":" suite
               ( "elif" expression ":" suite )*
               ["else" ":" suite]

It selects exactly one of the suites by evaluating the expressions one
by one until one is found to be true (see section *Boolean operations*
for the definition of true and false); then that suite is executed
(and no other part of the ``if`` statement is executed or evaluated).
If all expressions are false, the suite of the ``else`` clause, if
present, is executed.
 
Exceptions
**********

Exceptions are a means of breaking out of the normal flow of control
of a code block in order to handle errors or other exceptional
conditions.  An exception is *raised* at the point where the error is
detected; it may be *handled* by the surrounding code block or by any
code block that directly or indirectly invoked the code block where
the error occurred.

The Python interpreter raises an exception when it detects a run-time
error (such as division by zero).  A Python program can also
explicitly raise an exception with the ``raise`` statement. Exception
handlers are specified with the ``try`` ... ``except`` statement.  The
``finally`` clause of such a statement can be used to specify cleanup
code which does not handle the exception, but is executed whether an
exception occurred or not in the preceding code.

Python uses the "termination" model of error handling: an exception
handler can find out what happened and continue execution at an outer
level, but it cannot repair the cause of the error and retry the
failing operation (except by re-entering the offending piece of code
from the top).

When an exception is not handled at all, the interpreter terminates
execution of the program, or returns to its interactive main loop.  In
either case, it prints a stack backtrace, except when the exception is
``SystemExit``.

Exceptions are identified by class instances.  The ``except`` clause
is selected depending on the class of the instance: it must reference
the class of the instance or a base class thereof.  The instance can
be received by the handler and can carry additional information about
the exceptional condition.

Exceptions can also be identified by strings, in which case the
``except`` clause is selected by object identity.  An arbitrary value
can be raised along with the identifying string which can be passed to
the handler.

Warning: Messages to exceptions are not part of the Python API.  Their
  contents may change from one version of Python to the next without
  warning and should not be relied on by code which will run under
  multiple versions of the interpreter.

See also the description of the ``try`` statement in section *The try
statement* and ``raise`` statement in section *The raise statement*.

-[ Footnotes ]-

[1] This limitation occurs because the code that is executed by these
    operations is not available at the time the module is compiled.
 
The ``exec`` statement
**********************

   exec_stmt ::= "exec" or_expr ["in" expression ["," expression]]

This statement supports dynamic execution of Python code.  The first
expression should evaluate to either a string, an open file object, or
a code object.  If it is a string, the string is parsed as a suite of
Python statements which is then executed (unless a syntax error
occurs).  If it is an open file, the file is parsed until EOF and
executed.  If it is a code object, it is simply executed.  In all
cases, the code that's executed is expected to be valid as file input
(see section *File input*).  Be aware that the ``return`` and
``yield`` statements may not be used outside of function definitions
even within the context of code passed to the ``exec`` statement.

In all cases, if the optional parts are omitted, the code is executed
in the current scope.  If only the first expression after ``in`` is
specified, it should be a dictionary, which will be used for both the
global and the local variables.  If two expressions are given, they
are used for the global and local variables, respectively. If
provided, *locals* can be any mapping object.

Changed in version 2.4: Formerly, *locals* was required to be a
dictionary.

As a side effect, an implementation may insert additional keys into
the dictionaries given besides those corresponding to variable names
set by the executed code.  For example, the current implementation may
add a reference to the dictionary of the built-in module
``__builtin__`` under the key ``__builtins__`` (!).

**Programmer's hints:** dynamic evaluation of expressions is supported
by the built-in function ``eval()``.  The built-in functions
``globals()`` and ``locals()`` return the current global and local
dictionary, respectively, which may be useful to pass around for use
by ``exec``.
 
Execution model
***************


Naming and binding
==================

*Names* refer to objects.  Names are introduced by name binding
operations. Each occurrence of a name in the program text refers to
the *binding* of that name established in the innermost function block
containing the use.

A *block* is a piece of Python program text that is executed as a
unit. The following are blocks: a module, a function body, and a class
definition. Each command typed interactively is a block.  A script
file (a file given as standard input to the interpreter or specified
on the interpreter command line the first argument) is a code block.
A script command (a command specified on the interpreter command line
with the '**-c**' option) is a code block.  The file read by the
built-in function ``execfile()`` is a code block.  The string argument
passed to the built-in function ``eval()`` and to the ``exec``
statement is a code block. The expression read and evaluated by the
built-in function ``input()`` is a code block.

A code block is executed in an *execution frame*.  A frame contains
some administrative information (used for debugging) and determines
where and how execution continues after the code block's execution has
completed.

A *scope* defines the visibility of a name within a block.  If a local
variable is defined in a block, its scope includes that block.  If the
definition occurs in a function block, the scope extends to any blocks
contained within the defining one, unless a contained block introduces
a different binding for the name.  The scope of names defined in a
class block is limited to the class block; it does not extend to the
code blocks of methods -- this includes generator expressions since
they are implemented using a function scope.  This means that the
following will fail:

   class A:
       a = 42
       b = list(a + i for i in range(10))

When a name is used in a code block, it is resolved using the nearest
enclosing scope.  The set of all such scopes visible to a code block
is called the block's *environment*.

If a name is bound in a block, it is a local variable of that block.
If a name is bound at the module level, it is a global variable.  (The
variables of the module code block are local and global.)  If a
variable is used in a code block but not defined there, it is a *free
variable*.

When a name is not found at all, a ``NameError`` exception is raised.
If the name refers to a local variable that has not been bound, a
``UnboundLocalError`` exception is raised.  ``UnboundLocalError`` is a
subclass of ``NameError``.

The following constructs bind names: formal parameters to functions,
``import`` statements, class and function definitions (these bind the
class or function name in the defining block), and targets that are
identifiers if occurring in an assignment, ``for`` loop header, or in
the second position of an ``except`` clause header.  The ``import``
statement of the form "``from ...import *``" binds all names defined
in the imported module, except those beginning with an underscore.
This form may only be used at the module level.

A target occurring in a ``del`` statement is also considered bound for
this purpose (though the actual semantics are to unbind the name).  It
is illegal to unbind a name that is referenced by an enclosing scope;
the compiler will report a ``SyntaxError``.

Each assignment or import statement occurs within a block defined by a
class or function definition or at the module level (the top-level
code block).

If a name binding operation occurs anywhere within a code block, all
uses of the name within the block are treated as references to the
current block.  This can lead to errors when a name is used within a
block before it is bound. This rule is subtle.  Python lacks
declarations and allows name binding operations to occur anywhere
within a code block.  The local variables of a code block can be
determined by scanning the entire text of the block for name binding
operations.

If the global statement occurs within a block, all uses of the name
specified in the statement refer to the binding of that name in the
top-level namespace. Names are resolved in the top-level namespace by
searching the global namespace, i.e. the namespace of the module
containing the code block, and the builtin namespace, the namespace of
the module ``__builtin__``.  The global namespace is searched first.
If the name is not found there, the builtin namespace is searched.
The global statement must precede all uses of the name.

The built-in namespace associated with the execution of a code block
is actually found by looking up the name ``__builtins__`` in its
global namespace; this should be a dictionary or a module (in the
latter case the module's dictionary is used).  By default, when in the
``__main__`` module, ``__builtins__`` is the built-in module
``__builtin__`` (note: no 's'); when in any other module,
``__builtins__`` is an alias for the dictionary of the ``__builtin__``
module itself.  ``__builtins__`` can be set to a user-created
dictionary to create a weak form of restricted execution.

Note: Users should not touch ``__builtins__``; it is strictly an
  implementation detail.  Users wanting to override values in the
  built-in namespace should ``import`` the ``__builtin__`` (no 's')
  module and modify its attributes appropriately.

The namespace for a module is automatically created the first time a
module is imported.  The main module for a script is always called
``__main__``.

The global statement has the same scope as a name binding operation in
the same block.  If the nearest enclosing scope for a free variable
contains a global statement, the free variable is treated as a global.

A class definition is an executable statement that may use and define
names. These references follow the normal rules for name resolution.
The namespace of the class definition becomes the attribute dictionary
of the class.  Names defined at the class scope are not visible in
methods.


Interaction with dynamic features
---------------------------------

There are several cases where Python statements are illegal when used
in conjunction with nested scopes that contain free variables.

If a variable is referenced in an enclosing scope, it is illegal to
delete the name.  An error will be reported at compile time.

If the wild card form of import --- ``import *`` --- is used in a
function and the function contains or is a nested block with free
variables, the compiler will raise a ``SyntaxError``.

If ``exec`` is used in a function and the function contains or is a
nested block with free variables, the compiler will raise a
``SyntaxError`` unless the exec explicitly specifies the local
namespace for the ``exec``.  (In other words, ``exec obj`` would be
illegal, but ``exec obj in ns`` would be legal.)

The ``eval()``, ``execfile()``, and ``input()`` functions and the
``exec`` statement do not have access to the full environment for
resolving names.  Names may be resolved in the local and global
namespaces of the caller.  Free variables are not resolved in the
nearest enclosing namespace, but in the global namespace. [1] The
``exec`` statement and the ``eval()`` and ``execfile()`` functions
have optional arguments to override the global and local namespace.
If only one namespace is specified, it is used for both.


Exceptions
==========

Exceptions are a means of breaking out of the normal flow of control
of a code block in order to handle errors or other exceptional
conditions.  An exception is *raised* at the point where the error is
detected; it may be *handled* by the surrounding code block or by any
code block that directly or indirectly invoked the code block where
the error occurred.

The Python interpreter raises an exception when it detects a run-time
error (such as division by zero).  A Python program can also
explicitly raise an exception with the ``raise`` statement. Exception
handlers are specified with the ``try`` ... ``except`` statement.  The
``finally`` clause of such a statement can be used to specify cleanup
code which does not handle the exception, but is executed whether an
exception occurred or not in the preceding code.

Python uses the "termination" model of error handling: an exception
handler can find out what happened and continue execution at an outer
level, but it cannot repair the cause of the error and retry the
failing operation (except by re-entering the offending piece of code
from the top).

When an exception is not handled at all, the interpreter terminates
execution of the program, or returns to its interactive main loop.  In
either case, it prints a stack backtrace, except when the exception is
``SystemExit``.

Exceptions are identified by class instances.  The ``except`` clause
is selected depending on the class of the instance: it must reference
the class of the instance or a base class thereof.  The instance can
be received by the handler and can carry additional information about
the exceptional condition.

Exceptions can also be identified by strings, in which case the
``except`` clause is selected by object identity.  An arbitrary value
can be raised along with the identifying string which can be passed to
the handler.

Warning: Messages to exceptions are not part of the Python API.  Their
  contents may change from one version of Python to the next without
  warning and should not be relied on by code which will run under
  multiple versions of the interpreter.

See also the description of the ``try`` statement in section *The try
statement* and ``raise`` statement in section *The raise statement*.

-[ Footnotes ]-

[1] This limitation occurs because the code that is executed by these
    operations is not available at the time the module is compiled.
 
Expression lists
****************

   expression_list ::= expression ( "," expression )* [","]

An expression list containing at least one comma yields a tuple.  The
length of the tuple is the number of expressions in the list.  The
expressions are evaluated from left to right.

The trailing comma is required only to create a single tuple (a.k.a. a
*singleton*); it is optional in all other cases.  A single expression
without a trailing comma doesn't create a tuple, but rather yields the
value of that expression. (To create an empty tuple, use an empty pair
of parentheses: ``()``.)
 
Floating point literals
***********************

Floating point literals are described by the following lexical
definitions:

   floatnumber   ::= pointfloat | exponentfloat
   pointfloat    ::= [intpart] fraction | intpart "."
   exponentfloat ::= (intpart | pointfloat) exponent
   intpart       ::= digit+
   fraction      ::= "." digit+
   exponent      ::= ("e" | "E") ["+" | "-"] digit+

Note that the integer and exponent parts of floating point numbers can
look like octal integers, but are interpreted using radix 10.  For
example, ``077e010`` is legal, and denotes the same number as
``77e10``. The allowed range of floating point literals is
implementation-dependent. Some examples of floating point literals:

   3.14    10.    .001    1e100    3.14e-10    0e0

Note that numeric literals do not include a sign; a phrase like ``-1``
is actually an expression composed of the unary operator ``-`` and the
literal ``1``.
 
The ``for`` statement
*********************

The ``for`` statement is used to iterate over the elements of a
sequence (such as a string, tuple or list) or other iterable object:

   for_stmt ::= "for" target_list "in" expression_list ":" suite
                ["else" ":" suite]

The expression list is evaluated once; it should yield an iterable
object.  An iterator is created for the result of the
``expression_list``.  The suite is then executed once for each item
provided by the iterator, in the order of ascending indices.  Each
item in turn is assigned to the target list using the standard rules
for assignments, and then the suite is executed.  When the items are
exhausted (which is immediately when the sequence is empty), the suite
in the ``else`` clause, if present, is executed, and the loop
terminates.

A ``break`` statement executed in the first suite terminates the loop
without executing the ``else`` clause's suite.  A ``continue``
statement executed in the first suite skips the rest of the suite and
continues with the next item, or with the ``else`` clause if there was
no next item.

The suite may assign to the variable(s) in the target list; this does
not affect the next item assigned to it.

The target list is not deleted when the loop is finished, but if the
sequence is empty, it will not have been assigned to at all by the
loop.  Hint: the built-in function ``range()`` returns a sequence of
integers suitable to emulate the effect of Pascal's ``for i := a to b
do``; e.g., ``range(3)`` returns the list ``[0, 1, 2]``.

Warning: There is a subtlety when the sequence is being modified by the loop
  (this can only occur for mutable sequences, i.e. lists). An internal
  counter is used to keep track of which item is used next, and this
  is incremented on each iteration.  When this counter has reached the
  length of the sequence the loop terminates.  This means that if the
  suite deletes the current (or a previous) item from the sequence,
  the next item will be skipped (since it gets the index of the
  current item which has already been treated).  Likewise, if the
  suite inserts an item in the sequence before the current item, the
  current item will be treated again the next time through the loop.
  This can lead to nasty bugs that can be avoided by making a
  temporary copy using a slice of the whole sequence, e.g.,

   for x in a[:]:
       if x < 0: a.remove(x)
 
Format String Syntax
********************

The ``str.format()`` method and the ``Formatter`` class share the same
syntax for format strings (although in the case of ``Formatter``,
subclasses can define their own format string syntax.)

Format strings contain "replacement fields" surrounded by curly braces
``{}``. Anything that is not contained in braces is considered literal
text, which is copied unchanged to the output.  If you need to include
a brace character in the literal text, it can be escaped by doubling:
``{{`` and ``}}``.

The grammar for a replacement field is as follows:

      replacement_field ::= "{" field_name ["!" conversion] [":" format_spec] "}"
      field_name        ::= (identifier | integer) ("." attribute_name | "[" element_index "]")*
      attribute_name    ::= identifier
      element_index     ::= integer
      conversion        ::= "r" | "s"
      format_spec       ::= <described in the next section>

In less formal terms, the replacement field starts with a
*field_name*, which can either be a number (for a positional
argument), or an identifier (for keyword arguments).  Following this
is an optional *conversion* field, which is preceded by an exclamation
point ``'!'``, and a *format_spec*, which is preceded by a colon
``':'``.

The *field_name* itself begins with either a number or a keyword.  If
it's a number, it refers to a positional argument, and if it's a
keyword it refers to a named keyword argument.  This can be followed
by any number of index or attribute expressions. An expression of the
form ``'.name'`` selects the named attribute using ``getattr()``,
while an expression of the form ``'[index]'`` does an index lookup
using ``__getitem__()``.

Some simple format string examples:

   "First, thou shalt count to {0}" # References first positional argument
   "My quest is {name}"             # References keyword argument 'name'
   "Weight in tons {0.weight}"      # 'weight' attribute of first positional arg
   "Units destroyed: {players[0]}"  # First element of keyword argument 'players'.

The *conversion* field causes a type coercion before formatting.
Normally, the job of formatting a value is done by the
``__format__()`` method of the value itself.  However, in some cases
it is desirable to force a type to be formatted as a string,
overriding its own definition of formatting.  By converting the value
to a string before calling ``__format__()``, the normal formatting
logic is bypassed.

Two conversion flags are currently supported: ``'!s'`` which calls
``str()`` on the value, and ``'!r'`` which calls ``repr()``.

Some examples:

   "Harold's a clever {0!s}"        # Calls str() on the argument first
   "Bring out the holy {name!r}"    # Calls repr() on the argument first

The *format_spec* field contains a specification of how the value
should be presented, including such details as field width, alignment,
padding, decimal precision and so on.  Each value type can define it's
own "formatting mini-language" or interpretation of the *format_spec*.

Most built-in types support a common formatting mini-language, which
is described in the next section.

A *format_spec* field can also include nested replacement fields
within it. These nested replacement fields can contain only a field
name; conversion flags and format specifications are not allowed.  The
replacement fields within the format_spec are substituted before the
*format_spec* string is interpreted. This allows the formatting of a
value to be dynamically specified.

For example, suppose you wanted to have a replacement field whose
field width is determined by another variable:

   "A man with two {0:{1}}".format("noses", 10)

This would first evaluate the inner replacement field, making the
format string effectively:

   "A man with two {0:10}"

Then the outer replacement field would be evaluated, producing:

   "noses     "

Which is substituted into the string, yielding:

   "A man with two noses     "

(The extra space is because we specified a field width of 10, and
because left alignment is the default for strings.)


Format Specification Mini-Language
==================================

"Format specifications" are used within replacement fields contained
within a format string to define how individual values are presented
(see *Format String Syntax*.)  They can also be passed directly to the
builtin ``format()`` function.  Each formattable type may define how
the format specification is to be interpreted.

Most built-in types implement the following options for format
specifications, although some of the formatting options are only
supported by the numeric types.

A general convention is that an empty format string (``""``) produces
the same result as if you had called ``str()`` on the value.

The general form of a *standard format specifier* is:

   format_spec ::= [[fill]align][sign][#][0][width][.precision][type]
   fill        ::= <a character other than '}'>
   align       ::= "<" | ">" | "=" | "^"
   sign        ::= "+" | "-" | " "
   width       ::= integer
   precision   ::= integer
   type        ::= "b" | "c" | "d" | "e" | "E" | "f" | "F" | "g" | "G" | "n" | "o" | "x" | "X" | "%"

The *fill* character can be any character other than '}' (which
signifies the end of the field).  The presence of a fill character is
signaled by the *next* character, which must be one of the alignment
options. If the second character of *format_spec* is not a valid
alignment option, then it is assumed that both the fill character and
the alignment option are absent.

The meaning of the various alignment options is as follows:

   +-----------+------------------------------------------------------------+
   | Option    | Meaning                                                    |
   +===========+============================================================+
   | ``'<'``   | Forces the field to be left-aligned within the available   |
   |           | space (This is the default.)                               |
   +-----------+------------------------------------------------------------+
   | ``'>'``   | Forces the field to be right-aligned within the available  |
   |           | space.                                                     |
   +-----------+------------------------------------------------------------+
   | ``'='``   | Forces the padding to be placed after the sign (if any)    |
   |           | but before the digits.  This is used for printing fields   |
   |           | in the form '+000000120'. This alignment option is only    |
   |           | valid for numeric types.                                   |
   +-----------+------------------------------------------------------------+
   | ``'^'``   | Forces the field to be centered within the available       |
   |           | space.                                                     |
   +-----------+------------------------------------------------------------+

Note that unless a minimum field width is defined, the field width
will always be the same size as the data to fill it, so that the
alignment option has no meaning in this case.

The *sign* option is only valid for number types, and can be one of
the following:

   +-----------+------------------------------------------------------------+
   | Option    | Meaning                                                    |
   +===========+============================================================+
   | ``'+'``   | indicates that a sign should be used for both positive as  |
   |           | well as negative numbers.                                  |
   +-----------+------------------------------------------------------------+
   | ``'-'``   | indicates that a sign should be used only for negative     |
   |           | numbers (this is the default behavior).                    |
   +-----------+------------------------------------------------------------+
   | space     | indicates that a leading space should be used on positive  |
   |           | numbers, and a minus sign on negative numbers.             |
   +-----------+------------------------------------------------------------+

The ``'#'`` option is only valid for integers, and only for binary,
octal, or hexadecimal output.  If present, it specifies that the
output will be prefixed by ``'0b'``, ``'0o'``, or ``'0x'``,
respectively.

*width* is a decimal integer defining the minimum field width.  If not
specified, then the field width will be determined by the content.

If the *width* field is preceded by a zero (``'0'``) character, this
enables zero-padding.  This is equivalent to an *alignment* type of
``'='`` and a *fill* character of ``'0'``.

The *precision* is a decimal number indicating how many digits should
be displayed after the decimal point for a floating point value
formatted with ``'f'`` and ``'F'``, or before and after the decimal
point for a floating point value formatted with ``'g'`` or ``'G'``.
For non-number types the field indicates the maximum field size - in
other words, how many characters will be used from the field content.
The *precision* is ignored for integer values.

Finally, the *type* determines how the data should be presented.

The available integer presentation types are:

   +-----------+------------------------------------------------------------+
   | Type      | Meaning                                                    |
   +===========+============================================================+
   | ``'b'``   | Binary format. Outputs the number in base 2.               |
   +-----------+------------------------------------------------------------+
   | ``'c'``   | Character. Converts the integer to the corresponding       |
   |           | unicode character before printing.                         |
   +-----------+------------------------------------------------------------+
   | ``'d'``   | Decimal Integer. Outputs the number in base 10.            |
   +-----------+------------------------------------------------------------+
   | ``'o'``   | Octal format. Outputs the number in base 8.                |
   +-----------+------------------------------------------------------------+
   | ``'x'``   | Hex format. Outputs the number in base 16, using lower-    |
   |           | case letters for the digits above 9.                       |
   +-----------+------------------------------------------------------------+
   | ``'X'``   | Hex format. Outputs the number in base 16, using upper-    |
   |           | case letters for the digits above 9.                       |
   +-----------+------------------------------------------------------------+
   | ``'n'``   | Number. This is the same as ``'d'``, except that it uses   |
   |           | the current locale setting to insert the appropriate       |
   |           | number separator characters.                               |
   +-----------+------------------------------------------------------------+
   | None      | The same as ``'d'``.                                       |
   +-----------+------------------------------------------------------------+

The available presentation types for floating point and decimal values
are:

   +-----------+------------------------------------------------------------+
   | Type      | Meaning                                                    |
   +===========+============================================================+
   | ``'e'``   | Exponent notation. Prints the number in scientific         |
   |           | notation using the letter 'e' to indicate the exponent.    |
   +-----------+------------------------------------------------------------+
   | ``'E'``   | Exponent notation. Same as ``'e'`` except it uses an upper |
   |           | case 'E' as the separator character.                       |
   +-----------+------------------------------------------------------------+
   | ``'f'``   | Fixed point. Displays the number as a fixed-point number.  |
   +-----------+------------------------------------------------------------+
   | ``'F'``   | Fixed point. Same as ``'f'``.                              |
   +-----------+------------------------------------------------------------+
   | ``'g'``   | General format. This prints the number as a fixed-point    |
   |           | number, unless the number is too large, in which case it   |
   |           | switches to ``'e'`` exponent notation. Infinity and NaN    |
   |           | values are formatted as ``inf``, ``-inf`` and ``nan``,     |
   |           | respectively.                                              |
   +-----------+------------------------------------------------------------+
   | ``'G'``   | General format. Same as ``'g'`` except switches to ``'E'`` |
   |           | if the number gets to large. The representations of        |
   |           | infinity and NaN are uppercased, too.                      |
   +-----------+------------------------------------------------------------+
   | ``'n'``   | Number. This is the same as ``'g'``, except that it uses   |
   |           | the current locale setting to insert the appropriate       |
   |           | number separator characters.                               |
   +-----------+------------------------------------------------------------+
   | ``'%'``   | Percentage. Multiplies the number by 100 and displays in   |
   |           | fixed (``'f'``) format, followed by a percent sign.        |
   +-----------+------------------------------------------------------------+
   | None      | The same as ``'g'``.                                       |
   +-----------+------------------------------------------------------------+
 
Function definitions
********************

A function definition defines a user-defined function object (see
section *The standard type hierarchy*):

   decorated      ::= decorators (classdef | funcdef)
   decorators     ::= decorator+
   decorator      ::= "@" dotted_name ["(" [argument_list [","]] ")"] NEWLINE
   funcdef        ::= "def" funcname "(" [parameter_list] ")" ":" suite
   dotted_name    ::= identifier ("." identifier)*
   parameter_list ::= (defparameter ",")*
                      (  "*" identifier [, "**" identifier]
                      | "**" identifier
                      | defparameter [","] )
   defparameter   ::= parameter ["=" expression]
   sublist        ::= parameter ("," parameter)* [","]
   parameter      ::= identifier | "(" sublist ")"
   funcname       ::= identifier

A function definition is an executable statement.  Its execution binds
the function name in the current local namespace to a function object
(a wrapper around the executable code for the function).  This
function object contains a reference to the current global namespace
as the global namespace to be used when the function is called.

The function definition does not execute the function body; this gets
executed only when the function is called. [3]

A function definition may be wrapped by one or more *decorator*
expressions. Decorator expressions are evaluated when the function is
defined, in the scope that contains the function definition.  The
result must be a callable, which is invoked with the function object
as the only argument. The returned value is bound to the function name
instead of the function object.  Multiple decorators are applied in
nested fashion. For example, the following code:

   @f1(arg)
   @f2
   def func(): pass

is equivalent to:

   def func(): pass
   func = f1(arg)(f2(func))

When one or more top-level parameters have the form *parameter* ``=``
*expression*, the function is said to have "default parameter values."
For a parameter with a default value, the corresponding argument may
be omitted from a call, in which case the parameter's default value is
substituted.  If a parameter has a default value, all following
parameters must also have a default value --- this is a syntactic
restriction that is not expressed by the grammar.

**Default parameter values are evaluated when the function definition
is executed.**  This means that the expression is evaluated once, when
the function is defined, and that that same "pre-computed" value is
used for each call.  This is especially important to understand when a
default parameter is a mutable object, such as a list or a dictionary:
if the function modifies the object (e.g. by appending an item to a
list), the default value is in effect modified. This is generally not
what was intended.  A way around this  is to use ``None`` as the
default, and explicitly test for it in the body of the function, e.g.:

   def whats_on_the_telly(penguin=None):
       if penguin is None:
           penguin = []
       penguin.append("property of the zoo")
       return penguin

Function call semantics are described in more detail in section
*Calls*. A function call always assigns values to all parameters
mentioned in the parameter list, either from position arguments, from
keyword arguments, or from default values.  If the form
"``*identifier``" is present, it is initialized to a tuple receiving
any excess positional parameters, defaulting to the empty tuple.  If
the form "``**identifier``" is present, it is initialized to a new
dictionary receiving any excess keyword arguments, defaulting to a new
empty dictionary.

It is also possible to create anonymous functions (functions not bound
to a name), for immediate use in expressions.  This uses lambda forms,
described in section *Expression lists*.  Note that the lambda form is
merely a shorthand for a simplified function definition; a function
defined in a "``def``" statement can be passed around or assigned to
another name just like a function defined by a lambda form.  The
"``def``" form is actually more powerful since it allows the execution
of multiple statements.

**Programmer's note:** Functions are first-class objects.  A "``def``"
form executed inside a function definition defines a local function
that can be returned or passed around.  Free variables used in the
nested function can access the local variables of the function
containing the def.  See section *Naming and binding* for details.
 
The ``global`` statement
************************

   global_stmt ::= "global" identifier ("," identifier)*

The ``global`` statement is a declaration which holds for the entire
current code block.  It means that the listed identifiers are to be
interpreted as globals.  It would be impossible to assign to a global
variable without ``global``, although free variables may refer to
globals without being declared global.

Names listed in a ``global`` statement must not be used in the same
code block textually preceding that ``global`` statement.

Names listed in a ``global`` statement must not be defined as formal
parameters or in a ``for`` loop control target, ``class`` definition,
function definition, or ``import`` statement.

(The current implementation does not enforce the latter two
restrictions, but programs should not abuse this freedom, as future
implementations may enforce them or silently change the meaning of the
program.)

**Programmer's note:** the ``global`` is a directive to the parser.
It applies only to code parsed at the same time as the ``global``
statement. In particular, a ``global`` statement contained in an
``exec`` statement does not affect the code block *containing* the
``exec`` statement, and code contained in an ``exec`` statement is
unaffected by ``global`` statements in the code containing the
``exec`` statement.  The same applies to the ``eval()``,
``execfile()`` and ``compile()`` functions.
 
Reserved classes of identifiers
*******************************

Certain classes of identifiers (besides keywords) have special
meanings.  These classes are identified by the patterns of leading and
trailing underscore characters:

``_*``
   Not imported by ``from module import *``.  The special identifier
   ``_`` is used in the interactive interpreter to store the result of
   the last evaluation; it is stored in the ``__builtin__`` module.
   When not in interactive mode, ``_`` has no special meaning and is
   not defined. See section *The import statement*.

   Note: The name ``_`` is often used in conjunction with
     internationalization; refer to the documentation for the
     ``gettext`` module for more information on this convention.

``__*__``
   System-defined names.  These names are defined by the interpreter
   and its implementation (including the standard library);
   applications should not expect to define additional names using
   this convention.  The set of names of this class defined by Python
   may be extended in future versions. See section *Special method
   names*.

``__*``
   Class-private names.  Names in this category, when used within the
   context of a class definition, are re-written to use a mangled form
   to help avoid name clashes between "private" attributes of base and
   derived classes. See section *Identifiers (Names)*.
 
Identifiers and keywords
************************

Identifiers (also referred to as *names*) are described by the
following lexical definitions:

   identifier ::= (letter|"_") (letter | digit | "_")*
   letter     ::= lowercase | uppercase
   lowercase  ::= "a"..."z"
   uppercase  ::= "A"..."Z"
   digit      ::= "0"..."9"

Identifiers are unlimited in length.  Case is significant.


Keywords
========

The following identifiers are used as reserved words, or *keywords* of
the language, and cannot be used as ordinary identifiers.  They must
be spelled exactly as written here:

   and       del       from      not       while
   as        elif      global    or        with
   assert    else      if        pass      yield
   break     except    import    print
   class     exec      in        raise
   continue  finally   is        return
   def       for       lambda    try

Changed in version 2.4: ``None`` became a constant and is now
recognized by the compiler as a name for the built-in object ``None``.
Although it is not a keyword, you cannot assign a different object to
it.

Changed in version 2.5: Both ``as`` and ``with`` are only recognized
when the ``with_statement`` future feature has been enabled. It will
always be enabled in Python 2.6.  See section *The with statement* for
details.  Note that using ``as`` and ``with`` as identifiers will
always issue a warning, even when the ``with_statement`` future
directive is not in effect.


Reserved classes of identifiers
===============================

Certain classes of identifiers (besides keywords) have special
meanings.  These classes are identified by the patterns of leading and
trailing underscore characters:

``_*``
   Not imported by ``from module import *``.  The special identifier
   ``_`` is used in the interactive interpreter to store the result of
   the last evaluation; it is stored in the ``__builtin__`` module.
   When not in interactive mode, ``_`` has no special meaning and is
   not defined. See section *The import statement*.

   Note: The name ``_`` is often used in conjunction with
     internationalization; refer to the documentation for the
     ``gettext`` module for more information on this convention.

``__*__``
   System-defined names.  These names are defined by the interpreter
   and its implementation (including the standard library);
   applications should not expect to define additional names using
   this convention.  The set of names of this class defined by Python
   may be extended in future versions. See section *Special method
   names*.

``__*``
   Class-private names.  Names in this category, when used within the
   context of a class definition, are re-written to use a mangled form
   to help avoid name clashes between "private" attributes of base and
   derived classes. See section *Identifiers (Names)*.
 
The ``if`` statement
********************

The ``if`` statement is used for conditional execution:

   if_stmt ::= "if" expression ":" suite
               ( "elif" expression ":" suite )*
               ["else" ":" suite]

It selects exactly one of the suites by evaluating the expressions one
by one until one is found to be true (see section *Boolean operations*
for the definition of true and false); then that suite is executed
(and no other part of the ``if`` statement is executed or evaluated).
If all expressions are false, the suite of the ``else`` clause, if
present, is executed.
 
Imaginary literals
******************

Imaginary literals are described by the following lexical definitions:

   imagnumber ::= (floatnumber | intpart) ("j" | "J")

An imaginary literal yields a complex number with a real part of 0.0.
Complex numbers are represented as a pair of floating point numbers
and have the same restrictions on their range.  To create a complex
number with a nonzero real part, add a floating point number to it,
e.g., ``(3+4j)``.  Some examples of imaginary literals:

   3.14j   10.j    10j     .001j   1e100j  3.14e-10j
 
The ``import`` statement
************************

   import_stmt     ::= "import" module ["as" name] ( "," module ["as" name] )*
                   | "from" relative_module "import" identifier ["as" name]
                   ( "," identifier ["as" name] )*
                   | "from" relative_module "import" "(" identifier ["as" name]
                   ( "," identifier ["as" name] )* [","] ")"
                   | "from" module "import" "*"
   module          ::= (identifier ".")* identifier
   relative_module ::= "."* module | "."+
   name            ::= identifier

Import statements are executed in two steps: (1) find a module, and
initialize it if necessary; (2) define a name or names in the local
namespace (of the scope where the ``import`` statement occurs). The
first form (without ``from``) repeats these steps for each identifier
in the list.  The form with ``from`` performs step (1) once, and then
performs step (2) repeatedly.

In this context, to "initialize" a built-in or extension module means
to call an initialization function that the module must provide for
the purpose (in the reference implementation, the function's name is
obtained by prepending string "init" to the module's name); to
"initialize" a Python-coded module means to execute the module's body.

The system maintains a table of modules that have been or are being
initialized, indexed by module name.  This table is accessible as
``sys.modules``.  When a module name is found in this table, step (1)
is finished.  If not, a search for a module definition is started.
When a module is found, it is loaded.  Details of the module searching
and loading process are implementation and platform specific.  It
generally involves searching for a "built-in" module with the given
name and then searching a list of locations given as ``sys.path``.

If a built-in module is found, its built-in initialization code is
executed and step (1) is finished.  If no matching file is found,
``ImportError`` is raised. If a file is found, it is parsed, yielding
an executable code block.  If a syntax error occurs, ``SyntaxError``
is raised.  Otherwise, an empty module of the given name is created
and inserted in the module table, and then the code block is executed
in the context of this module.  Exceptions during this execution
terminate step (1).

When step (1) finishes without raising an exception, step (2) can
begin.

The first form of ``import`` statement binds the module name in the
local namespace to the module object, and then goes on to import the
next identifier, if any.  If the module name is followed by ``as``,
the name following ``as`` is used as the local name for the module.

The ``from`` form does not bind the module name: it goes through the
list of identifiers, looks each one of them up in the module found in
step (1), and binds the name in the local namespace to the object thus
found.  As with the first form of ``import``, an alternate local name
can be supplied by specifying "``as`` localname".  If a name is not
found, ``ImportError`` is raised.  If the list of identifiers is
replaced by a star (``'*'``), all public names defined in the module
are bound in the local namespace of the ``import`` statement..

The *public names* defined by a module are determined by checking the
module's namespace for a variable named ``__all__``; if defined, it
must be a sequence of strings which are names defined or imported by
that module.  The names given in ``__all__`` are all considered public
and are required to exist.  If ``__all__`` is not defined, the set of
public names includes all names found in the module's namespace which
do not begin with an underscore character (``'_'``). ``__all__``
should contain the entire public API. It is intended to avoid
accidentally exporting items that are not part of the API (such as
library modules which were imported and used within the module).

The ``from`` form with ``*`` may only occur in a module scope.  If the
wild card form of import --- ``import *`` --- is used in a function
and the function contains or is a nested block with free variables,
the compiler will raise a ``SyntaxError``.

**Hierarchical module names:** when the module names contains one or
more dots, the module search path is carried out differently.  The
sequence of identifiers up to the last dot is used to find a
"package"; the final identifier is then searched inside the package.
A package is generally a subdirectory of a directory on ``sys.path``
that has a file ``__init__.py``.

The built-in function ``__import__()`` is provided to support
applications that determine which modules need to be loaded
dynamically; refer to *Built-in Functions* for additional information.


Future statements
=================

A *future statement* is a directive to the compiler that a particular
module should be compiled using syntax or semantics that will be
available in a specified future release of Python.  The future
statement is intended to ease migration to future versions of Python
that introduce incompatible changes to the language.  It allows use of
the new features on a per-module basis before the release in which the
feature becomes standard.

   future_statement ::= "from" "__future__" "import" feature ["as" name]
                        ("," feature ["as" name])*
                        | "from" "__future__" "import" "(" feature ["as" name]
                        ("," feature ["as" name])* [","] ")"
   feature          ::= identifier
   name             ::= identifier

A future statement must appear near the top of the module.  The only
lines that can appear before a future statement are:

* the module docstring (if any),

* comments,

* blank lines, and

* other future statements.

The features recognized by Python 2.6 are ``unicode_literals``,
``print_function``, ``absolute_import``, ``division``, ``generators``,
``nested_scopes`` and ``with_statement``.  ``generators``,
``with_statement``, ``nested_scopes`` are redundant in Python version
2.6 and above because they are always enabled.

A future statement is recognized and treated specially at compile
time: Changes to the semantics of core constructs are often
implemented by generating different code.  It may even be the case
that a new feature introduces new incompatible syntax (such as a new
reserved word), in which case the compiler may need to parse the
module differently.  Such decisions cannot be pushed off until
runtime.

For any given release, the compiler knows which feature names have
been defined, and raises a compile-time error if a future statement
contains a feature not known to it.

The direct runtime semantics are the same as for any import statement:
there is a standard module ``__future__``, described later, and it
will be imported in the usual way at the time the future statement is
executed.

The interesting runtime semantics depend on the specific feature
enabled by the future statement.

Note that there is nothing special about the statement:

   import __future__ [as name]

That is not a future statement; it's an ordinary import statement with
no special semantics or syntax restrictions.

Code compiled by an ``exec`` statement or calls to the builtin
functions ``compile()`` and ``execfile()`` that occur in a module
``M`` containing a future statement will, by default, use the new
syntax or semantics associated with the future statement.  This can,
starting with Python 2.2 be controlled by optional arguments to
``compile()`` --- see the documentation of that function for details.

A future statement typed at an interactive interpreter prompt will
take effect for the rest of the interpreter session.  If an
interpreter is started with the *-i* option, is passed a script name
to execute, and the script includes a future statement, it will be in
effect in the interactive session started after the script is
executed.
 
Comparisons
***********

Unlike C, all comparison operations in Python have the same priority,
which is lower than that of any arithmetic, shifting or bitwise
operation.  Also unlike C, expressions like ``a < b < c`` have the
interpretation that is conventional in mathematics:

   comparison    ::= or_expr ( comp_operator or_expr )*
   comp_operator ::= "<" | ">" | "==" | ">=" | "<=" | "<>" | "!="
                     | "is" ["not"] | ["not"] "in"

Comparisons yield boolean values: ``True`` or ``False``.

Comparisons can be chained arbitrarily, e.g., ``x < y <= z`` is
equivalent to ``x < y and y <= z``, except that ``y`` is evaluated
only once (but in both cases ``z`` is not evaluated at all when ``x <
y`` is found to be false).

Formally, if *a*, *b*, *c*, ..., *y*, *z* are expressions and *op1*,
*op2*, ..., *opN* are comparison operators, then ``a op1 b op2 c ... y
opN z`` is equivalent to ``a op1 b and b op2 c and ... y opN z``,
except that each expression is evaluated at most once.

Note that ``a op1 b op2 c`` doesn't imply any kind of comparison
between *a* and *c*, so that, e.g., ``x < y > z`` is perfectly legal
(though perhaps not pretty).

The forms ``<>`` and ``!=`` are equivalent; for consistency with C,
``!=`` is preferred; where ``!=`` is mentioned below ``<>`` is also
accepted.  The ``<>`` spelling is considered obsolescent.

The operators ``<``, ``>``, ``==``, ``>=``, ``<=``, and ``!=`` compare
the values of two objects.  The objects need not have the same type.
If both are numbers, they are converted to a common type.  Otherwise,
objects of different types *always* compare unequal, and are ordered
consistently but arbitrarily. You can control comparison behavior of
objects of non-builtin types by defining a ``__cmp__`` method or rich
comparison methods like ``__gt__``, described in section *Special
method names*.

(This unusual definition of comparison was used to simplify the
definition of operations like sorting and the ``in`` and ``not in``
operators. In the future, the comparison rules for objects of
different types are likely to change.)

Comparison of objects of the same type depends on the type:

* Numbers are compared arithmetically.

* Strings are compared lexicographically using the numeric equivalents
  (the result of the built-in function ``ord()``) of their characters.
  Unicode and 8-bit strings are fully interoperable in this behavior.
  [4]

* Tuples and lists are compared lexicographically using comparison of
  corresponding elements.  This means that to compare equal, each
  element must compare equal and the two sequences must be of the same
  type and have the same length.

  If not equal, the sequences are ordered the same as their first
  differing elements.  For example, ``cmp([1,2,x], [1,2,y])`` returns
  the same as ``cmp(x,y)``.  If the corresponding element does not
  exist, the shorter sequence is ordered first (for example, ``[1,2] <
  [1,2,3]``).

* Mappings (dictionaries) compare equal if and only if their sorted
  (key, value) lists compare equal. [5] Outcomes other than equality
  are resolved consistently, but are not otherwise defined. [6]

* Most other objects of builtin types compare unequal unless they are
  the same object; the choice whether one object is considered smaller
  or larger than another one is made arbitrarily but consistently
  within one execution of a program.

The operators ``in`` and ``not in`` test for collection membership.
``x in s`` evaluates to true if *x* is a member of the collection *s*,
and false otherwise.  ``x not in s`` returns the negation of ``x in
s``. The collection membership test has traditionally been bound to
sequences; an object is a member of a collection if the collection is
a sequence and contains an element equal to that object.  However, it
make sense for many other object types to support membership tests
without being a sequence.  In particular, dictionaries (for keys) and
sets support membership testing.

For the list and tuple types, ``x in y`` is true if and only if there
exists an index *i* such that ``x == y[i]`` is true.

For the Unicode and string types, ``x in y`` is true if and only if
*x* is a substring of *y*.  An equivalent test is ``y.find(x) != -1``.
Note, *x* and *y* need not be the same type; consequently, ``u'ab' in
'abc'`` will return ``True``. Empty strings are always considered to
be a substring of any other string, so ``"" in "abc"`` will return
``True``.

Changed in version 2.3: Previously, *x* was required to be a string of
length ``1``.

For user-defined classes which define the ``__contains__()`` method,
``x in y`` is true if and only if ``y.__contains__(x)`` is true.

For user-defined classes which do not define ``__contains__()`` and do
define ``__getitem__()``, ``x in y`` is true if and only if there is a
non-negative integer index *i* such that ``x == y[i]``, and all lower
integer indices do not raise ``IndexError`` exception. (If any other
exception is raised, it is as if ``in`` raised that exception).

The operator ``not in`` is defined to have the inverse true value of
``in``.

The operators ``is`` and ``is not`` test for object identity: ``x is
y`` is true if and only if *x* and *y* are the same object.  ``x is
not y`` yields the inverse truth value. [7]
 
Integer and long integer literals
*********************************

Integer and long integer literals are described by the following
lexical definitions:

   longinteger    ::= integer ("l" | "L")
   integer        ::= decimalinteger | octinteger | hexinteger | bininteger
   decimalinteger ::= nonzerodigit digit* | "0"
   octinteger     ::= "0" ("o" | "O") octdigit+ | "0" octdigit+
   hexinteger     ::= "0" ("x" | "X") hexdigit+
   bininteger     ::= "0" ("b" | "B") bindigit+
   nonzerodigit   ::= "1"..."9"
   octdigit       ::= "0"..."7"
   bindigit       ::= "0" | "1"
   hexdigit       ::= digit | "a"..."f" | "A"..."F"

Although both lower case ``'l'`` and upper case ``'L'`` are allowed as
suffix for long integers, it is strongly recommended to always use
``'L'``, since the letter ``'l'`` looks too much like the digit
``'1'``.

Plain integer literals that are above the largest representable plain
integer (e.g., 2147483647 when using 32-bit arithmetic) are accepted
as if they were long integers instead. [1]  There is no limit for long
integer literals apart from what can be stored in available memory.

Some examples of plain integer literals (first row) and long integer
literals (second and third rows):

   7     2147483647                        0177
   3L    79228162514264337593543950336L    0377L   0x100000000L
         79228162514264337593543950336             0xdeadbeef
 
Expression lists
****************

   expression_list ::= expression ( "," expression )* [","]

An expression list containing at least one comma yields a tuple.  The
length of the tuple is the number of expressions in the list.  The
expressions are evaluated from left to right.

The trailing comma is required only to create a single tuple (a.k.a. a
*singleton*); it is optional in all other cases.  A single expression
without a trailing comma doesn't create a tuple, but rather yields the
value of that expression. (To create an empty tuple, use an empty pair
of parentheses: ``()``.)
 
List displays
*************

A list display is a possibly empty series of expressions enclosed in
square brackets:

   list_display        ::= "[" [expression_list | list_comprehension] "]"
   list_comprehension  ::= expression list_for
   list_for            ::= "for" target_list "in" old_expression_list [list_iter]
   old_expression_list ::= old_expression [("," old_expression)+ [","]]
   list_iter           ::= list_for | list_if
   list_if             ::= "if" old_expression [list_iter]

A list display yields a new list object.  Its contents are specified
by providing either a list of expressions or a list comprehension.
When a comma-separated list of expressions is supplied, its elements
are evaluated from left to right and placed into the list object in
that order.  When a list comprehension is supplied, it consists of a
single expression followed by at least one ``for`` clause and zero or
more ``for`` or ``if`` clauses.  In this case, the elements of the new
list are those that would be produced by considering each of the
``for`` or ``if`` clauses a block, nesting from left to right, and
evaluating the expression to produce a list element each time the
innermost block is reached [1].
 
Naming and binding
******************

*Names* refer to objects.  Names are introduced by name binding
operations. Each occurrence of a name in the program text refers to
the *binding* of that name established in the innermost function block
containing the use.

A *block* is a piece of Python program text that is executed as a
unit. The following are blocks: a module, a function body, and a class
definition. Each command typed interactively is a block.  A script
file (a file given as standard input to the interpreter or specified
on the interpreter command line the first argument) is a code block.
A script command (a command specified on the interpreter command line
with the '**-c**' option) is a code block.  The file read by the
built-in function ``execfile()`` is a code block.  The string argument
passed to the built-in function ``eval()`` and to the ``exec``
statement is a code block. The expression read and evaluated by the
built-in function ``input()`` is a code block.

A code block is executed in an *execution frame*.  A frame contains
some administrative information (used for debugging) and determines
where and how execution continues after the code block's execution has
completed.

A *scope* defines the visibility of a name within a block.  If a local
variable is defined in a block, its scope includes that block.  If the
definition occurs in a function block, the scope extends to any blocks
contained within the defining one, unless a contained block introduces
a different binding for the name.  The scope of names defined in a
class block is limited to the class block; it does not extend to the
code blocks of methods -- this includes generator expressions since
they are implemented using a function scope.  This means that the
following will fail:

   class A:
       a = 42
       b = list(a + i for i in range(10))

When a name is used in a code block, it is resolved using the nearest
enclosing scope.  The set of all such scopes visible to a code block
is called the block's *environment*.

If a name is bound in a block, it is a local variable of that block.
If a name is bound at the module level, it is a global variable.  (The
variables of the module code block are local and global.)  If a
variable is used in a code block but not defined there, it is a *free
variable*.

When a name is not found at all, a ``NameError`` exception is raised.
If the name refers to a local variable that has not been bound, a
``UnboundLocalError`` exception is raised.  ``UnboundLocalError`` is a
subclass of ``NameError``.

The following constructs bind names: formal parameters to functions,
``import`` statements, class and function definitions (these bind the
class or function name in the defining block), and targets that are
identifiers if occurring in an assignment, ``for`` loop header, or in
the second position of an ``except`` clause header.  The ``import``
statement of the form "``from ...import *``" binds all names defined
in the imported module, except those beginning with an underscore.
This form may only be used at the module level.

A target occurring in a ``del`` statement is also considered bound for
this purpose (though the actual semantics are to unbind the name).  It
is illegal to unbind a name that is referenced by an enclosing scope;
the compiler will report a ``SyntaxError``.

Each assignment or import statement occurs within a block defined by a
class or function definition or at the module level (the top-level
code block).

If a name binding operation occurs anywhere within a code block, all
uses of the name within the block are treated as references to the
current block.  This can lead to errors when a name is used within a
block before it is bound. This rule is subtle.  Python lacks
declarations and allows name binding operations to occur anywhere
within a code block.  The local variables of a code block can be
determined by scanning the entire text of the block for name binding
operations.

If the global statement occurs within a block, all uses of the name
specified in the statement refer to the binding of that name in the
top-level namespace. Names are resolved in the top-level namespace by
searching the global namespace, i.e. the namespace of the module
containing the code block, and the builtin namespace, the namespace of
the module ``__builtin__``.  The global namespace is searched first.
If the name is not found there, the builtin namespace is searched.
The global statement must precede all uses of the name.

The built-in namespace associated with the execution of a code block
is actually found by looking up the name ``__builtins__`` in its
global namespace; this should be a dictionary or a module (in the
latter case the module's dictionary is used).  By default, when in the
``__main__`` module, ``__builtins__`` is the built-in module
``__builtin__`` (note: no 's'); when in any other module,
``__builtins__`` is an alias for the dictionary of the ``__builtin__``
module itself.  ``__builtins__`` can be set to a user-created
dictionary to create a weak form of restricted execution.

Note: Users should not touch ``__builtins__``; it is strictly an
  implementation detail.  Users wanting to override values in the
  built-in namespace should ``import`` the ``__builtin__`` (no 's')
  module and modify its attributes appropriately.

The namespace for a module is automatically created the first time a
module is imported.  The main module for a script is always called
``__main__``.

The global statement has the same scope as a name binding operation in
the same block.  If the nearest enclosing scope for a free variable
contains a global statement, the free variable is treated as a global.

A class definition is an executable statement that may use and define
names. These references follow the normal rules for name resolution.
The namespace of the class definition becomes the attribute dictionary
of the class.  Names defined at the class scope are not visible in
methods.


Interaction with dynamic features
=================================

There are several cases where Python statements are illegal when used
in conjunction with nested scopes that contain free variables.

If a variable is referenced in an enclosing scope, it is illegal to
delete the name.  An error will be reported at compile time.

If the wild card form of import --- ``import *`` --- is used in a
function and the function contains or is a nested block with free
variables, the compiler will raise a ``SyntaxError``.

If ``exec`` is used in a function and the function contains or is a
nested block with free variables, the compiler will raise a
``SyntaxError`` unless the exec explicitly specifies the local
namespace for the ``exec``.  (In other words, ``exec obj`` would be
illegal, but ``exec obj in ns`` would be legal.)

The ``eval()``, ``execfile()``, and ``input()`` functions and the
``exec`` statement do not have access to the full environment for
resolving names.  Names may be resolved in the local and global
namespaces of the caller.  Free variables are not resolved in the
nearest enclosing namespace, but in the global namespace. [1] The
``exec`` statement and the ``eval()`` and ``execfile()`` functions
have optional arguments to override the global and local namespace.
If only one namespace is specified, it is used for both.
 
Numeric literals
****************

There are four types of numeric literals: plain integers, long
integers, floating point numbers, and imaginary numbers.  There are no
complex literals (complex numbers can be formed by adding a real
number and an imaginary number).

Note that numeric literals do not include a sign; a phrase like ``-1``
is actually an expression composed of the unary operator '``-``' and
the literal ``1``.
 
Emulating numeric types
***********************

The following methods can be defined to emulate numeric objects.
Methods corresponding to operations that are not supported by the
particular kind of number implemented (e.g., bitwise operations for
non-integral numbers) should be left undefined.

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.

   If one of those methods does not support the operation with the
   supplied arguments, it should return ``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. [3] 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*.

   Note that ternary ``pow()`` will not try calling ``__rpow__()``
   (the coercion rules would become too complicated).

   Note: If the right operand's type is a subclass of the left operand's
     type and that subclass provides the reflected method for the
     operation, this method will be called before the left operand's
     non-reflected method.  This behavior allows subclasses to
     override their ancestors' operations.

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
   operations (``+=``, ``-=``, ``*=``, ``/=``, ``//=``, ``%=``,
   ``**=``, ``<<=``, ``>>=``, ``&=``, ``^=``, ``|=``).  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
   operation falls back to the normal methods.  For instance, to
   evaluate the expression ``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)

   Called to implement the unary arithmetic operations (``-``, ``+``,
   ``abs()`` and ``~``).

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).

   New in version 2.5.

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``.
 
Objects, values and types
*************************

*Objects* are Python's abstraction for data.  All data in a Python
program is represented by objects or by relations between objects. (In
a sense, and in conformance to Von Neumann's model of a "stored
program computer," code is also represented by objects.)

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.

Objects are never explicitly destroyed; however, when they become
unreachable they may be garbage-collected.  An implementation is
allowed to postpone garbage collection or omit it altogether --- it is
a matter of implementation quality how garbage collection is
implemented, as long as no objects are collected that are still
reachable.  (Implementation note: the current implementation 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.)

Note that the use of the implementation's tracing or debugging
facilities may keep objects alive that would normally be collectable.
Also note that catching an exception with a '``try``...``except``'
statement may keep objects alive.

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.

Some objects contain references to other objects; these are called
*containers*. Examples of containers are tuples, lists and
dictionaries.  The references are part of a container's value.  In
most cases, when we talk about the value of a container, we imply the
values, not the identities of the contained objects; however, when we
talk about the mutability of a container, only the identities of the
immediately contained objects are implied.  So, if an immutable
container (like a tuple) contains a reference to a mutable object, its
value changes if that mutable object is changed.

Types affect almost all aspects of object behavior.  Even the
importance of object identity is affected in some sense: for immutable
types, operations that compute new values may actually return a
reference to any existing object with the same type and value, while
for mutable objects this is not allowed.  E.g., after ``a = 1; b =
1``, ``a`` and ``b`` may or may not refer to the same object with the
value one, depending on the implementation, but after ``c = []; d =
[]``, ``c`` and ``d`` are guaranteed to refer to two different,
unique, newly created empty lists. (Note that ``c = d = []`` assigns
the same object to both ``c`` and ``d``.)
 
Summary
*******

The following table summarizes the operator precedences in Python,
from lowest precedence (least binding) to highest precedence (most
binding). Operators in the same box have the same precedence.  Unless
the syntax is explicitly given, operators are binary.  Operators in
the same box group left to right (except for comparisons, including
tests, which all have the same precedence and chain from left to right
--- see section *Comparisons* --- and exponentiation, which groups
from right to left).

+-------------------------------------------------+---------------------------------------+
| Operator                                        | Description                           |
+=================================================+=======================================+
| ``lambda``                                      | Lambda expression                     |
+-------------------------------------------------+---------------------------------------+
| ``or``                                          | Boolean OR                            |
+-------------------------------------------------+---------------------------------------+
| ``and``                                         | Boolean AND                           |
+-------------------------------------------------+---------------------------------------+
| ``not`` *x*                                     | Boolean NOT                           |
+-------------------------------------------------+---------------------------------------+
| ``in``, ``not`` ``in``                          | Membership tests                      |
+-------------------------------------------------+---------------------------------------+
| ``is``, ``is not``                              | Identity tests                        |
+-------------------------------------------------+---------------------------------------+
| ``<``, ``<=``, ``>``, ``>=``, ``<>``, ``!=``,   | Comparisons                           |
| ``==``                                          |                                       |
+-------------------------------------------------+---------------------------------------+
| ``|``                                           | Bitwise OR                            |
+-------------------------------------------------+---------------------------------------+
| ``^``                                           | Bitwise XOR                           |
+-------------------------------------------------+---------------------------------------+
| ``&``                                           | Bitwise AND                           |
+-------------------------------------------------+---------------------------------------+
| ``<<``, ``>>``                                  | Shifts                                |
+-------------------------------------------------+---------------------------------------+
| ``+``, ``-``                                    | Addition and subtraction              |
+-------------------------------------------------+---------------------------------------+
| ``*``, ``/``, ``%``                             | Multiplication, division, remainder   |
+-------------------------------------------------+---------------------------------------+
| ``+x``, ``-x``                                  | Positive, negative                    |
+-------------------------------------------------+---------------------------------------+
| ``~x``                                          | Bitwise not                           |
+-------------------------------------------------+---------------------------------------+
| ``**``                                          | Exponentiation                        |
+-------------------------------------------------+---------------------------------------+
| ``x[index]``                                    | Subscription                          |
+-------------------------------------------------+---------------------------------------+
| ``x[index:index]``                              | Slicing                               |
+-------------------------------------------------+---------------------------------------+
| ``x(arguments...)``                             | Call                                  |
+-------------------------------------------------+---------------------------------------+
| ``x.attribute``                                 | Attribute reference                   |
+-------------------------------------------------+---------------------------------------+
| ``(expressions...)``                            | Binding or tuple display              |
+-------------------------------------------------+---------------------------------------+
| ``[expressions...]``                            | List display                          |
+-------------------------------------------------+---------------------------------------+
| ``{key:datum...}``                              | Dictionary display                    |
+-------------------------------------------------+---------------------------------------+
| ```expressions...```                            | String conversion                     |
+-------------------------------------------------+---------------------------------------+

-[ Footnotes ]-

[1] In Python 2.3 and later releases, a list comprehension "leaks" the
    control variables of each ``for`` it contains into the containing
    scope.  However, this behavior is deprecated, and relying on it
    will not work in Python 3.0

[2] While ``abs(x%y) < abs(y)`` is true mathematically, for floats it
    may not be true numerically due to roundoff.  For example, and
    assuming a platform on which a Python float is an IEEE 754 double-
    precision number, in order that ``-1e-100 % 1e100`` have the same
    sign as ``1e100``, the computed result is ``-1e-100 + 1e100``,
    which is numerically exactly equal to ``1e100``.  Function
    ``fmod()`` in the ``math`` module returns a result whose sign
    matches the sign of the first argument instead, and so returns
    ``-1e-100`` in this case. Which approach is more appropriate
    depends on the application.

[3] If x is very close to an exact integer multiple of y, it's
    possible for ``floor(x/y)`` to be one larger than ``(x-x%y)/y``
    due to rounding.  In such cases, Python returns the latter result,
    in order to preserve that ``divmod(x,y)[0] * y + x % y`` be very
    close to ``x``.

[4] While comparisons between unicode strings make sense at the byte
    level, they may be counter-intuitive to users. For example, the
    strings ``u"\u00C7"`` and ``u"\u0043\u0327"`` compare differently,
    even though they both represent the same unicode character (LATIN
    CAPTITAL LETTER C WITH CEDILLA). To compare strings in a human
    recognizable way, compare using ``unicodedata.normalize()``.

[5] The implementation computes this efficiently, without constructing
    lists or sorting.

[6] Earlier versions of Python used lexicographic comparison of the
    sorted (key, value) lists, but this was very expensive for the
    common case of comparing for equality.  An even earlier version of
    Python compared dictionaries by identity only, but this caused
    surprises because people expected to be able to test a dictionary
    for emptiness by comparing it to ``{}``.

[7] Due to automatic garbage-collection, free lists, and the dynamic
    nature of descriptors, you may notice seemingly unusual behaviour
    in certain uses of the ``is`` operator, like those involving
    comparisons between instance methods, or constants.  Check their
    documentation for more info.
 
The ``pass`` statement
**********************

   pass_stmt ::= "pass"

``pass`` is a null operation --- when it is executed, nothing happens.
It is useful as a placeholder when a statement is required
syntactically, but no code needs to be executed, for example:

   def f(arg): pass    # a function that does nothing (yet)

   class C: pass       # a class with no methods (yet)
 
The power operator
******************

The power operator binds more tightly than unary operators on its
left; it binds less tightly than unary operators on its right.  The
syntax is:

   power ::= primary ["**" u_expr]

Thus, in an unparenthesized sequence of power and unary operators, the
operators are evaluated from right to left (this does not constrain
the evaluation order for the operands): ``-1**2`` results in ``-1``.

The power operator has the same semantics as the built-in ``pow()``
function, when called with two arguments: it yields its left argument
raised to the power of its right argument.  The numeric arguments are
first converted to a common type.  The result type is that of the
arguments after coercion.

With mixed operand types, the coercion rules for binary arithmetic
operators apply. For int and long int operands, the result has the
same type as the operands (after coercion) unless the second argument
is negative; in that case, all arguments are converted to float and a
float result is delivered. For example, ``10**2`` returns ``100``, but
``10**-2`` returns ``0.01``. (This last feature was added in Python
2.2. In Python 2.1 and before, if both arguments were of integer types
and the second argument was negative, an exception was raised).

Raising ``0.0`` to a negative power results in a
``ZeroDivisionError``. Raising a negative number to a fractional power
results in a ``ValueError``.
 
The ``print`` statement
***********************

   print_stmt ::= "print" ([expression ("," expression)* [","]]
                  | ">>" expression [("," expression)+ [","]])

``print`` evaluates each expression in turn and writes the resulting
object to standard output (see below).  If an object is not a string,
it is first converted to a string using the rules for string
conversions.  The (resulting or original) string is then written.  A
space is written before each object is (converted and) written, unless
the output system believes it is positioned at the beginning of a
line.  This is the case (1) when no characters have yet been written
to standard output, (2) when the last character written to standard
output is ``'\n'``, or (3) when the last write operation on standard
output was not a ``print`` statement.  (In some cases it may be
functional to write an empty string to standard output for this
reason.)

Note: Objects which act like file objects but which are not the built-in
  file objects often do not properly emulate this aspect of the file
  object's behavior, so it is best not to rely on this.

A ``'\n'`` character is written at the end, unless the ``print``
statement ends with a comma.  This is the only action if the statement
contains just the keyword ``print``.

Standard output is defined as the file object named ``stdout`` in the
built-in module ``sys``.  If no such object exists, or if it does not
have a ``write()`` method, a ``RuntimeError`` exception is raised.

``print`` also has an extended form, defined by the second portion of
the syntax described above. This form is sometimes referred to as
"``print`` chevron." In this form, the first expression after the
``>>`` must evaluate to a "file-like" object, specifically an object
that has a ``write()`` method as described above.  With this extended
form, the subsequent expressions are printed to this file object.  If
the first expression evaluates to ``None``, then ``sys.stdout`` is
used as the file for output.
 
The ``raise`` statement
***********************

   raise_stmt ::= "raise" [expression ["," expression ["," expression]]]

If no expressions are present, ``raise`` re-raises the last exception
that was active in the current scope.  If no exception is active in
the current scope, a ``TypeError`` exception is raised indicating that
this is an error (if running under IDLE, a ``Queue.Empty`` exception
is raised instead).

Otherwise, ``raise`` evaluates the expressions to get three objects,
using ``None`` as the value of omitted expressions.  The first two
objects are used to determine the *type* and *value* of the exception.

If the first object is an instance, the type of the exception is the
class of the instance, the instance itself is the value, and the
second object must be ``None``.

If the first object is a class, it becomes the type of the exception.
The second object is used to determine the exception value: If it is
an instance of the class, the instance becomes the exception value. If
the second object is a tuple, it is used as the argument list for the
class constructor; if it is ``None``, an empty argument list is used,
and any other object is treated as a single argument to the
constructor.  The instance so created by calling the constructor is
used as the exception value.

If a third object is present and not ``None``, it must be a traceback
object (see section *The standard type hierarchy*), and it is
substituted instead of the current location as the place where the
exception occurred.  If the third object is present and not a
traceback object or ``None``, a ``TypeError`` exception is raised.
The three-expression form of ``raise`` is useful to re-raise an
exception transparently in an except clause, but ``raise`` with no
expressions should be preferred if the exception to be re-raised was
the most recently active exception in the current scope.

Additional information on exceptions can be found in section
*Exceptions*, and information about handling exceptions is in section
*The try statement*.
 
The ``return`` statement
************************

   return_stmt ::= "return" [expression_list]

``return`` may only occur syntactically nested in a function
definition, not within a nested class definition.

If an expression list is present, it is evaluated, else ``None`` is
substituted.

``return`` leaves the current function call with the expression list
(or ``None``) as return value.

When ``return`` passes control out of a ``try`` statement with a
``finally`` clause, that ``finally`` clause is executed before really
leaving the function.

In a generator function, the ``return`` statement is not allowed to
include an **expression_list**.  In that context, a bare ``return``
indicates that the generator is done and will cause ``StopIteration``
to be raised.
 
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)

   Deprecated since version 2.0: 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.maxint``, 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.
 
Emulating container types
*************************

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.

object.__getitem__(self, key)

   Called to implement evaluation of ``self[key]``. For sequence
   types, the accepted keys should be integers and slice objects.
   Note that the special interpretation of negative indexes (if the
   class wishes to emulate a sequence type) is up to the
   ``__getitem__()`` method. If *key* is of an inappropriate type,
   ``TypeError`` may be raised; if of a value outside the set of
   indexes for the sequence (after any special interpretation of
   negative values), ``IndexError`` should be raised. For mapping
   types, if *key* is missing (not in the container), ``KeyError``
   should be raised.

   Note: ``for`` loops expect that an ``IndexError`` will be raised for
     illegal indexes to allow proper detection of the end of the
     sequence.

object.__setitem__(self, key, value)

   Called to implement assignment to ``self[key]``.  Same note as for
   ``__getitem__()``.  This should only be implemented for mappings if
   the objects support changes to the values for keys, or if new keys
   can be added, or for sequences if elements can be replaced.  The
   same exceptions should be raised for improper *key* values as for
   the ``__getitem__()`` method.

object.__delitem__(self, key)

   Called to implement deletion of ``self[key]``.  Same note as for
   ``__getitem__()``.  This should only be implemented for mappings if
   the objects support removal of keys, or for sequences if elements
   can be removed from the sequence.  The same exceptions should be
   raised for improper *key* values as for the ``__getitem__()``
   method.

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()``.

   Iterator objects also need to implement this method; they are
   required to return themselves.  For more information on iterator
   objects, see *Iterator Types*.

object.__reversed__(self)

   Called (if present) by the ``reversed()`` builtin to implement
   reverse iteration.  It should return a new iterator object that
   iterates over all the objects in the container in reverse order.

   If the ``__reversed__()`` method is not provided, the
   ``reversed()`` builtin will fall back to using the sequence
   protocol (``__len__()`` and ``__getitem__()``).  Objects should
   normally only provide ``__reversed__()`` if they do not support the
   sequence protocol and an efficient implementation of reverse
   iteration is possible.

   New in version 2.6.

The membership test operators (``in`` and ``not in``) are normally
implemented as an iteration through a sequence.  However, container
objects can supply the following special method with a more efficient
implementation, which also does not require the object be a sequence.

object.__contains__(self, item)

   Called to implement membership test operators.  Should return true
   if *item* is in *self*, false otherwise.  For mapping objects, this
   should consider the keys of the mapping rather than the values or
   the key-item pairs.
 
Shifting operations
*******************

The shifting operations have lower priority than the arithmetic
operations:

   shift_expr ::= a_expr | shift_expr ( "<<" | ">>" ) a_expr

These operators accept plain or long integers as arguments.  The
arguments are converted to a common type.  They shift the first
argument to the left or right by the number of bits given by the
second argument.

A right shift by *n* bits is defined as division by ``pow(2, n)``.  A
left shift by *n* bits is defined as multiplication with ``pow(2,
n)``.  Negative shift counts raise a ``ValueError`` exception.
 
Slicings
********

A slicing selects a range of items in a sequence object (e.g., a
string, tuple or list).  Slicings may be used as expressions or as
targets in assignment or ``del`` statements.  The syntax for a
slicing:

   slicing          ::= simple_slicing | extended_slicing
   simple_slicing   ::= primary "[" short_slice "]"
   extended_slicing ::= primary "[" slice_list "]"
   slice_list       ::= slice_item ("," slice_item)* [","]
   slice_item       ::= expression | proper_slice | ellipsis
   proper_slice     ::= short_slice | long_slice
   short_slice      ::= [lower_bound] ":" [upper_bound]
   long_slice       ::= short_slice ":" [stride]
   lower_bound      ::= expression
   upper_bound      ::= expression
   stride           ::= expression
   ellipsis         ::= "..."

There is ambiguity in the formal syntax here: anything that looks like
an expression list also looks like a slice list, so any subscription
can be interpreted as a slicing.  Rather than further complicating the
syntax, this is disambiguated by defining that in this case the
interpretation as a subscription takes priority over the
interpretation as a slicing (this is the case if the slice list
contains no proper slice nor ellipses).  Similarly, when the slice
list has exactly one short slice and no trailing comma, the
interpretation as a simple slicing takes priority over that as an
extended slicing.

The semantics for a simple slicing are as follows.  The primary must
evaluate to a sequence object.  The lower and upper bound expressions,
if present, must evaluate to plain integers; defaults are zero and the
``sys.maxint``, respectively.  If either bound is negative, the
sequence's length is added to it.  The slicing now selects all items
with index *k* such that ``i <= k < j`` where *i* and *j* are the
specified lower and upper bounds.  This may be an empty sequence.  It
is not an error if *i* or *j* lie outside the range of valid indexes
(such items don't exist so they aren't selected).

The semantics for an extended slicing are as follows.  The primary
must evaluate to a mapping object, and it is indexed with a key that
is constructed from the slice list, as follows.  If the slice list
contains at least one comma, the key is a tuple containing the
conversion of the slice items; otherwise, the conversion of the lone
slice item is the key.  The conversion of a slice item that is an
expression is that expression.  The conversion of an ellipsis slice
item is the built-in ``Ellipsis`` object.  The conversion of a proper
slice is a slice object (see section *The standard type hierarchy*)
whose ``start``, ``stop`` and ``step`` attributes are the values of
the expressions given as lower bound, upper bound and stride,
respectively, substituting ``None`` for missing expressions.
 
Special Attributes
******************

The implementation adds a few special read-only attributes to several
object types, where they are relevant.  Some of these are not reported
by the ``dir()`` built-in function.

object.__dict__

   A dictionary or other mapping object used to store an object's
   (writable) attributes.

object.__methods__

   Deprecated since version 2.2: Use the built-in function ``dir()``
   to get a list of an object's attributes. This attribute is no
   longer available.

object.__members__

   Deprecated since version 2.2: Use the built-in function ``dir()``
   to get a list of an object's attributes. This attribute is no
   longer available.

instance.__class__

   The class to which a class instance belongs.

class.__bases__

   The tuple of base classes of a class object.  If there are no base
   classes, this will be an empty tuple.

class.__name__

   The name of the class or type.

-[ Footnotes ]-

[1] Additional information on these special methods may be found in
    the Python Reference Manual (*Basic customization*).

[2] As a consequence, the list ``[1, 2]`` is considered equal to
    ``[1.0, 2.0]``, and similarly for tuples.

[3] They must have since the parser can't tell the type of the
    operands.

[4] To format only a tuple you should therefore provide a singleton
    tuple whose only element is the tuple to be formatted.

[5] These numbers are fairly arbitrary.  They are intended to avoid
    printing endless strings of meaningless digits without hampering
    correct use and without having to know the exact precision of
    floating point values on a particular machine.

[6] The advantage of leaving the newline on is that returning an empty
    string is then an unambiguous EOF indication.  It is also possible
    (in cases where it might matter, for example, if you want to make
    an exact copy of a file while scanning its lines) to tell whether
    the last line of a file ended in a newline or not (yes this
    happens!).
 
Special method names
********************

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``).

When implementing a class that emulates any built-in type, it is
important that the emulation only be implemented to the degree that it
makes sense for the object being modelled.  For example, some
sequences may work well with retrieval of individual elements, but
extracting a slice may not make sense.  (One example of this is the
``NodeList`` interface in the W3C's Document Object Model.)


Basic customization
===================

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

   Called to create a new instance of class *cls*.  ``__new__()`` is a
   static method (special-cased so you need not declare it as such)
   that takes the class of which an instance was requested as its
   first argument.  The remaining arguments are those passed to the
   object constructor expression (the call to the class).  The return
   value of ``__new__()`` should be the new object instance (usually
   an instance of *cls*).

   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.

   If ``__new__()`` returns an instance of *cls*, then the new
   instance's ``__init__()`` method will be invoked like
   ``__init__(self[, ...])``, where *self* is the new instance and the
   remaining arguments are the same as were passed to ``__new__()``.

   If ``__new__()`` does not return an instance of *cls*, then the new
   instance's ``__init__()`` method will not be invoked.

   ``__new__()`` is intended mainly to allow subclasses of immutable
   types (like int, str, or tuple) to customize instance creation.  It
   is also commonly overridden in custom metaclasses in order to
   customize class creation.

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

   Called when the instance is created.  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...])``.  As a special constraint
   on constructors, no value may be returned; 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.

   Note: ``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.

   Warning: 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.  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.

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.

   This is typically used for debugging, so it is important that the
   representation is information-rich and unambiguous.

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)

   New in version 2.1.

   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)``.

   A rich comparison method may return the singleton
   ``NotImplemented`` if it does not implement the operation for a
   given pair of arguments. By convention, ``False`` and ``True`` are
   returned for a successful comparison. However, these methods can
   return any value, so if the comparison operator is used in a
   Boolean context (e.g., in the condition of an ``if`` statement),
   Python will call ``bool()`` on the value to determine if the result
   is true or false.

   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.

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)

   Changed in version 2.1: No longer supported.

object.__hash__(self)

   Called for the key object for dictionary operations, and by the
   built-in function ``hash()``.  Should return an integer usable as a
   hash value for dictionary operations.  The only required property
   is that objects which compare equal have the same hash value; it is
   advised to somehow mix together (e.g., using exclusive or) the hash
   values for the components of the object that also play a part in
   comparison of objects.

   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 as dictionary keys.  If a class
   defines mutable objects and implements a ``__cmp__()`` or
   ``__eq__()`` method, it should not implement ``__hash__()``, since
   the dictionary implementation requires that a key'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 ``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``).

   Changed in version 2.5: ``__hash__()`` may now also return a long
   integer object; the 32-bit integer is then derived from the hash of
   that object.

   Changed in version 2.6: ``__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 (see below).  If a class
   defines neither ``__len__()`` nor ``__nonzero__()``, all its
   instances are considered true.

object.__unicode__(self)

   Called to implement ``unicode()`` builtin; 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.


Customizing attribute access
============================

The following methods can be defined to customize the meaning of
attribute access (use of, assignment to, or deletion of ``x.name``)
for class instances.

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)

   Like ``__setattr__()`` but for attribute deletion instead of
   assignment.  This should only be implemented if ``del obj.name`` is
   meaningful for the object.


More attribute access for new-style classes
-------------------------------------------

The following methods only apply to new-style classes.

object.__getattribute__(self, name)

   Called unconditionally to implement attribute accesses for
   instances of the class. If the class also defines
   ``__getattr__()``, the latter will not be called unless
   ``__getattribute__()`` either calls it explicitly or raises an
   ``AttributeError``. This method should return the (computed)
   attribute value or raise an ``AttributeError`` exception. In order
   to avoid infinite recursion in this method, its implementation
   should always call the base class method with the same name to
   access any attributes it needs, for example,
   ``object.__getattribute__(self, name)``.

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


Implementing Descriptors
------------------------

The following methods only apply when an instance of the class
containing the method (a so-called *descriptor* class) appears in the
class dictionary of another new-style class, known as the *owner*
class. In the examples below, "the attribute" refers to the attribute
whose name is the key of the property in the owner class'
``__dict__``.  Descriptors can only be implemented as new-style
classes themselves.

object.__get__(self, instance, owner)

   Called to get the attribute of the owner class (class attribute
   access) or of an instance of that class (instance attribute
   access). *owner* is always the owner class, while *instance* is the
   instance that the attribute was accessed through, or ``None`` when
   the attribute is accessed through the *owner*.  This method should
   return the (computed) attribute value or raise an
   ``AttributeError`` exception.

object.__set__(self, instance, value)

   Called to set the attribute on an instance *instance* of the owner
   class to a new value, *value*.

object.__delete__(self, instance)

   Called to delete the attribute on an instance *instance* of the
   owner class.


Invoking Descriptors
--------------------

In general, a descriptor is an object attribute with "binding
behavior", one whose attribute access has been overridden by methods
in the descriptor protocol:  ``__get__()``, ``__set__()``, and
``__delete__()``. If any of those methods are defined for an object,
it is said to be a descriptor.

The default behavior for attribute access is to get, set, or delete
the attribute from an object's dictionary. For instance, ``a.x`` has a
lookup chain starting with ``a.__dict__['x']``, then
``type(a).__dict__['x']``, and continuing through the base classes of
``type(a)`` excluding metaclasses.

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()``).

The starting point for descriptor invocation is a binding, ``a.x``.
How the arguments are assembled depends on ``a``:

Direct Call
   The simplest and least common call is when user code directly
   invokes a descriptor method:    ``x.__get__(a)``.

Instance Binding
   If binding to a new-style object instance, ``a.x`` is transformed
   into the call: ``type(a).__dict__['x'].__get__(a, type(a))``.

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

Super Binding
   If ``a`` is an instance of ``super``, then the binding ``super(B,
   obj).m()`` searches ``obj.__class__.__mro__`` for the base class
   ``A`` immediately preceding ``B`` and then invokes the descriptor
   with the call: ``A.__dict__['m'].__get__(obj, A)``.

For instance bindings, the precedence of descriptor invocation depends
on the which descriptor methods are defined.  Normally, data
descriptors define both ``__get__()`` and ``__set__()``, while non-
data descriptors have just the ``__get__()`` method.  Data descriptors
always override a redefinition in an instance dictionary.  In
contrast, non-data descriptors can be overridden by instances. [2]

Python methods (including ``staticmethod()`` and ``classmethod()``)
are implemented as non-data descriptors.  Accordingly, instances can
redefine and override methods.  This allows individual instances to
acquire behaviors that differ from other instances of the same class.

The ``property()`` function is implemented as a data descriptor.
Accordingly, instances cannot override the behavior of a property.


__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.

   New in version 2.2.

Notes on using *__slots__*

* 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.

* Without a *__dict__* variable, instances cannot be assigned new
  variables not listed in the *__slots__* definition.  Attempts to
  assign to an unlisted variable name raises ``AttributeError``. If
  dynamic assignment of new variables is desired, then add
  ``'__dict__'`` to the sequence of strings in the *__slots__*
  declaration.

  Changed in version 2.3: 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.

* Without a *__weakref__* variable for each instance, classes defining
  *__slots__* do not support weak references to its instances. If weak
  reference support is needed, then add ``'__weakref__'`` to the
  sequence of strings in the *__slots__* declaration.

  Changed in version 2.3: Previously, adding ``'__weakref__'`` to the
  *__slots__* declaration would not enable support for weak
  references.

* *__slots__* are implemented at the class level by creating
  descriptors (*Implementing Descriptors*) for each variable name.  As
  a result, class attributes cannot be used to set default values for
  instance variables defined by *__slots__*; otherwise, the class
  attribute would overwrite the descriptor assignment.

* If a class defines a slot also defined in a base class, the instance
  variable defined by the base class slot is inaccessible (except by
  retrieving its descriptor directly from the base class). This
  renders the meaning of the program undefined.  In the future, a
  check may be added to prevent this.

* 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__*.

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

* Any non-string iterable may be assigned to *__slots__*. Mappings may
  also be used; however, in the future, special meaning may be
  assigned to the values corresponding to each key.

* *__class__* assignment works only if both classes have the same
  *__slots__*.

  Changed in version 2.6: Previously, *__class__* assignment raised an
  error if either new or old class had *__slots__*.


Customizing class creation
==========================

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()``.

   New in version 2.2.

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.


Emulating callable objects
==========================

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

   Called when the instance is "called" as a function; if this method
   is defined, ``x(arg1, arg2, ...)`` is a shorthand for
   ``x.__call__(arg1, arg2, ...)``.


Emulating container types
=========================

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.

object.__getitem__(self, key)

   Called to implement evaluation of ``self[key]``. For sequence
   types, the accepted keys should be integers and slice objects.
   Note that the special interpretation of negative indexes (if the
   class wishes to emulate a sequence type) is up to the
   ``__getitem__()`` method. If *key* is of an inappropriate type,
   ``TypeError`` may be raised; if of a value outside the set of
   indexes for the sequence (after any special interpretation of
   negative values), ``IndexError`` should be raised. For mapping
   types, if *key* is missing (not in the container), ``KeyError``
   should be raised.

   Note: ``for`` loops expect that an ``IndexError`` will be raised for
     illegal indexes to allow proper detection of the end of the
     sequence.

object.__setitem__(self, key, value)

   Called to implement assignment to ``self[key]``.  Same note as for
   ``__getitem__()``.  This should only be implemented for mappings if
   the objects support changes to the values for keys, or if new keys
   can be added, or for sequences if elements can be replaced.  The
   same exceptions should be raised for improper *key* values as for
   the ``__getitem__()`` method.

object.__delitem__(self, key)

   Called to implement deletion of ``self[key]``.  Same note as for
   ``__getitem__()``.  This should only be implemented for mappings if
   the objects support removal of keys, or for sequences if elements
   can be removed from the sequence.  The same exceptions should be
   raised for improper *key* values as for the ``__getitem__()``
   method.

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()``.

   Iterator objects also need to implement this method; they are
   required to return themselves.  For more information on iterator
   objects, see *Iterator Types*.

object.__reversed__(self)

   Called (if present) by the ``reversed()`` builtin to implement
   reverse iteration.  It should return a new iterator object that
   iterates over all the objects in the container in reverse order.

   If the ``__reversed__()`` method is not provided, the
   ``reversed()`` builtin will fall back to using the sequence
   protocol (``__len__()`` and ``__getitem__()``).  Objects should
   normally only provide ``__reversed__()`` if they do not support the
   sequence protocol and an efficient implementation of reverse
   iteration is possible.

   New in version 2.6.

The membership test operators (``in`` and ``not in``) are normally
implemented as an iteration through a sequence.  However, container
objects can supply the following special method with a more efficient
implementation, which also does not require the object be a sequence.

object.__contains__(self, item)

   Called to implement membership test operators.  Should return true
   if *item* is in *self*, false otherwise.  For mapping objects, this
   should consider the keys of the mapping rather than the values or
   the key-item pairs.


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)

   Deprecated since version 2.0: 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.maxint``, 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.


Emulating numeric types
=======================

The following methods can be defined to emulate numeric objects.
Methods corresponding to operations that are not supported by the
particular kind of number implemented (e.g., bitwise operations for
non-integral numbers) should be left undefined.

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.

   If one of those methods does not support the operation with the
   supplied arguments, it should return ``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. [3] 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*.

   Note that ternary ``pow()`` will not try calling ``__rpow__()``
   (the coercion rules would become too complicated).

   Note: If the right operand's type is a subclass of the left operand's
     type and that subclass provides the reflected method for the
     operation, this method will be called before the left operand's
     non-reflected method.  This behavior allows subclasses to
     override their ancestors' operations.

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
   operations (``+=``, ``-=``, ``*=``, ``/=``, ``//=``, ``%=``,
   ``**=``, ``<<=``, ``>>=``, ``&=``, ``^=``, ``|=``).  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
   operation falls back to the normal methods.  For instance, to
   evaluate the expression ``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)

   Called to implement the unary arithmetic operations (``-``, ``+``,
   ``abs()`` and ``~``).

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).

   New in version 2.5.

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``.


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 3.0, 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 operator 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`` and ``float`` do not use coercion; the type ``complex``
  however does use it.  The difference can become apparent when
  subclassing these types.  Over time, the type ``complex`` may be
  fixed to avoid coercion. All these types implement a
  ``__coerce__()`` method, for use by the built-in ``coerce()``
  function.


With Statement Context Managers
===============================

New in version 2.5.

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.

Typical uses of context managers include saving and restoring various
kinds of global state, locking and unlocking resources, closing opened
files, etc.

For more information on context managers, see *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)

   Exit the runtime context related to this object. The parameters
   describe the exception that caused the context to be exited. If the
   context was exited without an exception, all three arguments will
   be ``None``.

   If an exception is supplied, and the method wishes to suppress the
   exception (i.e., prevent it from being propagated), it should
   return a true value. Otherwise, the exception will be processed
   normally upon exit from this method.

   Note that ``__exit__()`` methods should not reraise the passed-in
   exception; this is the caller's responsibility.

See also:

   **PEP 0343** - The "with" statement
      The specification, background, and examples for the Python
      ``with`` statement.


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


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()

The rationale behind this behaviour lies with a number of special
methods such as ``__hash__()`` and ``__repr__()`` that are implemented
by all objects, including type objects. If the implicit lookup of
these methods used the conventional lookup process, they would fail
when invoked on the type object itself:

   >>> 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

Incorrectly attempting to invoke an unbound method of a class in this
way is sometimes referred to as 'metaclass confusion', and is avoided
by bypassing the instance when looking up special methods:

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

In addition to bypassing any instance attributes in the interest of
correctness, implicit special method lookup may also bypass the
``__getattribute__()`` method even of the object's metaclass:

   >>> 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

Bypassing the ``__getattribute__()`` machinery in this fashion
provides significant scope for speed optimisations within the
interpreter, at the cost of some flexibility in the handling of
special methods (the special method *must* be set on the class object
itself in order to be consistently invoked by the interpreter).

-[ Footnotes ]-

[1] It *is* possible in some cases to change an object's type, under
    certain controlled conditions. It generally isn't a good idea
    though, since it can lead to some very strange behaviour if it is
    handled incorrectly.

[2] A descriptor can define any combination of ``__get__()``,
    ``__set__()`` and ``__delete__()``.  If it does not define
    ``__get__()``, then accessing the attribute even on an instance
    will return the descriptor object itself.  If the descriptor
    defines ``__set__()`` and/or ``__delete__()``, it is a data
    descriptor; if it defines neither, it is a non-data descriptor.

[3] For operands of the same type, it is assumed that if the non-
    reflected method (such as ``__add__()``) fails the operation is
    not supported, which is why the reflected method is not called.
 
String conversions
******************

A string conversion is an expression list enclosed in reverse (a.k.a.
backward) quotes:

   string_conversion ::= "'" expression_list "'"

A string conversion evaluates the contained expression list and
converts the resulting object into a string according to rules
specific to its type.

If the object is a string, a number, ``None``, or a tuple, list or
dictionary containing only objects whose type is one of these, the
resulting string is a valid Python expression which can be passed to
the built-in function ``eval()`` to yield an expression with the same
value (or an approximation, if floating point numbers are involved).

(In particular, converting a string adds quotes around it and converts
"funny" characters to escape sequences that are safe to print.)

Recursive objects (for example, lists or dictionaries that contain a
reference to themselves, directly or indirectly) use ``...`` to
indicate a recursive reference, and the result cannot be passed to
``eval()`` to get an equal value (``SyntaxError`` will be raised
instead).

The built-in function ``repr()`` performs exactly the same conversion
in its argument as enclosing it in parentheses and reverse quotes
does.  The built-in function ``str()`` performs a similar but more
user-friendly conversion.
 
String Methods
**************

Below are listed the string methods which both 8-bit strings and
Unicode objects support. Note that none of these methods take keyword
arguments.

In addition, Python's strings support the sequence type methods
described in the *Sequence Types --- str, unicode, list, tuple,
buffer, xrange* section. To output formatted strings use template
strings or the ``%`` operator described in the *String Formatting
Operations* section. Also, see the ``re`` module for string functions
based on regular expressions.

str.capitalize()

   Return a copy of the string with only its first character
   capitalized.

   For 8-bit strings, this method is locale-dependent.

str.center(width[, fillchar])

   Return centered in a string of length *width*. Padding is done
   using the specified *fillchar* (default is a space).

   Changed in version 2.4: Support for the *fillchar* argument.

str.count(sub[, start[, end]])

   Return the number of occurrences of substring *sub* in the range
   [*start*, *end*].  Optional arguments *start* and *end* are
   interpreted as in slice notation.

str.decode([encoding[, errors]])

   Decodes the string using the codec registered for *encoding*.
   *encoding* defaults to the default string encoding.  *errors* may
   be given to set a different error handling scheme.  The default is
   ``'strict'``, meaning that encoding errors raise ``UnicodeError``.
   Other possible values are ``'ignore'``, ``'replace'`` and any other
   name registered via ``codecs.register_error()``, see section *Codec
   Base Classes*.

   New in version 2.2.

   Changed in version 2.3: Support for other error handling schemes
   added.

str.encode([encoding[, errors]])

   Return an encoded version of the string.  Default encoding is the
   current default string encoding.  *errors* may be given to set a
   different error handling scheme.  The default for *errors* is
   ``'strict'``, meaning that encoding errors raise a
   ``UnicodeError``.  Other possible values are ``'ignore'``,
   ``'replace'``, ``'xmlcharrefreplace'``, ``'backslashreplace'`` and
   any other name registered via ``codecs.register_error()``, see
   section *Codec Base Classes*. For a list of possible encodings, see
   section *Standard Encodings*.

   New in version 2.0.

   Changed in version 2.3: Support for ``'xmlcharrefreplace'`` and
   ``'backslashreplace'`` and other error handling schemes added.

str.endswith(suffix[, start[, end]])

   Return ``True`` if the string ends with the specified *suffix*,
   otherwise return ``False``.  *suffix* can also be a tuple of
   suffixes to look for.  With optional *start*, test beginning at
   that position.  With optional *end*, stop comparing at that
   position.

   Changed in version 2.5: Accept tuples as *suffix*.

str.expandtabs([tabsize])

   Return a copy of the string where all tab characters are replaced
   by one or more spaces, depending on the current column and the
   given tab size.  The column number is reset to zero after each
   newline occurring in the string. If *tabsize* is not given, a tab
   size of ``8`` characters is assumed.  This doesn't understand other
   non-printing characters or escape sequences.

str.find(sub[, start[, end]])

   Return the lowest index in the string where substring *sub* is
   found, such that *sub* is contained in the range [*start*, *end*].
   Optional arguments *start* and *end* are interpreted as in slice
   notation.  Return ``-1`` if *sub* is not found.

str.format(format_string, *args, **kwargs)

   Perform a string formatting operation.  The *format_string*
   argument can contain literal text or replacement fields delimited
   by braces ``{}``.  Each replacement field contains either the
   numeric index of a positional argument, or the name of a keyword
   argument.  Returns a copy of *format_string* where each replacement
   field is replaced with the string value of the corresponding
   argument.

   >>> "The sum of 1 + 2 is {0}".format(1+2)
   'The sum of 1 + 2 is 3'

   See *Format String Syntax* for a description of the various
   formatting options that can be specified in format strings.

   This method of string formatting is the new standard in Python 3.0,
   and should be preferred to the ``%`` formatting described in
   *String Formatting Operations* in new code.

   New in version 2.6.

str.index(sub[, start[, end]])

   Like ``find()``, but raise ``ValueError`` when the substring is not
   found.

str.isalnum()

   Return true if all characters in the string are alphanumeric and
   there is at least one character, false otherwise.

   For 8-bit strings, this method is locale-dependent.

str.isalpha()

   Return true if all characters in the string are alphabetic and
   there is at least one character, false otherwise.

   For 8-bit strings, this method is locale-dependent.

str.isdigit()

   Return true if all characters in the string are digits and there is
   at least one character, false otherwise.

   For 8-bit strings, this method is locale-dependent.

str.islower()

   Return true if all cased characters in the string are lowercase and
   there is at least one cased character, false otherwise.

   For 8-bit strings, this method is locale-dependent.

str.isspace()

   Return true if there are only whitespace characters in the string
   and there is at least one character, false otherwise.

   For 8-bit strings, this method is locale-dependent.

str.istitle()

   Return true if the string is a titlecased string and there is at
   least one character, for example uppercase characters may only
   follow uncased characters and lowercase characters only cased ones.
   Return false otherwise.

   For 8-bit strings, this method is locale-dependent.

str.isupper()

   Return true if all cased characters in the string are uppercase and
   there is at least one cased character, false otherwise.

   For 8-bit strings, this method is locale-dependent.

str.join(seq)

   Return a string which is the concatenation of the strings in the
   sequence *seq*. The separator between elements is the string
   providing this method.

str.ljust(width[, fillchar])

   Return the string left justified in a string of length *width*.
   Padding is done using the specified *fillchar* (default is a
   space).  The original string is returned if *width* is less than
   ``len(s)``.

   Changed in version 2.4: Support for the *fillchar* argument.

str.lower()

   Return a copy of the string converted to lowercase.

   For 8-bit strings, this method is locale-dependent.

str.lstrip([chars])

   Return a copy of the string with leading characters removed.  The
   *chars* argument is a string specifying the set of characters to be
   removed.  If omitted or ``None``, the *chars* argument defaults to
   removing whitespace.  The *chars* argument is not a prefix; rather,
   all combinations of its values are stripped:

   >>> '   spacious   '.lstrip()
   'spacious   '
   >>> 'www.example.com'.lstrip('cmowz.')
   'example.com'

   Changed in version 2.2.2: Support for the *chars* argument.

str.partition(sep)

   Split the string at the first occurrence of *sep*, and return a
   3-tuple containing the part before the separator, the separator
   itself, and the part after the separator.  If the separator is not
   found, return a 3-tuple containing the string itself, followed by
   two empty strings.

   New in version 2.5.

str.replace(old, new[, count])

   Return a copy of the string with all occurrences of substring *old*
   replaced by *new*.  If the optional argument *count* is given, only
   the first *count* occurrences are replaced.

str.rfind(sub[, start[, end]])

   Return the highest index in the string where substring *sub* is
   found, such that *sub* is contained within s[start,end].  Optional
   arguments *start* and *end* are interpreted as in slice notation.
   Return ``-1`` on failure.

str.rindex(sub[, start[, end]])

   Like ``rfind()`` but raises ``ValueError`` when the substring *sub*
   is not found.

str.rjust(width[, fillchar])

   Return the string right justified in a string of length *width*.
   Padding is done using the specified *fillchar* (default is a
   space). The original string is returned if *width* is less than
   ``len(s)``.

   Changed in version 2.4: Support for the *fillchar* argument.

str.rpartition(sep)

   Split the string at the last occurrence of *sep*, and return a
   3-tuple containing the part before the separator, the separator
   itself, and the part after the separator.  If the separator is not
   found, return a 3-tuple containing two empty strings, followed by
   the string itself.

   New in version 2.5.

str.rsplit([sep[, maxsplit]])

   Return a list of the words in the string, using *sep* as the
   delimiter string. If *maxsplit* is given, at most *maxsplit* splits
   are done, the *rightmost* ones.  If *sep* is not specified or
   ``None``, any whitespace string is a separator.  Except for
   splitting from the right, ``rsplit()`` behaves like ``split()``
   which is described in detail below.

   New in version 2.4.

str.rstrip([chars])

   Return a copy of the string with trailing characters removed.  The
   *chars* argument is a string specifying the set of characters to be
   removed.  If omitted or ``None``, the *chars* argument defaults to
   removing whitespace.  The *chars* argument is not a suffix; rather,
   all combinations of its values are stripped:

   >>> '   spacious   '.rstrip()
   '   spacious'
   >>> 'mississippi'.rstrip('ipz')
   'mississ'

   Changed in version 2.2.2: Support for the *chars* argument.

str.split([sep[, maxsplit]])

   Return a list of the words in the string, using *sep* as the
   delimiter string.  If *maxsplit* is given, at most *maxsplit*
   splits are done (thus, the list will have at most ``maxsplit+1``
   elements).  If *maxsplit* is not specified, then there is no limit
   on the number of splits (all possible splits are made).

   If *sep* is given, consecutive delimiters are not grouped together
   and are deemed to delimit empty strings (for example,
   ``'1,,2'.split(',')`` returns ``['1', '', '2']``).  The *sep*
   argument may consist of multiple characters (for example,
   ``'1<>2<>3'.split('<>')`` returns ``['1', '2', '3']``). Splitting
   an empty string with a specified separator returns ``['']``.

   If *sep* is not specified or is ``None``, a different splitting
   algorithm is applied: runs of consecutive whitespace are regarded
   as a single separator, and the result will contain no empty strings
   at the start or end if the string has leading or trailing
   whitespace.  Consequently, splitting an empty string or a string
   consisting of just whitespace with a ``None`` separator returns
   ``[]``.

   For example, ``' 1  2   3  '.split()`` returns ``['1', '2', '3']``,
   and ``'  1  2   3  '.split(None, 1)`` returns ``['1', '2   3  ']``.

str.splitlines([keepends])

   Return a list of the lines in the string, breaking at line
   boundaries.  Line breaks are not included in the resulting list
   unless *keepends* is given and true.

str.startswith(prefix[, start[, end]])

   Return ``True`` if string starts with the *prefix*, otherwise
   return ``False``. *prefix* can also be a tuple of prefixes to look
   for.  With optional *start*, test string beginning at that
   position.  With optional *end*, stop comparing string at that
   position.

   Changed in version 2.5: Accept tuples as *prefix*.

str.strip([chars])

   Return a copy of the string with the leading and trailing
   characters removed. The *chars* argument is a string specifying the
   set of characters to be removed. If omitted or ``None``, the
   *chars* argument defaults to removing whitespace. The *chars*
   argument is not a prefix or suffix; rather, all combinations of its
   values are stripped:

   >>> '   spacious   '.strip()
   'spacious'
   >>> 'www.example.com'.strip('cmowz.')
   'example'

   Changed in version 2.2.2: Support for the *chars* argument.

str.swapcase()

   Return a copy of the string with uppercase characters converted to
   lowercase and vice versa.

   For 8-bit strings, this method is locale-dependent.

str.title()

   Return a titlecased version of the string: words start with
   uppercase characters, all remaining cased characters are lowercase.

   For 8-bit strings, this method is locale-dependent.

str.translate(table[, deletechars])

   Return a copy of the string where all characters occurring in the
   optional argument *deletechars* are removed, and the remaining
   characters have been mapped through the given translation table,
   which must be a string of length 256.

   You can use the ``maketrans()`` helper function in the ``string``
   module to create a translation table. For string objects, set the
   *table* argument to ``None`` for translations that only delete
   characters:

   >>> 'read this short text'.translate(None, 'aeiou')
   'rd ths shrt txt'

   New in version 2.6: Support for a ``None`` *table* argument.

   For Unicode objects, the ``translate()`` method does not accept the
   optional *deletechars* argument.  Instead, it returns a copy of the
   *s* where all characters have been mapped through the given
   translation table which must be a mapping of Unicode ordinals to
   Unicode ordinals, Unicode strings or ``None``. Unmapped characters
   are left untouched. Characters mapped to ``None`` are deleted.
   Note, a more flexible approach is to create a custom character
   mapping codec using the ``codecs`` module (see ``encodings.cp1251``
   for an example).

str.upper()

   Return a copy of the string converted to uppercase.

   For 8-bit strings, this method is locale-dependent.

str.zfill(width)

   Return the numeric string left filled with zeros in a string of
   length *width*.  A sign prefix is handled correctly.  The original
   string is returned if *width* is less than ``len(s)``.

   New in version 2.2.2.

The following methods are present only on unicode objects:

unicode.isnumeric()

   Return ``True`` if there are only numeric characters in S,
   ``False`` otherwise. Numeric characters include digit characters,
   and all characters that have the Unicode numeric value property,
   e.g. U+2155, VULGAR FRACTION ONE FIFTH.

unicode.isdecimal()

   Return ``True`` if there are only decimal characters in S,
   ``False`` otherwise. Decimal characters include digit characters,
   and all characters that that can be used to form decimal-radix
   numbers, e.g. U+0660, ARABIC-INDIC DIGIT ZERO.
 
String literals
***************

String literals are described by the following lexical definitions:

   stringliteral   ::= [stringprefix](shortstring | longstring)
   stringprefix    ::= "r" | "u" | "ur" | "R" | "U" | "UR" | "Ur" | "uR"
   shortstring     ::= "'" shortstringitem* "'" | '"' shortstringitem* '"'
   longstring      ::= "'''" longstringitem* "'''"
                  | '"""' longstringitem* '"""'
   shortstringitem ::= shortstringchar | escapeseq
   longstringitem  ::= longstringchar | escapeseq
   shortstringchar ::= <any source character except "\" or newline or the quote>
   longstringchar  ::= <any source character except "\">
   escapeseq       ::= "\" <any ASCII character>

One syntactic restriction not indicated by these productions is that
whitespace is not allowed between the **stringprefix** and the rest of
the string literal. The source character set is defined by the
encoding declaration; it is ASCII if no encoding declaration is given
in the source file; see section *Encoding declarations*.

In plain English: String literals can be enclosed in matching single
quotes (``'``) or double quotes (``"``).  They can also be enclosed in
matching groups of three single or double quotes (these are generally
referred to as *triple-quoted strings*).  The backslash (``\``)
character is used to escape characters that otherwise have a special
meaning, such as newline, backslash itself, or the quote character.
String literals may optionally be prefixed with a letter ``'r'`` or
``'R'``; such strings are called *raw strings* and use different rules
for interpreting backslash escape sequences.  A prefix of ``'u'`` or
``'U'`` makes the string a Unicode string.  Unicode strings use the
Unicode character set as defined by the Unicode Consortium and ISO
10646.  Some additional escape sequences, described below, are
available in Unicode strings. The two prefix characters may be
combined; in this case, ``'u'`` must appear before ``'r'``.

In triple-quoted strings, unescaped newlines and quotes are allowed
(and are retained), except that three unescaped quotes in a row
terminate the string.  (A "quote" is the character used to open the
string, i.e. either ``'`` or ``"``.)

Unless an ``'r'`` or ``'R'`` prefix is present, escape sequences in
strings are interpreted according to rules similar to those used by
Standard C.  The recognized escape sequences are:

+-------------------+-----------------------------------+---------+
| Escape Sequence   | Meaning                           | Notes   |
+===================+===================================+=========+
| ``\newline``      | Ignored                           |         |
+-------------------+-----------------------------------+---------+
| ``\\``            | Backslash (``\``)                 |         |
+-------------------+-----------------------------------+---------+
| ``\'``            | Single quote (``'``)              |         |
+-------------------+-----------------------------------+---------+
| ``\"``            | Double quote (``"``)              |         |
+-------------------+-----------------------------------+---------+
| ``\a``            | ASCII Bell (BEL)                  |         |
+-------------------+-----------------------------------+---------+
| ``\b``            | ASCII Backspace (BS)              |         |
+-------------------+-----------------------------------+---------+
| ``\f``            | ASCII Formfeed (FF)               |         |
+-------------------+-----------------------------------+---------+
| ``\n``            | ASCII Linefeed (LF)               |         |
+-------------------+-----------------------------------+---------+
| ``\N{name}``      | Character named *name* in the     |         |
|                   | Unicode database (Unicode only)   |         |
+-------------------+-----------------------------------+---------+
| ``\r``            | ASCII Carriage Return (CR)        |         |
+-------------------+-----------------------------------+---------+
| ``\t``            | ASCII Horizontal Tab (TAB)        |         |
+-------------------+-----------------------------------+---------+
| ``\uxxxx``        | Character with 16-bit hex value   | (1)     |
|                   | *xxxx* (Unicode only)             |         |
+-------------------+-----------------------------------+---------+
| ``\Uxxxxxxxx``    | Character with 32-bit hex value   | (2)     |
|                   | *xxxxxxxx* (Unicode only)         |         |
+-------------------+-----------------------------------+---------+
| ``\v``            | ASCII Vertical Tab (VT)           |         |
+-------------------+-----------------------------------+---------+
| ``\ooo``          | Character with octal value *ooo*  | (3,5)   |
+-------------------+-----------------------------------+---------+
| ``\xhh``          | Character with hex value *hh*     | (4,5)   |
+-------------------+-----------------------------------+---------+

Notes:

1. Individual code units which form parts of a surrogate pair can be
   encoded using this escape sequence.

2. Any Unicode character can be encoded this way, but characters
   outside the Basic Multilingual Plane (BMP) will be encoded using a
   surrogate pair if Python is compiled to use 16-bit code units (the
   default).  Individual code units which form parts of a surrogate
   pair can be encoded using this escape sequence.

3. As in Standard C, up to three octal digits are accepted.

4. Unlike in Standard C, exactly two hex digits are required.

5. In a string literal, hexadecimal and octal escapes denote the byte
   with the given value; it is not necessary that the byte encodes a
   character in the source character set. In a Unicode literal, these
   escapes denote a Unicode character with the given value.

Unlike Standard C, all unrecognized escape sequences are left in the
string unchanged, i.e., *the backslash is left in the string*.  (This
behavior is useful when debugging: if an escape sequence is mistyped,
the resulting output is more easily recognized as broken.)  It is also
important to note that the escape sequences marked as "(Unicode only)"
in the table above fall into the category of unrecognized escapes for
non-Unicode string literals.

When an ``'r'`` or ``'R'`` prefix is present, a character following a
backslash is included in the string without change, and *all
backslashes are left in the string*.  For example, the string literal
``r"\n"`` consists of two characters: a backslash and a lowercase
``'n'``.  String quotes can be escaped with a backslash, but the
backslash remains in the string; for example, ``r"\""`` is a valid
string literal consisting of two characters: a backslash and a double
quote; ``r"\"`` is not a valid string literal (even a raw string
cannot end in an odd number of backslashes).  Specifically, *a raw
string cannot end in a single backslash* (since the backslash would
escape the following quote character).  Note also that a single
backslash followed by a newline is interpreted as those two characters
as part of the string, *not* as a line continuation.

When an ``'r'`` or ``'R'`` prefix is used in conjunction with a
``'u'`` or ``'U'`` prefix, then the ``\uXXXX`` and ``\UXXXXXXXX``
escape sequences are processed while  *all other backslashes are left
in the string*. For example, the string literal ``ur"\u0062\n"``
consists of three Unicode characters: 'LATIN SMALL LETTER B', 'REVERSE
SOLIDUS', and 'LATIN SMALL LETTER N'. Backslashes can be escaped with
a preceding backslash; however, both remain in the string.  As a
result, ``\uXXXX`` escape sequences are only recognized when there are
an odd number of backslashes.
 
Subscriptions
*************

A subscription selects an item of a sequence (string, tuple or list)
or mapping (dictionary) object:

   subscription ::= primary "[" expression_list "]"

The primary must evaluate to an object of a sequence or mapping type.

If the primary is a mapping, the expression list must evaluate to an
object whose value is one of the keys of the mapping, and the
subscription selects the value in the mapping that corresponds to that
key.  (The expression list is a tuple except if it has exactly one
item.)

If the primary is a sequence, the expression (list) must evaluate to a
plain integer.  If this value is negative, the length of the sequence
is added to it (so that, e.g., ``x[-1]`` selects the last item of
``x``.)  The resulting value must be a nonnegative integer less than
the number of items in the sequence, and the subscription selects the
item whose index is that value (counting from zero).

A string's items are characters.  A character is not a separate data
type but a string of exactly one character.
 
Truth Value Testing
*******************

Any object can be tested for truth value, for use in an ``if`` or
``while`` condition or as operand of the Boolean operations below. The
following values are considered false:

* ``None``

* ``False``

* zero of any numeric type, for example, ``0``, ``0L``, ``0.0``,
  ``0j``.

* any empty sequence, for example, ``''``, ``()``, ``[]``.

* any empty mapping, for example, ``{}``.

* instances of user-defined classes, if the class defines a
  ``__nonzero__()`` or ``__len__()`` method, when that method returns
  the integer zero or ``bool`` value ``False``. [1]

All other values are considered true --- so objects of many types are
always true.

Operations and built-in functions that have a Boolean result always
return ``0`` or ``False`` for false and ``1`` or ``True`` for true,
unless otherwise stated. (Important exception: the Boolean operations
``or`` and ``and`` always return one of their operands.)
 
The ``try`` statement
*********************

The ``try`` statement specifies exception handlers and/or cleanup code
for a group of statements:

   try_stmt  ::= try1_stmt | try2_stmt
   try1_stmt ::= "try" ":" suite
                 ("except" [expression [("as" | ",") target]] ":" suite)+
                 ["else" ":" suite]
                 ["finally" ":" suite]
   try2_stmt ::= "try" ":" suite
                 "finally" ":" suite

Changed in version 2.5: In previous versions of Python,
``try``...``except``...``finally`` did not work. ``try``...``except``
had to be nested in ``try``...``finally``.

The ``except`` clause(s) specify one or more exception handlers. When
no exception occurs in the ``try`` clause, no exception handler is
executed. When an exception occurs in the ``try`` suite, a search for
an exception handler is started.  This search inspects the except
clauses in turn until one is found that matches the exception.  An
expression-less except clause, if present, must be last; it matches
any exception.  For an except clause with an expression, that
expression is evaluated, and the clause matches the exception if the
resulting object is "compatible" with the exception.  An object is
compatible with an exception if it is the class or a base class of the
exception object, a tuple containing an item compatible with the
exception, or, in the (deprecated) case of string exceptions, is the
raised string itself (note that the object identities must match, i.e.
it must be the same string object, not just a string with the same
value).

If no except clause matches the exception, the search for an exception
handler continues in the surrounding code and on the invocation stack.
[1]

If the evaluation of an expression in the header of an except clause
raises an exception, the original search for a handler is canceled and
a search starts for the new exception in the surrounding code and on
the call stack (it is treated as if the entire ``try`` statement
raised the exception).

When a matching except clause is found, the exception is assigned to
the target specified in that except clause, if present, and the except
clause's suite is executed.  All except clauses must have an
executable block.  When the end of this block is reached, execution
continues normally after the entire try statement.  (This means that
if two nested handlers exist for the same exception, and the exception
occurs in the try clause of the inner handler, the outer handler will
not handle the exception.)

Before an except clause's suite is executed, details about the
exception are assigned to three variables in the ``sys`` module:
``sys.exc_type`` receives the object identifying the exception;
``sys.exc_value`` receives the exception's parameter;
``sys.exc_traceback`` receives a traceback object (see section *The
standard type hierarchy*) identifying the point in the program where
the exception occurred. These details are also available through the
``sys.exc_info()`` function, which returns a tuple ``(exc_type,
exc_value, exc_traceback)``.  Use of the corresponding variables is
deprecated in favor of this function, since their use is unsafe in a
threaded program.  As of Python 1.5, the variables are restored to
their previous values (before the call) when returning from a function
that handled an exception.

The optional ``else`` clause is executed if and when control flows off
the end of the ``try`` clause. [2] Exceptions in the ``else`` clause
are not handled by the preceding ``except`` clauses.

If ``finally`` is present, it specifies a 'cleanup' handler.  The
``try`` clause is executed, including any ``except`` and ``else``
clauses.  If an exception occurs in any of the clauses and is not
handled, the exception is temporarily saved. The ``finally`` clause is
executed.  If there is a saved exception, it is re-raised at the end
of the ``finally`` clause. If the ``finally`` clause raises another
exception or executes a ``return`` or ``break`` statement, the saved
exception is lost.  The exception information is not available to the
program during execution of the ``finally`` clause.

When a ``return``, ``break`` or ``continue`` statement is executed in
the ``try`` suite of a ``try``...``finally`` statement, the
``finally`` clause is also executed 'on the way out.' A ``continue``
statement is illegal in the ``finally`` clause. (The reason is a
problem with the current implementation --- this restriction may be
lifted in the future).

Additional information on exceptions can be found in section
*Exceptions*, and information on using the ``raise`` statement to
generate exceptions may be found in section *The raise statement*.
 
The standard type hierarchy
***************************

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.).

Some of the type descriptions below contain a paragraph listing
'special attributes.'  These are attributes that provide access to the
implementation and are not intended for general use.  Their definition
may change in the future.

None
   This type has a single value.  There is a single object with this
   value. This object is accessed through the built-in name ``None``.
   It is used to signify the absence of a value in many situations,
   e.g., it is returned from functions that don't explicitly return
   anything. Its truth value is false.

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``
   These are created by numeric literals and returned as results by
   arithmetic operators and arithmetic built-in functions.  Numeric
   objects are immutable; once created their value never changes.
   Python numbers are of course strongly related to mathematical
   numbers, but subject to the limitations of numerical representation
   in computers.

   Python distinguishes between integers, floating point numbers, and
   complex numbers:

   ``numbers.Integral``
      These represent elements from the mathematical set of integers
      (positive and negative).

      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
         These represent numbers in an unlimited range, subject to
         available (virtual) memory only.  For the purpose of shift
         and mask operations, a binary representation is assumed, and
         negative numbers are represented in a variant of 2's
         complement which gives the illusion of an infinite string of
         sign bits extending to the left.

      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``)
      These represent machine-level double precision floating point
      numbers. You are at the mercy of the underlying machine
      architecture (and C or Java implementation) for the accepted
      range and handling of overflow. Python does not support single-
      precision floating point numbers; the savings in processor and
      memory usage that are usually the reason for using these is
      dwarfed by the overhead of using objects in Python, so there is
      no reason to complicate the language with two kinds of floating
      point numbers.

   ``numbers.Complex``
      These represent complex numbers as a pair of machine-level
      double precision floating point numbers.  The same caveats apply
      as for floating point numbers. The real and imaginary parts of a
      complex number ``z`` can be retrieved through the read-only
      attributes ``z.real`` and ``z.imag``.

Sequences
   These represent finite ordered sets indexed by non-negative
   numbers. The built-in function ``len()`` returns the number of
   items of a sequence. When the length of a sequence is *n*, the
   index set contains the numbers 0, 1, ..., *n*-1.  Item *i* of
   sequence *a* is selected by ``a[i]``.

   Sequences also support slicing: ``a[i:j]`` selects all items with
   index *k* such that *i* ``<=`` *k* ``<`` *j*.  When used as an
   expression, a slice is a sequence of the same type.  This implies
   that the index set is renumbered so that it starts at 0.

   Some sequences also support "extended slicing" with a third "step"
   parameter: ``a[i:j:k]`` selects all items of *a* with index *x*
   where ``x = i + n*k``, *n* ``>=`` ``0`` and *i* ``<=`` *x* ``<``
   *j*.

   Sequences are distinguished according to their mutability:

   Immutable sequences
      An object of an immutable sequence type cannot change once it is
      created.  (If the object contains references to other objects,
      these other objects may be mutable and may be changed; however,
      the collection of objects directly referenced by an immutable
      object cannot change.)

      The following types are immutable sequences:

      Strings
         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()``.

      Tuples
         The items of a tuple are arbitrary Python objects. Tuples of
         two or more items are formed by comma-separated lists of
         expressions.  A tuple of one item (a 'singleton') can be
         formed by affixing a comma to an expression (an expression by
         itself does not create a tuple, since parentheses must be
         usable for grouping of expressions).  An empty tuple can be
         formed by an empty pair of parentheses.

   Mutable sequences
      Mutable sequences can be changed after they are created.  The
      subscription and slicing notations can be used as the target of
      assignment and ``del`` (delete) statements.

      There is currently a single intrinsic mutable sequence type:

      Lists
         The items of a list are arbitrary Python objects.  Lists are
         formed by placing a comma-separated list of expressions in
         square brackets. (Note that there are no special cases needed
         to form lists of length 0 or 1.)

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

Set types
   These represent unordered, finite sets of unique, immutable
   objects. As such, they cannot be indexed by any subscript. However,
   they can be iterated over, and the built-in function ``len()``
   returns the number of items in a set. Common uses for sets are fast
   membership testing, removing duplicates from a sequence, and
   computing mathematical operations such as intersection, union,
   difference, and symmetric difference.

   For set elements, the same immutability rules apply as for
   dictionary keys. Note that numeric types obey the normal rules for
   numeric comparison: if two numbers compare equal (e.g., ``1`` and
   ``1.0``), only one of them can be contained in a set.

   There are currently two intrinsic set types:

   Sets
      These represent a mutable set. They are created by the built-in
      ``set()`` constructor and can be modified afterwards by several
      methods, such as ``add()``.

   Frozen sets
      These represent an immutable set.  They are created by the
      built-in ``frozenset()`` constructor.  As a frozenset is
      immutable and *hashable*, it can be used again as an element of
      another set, or as a dictionary key.

Mappings
   These represent finite sets of objects indexed by arbitrary index
   sets. The subscript notation ``a[k]`` selects the item indexed by
   ``k`` from the mapping ``a``; this can be used in expressions and
   as the target of assignments or ``del`` statements. The built-in
   function ``len()`` returns the number of items in a mapping.

   There is currently a single intrinsic mapping type:

   Dictionaries
      These represent finite sets of objects indexed by nearly
      arbitrary values.  The only types of values not acceptable as
      keys are values containing lists or dictionaries or other
      mutable types that are compared by value rather than by object
      identity, the reason being that the efficient implementation of
      dictionaries requires a key's hash value to remain constant.
      Numeric types used for keys obey the normal rules for numeric
      comparison: if two numbers compare equal (e.g., ``1`` and
      ``1.0``) then they can be used interchangeably to index the same
      dictionary entry.

      Dictionaries are mutable; they can be created by the ``{...}``
      notation (see section *Dictionary displays*).

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

Callable types
   These are the types to which the function call operation (see
   section *Calls*) can be applied:

   User-defined functions
      A user-defined function object is created by a function
      definition (see section *Function definitions*).  It should be
      called with an argument list containing the same number of items
      as the function's formal parameter list.

      Special attributes:

      +-------------------------+---------------------------------+-------------+
      | Attribute               | Meaning                         |             |
      +=========================+=================================+=============+
      | ``func_doc``            | The function's documentation    | Writable    |
      |                         | string, or ``None`` if          |             |
      |                         | unavailable                     |             |
      +-------------------------+---------------------------------+-------------+
      | ``__doc__``             | Another way of spelling         | Writable    |
      |                         | ``func_doc``                    |             |
      +-------------------------+---------------------------------+-------------+
      | ``func_name``           | The function's name             | Writable    |
      +-------------------------+---------------------------------+-------------+
      | ``__name__``            | Another way of spelling         | Writable    |
      |                         | ``func_name``                   |             |
      +-------------------------+---------------------------------+-------------+
      | ``__module__``          | The name of the module the      | Writable    |
      |                         | function was defined in, or     |             |
      |                         | ``None`` if unavailable.        |             |
      +-------------------------+---------------------------------+-------------+
      | ``func_defaults``       | A tuple containing default      | Writable    |
      |                         | argument values for those       |             |
      |                         | arguments that have defaults,   |             |
      |                         | or ``None`` if no arguments     |             |
      |                         | have a default value            |             |
      +-------------------------+---------------------------------+-------------+
      | ``func_code``           | The code object representing    | Writable    |
      |                         | the compiled function body.     |             |
      +-------------------------+---------------------------------+-------------+
      | ``func_globals``        | A reference to the dictionary   | Read-only   |
      |                         | that holds the function's       |             |
      |                         | global variables --- the global |             |
      |                         | namespace of the module in      |             |
      |                         | which the function was defined. |             |
      +-------------------------+---------------------------------+-------------+
      | ``func_dict``           | The namespace supporting        | Writable    |
      |                         | arbitrary function attributes.  |             |
      +-------------------------+---------------------------------+-------------+
      | ``func_closure``        | ``None`` or a tuple of cells    | Read-only   |
      |                         | that contain bindings for the   |             |
      |                         | function's free variables.      |             |
      +-------------------------+---------------------------------+-------------+

      Most of the attributes labelled "Writable" check the type of the
      assigned value.

      Changed in version 2.4: ``func_name`` is now writable.

      Function objects also support getting and setting arbitrary
      attributes, which can be used, for example, to attach metadata
      to functions.  Regular attribute dot-notation is used to get and
      set such attributes. *Note that the current implementation only
      supports function attributes on user-defined functions. Function
      attributes on built-in functions may be supported in the
      future.*

      Additional information about a function's definition can be
      retrieved from its code object; see the description of internal
      types below.

   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.

      Changed in version 2.2: ``im_self`` used to refer to the class
      that defined the method.

      Changed in version 2.6: For 3.0 forward-compatibility,
      ``im_func`` is also available as ``__func__``, and ``im_self``
      as ``__self__``.

      Methods also support accessing (but not setting) the arbitrary
      function attributes on the underlying function object.

      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 (the same as the ``im_class``
      attribute), 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.

   Generator functions
      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.

   Built-in functions
      A built-in function object is a wrapper around a C function.
      Examples of built-in functions are ``len()`` and ``math.sin()``
      (``math`` is a standard built-in module). The number and type of
      the arguments are determined by the C function. Special read-
      only attributes: ``__doc__`` is the function's documentation
      string, or ``None`` if unavailable; ``__name__`` is the
      function's name; ``__self__`` is set to ``None`` (but see the
      next item); ``__module__`` is the name of the module the
      function was defined in or ``None`` if unavailable.

   Built-in methods
      This is really a different disguise of a built-in function, this
      time containing an object passed to the C function as an
      implicit extra argument.  An example of a built-in method is
      ``alist.append()``, assuming *alist* is a list object. In this
      case, the special read-only attribute ``__self__`` is set to the
      object denoted by *list*.

   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.

   Class instances
      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)``.

Modules
   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).

   Attribute assignment updates the module's namespace dictionary,
   e.g., ``m.x = 1`` is equivalent to ``m.__dict__["x"] = 1``.

   Special read-only attribute: ``__dict__`` is the module's namespace
   as a dictionary object.

   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.

Classes
   Both class types (new-style classes) and class objects (old-
   style/classic classes) are typically created by class definitions
   (see section *Class definitions*).  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 http://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_class`` and ``im_self`` attributes are
   both ``C``.  When it would yield a static method object, it is
   transformed into the object wrapped by the static method object.
   See section *Implementing Descriptors* 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).

   Class attribute assignments update the class's dictionary, never
   the dictionary of a base class.

   A class object can be called (see above) to yield a class instance
   (see below).

   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.

Class instances
   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 *Implementing Descriptors* 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.

   Attribute assignments and deletions update the instance's
   dictionary, never a class's dictionary.  If the class has a
   ``__setattr__()`` or ``__delattr__()`` method, this is called
   instead of updating the instance dictionary directly.

   Class instances can pretend to be numbers, sequences, or mappings
   if they have methods with certain special names.  See section
   *Special method names*.

   Special attributes: ``__dict__`` is the attribute dictionary;
   ``__class__`` is the instance's class.

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.

Internal types
   A few types used internally by the interpreter are exposed to the
   user. Their definitions may change with future versions of the
   interpreter, but they are mentioned here for completeness.

   Code objects
      Code objects represent *byte-compiled* executable Python code,
      or *bytecode*. The difference between a code object and a
      function object is that the function object contains an explicit
      reference to the function's globals (the module in which it was
      defined), while a code object contains no context; also the
      default argument values are stored in the function object, not
      in the code object (because they represent values calculated at
      run-time).  Unlike function objects, code objects are immutable
      and contain no references (directly or indirectly) to mutable
      objects.

      Special read-only attributes: ``co_name`` gives the function
      name; ``co_argcount`` is the number of positional arguments
      (including arguments with default values); ``co_nlocals`` is the
      number of local variables used by the function (including
      arguments); ``co_varnames`` is a tuple containing the names of
      the local variables (starting with the argument names);
      ``co_cellvars`` is a tuple containing the names of local
      variables that are referenced by nested functions;
      ``co_freevars`` is a tuple containing the names of free
      variables; ``co_code`` is a string representing the sequence of
      bytecode instructions; ``co_consts`` is a tuple containing the
      literals used by the bytecode; ``co_names`` is a tuple
      containing the names used by the bytecode; ``co_filename`` is
      the filename from which the code was compiled;
      ``co_firstlineno`` is the first line number of the function;
      ``co_lnotab`` is a string encoding the mapping from bytecode
      offsets to line numbers (for details see the source code of the
      interpreter); ``co_stacksize`` is the required stack size
      (including local variables); ``co_flags`` is an integer encoding
      a number of flags for the interpreter.

      The following flag bits are defined for ``co_flags``: bit
      ``0x04`` is set if the function uses the ``*arguments`` syntax
      to accept an arbitrary number of positional arguments; bit
      ``0x08`` is set if the function uses the ``**keywords`` syntax
      to accept arbitrary keyword arguments; bit ``0x20`` is set if
      the function is a generator.

      Future feature declarations (``from __future__ import
      division``) also use bits in ``co_flags`` to indicate whether a
      code object was compiled with a particular feature enabled: bit
      ``0x2000`` is set if the function was compiled with future
      division enabled; bits ``0x10`` and ``0x1000`` were used in
      earlier versions of Python.

      Other bits in ``co_flags`` are reserved for internal use.

      If a code object represents a function, the first item in
      ``co_consts`` is the documentation string of the function, or
      ``None`` if undefined.

   Frame objects
      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.

   Traceback objects
      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.

   Slice objects
      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.

      Special read-only attributes: ``start`` is the lower bound;
      ``stop`` is the upper bound; ``step`` is the step value; each is
      ``None`` if omitted. These attributes can have any type.

      Slice objects support one method:

      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.

         New in version 2.3.

   Static method objects
      Static method objects provide a way of defeating the
      transformation of function objects to method objects described
      above. A static method object is a wrapper around any other
      object, usually a user-defined method object. When a static
      method object is retrieved from a class or a class instance, the
      object actually returned is the wrapped object, which is not
      subject to any further transformation. Static method objects are
      not themselves callable, although the objects they wrap usually
      are. Static method objects are created by the built-in
      ``staticmethod()`` constructor.

   Class method objects
      A class method object, like a static method object, is a wrapper
      around another object that alters the way in which that object
      is retrieved from classes and class instances. The behaviour of
      class method objects upon such retrieval is described above,
      under "User-defined methods". Class method objects are created
      by the built-in ``classmethod()`` constructor.
 
Functions
*********

Function objects are created by function definitions.  The only
operation on a function object is to call it: ``func(argument-list)``.

There are really two flavors of function objects: built-in functions
and user-defined functions.  Both support the same operation (to call
the function), but the implementation is different, hence the
different object types.

See *Function definitions* for more information.
 
Mapping Types --- ``dict``
**************************

A *mapping* object maps *hashable* values to arbitrary objects.
Mappings are mutable objects.  There is currently only one standard
mapping type, the *dictionary*.  (For other containers see the built
in ``list``, ``set``, and ``tuple`` classes, and the ``collections``
module.)

A dictionary's keys are *almost* arbitrary values.  Values that are
not *hashable*, that is, values containing lists, dictionaries or
other mutable types (that are compared by value rather than by object
identity) may not be used as keys.  Numeric types used for keys obey
the normal rules for numeric comparison: if two numbers compare equal
(such as ``1`` and ``1.0``) then they can be used interchangeably to
index the same dictionary entry.  (Note however, that since computers
store floating-point numbers as approximations it is usually unwise to
use them as dictionary keys.)

Dictionaries can be created by placing a comma-separated list of
``key: value`` pairs within braces, for example: ``{'jack': 4098,
'sjoerd': 4127}`` or ``{4098: 'jack', 4127: 'sjoerd'}``, or by the
``dict`` constructor.

class dict([arg])

   Return a new dictionary initialized from an optional positional
   argument or from a set of keyword arguments. If no arguments are
   given, return a new empty dictionary. If the positional argument
   *arg* is a mapping object, return a dictionary mapping the same
   keys to the same values as does the mapping object. Otherwise the
   positional argument must be a sequence, a container that supports
   iteration, or an iterator object.  The elements of the argument
   must each also be of one of those kinds, and each must in turn
   contain exactly two objects. The first is used as a key in the new
   dictionary, and the second as the key's value.  If a given key is
   seen more than once, the last value associated with it is retained
   in the new dictionary.

   If keyword arguments are given, the keywords themselves with their
   associated values are added as items to the dictionary. If a key is
   specified both in the positional argument and as a keyword
   argument, the value associated with the keyword is retained in the
   dictionary. For example, these all return a dictionary equal to
   ``{"one": 2, "two": 3}``:

   * ``dict(one=2, two=3)``

   * ``dict({'one': 2, 'two': 3})``

   * ``dict(zip(('one', 'two'), (2, 3)))``

   * ``dict([['two', 3], ['one', 2]])``

   The first example only works for keys that are valid Python
   identifiers; the others work with any valid keys.

   New in version 2.2.

   Changed in version 2.3: Support for building a dictionary from
   keyword arguments added.

   These are the operations that dictionaries support (and therefore,
   custom mapping types should support too):

   len(d)

      Return the number of items in the dictionary *d*.

   d[key]

      Return the item of *d* with key *key*.  Raises a ``KeyError`` if
      *key* is not in the map.

      New in version 2.5: If a subclass of dict defines a method
      ``__missing__()``, if the key *key* is not present, the
      ``d[key]`` operation calls that method with the key *key* as
      argument.  The ``d[key]`` operation then returns or raises
      whatever is returned or raised by the ``__missing__(key)`` call
      if the key is not present. No other operations or methods invoke
      ``__missing__()``. If ``__missing__()`` is not defined,
      ``KeyError`` is raised.  ``__missing__()`` must be a method; it
      cannot be an instance variable. For an example, see
      ``collections.defaultdict``.

   d[key] = value

      Set ``d[key]`` to *value*.

   del d[key]

      Remove ``d[key]`` from *d*.  Raises a ``KeyError`` if *key* is
      not in the map.

   key in d

      Return ``True`` if *d* has a key *key*, else ``False``.

      New in version 2.2.

   key not in d

      Equivalent to ``not key in d``.

      New in version 2.2.

   clear()

      Remove all items from the dictionary.

   copy()

      Return a shallow copy of the dictionary.

   fromkeys(seq[, value])

      Create a new dictionary with keys from *seq* and values set to
      *value*.

      ``fromkeys()`` is a class method that returns a new dictionary.
      *value* defaults to ``None``.

      New in version 2.3.

   get(key[, default])

      Return the value for *key* if *key* is in the dictionary, else
      *default*. If *default* is not given, it defaults to ``None``,
      so that this method never raises a ``KeyError``.

   has_key(key)

      Test for the presence of *key* in the dictionary.  ``has_key()``
      is deprecated in favor of ``key in d``.

   items()

      Return a copy of the dictionary's list of ``(key, value)``
      pairs.

      Note: Keys and values are listed in an arbitrary order which is non-
        random, varies across Python implementations, and depends on
        the dictionary's history of insertions and deletions. If
        ``items()``, ``keys()``, ``values()``, ``iteritems()``,
        ``iterkeys()``, and ``itervalues()`` are called with no
        intervening modifications to the dictionary, the lists will
        directly correspond.  This allows the creation of ``(value,
        key)`` pairs using ``zip()``: ``pairs = zip(d.values(),
        d.keys())``.  The same relationship holds for the
        ``iterkeys()`` and ``itervalues()`` methods: ``pairs =
        zip(d.itervalues(), d.iterkeys())`` provides the same value
        for ``pairs``. Another way to create the same list is ``pairs
        = [(v, k) for (k, v) in d.iteritems()]``.

   iteritems()

      Return an iterator over the dictionary's ``(key, value)`` pairs.
      See the note for ``dict.items()``.

      New in version 2.2.

   iterkeys()

      Return an iterator over the dictionary's keys.  See the note for
      ``dict.items()``.

      New in version 2.2.

   itervalues()

      Return an iterator over the dictionary's values.  See the note
      for ``dict.items()``.

      New in version 2.2.

   keys()

      Return a copy of the dictionary's list of keys.  See the note
      for ``dict.items()``.

   pop(key[, default])

      If *key* is in the dictionary, remove it and return its value,
      else return *default*.  If *default* is not given and *key* is
      not in the dictionary, a ``KeyError`` is raised.

      New in version 2.3.

   popitem()

      Remove and return an arbitrary ``(key, value)`` pair from the
      dictionary.

      ``popitem()`` is useful to destructively iterate over a
      dictionary, as often used in set algorithms.  If the dictionary
      is empty, calling ``popitem()`` raises a ``KeyError``.

   setdefault(key[, default])

      If *key* is in the dictionary, return its value.  If not, insert
      *key* with a value of *default* and return *default*.  *default*
      defaults to ``None``.

   update([other])

      Update the dictionary with the key/value pairs from *other*,
      overwriting existing keys.  Return ``None``.

      ``update()`` accepts either another dictionary object or an
      iterable of key/value pairs (as a tuple or other iterable of
      length two).  If keyword arguments are specified, the dictionary
      is then is updated with those key/value pairs: ``d.update(red=1,
      blue=2)``.

      Changed in version 2.4: Allowed the argument to be an iterable
      of key/value pairs and allowed keyword arguments.

   values()

      Return a copy of the dictionary's list of values.  See the note
      for ``dict.items()``.
 
Methods
*******

Methods are functions that are called using the attribute notation.
There are two flavors: built-in methods (such as ``append()`` on
lists) and class instance methods.  Built-in methods are described
with the types that support them.

The implementation adds two special read-only attributes to class
instance methods: ``m.im_self`` is the object on which the method
operates, and ``m.im_func`` is the function implementing the method.
Calling ``m(arg-1, arg-2, ..., arg-n)`` is completely equivalent to
calling ``m.im_func(m.im_self, arg-1, arg-2, ..., arg-n)``.

Class instance methods are either *bound* or *unbound*, referring to
whether the method was accessed through an instance or a class,
respectively.  When a method is unbound, its ``im_self`` attribute
will be ``None`` and if called, an explicit ``self`` object must be
passed as the first argument.  In this case, ``self`` must be an
instance of the unbound method's class (or a subclass of that class),
otherwise a ``TypeError`` is raised.

Like function objects, methods objects support getting arbitrary
attributes. However, since method attributes are actually stored on
the underlying function object (``meth.im_func``), setting method
attributes on either bound or unbound methods is disallowed.
Attempting to set a method attribute results in a ``TypeError`` being
raised.  In order to set a method attribute, you need to explicitly
set it on the underlying function object:

   class C:
       def method(self):
           pass

   c = C()
   c.method.im_func.whoami = 'my name is c'

See *The standard type hierarchy* for more information.
 
Modules
*******

The only special operation on a module is attribute access:
``m.name``, where *m* is a module and *name* accesses a name defined
in *m*'s symbol table. Module attributes can be assigned to.  (Note
that the ``import`` statement is not, strictly speaking, an operation
on a module object; ``import foo`` does not require a module object
named *foo* to exist, rather it requires an (external) *definition*
for a module named *foo* somewhere.)

A special member of every module is ``__dict__``. This is the
dictionary containing the module's symbol table. Modifying this
dictionary will actually change the module's symbol table, but direct
assignment to the ``__dict__`` attribute is not possible (you can
write ``m.__dict__['a'] = 1``, which defines ``m.a`` to be ``1``, but
you can't write ``m.__dict__ = {}``).  Modifying ``__dict__`` directly
is not recommended.

Modules built into the interpreter are written like this: ``<module
'sys' (built-in)>``.  If loaded from a file, they are written as
``<module 'os' from '/usr/local/lib/pythonX.Y/os.pyc'>``.
 
Sequence Types --- ``str``, ``unicode``, ``list``, ``tuple``, ``buffer``, ``xrange``
************************************************************************************

There are six sequence types: strings, Unicode strings, lists, tuples,
buffers, and xrange objects. (For other containers see the built in
``dict``, ``list``, ``set``, and ``tuple`` classes, and the
``collections`` module.)

String literals are written in single or double quotes: ``'xyzzy'``,
``"frobozz"``.  See *String literals* for more about string literals.
Unicode strings are much like strings, but are specified in the syntax
using a preceding ``'u'`` character: ``u'abc'``, ``u"def"``. In
addition to the functionality described here, there are also string-
specific methods described in the *String Methods* section. Lists are
constructed with square brackets, separating items with commas: ``[a,
b, c]``. Tuples are constructed by the comma operator (not within
square brackets), with or without enclosing parentheses, but an empty
tuple must have the enclosing parentheses, such as ``a, b, c`` or
``()``.  A single item tuple must have a trailing comma, such as
``(d,)``.

Buffer objects are not directly supported by Python syntax, but can be
created by calling the builtin function ``buffer()``.  They don't
support concatenation or repetition.

Objects of type xrange are similar to buffers in that there is no
specific syntax to create them, but they are created using the
``xrange()`` function.  They don't support slicing, concatenation or
repetition, and using ``in``, ``not in``, ``min()`` or ``max()`` on
them is inefficient.

Most sequence types support the following operations.  The ``in`` and
``not in`` operations have the same priorities as the comparison
operations.  The ``+`` and ``*`` operations have the same priority as
the corresponding numeric operations. [3] Additional methods are
provided for *Mutable Sequence Types*.

This table lists the sequence operations sorted in ascending priority
(operations in the same box have the same priority).  In the table,
*s* and *t* are sequences of the same type; *n*, *i* and *j* are
integers:

+--------------------+----------------------------------+------------+
| Operation          | Result                           | Notes      |
+====================+==================================+============+
| ``x in s``         | ``True`` if an item of *s* is    | (1)        |
|                    | equal to *x*, else ``False``     |            |
+--------------------+----------------------------------+------------+
| ``x not in s``     | ``False`` if an item of *s* is   | (1)        |
|                    | equal to *x*, else ``True``      |            |
+--------------------+----------------------------------+------------+
| ``s + t``          | the concatenation of *s* and *t* | (6)        |
+--------------------+----------------------------------+------------+
| ``s * n, n * s``   | *n* shallow copies of *s*        | (2)        |
|                    | concatenated                     |            |
+--------------------+----------------------------------+------------+
| ``s[i]``           | *i*'th item of *s*, origin 0     | (3)        |
+--------------------+----------------------------------+------------+
| ``s[i:j]``         | slice of *s* from *i* to *j*     | (3)(4)     |
+--------------------+----------------------------------+------------+
| ``s[i:j:k]``       | slice of *s* from *i* to *j*     | (3)(5)     |
|                    | with step *k*                    |            |
+--------------------+----------------------------------+------------+
| ``len(s)``         | length of *s*                    |            |
+--------------------+----------------------------------+------------+
| ``min(s)``         | smallest item of *s*             |            |
+--------------------+----------------------------------+------------+
| ``max(s)``         | largest item of *s*              |            |
+--------------------+----------------------------------+------------+

Sequence types also support comparisons. In particular, tuples and
lists are compared lexicographically by comparing corresponding
elements. This means that to compare equal, every element must compare
equal and the two sequences must be of the same type and have the same
length. (For full details see *Comparisons* in the language
reference.)

Notes:

1. When *s* is a string or Unicode string object the ``in`` and ``not
   in`` operations act like a substring test.  In Python versions
   before 2.3, *x* had to be a string of length 1. In Python 2.3 and
   beyond, *x* may be a string of any length.

2. Values of *n* less than ``0`` are treated as ``0`` (which yields an
   empty sequence of the same type as *s*).  Note also that the copies
   are shallow; nested structures are not copied.  This often haunts
   new Python programmers; consider:

   >>> lists = [[]] * 3
   >>> lists
   [[], [], []]
   >>> lists[0].append(3)
   >>> lists
   [[3], [3], [3]]

   What has happened is that ``[[]]`` is a one-element list containing
   an empty list, so all three elements of ``[[]] * 3`` are (pointers
   to) this single empty list.  Modifying any of the elements of
   ``lists`` modifies this single list. You can create a list of
   different lists this way:

   >>> lists = [[] for i in range(3)]
   >>> lists[0].append(3)
   >>> lists[1].append(5)
   >>> lists[2].append(7)
   >>> lists
   [[3], [5], [7]]

3. If *i* or *j* is negative, the index is relative to the end of the
   string: ``len(s) + i`` or ``len(s) + j`` is substituted.  But note
   that ``-0`` is still ``0``.

4. The slice of *s* from *i* to *j* is defined as the sequence of
   items with index *k* such that ``i <= k < j``.  If *i* or *j* is
   greater than ``len(s)``, use ``len(s)``.  If *i* is omitted or
   ``None``, use ``0``.  If *j* is omitted or ``None``, use
   ``len(s)``.  If *i* is greater than or equal to *j*, the slice is
   empty.

5. The slice of *s* from *i* to *j* with step *k* is defined as the
   sequence of items with index  ``x = i + n*k`` such that ``0 <= n <
   (j-i)/k``.  In other words, the indices are ``i``, ``i+k``,
   ``i+2*k``, ``i+3*k`` and so on, stopping when *j* is reached (but
   never including *j*).  If *i* or *j* is greater than ``len(s)``,
   use ``len(s)``.  If *i* or *j* are omitted or ``None``, they become
   "end" values (which end depends on the sign of *k*).  Note, *k*
   cannot be zero. If *k* is ``None``, it is treated like ``1``.

6. If *s* and *t* are both strings, some Python implementations such
   as CPython can usually perform an in-place optimization for
   assignments of the form ``s=s+t`` or ``s+=t``.  When applicable,
   this optimization makes quadratic run-time much less likely.  This
   optimization is both version and implementation dependent. For
   performance sensitive code, it is preferable to use the
   ``str.join()`` method which assures consistent linear concatenation
   performance across versions and implementations.

   Changed in version 2.4: Formerly, string concatenation never
   occurred in-place.


String Methods
==============

Below are listed the string methods which both 8-bit strings and
Unicode objects support. Note that none of these methods take keyword
arguments.

In addition, Python's strings support the sequence type methods
described in the *Sequence Types --- str, unicode, list, tuple,
buffer, xrange* section. To output formatted strings use template
strings or the ``%`` operator described in the *String Formatting
Operations* section. Also, see the ``re`` module for string functions
based on regular expressions.

str.capitalize()

   Return a copy of the string with only its first character
   capitalized.

   For 8-bit strings, this method is locale-dependent.

str.center(width[, fillchar])

   Return centered in a string of length *width*. Padding is done
   using the specified *fillchar* (default is a space).

   Changed in version 2.4: Support for the *fillchar* argument.

str.count(sub[, start[, end]])

   Return the number of occurrences of substring *sub* in the range
   [*start*, *end*].  Optional arguments *start* and *end* are
   interpreted as in slice notation.

str.decode([encoding[, errors]])

   Decodes the string using the codec registered for *encoding*.
   *encoding* defaults to the default string encoding.  *errors* may
   be given to set a different error handling scheme.  The default is
   ``'strict'``, meaning that encoding errors raise ``UnicodeError``.
   Other possible values are ``'ignore'``, ``'replace'`` and any other
   name registered via ``codecs.register_error()``, see section *Codec
   Base Classes*.

   New in version 2.2.

   Changed in version 2.3: Support for other error handling schemes
   added.

str.encode([encoding[, errors]])

   Return an encoded version of the string.  Default encoding is the
   current default string encoding.  *errors* may be given to set a
   different error handling scheme.  The default for *errors* is
   ``'strict'``, meaning that encoding errors raise a
   ``UnicodeError``.  Other possible values are ``'ignore'``,
   ``'replace'``, ``'xmlcharrefreplace'``, ``'backslashreplace'`` and
   any other name registered via ``codecs.register_error()``, see
   section *Codec Base Classes*. For a list of possible encodings, see
   section *Standard Encodings*.

   New in version 2.0.

   Changed in version 2.3: Support for ``'xmlcharrefreplace'`` and
   ``'backslashreplace'`` and other error handling schemes added.

str.endswith(suffix[, start[, end]])

   Return ``True`` if the string ends with the specified *suffix*,
   otherwise return ``False``.  *suffix* can also be a tuple of
   suffixes to look for.  With optional *start*, test beginning at
   that position.  With optional *end*, stop comparing at that
   position.

   Changed in version 2.5: Accept tuples as *suffix*.

str.expandtabs([tabsize])

   Return a copy of the string where all tab characters are replaced
   by one or more spaces, depending on the current column and the
   given tab size.  The column number is reset to zero after each
   newline occurring in the string. If *tabsize* is not given, a tab
   size of ``8`` characters is assumed.  This doesn't understand other
   non-printing characters or escape sequences.

str.find(sub[, start[, end]])

   Return the lowest index in the string where substring *sub* is
   found, such that *sub* is contained in the range [*start*, *end*].
   Optional arguments *start* and *end* are interpreted as in slice
   notation.  Return ``-1`` if *sub* is not found.

str.format(format_string, *args, **kwargs)

   Perform a string formatting operation.  The *format_string*
   argument can contain literal text or replacement fields delimited
   by braces ``{}``.  Each replacement field contains either the
   numeric index of a positional argument, or the name of a keyword
   argument.  Returns a copy of *format_string* where each replacement
   field is replaced with the string value of the corresponding
   argument.

   >>> "The sum of 1 + 2 is {0}".format(1+2)
   'The sum of 1 + 2 is 3'

   See *Format String Syntax* for a description of the various
   formatting options that can be specified in format strings.

   This method of string formatting is the new standard in Python 3.0,
   and should be preferred to the ``%`` formatting described in
   *String Formatting Operations* in new code.

   New in version 2.6.

str.index(sub[, start[, end]])

   Like ``find()``, but raise ``ValueError`` when the substring is not
   found.

str.isalnum()

   Return true if all characters in the string are alphanumeric and
   there is at least one character, false otherwise.

   For 8-bit strings, this method is locale-dependent.

str.isalpha()

   Return true if all characters in the string are alphabetic and
   there is at least one character, false otherwise.

   For 8-bit strings, this method is locale-dependent.

str.isdigit()

   Return true if all characters in the string are digits and there is
   at least one character, false otherwise.

   For 8-bit strings, this method is locale-dependent.

str.islower()

   Return true if all cased characters in the string are lowercase and
   there is at least one cased character, false otherwise.

   For 8-bit strings, this method is locale-dependent.

str.isspace()

   Return true if there are only whitespace characters in the string
   and there is at least one character, false otherwise.

   For 8-bit strings, this method is locale-dependent.

str.istitle()

   Return true if the string is a titlecased string and there is at
   least one character, for example uppercase characters may only
   follow uncased characters and lowercase characters only cased ones.
   Return false otherwise.

   For 8-bit strings, this method is locale-dependent.

str.isupper()

   Return true if all cased characters in the string are uppercase and
   there is at least one cased character, false otherwise.

   For 8-bit strings, this method is locale-dependent.

str.join(seq)

   Return a string which is the concatenation of the strings in the
   sequence *seq*. The separator between elements is the string
   providing this method.

str.ljust(width[, fillchar])

   Return the string left justified in a string of length *width*.
   Padding is done using the specified *fillchar* (default is a
   space).  The original string is returned if *width* is less than
   ``len(s)``.

   Changed in version 2.4: Support for the *fillchar* argument.

str.lower()

   Return a copy of the string converted to lowercase.

   For 8-bit strings, this method is locale-dependent.

str.lstrip([chars])

   Return a copy of the string with leading characters removed.  The
   *chars* argument is a string specifying the set of characters to be
   removed.  If omitted or ``None``, the *chars* argument defaults to
   removing whitespace.  The *chars* argument is not a prefix; rather,
   all combinations of its values are stripped:

   >>> '   spacious   '.lstrip()
   'spacious   '
   >>> 'www.example.com'.lstrip('cmowz.')
   'example.com'

   Changed in version 2.2.2: Support for the *chars* argument.

str.partition(sep)

   Split the string at the first occurrence of *sep*, and return a
   3-tuple containing the part before the separator, the separator
   itself, and the part after the separator.  If the separator is not
   found, return a 3-tuple containing the string itself, followed by
   two empty strings.

   New in version 2.5.

str.replace(old, new[, count])

   Return a copy of the string with all occurrences of substring *old*
   replaced by *new*.  If the optional argument *count* is given, only
   the first *count* occurrences are replaced.

str.rfind(sub[, start[, end]])

   Return the highest index in the string where substring *sub* is
   found, such that *sub* is contained within s[start,end].  Optional
   arguments *start* and *end* are interpreted as in slice notation.
   Return ``-1`` on failure.

str.rindex(sub[, start[, end]])

   Like ``rfind()`` but raises ``ValueError`` when the substring *sub*
   is not found.

str.rjust(width[, fillchar])

   Return the string right justified in a string of length *width*.
   Padding is done using the specified *fillchar* (default is a
   space). The original string is returned if *width* is less than
   ``len(s)``.

   Changed in version 2.4: Support for the *fillchar* argument.

str.rpartition(sep)

   Split the string at the last occurrence of *sep*, and return a
   3-tuple containing the part before the separator, the separator
   itself, and the part after the separator.  If the separator is not
   found, return a 3-tuple containing two empty strings, followed by
   the string itself.

   New in version 2.5.

str.rsplit([sep[, maxsplit]])

   Return a list of the words in the string, using *sep* as the
   delimiter string. If *maxsplit* is given, at most *maxsplit* splits
   are done, the *rightmost* ones.  If *sep* is not specified or
   ``None``, any whitespace string is a separator.  Except for
   splitting from the right, ``rsplit()`` behaves like ``split()``
   which is described in detail below.

   New in version 2.4.

str.rstrip([chars])

   Return a copy of the string with trailing characters removed.  The
   *chars* argument is a string specifying the set of characters to be
   removed.  If omitted or ``None``, the *chars* argument defaults to
   removing whitespace.  The *chars* argument is not a suffix; rather,
   all combinations of its values are stripped:

   >>> '   spacious   '.rstrip()
   '   spacious'
   >>> 'mississippi'.rstrip('ipz')
   'mississ'

   Changed in version 2.2.2: Support for the *chars* argument.

str.split([sep[, maxsplit]])

   Return a list of the words in the string, using *sep* as the
   delimiter string.  If *maxsplit* is given, at most *maxsplit*
   splits are done (thus, the list will have at most ``maxsplit+1``
   elements).  If *maxsplit* is not specified, then there is no limit
   on the number of splits (all possible splits are made).

   If *sep* is given, consecutive delimiters are not grouped together
   and are deemed to delimit empty strings (for example,
   ``'1,,2'.split(',')`` returns ``['1', '', '2']``).  The *sep*
   argument may consist of multiple characters (for example,
   ``'1<>2<>3'.split('<>')`` returns ``['1', '2', '3']``). Splitting
   an empty string with a specified separator returns ``['']``.

   If *sep* is not specified or is ``None``, a different splitting
   algorithm is applied: runs of consecutive whitespace are regarded
   as a single separator, and the result will contain no empty strings
   at the start or end if the string has leading or trailing
   whitespace.  Consequently, splitting an empty string or a string
   consisting of just whitespace with a ``None`` separator returns
   ``[]``.

   For example, ``' 1  2   3  '.split()`` returns ``['1', '2', '3']``,
   and ``'  1  2   3  '.split(None, 1)`` returns ``['1', '2   3  ']``.

str.splitlines([keepends])

   Return a list of the lines in the string, breaking at line
   boundaries.  Line breaks are not included in the resulting list
   unless *keepends* is given and true.

str.startswith(prefix[, start[, end]])

   Return ``True`` if string starts with the *prefix*, otherwise
   return ``False``. *prefix* can also be a tuple of prefixes to look
   for.  With optional *start*, test string beginning at that
   position.  With optional *end*, stop comparing string at that
   position.

   Changed in version 2.5: Accept tuples as *prefix*.

str.strip([chars])

   Return a copy of the string with the leading and trailing
   characters removed. The *chars* argument is a string specifying the
   set of characters to be removed. If omitted or ``None``, the
   *chars* argument defaults to removing whitespace. The *chars*
   argument is not a prefix or suffix; rather, all combinations of its
   values are stripped:

   >>> '   spacious   '.strip()
   'spacious'
   >>> 'www.example.com'.strip('cmowz.')
   'example'

   Changed in version 2.2.2: Support for the *chars* argument.

str.swapcase()

   Return a copy of the string with uppercase characters converted to
   lowercase and vice versa.

   For 8-bit strings, this method is locale-dependent.

str.title()

   Return a titlecased version of the string: words start with
   uppercase characters, all remaining cased characters are lowercase.

   For 8-bit strings, this method is locale-dependent.

str.translate(table[, deletechars])

   Return a copy of the string where all characters occurring in the
   optional argument *deletechars* are removed, and the remaining
   characters have been mapped through the given translation table,
   which must be a string of length 256.

   You can use the ``maketrans()`` helper function in the ``string``
   module to create a translation table. For string objects, set the
   *table* argument to ``None`` for translations that only delete
   characters:

   >>> 'read this short text'.translate(None, 'aeiou')
   'rd ths shrt txt'

   New in version 2.6: Support for a ``None`` *table* argument.

   For Unicode objects, the ``translate()`` method does not accept the
   optional *deletechars* argument.  Instead, it returns a copy of the
   *s* where all characters have been mapped through the given
   translation table which must be a mapping of Unicode ordinals to
   Unicode ordinals, Unicode strings or ``None``. Unmapped characters
   are left untouched. Characters mapped to ``None`` are deleted.
   Note, a more flexible approach is to create a custom character
   mapping codec using the ``codecs`` module (see ``encodings.cp1251``
   for an example).

str.upper()

   Return a copy of the string converted to uppercase.

   For 8-bit strings, this method is locale-dependent.

str.zfill(width)

   Return the numeric string left filled with zeros in a string of
   length *width*.  A sign prefix is handled correctly.  The original
   string is returned if *width* is less than ``len(s)``.

   New in version 2.2.2.

The following methods are present only on unicode objects:

unicode.isnumeric()

   Return ``True`` if there are only numeric characters in S,
   ``False`` otherwise. Numeric characters include digit characters,
   and all characters that have the Unicode numeric value property,
   e.g. U+2155, VULGAR FRACTION ONE FIFTH.

unicode.isdecimal()

   Return ``True`` if there are only decimal characters in S,
   ``False`` otherwise. Decimal characters include digit characters,
   and all characters that that can be used to form decimal-radix
   numbers, e.g. U+0660, ARABIC-INDIC DIGIT ZERO.


String Formatting Operations
============================

String and Unicode objects have one unique built-in operation: the
``%`` operator (modulo).  This is also known as the string
*formatting* or *interpolation* operator.  Given ``format % values``
(where *format* is a string or Unicode object), ``%`` conversion
specifications in *format* are replaced with zero or more elements of
*values*.  The effect is similar to the using ``sprintf`` in the C
language.  If *format* is a Unicode object, or if any of the objects
being converted using the ``%s`` conversion are Unicode objects, the
result will also be a Unicode object.

If *format* requires a single argument, *values* may be a single non-
tuple object. [4]  Otherwise, *values* must be a tuple with exactly
the number of items specified by the format string, or a single
mapping object (for example, a dictionary).

A conversion specifier contains two or more characters and has the
following components, which must occur in this order:

1. The ``'%'`` character, which marks the start of the specifier.

2. Mapping key (optional), consisting of a parenthesised sequence of
   characters (for example, ``(somename)``).

3. Conversion flags (optional), which affect the result of some
   conversion types.

4. Minimum field width (optional).  If specified as an ``'*'``
   (asterisk), the actual width is read from the next element of the
   tuple in *values*, and the object to convert comes after the
   minimum field width and optional precision.

5. Precision (optional), given as a ``'.'`` (dot) followed by the
   precision.  If specified as ``'*'`` (an asterisk), the actual width
   is read from the next element of the tuple in *values*, and the
   value to convert comes after the precision.

6. Length modifier (optional).

7. Conversion type.

When the right argument is a dictionary (or other mapping type), then
the formats in the string *must* include a parenthesised mapping key
into that dictionary inserted immediately after the ``'%'`` character.
The mapping key selects the value to be formatted from the mapping.
For example:

>>> print '%(language)s has %(#)03d quote types.' % \
...       {'language': "Python", "#": 2}
Python has 002 quote types.

In this case no ``*`` specifiers may occur in a format (since they
require a sequential parameter list).

The conversion flag characters are:

+-----------+-----------------------------------------------------------------------+
| Flag      | Meaning                                                               |
+===========+=======================================================================+
| ``'#'``   | The value conversion will use the "alternate form" (where defined     |
|           | below).                                                               |
+-----------+-----------------------------------------------------------------------+
| ``'0'``   | The conversion will be zero padded for numeric values.                |
+-----------+-----------------------------------------------------------------------+
| ``'-'``   | The converted value is left adjusted (overrides the ``'0'``           |
|           | conversion if both are given).                                        |
+-----------+-----------------------------------------------------------------------+
| ``' '``   | (a space) A blank should be left before a positive number (or empty   |
|           | string) produced by a signed conversion.                              |
+-----------+-----------------------------------------------------------------------+
| ``'+'``   | A sign character (``'+'`` or ``'-'``) will precede the conversion     |
|           | (overrides a "space" flag).                                           |
+-----------+-----------------------------------------------------------------------+

A length modifier (``h``, ``l``, or ``L``) may be present, but is
ignored as it is not necessary for Python -- so e.g. ``%ld`` is
identical to ``%d``.

The conversion types are:

+--------------+-------------------------------------------------------+---------+
| Conversion   | Meaning                                               | Notes   |
+==============+=======================================================+=========+
| ``'d'``      | Signed integer decimal.                               |         |
+--------------+-------------------------------------------------------+---------+
| ``'i'``      | Signed integer decimal.                               |         |
+--------------+-------------------------------------------------------+---------+
| ``'o'``      | Signed octal value.                                   | (1)     |
+--------------+-------------------------------------------------------+---------+
| ``'u'``      | Obselete type -- it is identical to ``'d'``.          | (7)     |
+--------------+-------------------------------------------------------+---------+
| ``'x'``      | Signed hexadecimal (lowercase).                       | (2)     |
+--------------+-------------------------------------------------------+---------+
| ``'X'``      | Signed hexadecimal (uppercase).                       | (2)     |
+--------------+-------------------------------------------------------+---------+
| ``'e'``      | Floating point exponential format (lowercase).        | (3)     |
+--------------+-------------------------------------------------------+---------+
| ``'E'``      | Floating point exponential format (uppercase).        | (3)     |
+--------------+-------------------------------------------------------+---------+
| ``'f'``      | Floating point decimal format.                        | (3)     |
+--------------+-------------------------------------------------------+---------+
| ``'F'``      | Floating point decimal format.                        | (3)     |
+--------------+-------------------------------------------------------+---------+
| ``'g'``      | Floating point format. Uses lowercase exponential     | (4)     |
|              | format if exponent is less than -4 or not less than   |         |
|              | precision, decimal format otherwise.                  |         |
+--------------+-------------------------------------------------------+---------+
| ``'G'``      | Floating point format. Uses uppercase exponential     | (4)     |
|              | format if exponent is less than -4 or not less than   |         |
|              | precision, decimal format otherwise.                  |         |
+--------------+-------------------------------------------------------+---------+
| ``'c'``      | Single character (accepts integer or single character |         |
|              | string).                                              |         |
+--------------+-------------------------------------------------------+---------+
| ``'r'``      | String (converts any python object using ``repr()``). | (5)     |
+--------------+-------------------------------------------------------+---------+
| ``'s'``      | String (converts any python object using ``str()``).  | (6)     |
+--------------+-------------------------------------------------------+---------+
| ``'%'``      | No argument is converted, results in a ``'%'``        |         |
|              | character in the result.                              |         |
+--------------+-------------------------------------------------------+---------+

Notes:

1. The alternate form causes a leading zero (``'0'``) to be inserted
   between left-hand padding and the formatting of the number if the
   leading character of the result is not already a zero.

2. The alternate form causes a leading ``'0x'`` or ``'0X'`` (depending
   on whether the ``'x'`` or ``'X'`` format was used) to be inserted
   between left-hand padding and the formatting of the number if the
   leading character of the result is not already a zero.

3. The alternate form causes the result to always contain a decimal
   point, even if no digits follow it.

   The precision determines the number of digits after the decimal
   point and defaults to 6.

4. The alternate form causes the result to always contain a decimal
   point, and trailing zeroes are not removed as they would otherwise
   be.

   The precision determines the number of significant digits before
   and after the decimal point and defaults to 6.

5. The ``%r`` conversion was added in Python 2.0.

   The precision determines the maximal number of characters used.

6. If the object or format provided is a ``unicode`` string, the
   resulting string will also be ``unicode``.

   The precision determines the maximal number of characters used.

7. See **PEP 237**.

Since Python strings have an explicit length, ``%s`` conversions do
not assume that ``'\0'`` is the end of the string.

For safety reasons, floating point precisions are clipped to 50;
``%f`` conversions for numbers whose absolute value is over 1e25 are
replaced by ``%g`` conversions. [5]  All other errors raise
exceptions.

Additional string operations are defined in standard modules
``string`` and ``re``.


XRange Type
===========

The ``xrange`` type is an immutable sequence which is commonly used
for looping.  The advantage of the ``xrange`` type is that an
``xrange`` object will always take the same amount of memory, no
matter the size of the range it represents.  There are no consistent
performance advantages.

XRange objects have very little behavior: they only support indexing,
iteration, and the ``len()`` function.


Mutable Sequence Types
======================

List objects support additional operations that allow in-place
modification of the object. Other mutable sequence types (when added
to the language) should also support these operations. Strings and
tuples are immutable sequence types: such objects cannot be modified
once created. The following operations are defined on mutable sequence
types (where *x* is an arbitrary object):

+--------------------------------+----------------------------------+-----------------------+
| Operation                      | Result                           | Notes                 |
+================================+==================================+=======================+
| ``s[i] = x``                   | item *i* of *s* is replaced by   |                       |
|                                | *x*                              |                       |
+--------------------------------+----------------------------------+-----------------------+
| ``s[i:j] = t``                 | slice of *s* from *i* to *j* is  |                       |
|                                | replaced by the contents of the  |                       |
|                                | iterable *t*                     |                       |
+--------------------------------+----------------------------------+-----------------------+
| ``del s[i:j]``                 | same as ``s[i:j] = []``          |                       |
+--------------------------------+----------------------------------+-----------------------+
| ``s[i:j:k] = t``               | the elements of ``s[i:j:k]`` are | (1)                   |
|                                | replaced by those of *t*         |                       |
+--------------------------------+----------------------------------+-----------------------+
| ``del s[i:j:k]``               | removes the elements of          |                       |
|                                | ``s[i:j:k]`` from the list       |                       |
+--------------------------------+----------------------------------+-----------------------+
| ``s.append(x)``                | same as ``s[len(s):len(s)] =     | (2)                   |
|                                | [x]``                            |                       |
+--------------------------------+----------------------------------+-----------------------+
| ``s.extend(x)``                | same as ``s[len(s):len(s)] = x`` | (3)                   |
+--------------------------------+----------------------------------+-----------------------+
| ``s.count(x)``                 | return number of *i*'s for which |                       |
|                                | ``s[i] == x``                    |                       |
+--------------------------------+----------------------------------+-----------------------+
| ``s.index(x[, i[, j]])``       | return smallest *k* such that    | (4)                   |
|                                | ``s[k] == x`` and ``i <= k < j`` |                       |
+--------------------------------+----------------------------------+-----------------------+
| ``s.insert(i, x)``             | same as ``s[i:i] = [x]``         | (5)                   |
+--------------------------------+----------------------------------+-----------------------+
| ``s.pop([i])``                 | same as ``x = s[i]; del s[i];    | (6)                   |
|                                | return x``                       |                       |
+--------------------------------+----------------------------------+-----------------------+
| ``s.remove(x)``                | same as ``del s[s.index(x)]``    | (4)                   |
+--------------------------------+----------------------------------+-----------------------+
| ``s.reverse()``                | reverses the items of *s* in     | (7)                   |
|                                | place                            |                       |
+--------------------------------+----------------------------------+-----------------------+
| ``s.sort([cmp[, key[,          | sort the items of *s* in place   | (7)(8)(9)(10)         |
| reverse]]])``                  |                                  |                       |
+--------------------------------+----------------------------------+-----------------------+

Notes:

1. *t* must have the same length as the slice it is  replacing.

2. The C implementation of Python has historically accepted multiple
   parameters and implicitly joined them into a tuple; this no longer
   works in Python 2.0.  Use of this misfeature has been deprecated
   since Python 1.4.

3. *x* can be any iterable object.

4. Raises ``ValueError`` when *x* is not found in *s*. When a negative
   index is passed as the second or third parameter to the ``index()``
   method, the list length is added, as for slice indices.  If it is
   still negative, it is truncated to zero, as for slice indices.

   Changed in version 2.3: Previously, ``index()`` didn't have
   arguments for specifying start and stop positions.

5. When a negative index is passed as the first parameter to the
   ``insert()`` method, the list length is added, as for slice
   indices.  If it is still negative, it is truncated to zero, as for
   slice indices.

   Changed in version 2.3: Previously, all negative indices were
   truncated to zero.

6. The ``pop()`` method is only supported by the list and array types.
   The optional argument *i* defaults to ``-1``, so that by default
   the last item is removed and returned.

7. The ``sort()`` and ``reverse()`` methods modify the list in place
   for economy of space when sorting or reversing a large list.  To
   remind you that they operate by side effect, they don't return the
   sorted or reversed list.

8. The ``sort()`` method takes optional arguments for controlling the
   comparisons.

   *cmp* specifies a custom comparison function of two arguments (list
   items) which should return a negative, zero or positive number
   depending on whether the first argument is considered smaller than,
   equal to, or larger than the second argument: ``cmp=lambda x,y:
   cmp(x.lower(), y.lower())``.  The default value is ``None``.

   *key* specifies a function of one argument that is used to extract
   a comparison key from each list element: ``key=str.lower``.  The
   default value is ``None``.

   *reverse* is a boolean value.  If set to ``True``, then the list
   elements are sorted as if each comparison were reversed.

   In general, the *key* and *reverse* conversion processes are much
   faster than specifying an equivalent *cmp* function.  This is
   because *cmp* is called multiple times for each list element while
   *key* and *reverse* touch each element only once.

   Changed in version 2.3: Support for ``None`` as an equivalent to
   omitting *cmp* was added.

   Changed in version 2.4: Support for *key* and *reverse* was added.

9. Starting with Python 2.3, the ``sort()`` method is guaranteed to be
   stable.  A sort is stable if it guarantees not to change the
   relative order of elements that compare equal --- this is helpful
   for sorting in multiple passes (for example, sort by department,
   then by salary grade).

10. While a list is being sorted, the effect of attempting to mutate,
    or even inspect, the list is undefined.  The C implementation of
    Python 2.3 and newer makes the list appear empty for the duration,
    and raises ``ValueError`` if it can detect that the list has been
    mutated during a sort.
 
Mutable Sequence Types
**********************

List objects support additional operations that allow in-place
modification of the object. Other mutable sequence types (when added
to the language) should also support these operations. Strings and
tuples are immutable sequence types: such objects cannot be modified
once created. The following operations are defined on mutable sequence
types (where *x* is an arbitrary object):

+--------------------------------+----------------------------------+-----------------------+
| Operation                      | Result                           | Notes                 |
+================================+==================================+=======================+
| ``s[i] = x``                   | item *i* of *s* is replaced by   |                       |
|                                | *x*                              |                       |
+--------------------------------+----------------------------------+-----------------------+
| ``s[i:j] = t``                 | slice of *s* from *i* to *j* is  |                       |
|                                | replaced by the contents of the  |                       |
|                                | iterable *t*                     |                       |
+--------------------------------+----------------------------------+-----------------------+
| ``del s[i:j]``                 | same as ``s[i:j] = []``          |                       |
+--------------------------------+----------------------------------+-----------------------+
| ``s[i:j:k] = t``               | the elements of ``s[i:j:k]`` are | (1)                   |
|                                | replaced by those of *t*         |                       |
+--------------------------------+----------------------------------+-----------------------+
| ``del s[i:j:k]``               | removes the elements of          |                       |
|                                | ``s[i:j:k]`` from the list       |                       |
+--------------------------------+----------------------------------+-----------------------+
| ``s.append(x)``                | same as ``s[len(s):len(s)] =     | (2)                   |
|                                | [x]``                            |                       |
+--------------------------------+----------------------------------+-----------------------+
| ``s.extend(x)``                | same as ``s[len(s):len(s)] = x`` | (3)                   |
+--------------------------------+----------------------------------+-----------------------+
| ``s.count(x)``                 | return number of *i*'s for which |                       |
|                                | ``s[i] == x``                    |                       |
+--------------------------------+----------------------------------+-----------------------+
| ``s.index(x[, i[, j]])``       | return smallest *k* such that    | (4)                   |
|                                | ``s[k] == x`` and ``i <= k < j`` |                       |
+--------------------------------+----------------------------------+-----------------------+
| ``s.insert(i, x)``             | same as ``s[i:i] = [x]``         | (5)                   |
+--------------------------------+----------------------------------+-----------------------+
| ``s.pop([i])``                 | same as ``x = s[i]; del s[i];    | (6)                   |
|                                | return x``                       |                       |
+--------------------------------+----------------------------------+-----------------------+
| ``s.remove(x)``                | same as ``del s[s.index(x)]``    | (4)                   |
+--------------------------------+----------------------------------+-----------------------+
| ``s.reverse()``                | reverses the items of *s* in     | (7)                   |
|                                | place                            |                       |
+--------------------------------+----------------------------------+-----------------------+
| ``s.sort([cmp[, key[,          | sort the items of *s* in place   | (7)(8)(9)(10)         |
| reverse]]])``                  |                                  |                       |
+--------------------------------+----------------------------------+-----------------------+

Notes:

1. *t* must have the same length as the slice it is  replacing.

2. The C implementation of Python has historically accepted multiple
   parameters and implicitly joined them into a tuple; this no longer
   works in Python 2.0.  Use of this misfeature has been deprecated
   since Python 1.4.

3. *x* can be any iterable object.

4. Raises ``ValueError`` when *x* is not found in *s*. When a negative
   index is passed as the second or third parameter to the ``index()``
   method, the list length is added, as for slice indices.  If it is
   still negative, it is truncated to zero, as for slice indices.

   Changed in version 2.3: Previously, ``index()`` didn't have
   arguments for specifying start and stop positions.

5. When a negative index is passed as the first parameter to the
   ``insert()`` method, the list length is added, as for slice
   indices.  If it is still negative, it is truncated to zero, as for
   slice indices.

   Changed in version 2.3: Previously, all negative indices were
   truncated to zero.

6. The ``pop()`` method is only supported by the list and array types.
   The optional argument *i* defaults to ``-1``, so that by default
   the last item is removed and returned.

7. The ``sort()`` and ``reverse()`` methods modify the list in place
   for economy of space when sorting or reversing a large list.  To
   remind you that they operate by side effect, they don't return the
   sorted or reversed list.

8. The ``sort()`` method takes optional arguments for controlling the
   comparisons.

   *cmp* specifies a custom comparison function of two arguments (list
   items) which should return a negative, zero or positive number
   depending on whether the first argument is considered smaller than,
   equal to, or larger than the second argument: ``cmp=lambda x,y:
   cmp(x.lower(), y.lower())``.  The default value is ``None``.

   *key* specifies a function of one argument that is used to extract
   a comparison key from each list element: ``key=str.lower``.  The
   default value is ``None``.

   *reverse* is a boolean value.  If set to ``True``, then the list
   elements are sorted as if each comparison were reversed.

   In general, the *key* and *reverse* conversion processes are much
   faster than specifying an equivalent *cmp* function.  This is
   because *cmp* is called multiple times for each list element while
   *key* and *reverse* touch each element only once.

   Changed in version 2.3: Support for ``None`` as an equivalent to
   omitting *cmp* was added.

   Changed in version 2.4: Support for *key* and *reverse* was added.

9. Starting with Python 2.3, the ``sort()`` method is guaranteed to be
   stable.  A sort is stable if it guarantees not to change the
   relative order of elements that compare equal --- this is helpful
   for sorting in multiple passes (for example, sort by department,
   then by salary grade).

10. While a list is being sorted, the effect of attempting to mutate,
    or even inspect, the list is undefined.  The C implementation of
    Python 2.3 and newer makes the list appear empty for the duration,
    and raises ``ValueError`` if it can detect that the list has been
    mutated during a sort.
 
Unary arithmetic operations
***************************

All unary arithmetic (and bitwise) operations have the same priority:

   u_expr ::= power | "-" u_expr | "+" u_expr | "~" u_expr

The unary ``-`` (minus) operator yields the negation of its numeric
argument.

The unary ``+`` (plus) operator yields its numeric argument unchanged.

The unary ``~`` (invert) operator yields the bitwise inversion of its
plain or long integer argument.  The bitwise inversion of ``x`` is
defined as ``-(x+1)``.  It only applies to integral numbers.

In all three cases, if the argument does not have the proper type, a
``TypeError`` exception is raised.
 
The ``while`` statement
***********************

The ``while`` statement is used for repeated execution as long as an
expression is true:

   while_stmt ::= "while" expression ":" suite
                  ["else" ":" suite]

This repeatedly tests the expression and, if it is true, executes the
first suite; if the expression is false (which may be the first time
it is tested) the suite of the ``else`` clause, if present, is
executed and the loop terminates.

A ``break`` statement executed in the first suite terminates the loop
without executing the ``else`` clause's suite.  A ``continue``
statement executed in the first suite skips the rest of the suite and
goes back to testing the expression.
 
The ``with`` statement
**********************

New in version 2.5.

The ``with`` statement is used to wrap the execution of a block with
methods defined by a context manager (see section *With Statement
Context Managers*). This allows common
``try``...``except``...``finally`` usage patterns to be encapsulated
for convenient reuse.

   with_stmt ::= "with" expression ["as" target] ":" suite

The execution of the ``with`` statement proceeds as follows:

1. The context expression is evaluated to obtain a context manager.

2. The context manager's ``__enter__()`` method is invoked.

3. If a target was included in the ``with`` statement, the return
   value from ``__enter__()`` is assigned to it.

   Note: The ``with`` statement guarantees that if the ``__enter__()``
     method returns without an error, then ``__exit__()`` will always
     be called. Thus, if an error occurs during the assignment to the
     target list, it will be treated the same as an error occurring
     within the suite would be. See step 5 below.

4. The suite is executed.

5. The context manager's ``__exit__()`` method is invoked. If an
   exception caused the suite to be exited, its type, value, and
   traceback are passed as arguments to ``__exit__()``. Otherwise,
   three ``None`` arguments are supplied.

   If the suite was exited due to an exception, and the return value
   from the ``__exit__()`` method was false, the exception is
   reraised. If the return value was true, the exception is
   suppressed, and execution continues with the statement following
   the ``with`` statement.

   If the suite was exited for any reason other than an exception, the
   return value from ``__exit__()`` is ignored, and execution proceeds
   at the normal location for the kind of exit that was taken.

Note: In Python 2.5, the ``with`` statement is only allowed when the
  ``with_statement`` feature has been enabled.  It is always enabled
  in Python 2.6.

See also:

   **PEP 0343** - The "with" statement
      The specification, background, and examples for the Python
      ``with`` statement.
 
The ``yield`` statement
***********************

   yield_stmt ::= yield_expression

The ``yield`` statement is only used when defining a generator
function, and is only used in the body of the generator function.
Using a ``yield`` statement in a function definition is sufficient to
cause that definition to create a generator function instead of a
normal function.

When a generator function is called, it returns an iterator known as a
generator iterator, or more commonly, a generator.  The body of the
generator function is executed by calling the generator's ``next()``
method repeatedly until it raises an exception.

When a ``yield`` statement is executed, the state of the generator is
frozen and the value of **expression_list** is returned to
``next()``'s caller.  By "frozen" we mean that all local state is
retained, including the current bindings of local variables, the
instruction pointer, and the internal evaluation stack: enough
information is saved so that the next time ``next()`` is invoked, the
function can proceed exactly as if the ``yield`` statement were just
another external call.

As of Python version 2.5, the ``yield`` statement is now allowed in
the ``try`` clause of a ``try`` ...  ``finally`` construct.  If the
generator is not resumed before it is finalized (by reaching a zero
reference count or by being garbage collected), the generator-
iterator's ``close()`` method will be called, allowing any pending
``finally`` clauses to execute.

Note: In Python 2.2, the ``yield`` statement was only allowed when the
  ``generators`` feature has been enabled.  This ``__future__`` import
  statement was used to enable the feature:

     from __future__ import generators

See also:

   **PEP 0255** - Simple Generators
      The proposal for adding generators and the ``yield`` statement
      to Python.

   **PEP 0342** - Coroutines via Enhanced Generators
      The proposal that, among other generator enhancements, proposed
      allowing ``yield`` to appear inside a ``try`` ... ``finally``
      block.
