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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

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

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

== 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

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

with

x == z

is produced while iterating over

. If an

exception is raised during the iteration, it is as if

raised that exception.

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

__getitem__()

x in y

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,

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it is as if

raised that exception).

The operator

not in

is defined to have the inverse true value of

The operators

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]

5.10. Boolean operations

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 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

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

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

5.11. Conditional Expressions

New in version 2.5.

conditional_expression ::= or_test ["if" or_test "else" expression]

expression ::= conditional_expression | lambda_expr

Conditional expressions (sometimes called a “ternary operator”) have the lowest priority

of all Python operations.

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The expression

x if C else y

first evaluates the condition, C (not x); if C is true, x is

evaluated and its value is returned; otherwise, y is evaluated and its value is returned.

See PEP 308 for more details about conditional expressions.

5.12. Lambdas

lambda_expr ::= "lambda" [parameter_list]: expression

old_lambda_expr ::= "lambda" [parameter_list]: old_expression

Lambda expressions (sometimes called lambda forms) 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 expressions cannot contain statements.

5.13. 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:

()

5.14. 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:

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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

5.15. Operator precedence

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

–

else

Conditional expression

Boolean OR

and

Boolean AND

not

Boolean NOT

not in

is not

Comparisons, including membership

tests and identity tests

Bitwise OR

Bitwise XOR

Bitwise AND

Shifts

Addition and subtraction

Multiplication, division, remainder [8]

-x

Positive, negative, bitwise NOT

Exponentiation [9]

x[index]

x[index:index]

x(arguments...)

x.attribute

Subscription, slicing, call, attribute

reference

(expressions...)

[expressions...]

{key:

value...}

`expressions...`

Binding or tuple display, list 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.

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[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

. The function

math.fmod()

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

[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 CAPITAL 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

operator, like those involving comparisons between instance methods, or constants.

Check their documentation for more info.

[8] The

operator is also used for string formatting; the same precedence applies.

[9]

The power operator

binds less tightly than an arithmetic or bitwise unary operator

on its right, that is,

2**-1

0.5

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6. Simple statements

Simple statements are comprised within a single logical line. Several simple statements

may occur on a single line separated by semicolons. The syntax for simple statements is:

simple_stmt ::= expression_stmt

| assert_stmt

| assignment_stmt

| augmented_assignment_stmt

| pass_stmt

| del_stmt

| print_stmt

| return_stmt

| yield_stmt

| raise_stmt

| break_stmt

| continue_stmt

| import_stmt

| global_stmt

| exec_stmt

6.1. Expression statements

Expression statements are used (mostly interactively) to compute and write a value, or

(usually) to call a procedure (a function that returns no meaningful result; in Python,

procedures return the value

None

). Other uses of expression statements are allowed and

occasionally useful. The syntax for an expression statement is:

expression_stmt ::= expression_list

An expression statement evaluates the expression list (which may be a single

expression).

In interactive mode, if the value is not

None

, it is converted to a string using the built-in

repr()

function and the resulting string is written to standard output (see section The

print statement) on a line by itself. (Expression statements yielding

None

are not written,

so that procedure calls do not cause any output.)

6.2. Assignment statements

Assignment statements are used to (re)bind names to values and to modify attributes or

items of mutable objects:

Python » Python v2.7.6 documentation » The Python Language Reference »

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 an iterable

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.

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 an iterable 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

Note: If the object is a class instance and the attribute reference occurs on both

sides of the assignment operator, the RHS expression,

a.x

can access either an

instance attribute or (if no instance attribute exists) a class attribute. The LHS target

a.x

is always set as an instance attribute, creating it if necessary. Thus, the two

occurrences of

a.x

do not necessarily refer to the same attribute: if the RHS

expression refers to a class attribute, the LHS creates a new instance attribute as

the target of the assignment:

class Cls:

x = 3 # class variable

inst = Cls()

inst.x = inst.x + 1 # writes inst.x as 4 leaving Cls.x as 3

This description does not necessarily apply to descriptor attributes, such as

properties created with

property()

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.

CPython implementation detail: 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

6.2.1. Augmented assignment statements

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

and an assignment statement:

augmented_assignment_stmt ::= augtarget augop (expression_list | yield_expression

augtarget ::= identifier | attributeref | subscription | slicing

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

achieve a similar, but not exactly equal effect. In the augmented version,

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 same caveat about class and instance

attributes applies as for regular assignments.

6.3. 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__

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.

6.4. The

pass

statement

pass_stmt ::= "pass"

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