
Expressions
***********

This chapter explains the meaning of the elements of expressions in
Python.

**Syntax Notes:** In this and the following chapters, extended BNF
notation will be used to describe syntax, not lexical analysis.  When
(one alternative of) a syntax rule has the form

   name ::= othername

and no semantics are given, the semantics of this form of ``name`` are
the same as for ``othername``.


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.


Atoms
=====

Atoms are the most basic elements of expressions.  The simplest atoms
are identifiers or literals.  Forms enclosed in reverse quotes or in
parentheses, brackets or braces are also categorized syntactically as
atoms.  The syntax for atoms is:

   atom      ::= identifier | literal | enclosure
   enclosure ::= parenth_form | list_display
                 | generator_expression | dict_display
                 | string_conversion | yield_atom


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.


Parenthesized forms
-------------------

A parenthesized form is an optional expression list enclosed in
parentheses:

   parenth_form ::= "(" [expression_list] ")"

A parenthesized expression list yields whatever that expression list
yields: if the list contains at least one comma, it yields a tuple;
otherwise, it yields the single expression that makes up the
expression list.

An empty pair of parentheses yields an empty tuple object.  Since
tuples are immutable, the rules for literals apply (i.e., two
occurrences of the empty tuple may or may not yield the same object).

Note that tuples are not formed by the parentheses, but rather by use
of the comma operator.  The exception is the empty tuple, for which
parentheses *are* required --- allowing unparenthesized "nothing" in
expressions would cause ambiguities and allow common typos to pass
uncaught.


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].


Generator expressions
---------------------

A generator expression is a compact generator notation in parentheses:

   generator_expression ::= "(" expression genexpr_for ")"
   genexpr_for          ::= "for" target_list "in" or_test [genexpr_iter]
   genexpr_iter         ::= genexpr_for | genexpr_if
   genexpr_if           ::= "if" old_expression [genexpr_iter]

A generator expression yields a new generator object.  It consists of
a single expression followed by at least one ``for`` clause and zero
or more ``for`` or ``if`` clauses.  The iterating values of the new
generator 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 yield a value that is reached the
innermost block for each iteration.

Variables used in the generator expression are evaluated lazily in a
separate scope when the ``next()`` method is called for the generator
object (in the same fashion as for normal generators).  However, the
``in`` expression of the leftmost ``for`` clause is immediately
evaluated in the current scope so that an error produced by it can be
seen before any other possible error in the code that handles the
generator expression.  Subsequent ``for`` and ``if`` clauses cannot be
evaluated immediately since they may depend on the previous ``for``
loop.  For example: ``(x*y for x in range(10) for y in bar(x))``.

The parentheses can be omitted on calls with only one argument. See
section *Calls* for the detail.


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.


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.


Yield expressions
-----------------

   yield_atom       ::= "(" yield_expression ")"
   yield_expression ::= "yield" [expression_list]

New in version 2.5.

The ``yield`` expression is only used when defining a generator
function, and can only be used in the body of a function definition.
Using a ``yield`` expression 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.  That generator then controls the execution of a generator
function. The execution starts when one of the generator's methods is
called.  At that time, the execution proceeds to the first ``yield``
expression, where it is suspended again, returning the value of
**expression_list** to generator's caller.  By suspended we mean that
all local state is retained, including the current bindings of local
variables, the instruction pointer, and the internal evaluation stack.
When the execution is resumed by calling one of the generator's
methods, the function can proceed exactly as if the ``yield``
expression was just another external call. The value of the ``yield``
expression after resuming depends on the method which resumed the
execution.

All of this makes generator functions quite similar to coroutines;
they yield multiple times, they have more than one entry point and
their execution can be suspended.  The only difference is that a
generator function cannot control where should the execution continue
after it yields; the control is always transfered to the generator's
caller.

The following generator's methods can be used to control the execution
of a generator function:

generator.next()

   Starts the execution of a generator function or resumes it at the
   last executed ``yield`` expression.  When a generator function is
   resumed with a ``next()`` method, the current ``yield`` expression
   always evaluates to ``None``.  The execution then continues to the
   next ``yield`` expression, where the generator is suspended again,
   and the value of the **expression_list** is returned to
   ``next()``'s caller. If the generator exits without yielding
   another value, a ``StopIteration`` exception is raised.

generator.send(value)

   Resumes the execution and "sends" a value into the generator
   function.  The ``value`` argument becomes the result of the current
   ``yield`` expression.  The ``send()`` method returns the next value
   yielded by the generator, or raises ``StopIteration`` if the
   generator exits without yielding another value. When ``send()`` is
   called to start the generator, it must be called with ``None`` as
   the argument, because there is no ``yield`` expression that could
   receive the value.

generator.throw(type[, value[, traceback]])

   Raises an exception of type ``type`` at the point where generator
   was paused, and returns the next value yielded by the generator
   function.  If the generator exits without yielding another value, a
   ``StopIteration`` exception is raised.  If the generator function
   does not catch the passed-in exception, or raises a different
   exception, then that exception propagates to the caller.

generator.close()

   Raises a ``GeneratorExit`` at the point where the generator
   function was paused.  If the generator function then raises
   ``StopIteration`` (by exiting normally, or due to already being
   closed) or ``GeneratorExit`` (by not catching the exception), close
   returns to its caller.  If the generator yields a value, a
   ``RuntimeError`` is raised.  If the generator raises any other
   exception, it is propagated to the caller.  ``close()`` does
   nothing if the generator has already exited due to an exception or
   normal exit.

Here is a simple example that demonstrates the behavior of generators
and generator functions:

   >>> def echo(value=None):
   ...     print "Execution starts when 'next()' is called for the first time."
   ...     try:
   ...         while True:
   ...             try:
   ...                 value = (yield value)
   ...             except Exception, e:
   ...                 value = e
   ...     finally:
   ...         print "Don't forget to clean up when 'close()' is called."
   ...
   >>> generator = echo(1)
   >>> print generator.next()
   Execution starts when 'next()' is called for the first time.
   1
   >>> print generator.next()
   None
   >>> print generator.send(2)
   2
   >>> generator.throw(TypeError, "spam")
   TypeError('spam',)
   >>> generator.close()
   Don't forget to clean up when 'close()' is called.

See also:

   **PEP 0342** - Coroutines via Enhanced Generators
      The proposal to enhance the API and syntax of generators, making
      them usable as simple coroutines.


Primaries
=========

Primaries represent the most tightly bound operations of the language.
Their syntax is:

   primary ::= atom | attributeref | subscription | slicing | call


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.


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.


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.


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.

**CPython implementation detail:** An implementation may provide
built-in 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.


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``.


Unary arithmetic and bitwise 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.


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.


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.


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.


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-built-in 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 built-in 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__()`` but do
define ``__iter__()``, ``x in y`` is true if some value ``z`` with ``x
== z`` is produced while iterating over ``y``.  If an exception is
raised during the iteration, it is as if ``in`` raised that exception.

Lastly, the old-style iteration protocol is tried: if a class defines
``__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]


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 ``''``.)


Lambdas
=======

   lambda_form     ::= "lambda" [parameter_list]: expression
   old_lambda_form ::= "lambda" [parameter_list]: old_expression

Lambda forms (lambda expressions) have the same syntactic position as
expressions.  They are a shorthand to create anonymous functions; the
expression ``lambda arguments: expression`` yields a function object.
The unnamed object behaves like a function object defined with

   def name(arguments):
       return expression

See section *Function definitions* for the syntax of parameter lists.
Note that functions created with lambda forms cannot contain
statements.


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: ``()``.)


Evaluation order
================

Python evaluates expressions from left to right. Notice that while
evaluating an assignment, the right-hand side is evaluated before the
left-hand side.

In the following lines, expressions will be evaluated in the
arithmetic order of their suffixes:

   expr1, expr2, expr3, expr4
   (expr1, expr2, expr3, expr4)
   {expr1: expr2, expr3: expr4}
   expr1 + expr2 * (expr3 - expr4)
   expr1(expr2, expr3, *expr4, **expr5)
   expr3, expr4 = expr1, expr2


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``, ``is``, ``is not``,     | Comparisons, including membership     |
| ``<``, ``<=``, ``>``, ``>=``, ``<>``, ``!=``,   | tests and identity tests,             |
| ``==``                                          |                                       |
+-------------------------------------------------+---------------------------------------+
| ``|``                                           | Bitwise OR                            |
+-------------------------------------------------+---------------------------------------+
| ``^``                                           | Bitwise XOR                           |
+-------------------------------------------------+---------------------------------------+
| ``&``                                           | Bitwise AND                           |
+-------------------------------------------------+---------------------------------------+
| ``<<``, ``>>``                                  | Shifts                                |
+-------------------------------------------------+---------------------------------------+
| ``+``, ``-``                                    | Addition and subtraction              |
+-------------------------------------------------+---------------------------------------+
| ``*``, ``/``, ``//``, ``%``                     | Multiplication, division, remainder   |
+-------------------------------------------------+---------------------------------------+
| ``+x``, ``-x``, ``~x``                          | Positive, negative, bitwise NOT       |
+-------------------------------------------------+---------------------------------------+
| ``**``                                          | Exponentiation [8]                    |
+-------------------------------------------------+---------------------------------------+
| ``x[index]``, ``x[index:index]``,               | Subscription, slicing, call,          |
| ``x(arguments...)``, ``x.attribute``            | attribute reference                   |
+-------------------------------------------------+---------------------------------------+
| ``(expressions...)``, ``[expressions...]``,     | Binding or tuple display, list        |
| ``{key:datum...}``, ```expressions...```        | display, dictionary display, 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.

[8] The power operator ``**`` binds less tightly than an arithmetic or
    bitwise unary operator on its right, that is, ``2**-1`` is
    ``0.5``.
