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: Emulating numeric types, Prev: Additional methods for emulation of sequence types, Up: Special method names Emulating numeric types ----------------------- The following methods can be defined to emulate numeric objects. Methods corresponding to operations that are not supported by the particular kind of number implemented (e.g., bitwise operations for non-integral numbers) should be left undefined. `__add__(self, other)' `__sub__(self, other)' `__mul__(self, other)' `__div__(self, other)' `__mod__(self, other)' `__divmod__(self, other)' `__pow__(self, other[, modulo])' `__lshift__(self, other)' `__rshift__(self, other)' `__and__(self, other)' `__xor__(self, other)' `__or__(self, other)' These functions are called to implement the binary arithmetic operations (`+', `-', `*', `/', `%', `divmod()', `pow()', `**', `<'`<', `>'`>', `&', `^', `|'). For instance, to evaluate the expression X`+'Y, where X is an instance of a class that has an `__add__()' method, `X.__add__(Y)' is called. Note that `__pow__()' should be defined to accept an optional third argument if the ternary version of the built-in `pow()' function is to be supported. `__radd__(self, other)' `__rsub__(self, other)' `__rmul__(self, other)' `__rdiv__(self, other)' `__rmod__(self, other)' `__rdivmod__(self, other)' `__rpow__(self, other)' `__rlshift__(self, other)' `__rrshift__(self, other)' `__rand__(self, other)' `__rxor__(self, other)' `__ror__(self, other)' These functions are called to implement the binary arithmetic operations (`+', `-', `*', `/', `%', `divmod()', `pow()', `**', `<'`<', `>'`>', `&', `^', `|') with reflected (swapped) operands. These functions are only called if the left operand does not support the corresponding operation. For instance, to evaluate the expression X`-'Y, where Y is an instance of a class that has an `__rsub__()' method, `Y.__rsub__(X)' is called. Note that ternary `pow()' will not try calling `__rpow__()' (the coercion rules would become too complicated). `__iadd__(self, other)' `__isub__(self, other)' `__imul__(self, other)' `__idiv__(self, other)' `__imod__(self, other)' `__ipow__(self, other[, modulo])' `__ilshift__(self, other)' `__irshift__(self, other)' `__iand__(self, other)' `__ixor__(self, other)' `__ior__(self, other)' These methods are called to implement the augmented arithmetic operations (`+=', `-=', `*=', `/=', `%=', `**=', `<'`<=', `>'`>=', `&=', `^=', `|='). These methods should attempt to do the operation in-place (modifying SELF) and return the result (which could be, but does not have to be, SELF). If a specific method is not defined, the augmented operation falls back to the normal methods. For instance, to evaluate the expression X`+='Y, where X is an instance of a class that has an `__iadd__()' method, `X.__iadd__(Y)' is called. If X is an instance of a class that does not define a `__iadd()' method, `X.__add__(Y)' and `Y.__radd__(X)' are considered, as with the evaluation of X`+'Y. `__neg__(self)' `__pos__(self)' `__abs__(self)' `__invert__(self)' Called to implement the unary arithmetic operations (`-', `+', `abs()' and `~{}'). `__complex__(self)' `__int__(self)' `__long__(self)' `__float__(self)' Called to implement the built-in functions `complex()', `int()', `long()', and `float()'. Should return a value of the appropriate type. `__oct__(self)' `__hex__(self)' Called to implement the built-in functions `oct()' and `hex()'. Should return a string value. `__coerce__(self, other)' Called to implement "mixed-mode" numeric arithmetic. Should either return a 2-tuple containing SELF and OTHER converted to a common numeric type, or `None' if conversion is impossible. When the common type would be the type of `other', it is sufficient to return `None', since the interpreter will also ask the other object to attempt a coercion (but sometimes, if the implementation of the other type cannot be changed, it is useful to do the conversion to the other type here). *Coercion rules*: to evaluate X OP Y, the following steps are taken (where `__OP__()' and `__rOP__()' are the method names corresponding to OP, e.g., if OP is ``+'', `__add__()' and `__radd__()' are used). If an exception occurs at any point, the evaluation is abandoned and exception handling takes over. * 0. If X is a string object and OP is the modulo operator (%), the string formatting operation is invoked and the remaining steps are skipped. * 1. If X is a class instance: * 1a. If X has a `__coerce__()' method: replace X and Y with the 2-tuple returned by `X.__coerce__(Y)'; skip to step 2 if the coercion returns `None'. * 1b. If neither X nor Y is a class instance after coercion, go to step 3. * 1c. If X has a method `__OP__()', return `X.__OP__(Y)'; otherwise, restore X and Y to their value before step 1a. * 2. If Y is a class instance: * 2a. If Y has a `__coerce__()' method: replace Y and X with the 2-tuple returned by `Y.__coerce__(X)'; skip to step 3 if the coercion returns `None'. * 2b. If neither X nor Y is a class instance after coercion, go to step 3. * 2b. If Y has a method `__rOP__()', return `Y.__rOP__(X)'; otherwise, restore X and Y to their value before step 2a. * 3. We only get here if neither X nor Y is a class instance. * 3a. If OP is ``+'' and X is a sequence, sequence concatenation is invoked. * 3b. If OP is ``*'' and one operand is a sequence and the other an integer, sequence repetition is invoked. * 3c. Otherwise, both operands must be numbers; they are coerced to a common type if possible, and the numeric operation is invoked for that type.  File: python-ref.info, Node: Execution model, Next: Expressions, Prev: Data model, Up: Top Execution model *************** * Menu: * Code blocks:: * Exceptions::  File: python-ref.info, Node: Code blocks, Next: Exceptions, Prev: Execution model, Up: Execution model Code blocks, execution frames, and namespaces ============================================= A "code block" is a piece of Python program text that can be executed as a unit, such as a module, a class definition or a function body. Some code blocks (like modules) are normally executed only once, others (like function bodies) may be executed many times. Code blocks may textually contain other code blocks. Code blocks may invoke other code blocks (that may or may not be textually contained in them) as part of their execution, e.g., by invoking (calling) a function. The following are code blocks: A module is a code block. A function body is a code block. A class definition is a code block. Each command typed interactively is a separate code block; a script file (a file given as standard input to the interpreter or specified on the interpreter command line the first argument) is a code block; a script command (a command specified on the interpreter command line with the `*-c*' option) is a code block. The file read by the built-in function `execfile()' is a code block. The string argument passed to the built-in function `eval()' and to the `exec' statement is a code block. And finally, the expression read and evaluated by the built-in function `input()' is a code block. A code block is executed in an execution frame. An "execution frame" contains some administrative information (used for debugging), determines where and how execution continues after the code block's execution has completed, and (perhaps most importantly) defines two namespaces, the local and the global namespace, that affect execution of the code block. A "namespace" is a mapping from names (identifiers) to objects. A particular namespace may be referenced by more than one execution frame, and from other places as well. Adding a name to a namespace is called "binding" a name (to an object); changing the mapping of a name is called "rebinding"; removing a name is "unbinding". Namespaces are functionally equivalent to dictionaries (and often implemented as dictionaries). The "local namespace" of an execution frame determines the default place where names are defined and searched. The "global namespace" determines the place where names listed in `global' statements are defined and searched, and where names that are not bound anywhere in the current code block are searched. Whether a name is local or global in a code block is determined by static inspection of the source text for the code block: in the absence of `global' statements, a name that is bound anywhere in the code block is local in the entire code block; all other names are considered global. The `global' statement forces global interpretation of selected names throughout the code block. The following constructs bind names: formal parameters to functions, `import' statements, class and function definitions (these bind the class or function name in the defining block), and targets that are identifiers if occurring in an assignment, `for' loop header, or in the second position of an `except' clause header. Local names are searched only on the local namespace; global names are searched only in the global and built-in namespace.(1) A target occurring in a `del' statement is also considered bound for this purpose (though the actual semantics are to "unbind" the name). When a global name is not found in the global namespace, it is searched in the built-in namespace (which is actually the global namespace of the module `__builtin__'). The built-in namespace associated with the execution of a code block is actually found by looking up the name `__builtins__' is its global namespace; this should be a dictionary or a module (in the latter case its dictionary is used). Normally, the `__builtins__' namespace is the dictionary of the built-in module `__builtin__' (note: no `s'); if it isn't, restricted execution mode is in effect. When a name is not found at all, a `NameError' exception is raised. The following table lists the meaning of the local and global namespace for various types of code blocks. The namespace for a particular module is automatically created when the module is first imported (i.e., when it is loaded). Note that in almost all cases, the global namespace is the namespace of the containing module -- scopes in Python do not nest! Code block type Global namespace Local namespace Notes ------ ------ ------ ------ Module n.s. for this same as global module Script (file or n.s. for same as global (1) command) `__main__' Interactive n.s. for same as global command `__main__' Class definition global n.s. of new n.s. containing block Function body global n.s. of new n.s. (2) containing block String passed to global n.s. of local n.s. of (2), (3) `exec' statement containing block containing block String passed to global n.s. of local n.s. of (2), (3) `eval()' caller caller File read by global n.s. of local n.s. of (2), (3) `execfile()' caller caller Expression read global n.s. of local n.s. of by `input()' caller caller Notes: `n.s.' means _namespace_ `(1)' The main module for a script is always called `__main__'; "the filename don't enter into it." `(2)' The global and local namespace for these can be overridden with optional extra arguments. `(3)' The `exec' statement and the `eval()' and `execfile()' functions have optional arguments to override the global and local namespace. If only one namespace is specified, it is used for both. The built-in functions `globals()' and `locals()' returns a dictionary representing the current global and local namespace, respectively. The effect of modifications to this dictionary on the namespace are undefined.(2) ---------- Footnotes ---------- (1) If the code block contains `exec' statements or the construct "`from ...import *'", the semantics of local names change: local name lookup first searches the local namespace, then the global namespace and the built-in namespace. (2) The current implementations return the dictionary actually used to implement the namespace, _except_ for functions, where the optimizer may cause the local namespace to be implemented differently, and `locals()' returns a read-only dictionary.  File: python-ref.info, Node: Exceptions, Prev: Code blocks, Up: Execution model Exceptions ========== Exceptions are a means of breaking out of the normal flow of control of a code block in order to handle errors or other exceptional conditions. An exception is _raised_ at the point where the error is detected; it may be _handled_ by the surrounding code block or by any code block that directly or indirectly invoked the code block where the error occurred. The Python interpreter raises an exception when it detects a run-time error (such as division by zero). A Python program can also explicitly raise an exception with the `raise' statement. Exception handlers are specified with the `try' ... `except' statement. The `try' ... `finally' statement specifies cleanup code which does not handle the exception, but is executed whether an exception occurred or not in the preceding code. Python uses the "termination" model of error handling: an exception handler can find out what happened and continue execution at an outer level, but it cannot repair the cause of the error and retry the failing operation (except by re-entering the offending piece of code from the top). When an exception is not handled at all, the interpreter terminates execution of the program, or returns to its interactive main loop. In either case, it prints a stack backtrace, except when the exception is `SystemExit'. Exceptions are identified by string objects or class instances. Selection of a matching except clause is based on object identity (i.e., two different string objects with the same value represent different exceptions!) For string exceptions, the `except' clause must reference the same string object. For class exceptions, the `except' clause must reference the same class or a base class of it. When an exception is raised, an object (maybe `None') is passed as the exception's "parameter" or "value"; this object does not affect the selection of an exception handler, but is passed to the selected exception handler as additional information. For class exceptions, this object must be an instance of the exception class being raised. See also the description of the `try' statement in section *Note try statement:: and `raise' statement in section *Note raise statement::.  File: python-ref.info, Node: Expressions, Next: Simple statements, Prev: Execution model, Up: Top 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'. * Menu: * Arithmetic conversions:: * Atoms:: * Primaries:: * power operator:: * Unary arithmetic operations:: * Binary arithmetic operations:: * Shifting operations:: * Binary bit-wise operations:: * Comparisons:: * Boolean operations:: * Expression lists:: * Summary::  File: python-ref.info, Node: Arithmetic conversions, Next: Atoms, Prev: Expressions, Up: Expressions 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 the end of chapter 3. 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.  File: python-ref.info, Node: Atoms, Next: Primaries, Prev: Arithmetic conversions, Up: Expressions 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|dict_display|string_conversion * Menu: * Identifiers Names:: * Literals 2:: * Parenthesized forms:: * List displays:: * Dictionary displays:: * String conversions::  File: python-ref.info, Node: Identifiers Names, Next: Literals 2, Prev: Atoms, Up: Atoms Identifiers (Names) ------------------- An identifier occurring as an atom is a reference to a local, global or built-in name binding. If a name is assigned to anywhere in a code block (even in unreachable code), and is not mentioned in a `global' statement in that code block, then it refers to a local name throughout that code block. When it is not assigned to anywhere in the block, or when it is assigned to but also explicitly listed in a `global' statement, it refers to a global name if one exists, else to a built-in name (and this binding may dynamically change).(1) 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. ---------- Footnotes ---------- (1) The Python interpreter provides a useful set of predefined built-in functions. It is not recommended to reuse (hide) these names with self defined objects. See the for the descriptions of built-in functions and methods.  File: python-ref.info, Node: Literals 2, Next: Parenthesized forms, Prev: Identifiers Names, Up: Atoms 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 *Note 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.  File: python-ref.info, Node: Parenthesized forms, Next: List displays, Prev: Literals 2, Up: Atoms 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.  File: python-ref.info, Node: List displays, Next: Dictionary displays, Prev: Parenthesized forms, Up: Atoms List displays ------------- A list display is a possibly empty series of expressions enclosed in square brackets: list_display: "[" [listmaker] "]" listmaker: expression ( list_for | ( "," expression)* [","] ) list_iter: list_for | list_if list_for: "for" expression_list "in" testlist [list_iter] list_if: "if" test [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.  File: python-ref.info, Node: Dictionary displays, Next: String conversions, Prev: List displays, Up: Atoms 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 *Note 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.  File: python-ref.info, Node: String conversions, Prev: Dictionary displays, Up: Atoms 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.) It is illegal to attempt to convert recursive objects (e.g., lists or dictionaries that contain a reference to themselves, directly or indirectly.) 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.  File: python-ref.info, Node: Primaries, Next: power operator, Prev: Atoms, Up: Expressions Primaries ========= Primaries represent the most tightly bound operations of the language. Their syntax is: primary: atom | attributeref | subscription | slicing | call * Menu: * Attribute references:: * Subscriptions:: * Slicings:: * Calls::  File: python-ref.info, Node: Attribute references, Next: Subscriptions, Prev: Primaries, Up: Primaries 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.  File: python-ref.info, Node: Subscriptions, Next: Slicings, Prev: Attribute references, Up: Primaries 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.  File: python-ref.info, Node: Slicings, Next: Calls, Prev: Subscriptions, Up: Primaries 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 *Note 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.  File: python-ref.info, Node: Calls, Prev: Slicings, Up: Primaries Calls ----- A call calls a callable object (e.g., a function) with a possibly empty series of arguments: call: primary "(" [argument_list [","]] ")" argument_list: positional_arguments ["," keyword_arguments] | keyword_arguments positional_arguments: expression ("," expression)* keyword_arguments: keyword_item ("," keyword_item)* keyword_item: identifier "=" expression A trailing comma may be present after an argument list 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 *Note 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. 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. 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 *Note 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 the 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.  File: python-ref.info, Node: power operator, Next: Unary arithmetic operations, Prev: Primaries, Up: Expressions 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). 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; if the result is not expressible in that type (as in raising an integer to a negative power, or a negative floating point number to a broken power), a `TypeError' exception is raised.  File: python-ref.info, Node: Unary arithmetic operations, Next: Binary arithmetic operations, Prev: power operator, Up: Expressions Unary arithmetic operations =========================== All unary arithmetic (and bit-wise) 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 bit-wise inversion of its plain or long integer argument. The bit-wise 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.  File: python-ref.info, Node: Binary arithmetic operations, Next: Shifting operations, Prev: Unary arithmetic operations, Up: Expressions 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 a_expr: m_expr | aexpr "+" m_expr | aexpr "-" 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) operator yields the quotient of its 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 second operand. 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 and complex numbers; there similar identities hold approximately where `x/y' is replaced by `floor(x/y)') or `floor(x/y) - 1' (for floats),(1) or `floor((x/y).real)' (for complex). 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. ---------- Footnotes ---------- (1) 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'.  File: python-ref.info, Node: Shifting operations, Next: Binary bit-wise operations, Prev: Binary arithmetic operations, Up: Expressions 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)'; for plain integers there is no overflow check so in that case the operation drops bits and flips the sign if the result is not less than `pow(2,31)' in absolute value. Negative shift counts raise a `ValueError' exception.  File: python-ref.info, Node: Binary bit-wise operations, Next: Comparisons, Prev: Shifting operations, Up: Expressions Binary bit-wise 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.  File: python-ref.info, Node: Comparisons, Next: Boolean operations, Prev: Binary bit-wise operations, Up: Expressions 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 integer values: `1' for true, `0' for 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 OPA, OPB, ..., OPY are comparison operators, then A OPA B OPB C ...Y OPY Z is equivalent to A OPA B `and' B OPB C `and' ... Y OPY Z, except that each expression is evaluated at most once. Note that A OPA B OPB 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 coverted to a common type. Otherwise, objects of different types _always_ compare unequal, and are ordered consistently but arbitrarily. (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. * Tuples and lists are compared lexicographically using comparison of corresponding items. * Mappings (dictionaries) are compared through lexicographic comparison of their sorted (key, value) lists.(1) * Most other 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 set membership. `X in S' evaluates to true if X is a member of the set S, and false otherwise. `X not in S' returns the negation of `X in S'. The set membership test has traditionally been bound to sequences; an object is a member of a set if the set is a sequence and contains an element equal to that object. However, it is possible for an object to support membership tests without being a sequence. 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 there exists an index I such that `X == Y[I]' is true. If `X' is not a string or Unicode object of length `1', a `TypeError' exception is raised. For user-defined classes which define the `__contains__()' method, `X in Y' is true if and only if `Y.__contains__(X)' is true. For user-defined classes which do not define `__contains__()' and do define `__getitem__()', `X in Y' is true if and only if there is a non-negative integer index I such that `X == Y[I]', and all lower integer indices do not raise `IndexError' exception. (If any other exception is raised, it is as if `in' raised that exception). The operator `not in' is defined to have the inverse true value of `in'. The operators `is' and `is not' test for object identity: `X is Y' is true if and only if X and Y are the same object. `X is not Y' yields the inverse truth value. ---------- Footnotes ---------- (1) This is expensive since it requires sorting the keys first, but it is about the only sensible definition. An 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 `{}'.  File: python-ref.info, Node: Boolean operations, Next: Expression lists, Prev: Comparisons, Up: Expressions Boolean operations ================== Boolean operations have the lowest priority of all Python operations: expression: or_test | lambda_form or_test: and_test | or_test "or" and_test and_test: not_test | and_test "and" not_test not_test: comparison | "not" not_test lambda_form: "lambda" [parameter_list]: expression In the context of Boolean operations, and also when expressions are used by control flow statements, the following values are interpreted as false: `None', numeric zero of all types, empty sequences (strings, tuples and lists), and empty mappings (dictionaries). All other values are interpreted as true. The operator `not' yields `1' if its argument is false, `0' 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 `or' restrict the value and type they return to `0' and `1', 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 `0', not `'''.) 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 that behaves virtually identical to one defined with def name(arguments): return expression See section *Note Function definitions:: for the syntax of parameter lists. Note that functions created with lambda forms cannot contain statements. *Programmer's note:* a lambda form defined inside a function has no access to names defined in the function's namespace. This is because Python has only two scopes: local and global. A common work-around is to use default argument values to pass selected variables into the lambda's namespace, e.g.: def make_incrementor(increment): return lambda x, n=increment: x+n  File: python-ref.info, Node: Expression lists, Next: Summary, Prev: Boolean operations, Up: Expressions 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: `()'.)