% Format this file with latex.

\documentstyle[11pt,myformat]{report}

\title{\bf

Python Reference Manual

}

\author{

Guido van Rossum \\

Dept. CST, CWI, Kruislaan 413 \\

1098 SJ Amsterdam, The Netherlands \\

E-mail: {\tt [email protected]}

}

\begin{document}

\pagenumbering{roman}

\maketitle

\begin{abstract}

\noindent

Python is a simple, yet powerful, interpreted programming language

that bridges the gap between C and shell programming, and is thus

ideally suited for ``throw-away programming'' and rapid prototyping.

Its syntax is put together from constructs borrowed from a variety of

other languages; most prominent are influences from ABC, C, Modula-3

and Icon.

The Python interpreter is easily extended with new functions and data

types implemented in C. Python is also suitable as an extension

language for highly customizable C applications such as editors or

window managers.

Python is available for various operating systems, amongst which

several flavors of {\UNIX}, Amoeba, the Apple Macintosh O.S.,

and MS-DOS.

This reference manual describes the syntax and ``core semantics'' of

the language. It is terse, but attempts to be exact and complete.

The semantics of non-essential built-in object types and of the

built-in functions and modules are described in the {\em Python

Library Reference}. For an informal introduction to the language, see

the {\em Python Tutorial}.

\end{abstract}

\pagebreak

{

\parskip = 0mm

\tableofcontents

}

\pagebreak

\pagenumbering{arabic}

\chapter{Introduction}

This reference manual describes the Python programming language.

It is not intended as a tutorial.

While I am trying to be as precise as possible, I chose to use English

rather than formal specifications for everything except syntax and

lexical analysis. This should make the document better understandable

to the average reader, but will leave room for ambiguities.

Consequently, if you were coming from Mars and tried to re-implement

Python from this document alone, you might have to guess things and in

fact you would be implementing quite a different language.

On the other hand, if you are using

Python and wonder what the precise rules about a particular area of

the language are, you should definitely be able to find it here.

It is dangerous to add too many implementation details to a language

reference document -- the implementation may change, and other

implementations of the same language may work differently. On the

other hand, there is currently only one Python implementation, and

its particular quirks are sometimes worth being mentioned, especially

where the implementation imposes additional limitations.

Every Python implementation comes with a number of built-in and

standard modules. These are not documented here, but in the separate

{\em Python Library Reference} document. A few built-in modules are

mentioned when they interact in a significant way with the language

definition.

\section{Notation}

The descriptions of lexical analysis and syntax use a modified BNF

grammar notation. This uses the following style of definition:

\begin{verbatim}

name: lc_letter (lc_letter | "_")*

lc_letter: "a"..."z"

\end{verbatim}

The first line says that a \verb\name\ is an \verb\lc_letter\ followed by

a sequence of zero or more \verb\lc_letter\s and underscores. An

\verb\lc_letter\ in turn is any of the single characters `a' through `z'.

(This rule is actually adhered to for the names defined in syntax and

grammar rules in this document.)

Each rule begins with a name (which is the name defined by the rule)

and a colon. A vertical bar

(\verb\|\) is used to separate alternatives; it is the least binding

operator in this notation. A star (\verb\*\) means zero or more

repetitions of the preceding item; likewise, a plus (\verb\+\) means

one or more repetitions, and a question mark (\verb\?\) zero or one

(in other words, the preceding item is optional). These three

operators bind as tightly as possible; parentheses are used for

grouping. Literal strings are enclosed in double quotes. White space

is only meaningful to separate tokens. Rules are normally contained

on a single line; rules with many alternatives may be formatted

alternatively with each line after the first beginning with a

vertical bar.

In lexical definitions (as the example above), two more conventions

are used: Two literal characters separated by three dots mean a choice

of any single character in the given (inclusive) range of ASCII

characters. A phrase between angular brackets (\verb\<...>\) gives an

informal description of the symbol defined; e.g., this could be used

to describe the notion of `control character' if needed.

Even though the notation used is almost the same, there is a big

difference between the meaning of lexical and syntactic definitions:

a lexical definition operates on the individual characters of the

input source, while a syntax definition operates on the stream of

tokens generated by the lexical analysis.

\chapter{Lexical analysis}

A Python program is read by a {\em parser}. Input to the parser is a

stream of {\em tokens}, generated by the {\em lexical analyzer}. This

chapter describes how the lexical analyzer breaks a file into tokens.

\section{Line structure}

A Python program is divided in a number of logical lines. The end of

a logical line is represented by the token NEWLINE. Statements cannot

cross logical line boundaries except where NEWLINE is allowed by the

syntax (e.g., between statements in compound statements).

\subsection{Comments}

A comment starts with a hash character (\verb\#\) that is not part of

a string literal, and ends at the end of the physical line. A comment

always signifies the end of the logical line. Comments are ignored by

the syntax.

\subsection{Line joining}

Two or more physical lines may be joined into logical lines using

backslash characters (\verb/\/), as follows: when a physical line ends

in a backslash that is not part of a string literal or comment, it is

joined with the following forming a single logical line, deleting the

backslash and the following end-of-line character. For example:

%

\begin{verbatim}

moth_names = ['Januari', 'Februari', 'Maart', \

'April', 'Mei', 'Juni', \

'Juli', 'Augustus', 'September', \

'Oktober', 'November', 'December']

\end{verbatim}

\subsection{Blank lines}

A logical line that contains only spaces, tabs, and possibly a

comment, is ignored (i.e., no NEWLINE token is generated), except that

during interactive input of statements, an entirely blank logical line

terminates a multi-line statement.

\subsection{Indentation}

Leading whitespace (spaces and tabs) at the beginning of a logical

line is used to compute the indentation level of the line, which in

turn is used to determine the grouping of statements.

First, tabs are replaced (from left to right) by one to eight spaces

such that the total number of characters up to there is a multiple of

eight (this is intended to be the same rule as used by UNIX). The

total number of spaces preceding the first non-blank character then

determines the line's indentation. Indentation cannot be split over

multiple physical lines using backslashes.

The indentation levels of consecutive lines are used to generate

INDENT and DEDENT tokens, using a stack, as follows.

Before the first line of the file is read, a single zero is pushed on

the stack; this will never be popped off again. The numbers pushed on

the stack will always be strictly increasing from bottom to top. At

the beginning of each logical line, the line's indentation level is

compared to the top of the stack. If it is equal, nothing happens.

If it larger, it is pushed on the stack, and one INDENT token is

generated. If it is smaller, it {\em must} be one of the numbers

occurring on the stack; all numbers on the stack that are larger are

popped off, and for each number popped off a DEDENT token is

generated. At the end of the file, a DEDENT token is generated for

each number remaining on the stack that is larger than zero.

Here is an example of a correctly (though confusingly) indented piece

of Python code:

\begin{verbatim}

def perm(l):

# Compute the list of all permutations of l

if len(l) <= 1:

return [l]

r = []

for i in range(len(l)):

s = l[:i] + l[i+1:]

p = perm(s)

for x in p:

r.append(l[i:i+1] + x)

return r

\end{verbatim}

The following example shows various indentation errors:

\begin{verbatim}

def perm(l): # error: first line indented

for i in range(len(l)): # error: not indented

s = l[:i] + l[i+1:]

p = perm(l[:i] + l[i+1:]) # error: unexpected indent

for x in p:

r.append(l[i:i+1] + x)

return r # error: inconsistent indent

\end{verbatim}

(Actually, the first three errors are detected by the parser; only the

last error is found by the lexical analyzer -- the indentation of

\verb\return r\ does not match a level popped off the stack.)

\section{Other tokens}

Besides NEWLINE, INDENT and DEDENT, the following categories of tokens

exist: identifiers, keywords, literals, operators, and delimiters.

Spaces and tabs are not tokens, but serve to delimit tokens. Where

ambiguity exists, a token comprises the longest possible string that

forms a legal token, when read from left to right.

\section{Identifiers}

Identifiers are described by the following regular expressions:

\begin{verbatim}

identifier: (letter|"_") (letter|digit|"_")*

letter: lowercase | uppercase

lowercase: "a"..."z"

uppercase: "A"..."Z"

digit: "0"..."9"

\end{verbatim}

Identifiers are unlimited in length. Case is significant.

\subsection{Keywords}

The following identifiers are used as reserved words, or {\em

keywords} of the language, and cannot be used as ordinary

identifiers. They must be spelled exactly as written here:

\begin{verbatim}

and del for in print

break elif from is raise

class else global not return

continue except if or try

def finally import pass while

\end{verbatim}

% # This Python program sorts and formats the above table

% import string

% l = []

% try:

% while 1:

% l = l + string.split(raw_input())

% except EOFError:

% pass

% l.sort()

% for i in range((len(l)+4)/5):

% for j in range(i, len(l), 5):

% print string.ljust(l[j], 10),

% print

\section{Literals}

\subsection{String literals}

String literals are described by the following regular expressions:

\begin{verbatim}

stringliteral: "'" stringitem* "'"

stringitem: stringchar | escapeseq

stringchar: <any ASCII character except newline or "\" or "'">

escapeseq: "'" <any ASCII character except newline>

\end{verbatim}

String literals cannot span physical line boundaries. Escape

sequences in strings are actually interpreted according to rules

simular to those used by Standard C. The recognized escape sequences

are:

\begin{center}

\begin{tabular}{|l|l|}

\hline

\verb/\\/ & Backslash (\verb/\/) \\

\verb/\'/ & Single quote (\verb/'/) \\

\verb/\a/ & ASCII Bell (BEL) \\

\verb/\b/ & ASCII Backspace (BS) \\

%\verb/\E/ & ASCII Escape (ESC) \\

\verb/\f/ & ASCII Formfeed (FF) \\

\verb/\n/ & ASCII Linefeed (LF) \\

\verb/\r/ & ASCII Carriage Return (CR) \\

\verb/\t/ & ASCII Horizontal Tab (TAB) \\

\verb/\v/ & ASCII Vertical Tab (VT) \\

\verb/\/{\em ooo} & ASCII character with octal value {\em ooo} \\

\verb/\x/{em xx...} & ASCII character with hex value {\em xx...} \\

\hline

\end{tabular}

\end{center}

In strict compatibility with in Standard C, up to three octal digits are

accepted, but an unlimited number of hex digits is taken to be part of

the hex escape (and then the lower 8 bits of the resulting hex number

are used in all current implementations...).

All unrecognized escape sequences are left in the string unchanged,

i.e., {\em the backslash is left in the string.} (This rule is

useful when debugging: if an escape sequence is mistyped, the

resulting output is more easily recognized as broken. It also helps a

great deal for string literals used as regular expressions or

otherwise passed to other modules that do their own escape handling --

but you may end up quadrupling backslashes that must appear literally.)

\subsection{Numeric literals}

There are three types of numeric literals: plain integers, long

integers, and floating point numbers.

Integers and long integers are described by the following regular expressions:

\begin{verbatim}

longinteger: integer ("l"|"L")

integer: decimalinteger | octinteger | hexinteger

decimalinteger: nonzerodigit digit* | "0"

octinteger: "0" octdigit+

hexinteger: "0" ("x"|"X") hexdigit+

nonzerodigit: "1"..."9"

octdigit: "0"..."7"

hexdigit: digit|"a"..."f"|"A"..."F"

\end{verbatim}

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 decimal literals must be at most $2^{31} - 1$ (i.e., the

largest positive integer, assuming 32-bit arithmetic); octal and

hexadecimal literals may be as large as $2^{32} - 1$. There is no limit

for long integer literals.

Some examples of plain and long integer literals:

\begin{verbatim}

7 2147483647 0177 0x80000000

3L 79228162514264337593543950336L 0377L 0100000000L

\end{verbatim}

Floating point numbers are described by the following regular expressions:

\begin{verbatim}

floatnumber: pointfloat | exponentfloat

pointfloat: [intpart] fraction | intpart "."

exponentfloat: (intpart | pointfloat) exponent

intpart: digit+

fraction: "." digit+

exponent: ("e"|"E") ["+"|"-"] digit+

\end{verbatim}

The allowed range of floating point literals is

implementation-dependent.

Some examples of floating point literals:

\begin{verbatim}

3.14 10. .001 1e100 3.14e-10

\end{verbatim}

Note that numeric literals do not include a sign; a phrase like

\verb\-1\ is actually an expression composed of the operator

\verb\-\ and the literal \verb\1\.

\section{Operators}

The following tokens are operators:

\begin{verbatim}

+ - * / %

<< >> & | ^ ~

< == > <= <> != >=

\end{verbatim}

The comparison operators \verb\<>\ and \verb\!=\ are alternate

spellings of the same operator.

\section{Delimiters}

The following tokens serve as delimiters or otherwise have a special

meaning:

\begin{verbatim}

( ) [ ] { }

; , : . ` =

\end{verbatim}

The following printing ASCII characters are not used in Python (except

in string literals and in comments). Their occurrence is an

unconditional error:

\begin{verbatim}

! @ $ " ?

\end{verbatim}

They may be used by future versions of the language though!

\chapter{Execution model}

\section{Objects, values and types}

I won't try to define rigorously here what an object is, but I'll give

some properties of objects that are important to know about.

Every object has an identity, a type and a value. An object's {\em

identity} never changes once it has been created; think of it as the

object's (permanent) address. An object's {\em type} determines the

operations that an object supports (e.g., does it have a length?) and

also defines the ``meaning'' of the object's value. The type also

never changes. The {\em value} of some objects can change; whether

this is possible is a property of its type.

Objects are never explicitly destroyed; however, when they become

unreachable they may be garbage-collected. An implementation is

allowed to delay 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 which collects most objects as soon as they

become unreachable, but never collects garbage containing circular

references.)

Note that the use of the implementation's tracing or debugging

facilities may keep objects alive that would normally be collectable.

(Some objects contain references to ``external'' resources such as

open files. It is understood that these resources are freed when the

object is garbage-collected, but since garbage collection is not

guaranteed, such objects also provide an explicit way to release the

external resource (e.g., a \verb\close\ method). Programs are strongly

recommended to use this.)

Some objects contain references to other objects. These references

are part of the object's value; in most cases, when such a

``container'' object is compared to another (of the same type), the

comparison applies to the {\em values} of the referenced objects (not

their identities).

Types affect almost all aspects of objects.

Even 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

\begin{verbatim}

a = 1; b = 1; c = []; d = []

\end{verbatim}

\verb\a\ and \verb\b\ may or may not refer to the same object, but

\verb\c\ and \verb\d\ are guaranteed to refer to two different, unique,

newly created lists.

\section{Execution frames, name spaces, and scopes}

XXX code blocks, scopes, name spaces, name binding, exceptions

\chapter{The standard type hierarchy}

The following types are built into Python. Extension modules

written in C can define additional types. Future versions of Python

may also add types to the type hierarchy (e.g., rational or complex

numbers, lists of efficiently stored integers, etc.).

\begin{description}

\item[None]

This type has a single value. There is a single object with this value.

This object is accessed through the built-in name \verb\None\.

It is returned from functions that don't explicitly return an object.

\item[Numbers]

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 and floating point numbers:

\begin{description}

\item[Integers]

These represent elements from the mathematical set of whole numbers.

There are two types of integers:

\begin{description}

\item[Plain integers]

These represent numbers in the range $-2^{31}$ through $2^{31}-1$.

(The range may be larger on machines with a larger natural word

size, but not smaller.)

When the result of an operation falls outside this range, the

exception \verb\OverflowError\ is raised.

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 $2^{32}$ different bit

patterns correspond to different values).

\item[Long integers]

These represent numbers in an unlimited range, subject to avaiable

(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.

\end{description} % Integers

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. For any operation except left shift,

if it yields a result in the plain integer domain without causing

overflow, it will yield the same result in the long integer domain or

when using mixed operands.

\item[Floating point numbers]

These represent machine-level double precision floating point numbers.

You are at the mercy of the underlying machine architecture and

C implementation for the accepted range and handling of overflow.

\end{description} % Numbers

\item[Sequences]

These represent finite ordered sets indexed by natural numbers.

The built-in function \verb\len()\ returns the number of elements

of a sequence. When this number is $n$, the index set contains

the numbers $0, 1, \ldots, n-1$. Element \verb\i\ of sequence

\verb\a\ is selected by \verb\a[i]\.

Sequences also support slicing: \verb\a[i:j]\ selects all elements

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 again.

Sequences are distinguished according to their mutability:

\begin{description}

%

\item[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:

\begin{description}

\item[Strings]

The elements of a string are characters. There is no separate

character type; a character is represented by a string of one element.

Characters represent (at least) 8-bit bytes. The built-in

functions \verb\chr()\ and \verb\ord()\ convert between characters

and nonnegative integers representing the byte values.

Bytes with the values 0-127 represent the corresponding ASCII values.

(On systems whose native character set is not ASCII, strings may use

EBCDIC in their internal representation, provided the functions

\verb\chr()\ and \verb\ord()\ implement a mapping between ASCII and

EBCDIC, and string comparisons preserve the ASCII order.

Or perhaps someone can propose a better rule?)

\item[Tuples]

The elements of a tuple are arbitrary Python objects.

Tuples of two or more elements are formed by comma-separated lists

of expressions. A tuple of one element can be formed by affixing

a comma to an expression (an expression by itself of course does

not create a tuple). An empty tuple can be formed by enclosing

`nothing' in parentheses.

\end{description} % Immutable sequences

\item[Mutable sequences]

Mutable sequences can be changed after they are created.

The subscript and slice notations can be used as the target

of assignment and \verb\del\ (delete) statements.

There is currently a single mutable sequence type:

\begin{description}

\item[Lists]

The elements 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 for lists

of length 0 or 1.)

\end{description} % Mutable sequences

\end{description} % Sequences

\item[Mapping types]

These represent finite sets of objects indexed by arbitrary index sets.

The subscript notation \verb\a[k]\ selects the element indexed

by \verb\k\ from the mapping \verb\a\; this can be used in

expressions and as the target of assignments or \verb\del\ statements.

The built-in function \verb\len()\ returns the number of elements

in a mapping.

There is currently a single mapping type:

\begin{description}

\item[Dictionaries]

These represent finite sets of objects indexed by strings.

Dictionaries are created by the \verb\{...}\ notation (see section

\ref{dict}). (Implementation note: the strings used for indexing must

not contain null bytes.)

\end{description} % Mapping types

\item[Callable types]

These are the types to which the function call operation (written as

\verb\function(argument, argument, ...)\) can be applied:

\begin{description}

\item[User-defined functions]

A user-defined function is created by a function definition (starting

with the \verb\def\ keyword). It should be called with an argument

list containing the same number of items as the function's

formal parameter list.

Special read-only attributes: \verb\func_code\ is the code object

representing the compiled function body, and \verb\func_globals\ is (a

reference to) the dictionary that holds the function's global

variables -- it implements the global name space of the module in

which the function was defined.

\item[User-defined methods]

A user-defined method (a.k.a. {\tt object closure}) is a pair of a

class instance object and a user-defined function. It should be

called with an argument list containing one item less than the number

of items in the function's formal parameter list. When called, the

class instance becomes the first argument, and the call arguments are

shifted one to the right.

Special read-only attributes: \verb\im_self\ is the class instance

object, \verb\im_func\ is the function object.

\item[Built-in functions]

A built-in function object is a wrapper around a C function. Examples

of built-in functions are \verb\len\ and \verb\math.sin\. There

are no special attributes. The number and type of the arguments are

determined by the C function.

\item[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 \verb\list.append\ if

\verb\list\ is a list object.

\item[Classes]

Class objects are described below. When a class object is called as a

parameterless function, a new class instance (also described below) is

created and returned. The class's initialization function is not

called -- this is the responsibility of the caller. It is illegal to

call a class object with one or more arguments.

\end{description}

\item[Modules]

A module object is a container for a module's name space, which is a

dictionary (the same dictionary as referenced by the

\ver\func_globals\ attribute of functions defined in the module).

Module attribute references are translated to lookups in this

dictionary. A module object does not contain the code object used to

initialize the module (since it isn't needed once the initialization

is done).

There are two special read-only attributes: \verb\__dict__\ yields the

module's name space as a dictionary object; \verb\__name__\ yields the

module's name.

\item[Classes]

XXX

\item[Class instances]

XXX

\item[Files]

A file object represents an open file. (It is a wrapper around a C

{\tt stdio} file pointer.) File objects are created by the

\verb\open()\ built-in function, and also by \verb\posix.popen()\ and

the \verb\makefile\ method of socket objects. \verb\sys.stdin\,

\verb\sys.stdout\ and \verb\sys.stderr\ are file objects corresponding

the the interpreter's standard input, output and error streams.

See the Python Library Reference for methods of file objects and other

details.

\item[Internal types]

A few types used internally by the interpreter are exposed to the user.

Their definition may change with future versions of the interpreter,

but they are mentioned here for completeness.

\begin{description}

\item[Code objects]

Code objects represent executable code. The difference between a code

object and a function object is that the function object contains an

explicit reference to the function's context (the module in which it

was defined) which a code object contains no context. There is no way

to execute a bare code object.

Special read-only attributes: \verb\co_code\ is a string representing

the sequence of instructions; \verb\co_consts\ is a list of literals

used by the code; \verb\co_names\ is a list of names (strings) used by

the code; \verb\co_filename\ is the filename from which the code was

compiled. (To find out the line numbers, you would have to decode the

instructions; the standard library module \verb\dis\ contains an

example of how to do this.)

\item[Frame objects]

Frame objects represent execution frames. They may occur in traceback

objects (see below).

Special read-only attributes: \verb\f_back\ is to the previous

stack frame (towards the caller), or \verb\None\ if this is the bottom

stack frame; \verb\f_code\ is the code object being executed in this

frame; \verb\f_globals\ is the dictionary used to look up global

variables; \verb\f_locals\ is used for local variables;

\verb\f_lineno\ gives the line number and \verb\f_lasti\ gives the

precise instruction (this is an index into the instruction string of

the code object).

\item[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 as \verb\sys.exc_traceback\. 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 made available to the user as

\verb\sys.last_traceback\.

Special read-only attributes: \verb\tb_next\ is the next level in the

stack trace (towards the frame where the exception occurred), or

\verb\None\ if there is no next level; \verb\tb_frame\ points to the

execution frame of the current level; \verb\tb_lineno\ gives the line

number where the exception occurred; \verb\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 \verb\try\ statement with no matching

\verb\except\ clause or with a \verb\finally\ clause.

\end{description} % Internal types

\end{description} % Types

\chapter{Expressions and conditions}

From now on, extended BNF notation will be used to describe syntax,

not lexical analysis.

This chapter explains the meaning of the elements of expressions and

conditions. Conditions are a superset of expressions, and a condition

may be used wherever an expression is required by enclosing it in

parentheses. The only places where expressions are used in the syntax

instead of conditions is in expression statements and on the

right-hand side of assignments; this catches some nasty bugs like

accedentally writing \verb\x == 1\ instead of \verb\x = 1\.

The comma has several roles in Python's syntax. It is usually an

operator with a lower precedence than all others, but occasionally

serves other purposes as well; e.g., it separates function arguments,

is used in list and dictionary constructors, and has special semantics

in \verb\print\ statements.

When (one alternative of) a syntax rule has the form

\begin{verbatim}

name: othername

\end{verbatim}

and no semantics are given, the semantics of this form of \verb\name\

are the same as for \verb\othername\.

\section{Arithmetic conversions}

When a description of an arithmetic operator below uses the phrase

``the numeric arguments are converted to a common type'',

this both means that if either argument is not a number, a

\verb\TypeError\ exception is raised, and that otherwise

the following conversions are applied:

\begin{itemize}

\item first, if either argument is a floating point number,

the other is converted to floating point;

\item else, if either argument is a long integer,

the other is converted to long integer;

\item otherwise, both must be plain integers and no conversion

is necessary.

\end{itemize}

\section{Atoms}

Atoms are the most basic elements of expressions. Forms enclosed in

reverse quotes or in parentheses, brackets or braces are also

categorized syntactically as atoms. The syntax for atoms is:

\begin{verbatim}

atom: identifier | literal | enclosure

enclosure: parenth_form | list_display | dict_display | string_conversion

\end{verbatim}

\subsection{Identifiers (Names)}

An identifier occurring as an atom is a reference to a local, global

or built-in name binding. If a name can be assigned to anywhere in a

code block, and is not mentioned in a \verb\global\ statement in that

code block, it refers to a local name throughout that code block.

Otherwise, it refers to a global name if one exists, else to a

built-in name.

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 \verb\NameError\ exception.

\subsection{Literals}

Python knows string and numeric literals:

\begin{verbatim}

literal: stringliteral | integer | longinteger | floatnumber

\end{verbatim}

Evaluation of a literal yields an object of the given type

(string, integer, long integer, floating point number)

with the given value.

The value may be approximated in the case of floating point literals.

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.

(In the original implementation, all literals in the same code block

with the same type and value yield the same object.)

\subsection{Parenthesized forms}

A parenthesized form is an optional condition list enclosed in

parentheses:

\begin{verbatim}

parenth_form: "(" [condition_list] ")"

\end{verbatim}

A parenthesized condition list yields whatever that condition list

yields.

An empty pair of parentheses yields an empty tuple object. Since

tuples are immutable, the rules for literals apply here.

(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 {\em are} required -- allowing unparenthesized ``nothing''

in expressions would causes ambiguities and allow common typos to

pass uncaught.)

\subsection{List displays}

A list display is a possibly empty series of conditions enclosed in

square brackets:

\begin{verbatim}

list_display: "[" [condition_list] "]"

\end{verbatim}

A list display yields a new list object.

If it has no condition list, the list object has no items.

Otherwise, the elements of the condition list are evaluated

from left to right and inserted in the list object in that order.

\subsection{Dictionary displays} \label{dict}

A dictionary display is a possibly empty series of key/datum pairs

enclosed in curly braces:

\begin{verbatim}

dict_display: "{" [key_datum_list] "}"

key_datum_list: [key_datum ("," key_datum)* [","]

key_datum: condition ":" condition

\end{verbatim}

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.

Keys must be strings, otherwise a \verb\TypeError\ exception is raised.

Clashes between duplicate keys are not detected; the last datum

(textually rightmost in the display) stored for a given key value

prevails.

\subsection{String conversions}

A string conversion is a condition list enclosed in reverse (or

backward) quotes:

\begin{verbatim}

string_conversion: "`" condition_list "`"

\end{verbatim}

A string conversion evaluates the contained condition list and converts the

resulting object into a string according to rules specific to its type.

If the object is a string, a number, \verb\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 \verb\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.)

It is illegal to attempt to convert recursive objects (e.g., lists or

dictionaries that contain a reference to themselves, directly or

indirectly.)

\section{Primaries}

Primaries represent the most tightly bound operations of the language.

Their syntax is:

\begin{verbatim}

primary: atom | attributeref | subscription | slicing | call

\end{verbatim}

\subsection{Attribute references}

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

\begin{verbatim}

attributeref: primary "." identifier

\end{verbatim}

The primary must evaluate to an object of a type that supports

attribute references, e.g., a module or a list. This object is then

asked to produce the attribute whose name is the identifier. If this

attribute is not available, the exception \verb\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.

\subsection{Subscriptions}

A subscription selects an item of a sequence or mapping object:

\begin{verbatim}

subscription: primary "[" condition "]"

\end{verbatim}

The primary must evaluate to an object of a sequence or mapping type.

If it is a mapping, the condition 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.

If it is a sequence, the condition must evaluate to a plain integer.

If this value is negative, the length of the sequence is added to it

(so that, e.g., \verb\x[-1]\ selects the last item of \verb\x\.)