This is /home/pdm/install/Python-2.1/Doc/ref/python-ref.info, produced by makeinfo version 4.0 from ref.texi. April 15, 2001 2.1  File: python-ref.info, Node: Top, Next: Front Matter, Prev: (dir), Up: (dir) Python Reference Manual *********************** * Menu: * Front Matter:: * Introduction:: * Lexical analysis:: * Data model:: * Execution model:: * Expressions:: * Simple statements:: * Compound statements:: * Top-level components:: * Future statements and nested scopes:: * Module Index:: * Class-Exception-Object Index:: * Function-Method-Variable Index:: * Miscellaneous Index::  File: python-ref.info, Node: Front Matter, Next: Introduction, Prev: Top, Up: Top Front Matter ************ Copyright (C) 2001 Python Software Foundation. All rights reserved. Copyright (C) 2000 BeOpen.com. All rights reserved. Copyright (C) 1995-2000 Corporation for National Research Initiatives. All rights reserved. Copyright (C) 1991-1995 Stichting Mathematisch Centrum. All rights reserved. *BEOPEN PYTHON OPEN SOURCE LICENSE AGREEMENT VERSION 1* 1. This LICENSE AGREEMENT is between BeOpen.com ("BeOpen"), having an office at 160 Saratoga Avenue, Santa Clara, CA 95051, and the Individual or Organization ("Licensee") accessing and otherwise using this software in source or binary form and its associated documentation ("the Software"). 2. Subject to the terms and conditions of this BeOpen Python License Agreement, BeOpen hereby grants Licensee a non-exclusive, royalty-free, world-wide license to reproduce, analyze, test, perform and/or display publicly, prepare derivative works, distribute, and otherwise use the Software alone or in any derivative version, provided, however, that the BeOpen Python License is retained in the Software, alone or in any derivative version prepared by Licensee. 3. BeOpen is making the Software available to Licensee on an "AS IS" basis. BEOPEN MAKES NO REPRESENTATIONS OR WARRANTIES, EXPRESS OR IMPLIED. 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This Agreement may also be obtained from a proxy server on the Internet using the following URL: . *CWI PERMISSIONS STATEMENT AND DISCLAIMER* Copyright (C) 1991 - 1995, Stichting Mathematisch Centrum Amsterdam, The Netherlands. All rights reserved. Permission to use, copy, modify, and distribute this software and its documentation for any purpose and without fee is hereby granted, provided that the above copyright notice appear in all copies and that both that copyright notice and this permission notice appear in supporting documentation, and that the name of Stichting Mathematisch Centrum or CWI not be used in advertising or publicity pertaining to distribution of the software without specific, written prior permission. STICHTING MATHEMATISCH CENTRUM DISCLAIMS ALL WARRANTIES WITH REGARD TO THIS SOFTWARE, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS, IN NO EVENT SHALL STICHTING MATHEMATISCH CENTRUM BE LIABLE FOR ANY SPECIAL, INDIRECT OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE. Python is an interpreted, object-oriented, high-level programming language with dynamic semantics. Its high-level built in data structures, combined with dynamic typing and dynamic binding, make it very attractive for rapid application development, as well as for use as a scripting or glue language to connect existing components together. Python's simple, easy to learn syntax emphasizes readability and therefore reduces the cost of program maintenance. Python supports modules and packages, which encourages program modularity and code reuse. The Python interpreter and the extensive standard library are available in source or binary form without charge for all major platforms, and can be freely distributed. 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 . For an informal introduction to the language, see the . For C or C++ programmers, two additional manuals exist: describes the high-level picture of how to write a Python extension module, and the describes the interfaces available to C/C++ programmers in detail.  File: python-ref.info, Node: Introduction, Next: Lexical analysis, Prev: Front Matter, Up: Top 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 more 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 probably end up 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 them here. If you would like to see a more formal definition of the language, maybe you could volunteer your time -- or invent a cloning machine :-). 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 in widespread use (although a second one now exists!), and its particular quirks are sometimes worth being mentioned, especially where the implementation imposes additional limitations. Therefore, you'll find short "implementation notes" sprinkled throughout the text. Every Python implementation comes with a number of built-in and standard modules. These are not documented here, but in the separate document. A few built-in modules are mentioned when they interact in a significant way with the language definition. * Menu: * Notation::  File: python-ref.info, Node: Notation, Prev: Introduction, Up: Introduction Notation ======== The descriptions of lexical analysis and syntax use a modified BNF grammar notation. This uses the following style of definition: name: lc_letter (lc_letter | "_")* lc_letter: "a"..."z" The first line says that a `name' is an `lc_letter' followed by a sequence of zero or more `lc_letter's and underscores. An `lc_letter' in turn is any of the single characters `a' through `z'. (This rule is actually adhered to for the names defined in lexical 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 (`|') is used to separate alternatives; it is the least binding operator in this notation. A star (`*') means zero or more repetitions of the preceding item; likewise, a plus (`+') means one or more repetitions, and a phrase enclosed in square brackets (`[ ]') means zero or one occurrences (in other words, the enclosed phrase is optional). The `*' and `+' operators bind as tightly as possible; parentheses are used for grouping. Literal strings are enclosed in 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 (`<...>') 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. All uses of BNF in the next chapter ("Lexical Analysis") are lexical definitions; uses in subsequent chapters are syntactic definitions.  File: python-ref.info, Node: Lexical analysis, Next: Data model, Prev: Introduction, Up: Top Lexical analysis **************** A Python program is read by a _parser_. Input to the parser is a stream of _tokens_, generated by the _lexical analyzer_. This chapter describes how the lexical analyzer breaks a file into tokens. Python uses the 7-bit ASCII character set for program text and string literals. 8-bit characters may be used in string literals and comments but their interpretation is platform dependent; the proper way to insert 8-bit characters in string literals is by using octal or hexadecimal escape sequences. The run-time character set depends on the I/O devices connected to the program but is generally a superset of ASCII. *Future compatibility note:* It may be tempting to assume that the character set for 8-bit characters is ISO Latin-1 (an ASCII superset that covers most western languages that use the Latin alphabet), but it is possible that in the future Unicode text editors will become common. These generally use the UTF-8 encoding, which is also an ASCII superset, but with very different use for the characters with ordinals 128-255. While there is no consensus on this subject yet, it is unwise to assume either Latin-1 or UTF-8, even though the current implementation appears to favor Latin-1. This applies both to the source character set and the run-time character set. * Menu: * Line structure:: * Other tokens:: * Identifiers and keywords:: * Literals:: * Operators:: * Delimiters::  File: python-ref.info, Node: Line structure, Next: Other tokens, Prev: Lexical analysis, Up: Lexical analysis Line structure ============== A Python program is divided into a number of _logical lines_. * Menu: * Logical lines:: * Physical lines:: * Comments:: * Explicit line joining:: * Implicit line joining:: * Blank lines blank line:: * Indentation:: * Whitespace between tokens::  File: python-ref.info, Node: Logical lines, Next: Physical lines, Prev: Line structure, Up: Line structure 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). A logical line is constructed from one or more _physical lines_ by following the explicit or implicit _line joining_ rules.  File: python-ref.info, Node: Physical lines, Next: Comments, Prev: Logical lines, Up: Line structure Physical lines -------------- A physical line ends in whatever the current platform's convention is for terminating lines. On UNIX, this is the ASCII LF (linefeed) character. On DOS/Windows, it is the ASCII sequence CR LF (return followed by linefeed). On Macintosh, it is the ASCII CR (return) character.  File: python-ref.info, Node: Comments, Next: Explicit line joining, Prev: Physical lines, Up: Line structure Comments -------- A comment starts with a hash character (`#') that is not part of a string literal, and ends at the end of the physical line. A comment signifies the end of the logical line unless the implicit line joining rules are invoked. Comments are ignored by the syntax; they are not tokens.  File: python-ref.info, Node: Explicit line joining, Next: Implicit line joining, Prev: Comments, Up: Line structure Explicit line joining --------------------- Two or more physical lines may be joined into logical lines using backslash characters (`\'), 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: if 1900 < year < 2100 and 1 <= month <= 12 \ and 1 <= day <= 31 and 0 <= hour < 24 \ and 0 <= minute < 60 and 0 <= second < 60: # Looks like a valid date return 1 A line ending in a backslash cannot carry a comment. A backslash does not continue a comment. A backslash does not continue a token except for string literals (i.e., tokens other than string literals cannot be split across physical lines using a backslash). A backslash is illegal elsewhere on a line outside a string literal.  File: python-ref.info, Node: Implicit line joining, Next: Blank lines blank line, Prev: Explicit line joining, Up: Line structure Implicit line joining --------------------- Expressions in parentheses, square brackets or curly braces can be split over more than one physical line without using backslashes. For example: month_names = ['Januari', 'Februari', 'Maart', # These are the 'April', 'Mei', 'Juni', # Dutch names 'Juli', 'Augustus', 'September', # for the months 'Oktober', 'November', 'December'] # of the year Implicitly continued lines can carry comments. The indentation of the continuation lines is not important. Blank continuation lines are allowed. There is no NEWLINE token between implicit continuation lines. Implicitly continued lines can also occur within triple-quoted strings (see below); in that case they cannot carry comments.  File: python-ref.info, Node: Blank lines blank line, Next: Indentation, Prev: Implicit line joining, Up: Line structure Blank lines ----------- A logical line that contains only spaces, tabs, formfeeds and possibly a comment, is ignored (i.e., no NEWLINE token is generated). During interactive input of statements, handling of a blank line may differ depending on the implementation of the read-eval-print loop. In the standard implementation, an entirely blank logical line (i.e. one containing not even whitespace or a comment) terminates a multi-line statement.  File: python-ref.info, Node: Indentation, Next: Whitespace between tokens, Prev: Blank lines blank line, Up: Line structure 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 and including the replacement 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 whitespace up to the first backslash determines the indentation. *Cross-platform compatibility note:* because of the nature of text editors on non-UNIX platforms, it is unwise to use a mixture of spaces and tabs for the indentation in a single source file. A formfeed character may be present at the start of the line; it will be ignored for the indentation calculations above. Formfeed characters occurring elsewhere in the leading whitespace have an undefined effect (for instance, they may reset the space count to zero). 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 is larger, it is pushed on the stack, and one INDENT token is generated. If it is smaller, it _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: 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 The following example shows various indentation errors: 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 dedent (Actually, the first three errors are detected by the parser; only the last error is found by the lexical analyzer -- the indentation of `return r' does not match a level popped off the stack.)  File: python-ref.info, Node: Whitespace between tokens, Prev: Indentation, Up: Line structure Whitespace between tokens ------------------------- Except at the beginning of a logical line or in string literals, the whitespace characters space, tab and formfeed can be used interchangeably to separate tokens. Whitespace is needed between two tokens only if their concatenation could otherwise be interpreted as a different token (e.g., ab is one token, but a b is two tokens).  File: python-ref.info, Node: Other tokens, Next: Identifiers and keywords, Prev: Line structure, Up: Lexical analysis Other tokens ============ Besides NEWLINE, INDENT and DEDENT, the following categories of tokens exist: _identifiers_, _keywords_, _literals_, _operators_, and _delimiters_. Whitespace characters (other than line terminators, discussed earlier) 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.  File: python-ref.info, Node: Identifiers and keywords, Next: Literals, Prev: Other tokens, Up: Lexical analysis Identifiers and keywords ======================== Identifiers (also referred to as _names_) are described by the following lexical definitions: identifier: (letter|"_") (letter|digit|"_")* letter: lowercase | uppercase lowercase: "a"..."z" uppercase: "A"..."Z" digit: "0"..."9" Identifiers are unlimited in length. Case is significant. * Menu: * Keywords:: * Reserved classes of identifiers::  File: python-ref.info, Node: Keywords, Next: Reserved classes of identifiers, Prev: Identifiers and keywords, Up: Identifiers and keywords Keywords -------- The following identifiers are used as reserved words, or _keywords_ of the language, and cannot be used as ordinary identifiers. They must be spelled exactly as written here: and del for is raise assert elif from lambda return break else global not try class except if or while continue exec import pass def finally in print  File: python-ref.info, Node: Reserved classes of identifiers, Prev: Keywords, Up: Identifiers and keywords Reserved classes of identifiers ------------------------------- Certain classes of identifiers (besides keywords) have special meanings. These are: Form Meaning Notes ------ ----- ----- _* Not imported by `from (1) MODULE import *' __*__ System-defined name __* Class-private name mangling (XXX need section references here.) Note: `(1)' The special identifier `_' is used in the interactive interpreter to store the result of the last evaluation; it is stored in the `__builtin__' module. When not in interactive mode, `_' has no special meaning and is not defined.  File: python-ref.info, Node: Literals, Next: Operators, Prev: Identifiers and keywords, Up: Lexical analysis Literals ======== Literals are notations for constant values of some built-in types. * Menu: * String literals:: * String literal concatenation:: * Unicode literals:: * Numeric literals:: * Integer and long integer literals:: * Floating point literals:: * Imaginary literals::  File: python-ref.info, Node: String literals, Next: String literal concatenation, Prev: Literals, Up: Literals String literals --------------- String literals are described by the following lexical definitions: stringliteral: shortstring | longstring shortstring: "'" shortstringitem* "'" | '"' shortstringitem* '"' longstring: "'''" longstringitem* "'''" | '"""' longstringitem* '"""' shortstringitem: shortstringchar | escapeseq longstringitem: longstringchar | escapeseq shortstringchar: longstringchar: escapeseq: "\" In plain English: String literals can be enclosed in matching single quotes (`'') or double quotes (`"'). They can also be enclosed in matching groups of three single or double quotes (these are generally referred to as _triple-quoted strings_). The backslash (`\') character is used to escape characters that otherwise have a special meaning, such as newline, backslash itself, or the quote character. String literals may optionally be prefixed with a letter `r' or `R'; such strings are called "raw strings" and use different rules for backslash escape sequences. A prefix of 'u' or 'U' makes the string a Unicode string. Unicode strings use the Unicode character set as defined by the Unicode Consortium and ISO~10646. Some additional escape sequences, described below, are available in Unicode strings. In triple-quoted strings, unescaped newlines and quotes are allowed (and are retained), except that three unescaped quotes in a row terminate the string. (A "quote" is the character used to open the string, i.e. either `'' or `"'.) Unless an `r' or `R' prefix is present, escape sequences in strings are interpreted according to rules similar to those used by Standard C. The recognized escape sequences are: Escape Sequence Meaning ------ ----- \NEWLINE Ignored \\ Backslash (`\') \' Single quote (`'') \" Double quote (`"') \a ASCII Bell (BEL) \b ASCII Backspace (BS) \f ASCII Formfeed (FF) \n ASCII Linefeed (LF) \N{NAME} Character named NAME in the Unicode database (Unicode only) \r ASCII Carriage Return (CR) \t ASCII Horizontal Tab (TAB) \uXXXX Character with 16-bit hex value XXXX (Unicode only) \UXXXXXXXX Character with 32-bit hex value XXXXXXXX (Unicode only) \v ASCII Vertical Tab (VT) \OOO ASCII character with octal value OOO \xHH ASCII character with hex value HH As in Standard C, up to three octal digits are accepted. However, exactly two hex digits are taken in hex escapes. Unlike Standard C, all unrecognized escape sequences are left in the string unchanged, i.e., _the backslash is left in the string_. (This behavior is useful when debugging: if an escape sequence is mistyped, the resulting output is more easily recognized as broken.) It is also important to note that the escape sequences marked as "(Unicode only)" in the table above fall into the category of unrecognized escapes for non-Unicode string literals. When an `r' or `R' prefix is present, a character following a backslash is included in the string without change, and _all backslashes are left in the string_. For example, the string literal `r"\n"' consists of two characters: a backslash and a lowercase `n'. String quotes can be escaped with a backslash, but the backslash remains in the string; for example, `r"\""' is a valid string literal consisting of two characters: a backslash and a double quote; `r"\"' is not a value string literal (even a raw string cannot end in an odd number of backslashes). Specifically, _a raw string cannot end in a single backslash_ (since the backslash would escape the following quote character). Note also that a single backslash followed by a newline is interpreted as those two characters as part of the string, _not_ as a line continuation.  File: python-ref.info, Node: String literal concatenation, Next: Unicode literals, Prev: String literals, Up: Literals String literal concatenation ---------------------------- Multiple adjacent string literals (delimited by whitespace), possibly using different quoting conventions, are allowed, and their meaning is the same as their concatenation. Thus, `"hello" 'world'' is equivalent to `"helloworld"'. This feature can be used to reduce the number of backslashes needed, to split long strings conveniently across long lines, or even to add comments to parts of strings, for example: re.compile("[A-Za-z_]" # letter or underscore "[A-Za-z0-9_]*" # letter, digit or underscore ) Note that this feature is defined at the syntactical level, but implemented at compile time. The `+' operator must be used to concatenate string expressions at run time. Also note that literal concatenation can use different quoting styles for each component (even mixing raw strings and triple quoted strings).  File: python-ref.info, Node: Unicode literals, Next: Numeric literals, Prev: String literal concatenation, Up: Literals Unicode literals ---------------- XXX explain more here...  File: python-ref.info, Node: Numeric literals, Next: Integer and long integer literals, Prev: Unicode literals, Up: Literals Numeric literals ---------------- There are four types of numeric literals: plain integers, long integers, floating point numbers, and imaginary numbers. There are no complex literals (complex numbers can be formed by adding a real number and an imaginary number). Note that numeric literals do not include a sign; a phrase like `-1' is actually an expression composed of the unary operator ``-'' and the literal `1'.  File: python-ref.info, Node: Integer and long integer literals, Next: Floating point literals, Prev: Numeric literals, Up: Literals Integer and long integer literals --------------------------------- Integer and long integer literals are described by the following lexical definitions: longinteger: integer ("l"|"L") integer: decimalinteger | octinteger | hexinteger decimalinteger: nonzerodigit digit* | "0" octinteger: "0" octdigit+ hexinteger: "0" ("x"|"X") hexdigit+ nonzerodigit: "1"..."9" octdigit: "0"..."7" hexdigit: digit|"a"..."f"|"A"..."F" Although both lower case `l' and upper case `L' are allowed as suffix for long integers, it is strongly recommended to always use `L', since the letter `l' looks too much like the digit `1'. Plain integer decimal literals must be at most 2147483647 (i.e., the largest positive integer, using 32-bit arithmetic). Plain octal and hexadecimal literals may be as large as 4294967295, but values larger than 2147483647 are converted to a negative value by subtracting 4294967296. There is no limit for long integer literals apart from what can be stored in available memory. Some examples of plain and long integer literals: 7 2147483647 0177 0x80000000 3L 79228162514264337593543950336L 0377L 0x100000000L  File: python-ref.info, Node: Floating point literals, Next: Imaginary literals, Prev: Integer and long integer literals, Up: Literals Floating point literals ----------------------- Floating point literals are described by the following lexical definitions: floatnumber: pointfloat | exponentfloat pointfloat: [intpart] fraction | intpart "." exponentfloat: (nonzerodigit digit* | pointfloat) exponent intpart: nonzerodigit digit* | "0" fraction: "." digit+ exponent: ("e"|"E") ["+"|"-"] digit+ Note that the integer part of a floating point number cannot look like an octal integer, though the exponent may look like an octal literal but will always be interpreted using radix 10. For example, `1e010' is legal, while `07.1' is a syntax error. The allowed range of floating point literals is implementation-dependent. Some examples of floating point literals: 3.14 10. .001 1e100 3.14e-10 Note that numeric literals do not include a sign; a phrase like `-1' is actually an expression composed of the operator `-' and the literal `1'.  File: python-ref.info, Node: Imaginary literals, Prev: Floating point literals, Up: Literals Imaginary literals ------------------ Imaginary literals are described by the following lexical definitions: imagnumber: (floatnumber | intpart) ("j"|"J") An imaginary literal yields a complex number with a real part of 0.0. Complex numbers are represented as a pair of floating point numbers and have the same restrictions on their range. To create a complex number with a nonzero real part, add a floating point number to it, e.g., `(3+4j)'. Some examples of imaginary literals: 3.14j 10.j 10j .001j 1e100j 3.14e-10j  File: python-ref.info, Node: Operators, Next: Delimiters, Prev: Literals, Up: Lexical analysis Operators ========= The following tokens are operators: + - * ** / % << >> & | ^ ~ < > <= >= == != <> The comparison operators `<>' and `!=' are alternate spellings of the same operator. `!=' is the preferred spelling; `<>' is obsolescent.  File: python-ref.info, Node: Delimiters, Prev: Operators, Up: Lexical analysis Delimiters ========== The following tokens serve as delimiters in the grammar: ( ) [ ] { } , : . ` = ; += -= *= /= %= **= &= |= ^= >>= <<= The period can also occur in floating-point and imaginary literals. A sequence of three periods has a special meaning as an ellipsis in slices. The second half of the list, the augmented assignment operators, serve lexically as delimiters, but also perform an operation. The following printing ASCII characters have special meaning as part of other tokens or are otherwise significant to the lexical analyzer: ' " # \ The following printing ASCII characters are not used in Python. Their occurrence outside string literals and comments is an unconditional error: @ $ ?  File: python-ref.info, Node: Data model, Next: Execution model, Prev: Lexical analysis, Up: Top Data model ********** * Menu: * Objects:: * standard type hierarchy:: * Special method names::  File: python-ref.info, Node: Objects, Next: standard type hierarchy, Prev: Data model, Up: Data model Objects, values and types ========================= "Objects" are Python's abstraction for data. All data in a Python program is represented by objects or by relations between objects. (In a sense, and in conformance to Von Neumann's model of a "stored program computer," code is also represented by objects.) Every object has an identity, a type and a value. An object's _identity_ never changes once it has been created; you may think of it as the object's address in memory. The ``is'' operator compares the identity of two objects; the `id()' function returns an integer representing its identity (currently implemented as its address). An object's "type" is also unchangeable. It determines the operations that an object supports (e.g., "does it have a length?") and also defines the possible values for objects of that type. The `type()' function returns an object's type (which is an object itself). The _value_ of some objects can change. Objects whose value can change are said to be _mutable_; objects whose value is unchangeable once they are created are called _immutable_. (The value of an immutable container object that contains a reference to a mutable object can change when the latter's value is changed; however the container is still considered immutable, because the collection of objects it contains cannot be changed. So, immutability is not strictly the same as having an unchangeable value, it is more subtle.) An object's mutability is determined by its type; for instance, numbers, strings and tuples are immutable, while dictionaries and lists are mutable. Objects are never explicitly destroyed; however, when they become unreachable they may be garbage-collected. An implementation is allowed to postpone garbage collection or omit it altogether -- it is a matter of implementation quality how garbage collection is implemented, as long as no objects are collected that are still reachable. (Implementation note: the current implementation uses a reference-counting scheme with (optional) delayed detection of cyclicly linked garbage, which collects most objects as soon as they become unreachable, but is not guaranteed to collect garbage containing circular references. See the for information on controlling the collection of cyclic garbage.) Note that the use of the implementation's tracing or debugging facilities may keep objects alive that would normally be collectable. Also note that catching an exception with a ``try'...`except'' statement may keep objects alive. Some objects contain references to "external" resources such as open files or windows. It is understood that these resources are freed when the object is garbage-collected, but since garbage collection is not guaranteed to happen, such objects also provide an explicit way to release the external resource, usually a `close()' method. Programs are strongly recommended to explicitly close such objects. The ``try'...`finally'' statement provides a convenient way to do this. Some objects contain references to other objects; these are called _containers_. Examples of containers are tuples, lists and dictionaries. The references are part of a container's value. In most cases, when we talk about the value of a container, we imply the values, not the identities of the contained objects; however, when we talk about the mutability of a container, only the identities of the immediately contained objects are implied. So, if an immutable container (like a tuple) contains a reference to a mutable object, its value changes if that mutable object is changed. Types affect almost all aspects of object behavior. Even the importance of object identity is affected in some sense: for immutable types, operations that compute new values may actually return a reference to any existing object with the same type and value, while for mutable objects this is not allowed. E.g., after `a = 1; b = 1', `a' and `b' may or may not refer to the same object with the value one, depending on the implementation, but after `c = []; d = []', `c' and `d' are guaranteed to refer to two different, unique, newly created empty lists. (Note that `c = d = []' assigns the same object to both `c' and `d'.)