Chapter 3: Data model

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## Chapter 3: Data model
### 3.1 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 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. The `==' operator compares the value of two objects. Objects whose value can change are said to be mutable; objects whose value is unchangeable once they are created are called immutable. An object's (im)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 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. 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 always 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 (im)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.)
### 3.2 The standard type hierarchy
Below is a list of the types that are built into Python. Extension modules written in C can define additional types. Future versions of Python may add types to the type hierarchy (e.g. rational numbers, efficiently stored arrays of integers, etc.).
Some of the type descriptions below contain a paragraph listing `special attributes'. These are attributes that provide access to the implementation and are not intended for general use. Their definition may change in the future. There are also some `generic' special attributes, not listed with the individual objects: `__methods__`is a list of the method names of a built-in object, if it has any; `__members__` is a list of the data attribute names of a built-in object, if it has any.
NoneThis type has a single value. There is a single object with this value. This object is accessed through the built-in name `None`. It is used to signify the absence of a value in many situations, e.g. it is returned from functions that don't explicitly return anything. Its truth value is false.
Ellipsis This type has a single value. There is a single object with this value. This object is accessed through the built-in name `Ellipsis`. It is used to indicate the presence of the ``...'' syntax in a slice. Its truth value is true.
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:
Integers These represent elements from the mathematical set of whole numbers
There are two types of integers:
Plain integers These represent numbers in the range -2147483648 through 2147483647. (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 `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 4294967296 different bit patterns correspond to different values).
Long integers These represent numbers in an unlimited range, subject to available (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.
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.
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. Python does not support single-precision floating point numbers; the savings in CPU and memory usage that are usually the reason for using these is dwarfed by the overhead of using objects in Python, so there is no reason to complicate the language with two kinds of floating point numbers.
Complex numbers These represent complex numbers as a pair of machine-level double precision floating point numbers. The same caveats apply as for floating point numbers. The real and imaginary value of a complex number z can be retrieved through the attributes z.real and z.imag.
Sequences These represent finite ordered sets indexed by natural numbers. The built-in function `len()` returns the number of items of a sequence. When the length of a sequence is n, the index set contains the numbers 0, 1, ..., n. Item i of sequence a is selected by a[i].
Sequences also support slicing: `a[i:j]` selects all items 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:
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 array of objects directly referenced by an immutable object cannot change.)
The following types are immutable sequences:
StringsThe items of a string are characters. There is no separate character type; a character is represented by a string of one item. Characters represent (at least) 8-bit bytes. The built-in functions `chr()` and `ord()` convert between characters and nonnegative integers representing the byte values. Bytes with the values 0-127 usually represent the corresponding ASCII values, but the interpretation of values is up to the program. The string data type is also used to represent arrays of bytes, e.g. to hold data read from a file.
(What should be done on systems whose native character set is not ASCII???)
TuplesThe items of a tuple are arbitrary Python objects. Tuples of two or more items are formed by comma-separated lists of expressions. A tuple of one item (a `singleton') can be formed by affixing a comma to an expression (an expression by itself does not create a tuple, since parentheses must be usable for grouping of expressions). An empty tuple can be formed by enclosing `nothing' in parentheses: ``()''.
Mutable sequences Mutable sequences can be changed after they are created. The subscription and slicing notations can be used as the target of assignment and `del` (delete) statements.
There is currently a single mutable sequence type:
ListsThe items 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 needed to form lists of length 0 or 1.)
The optional module array provides an additional example of a mutable sequence type.
Mappings These represent finite sets of objects indexed by arbitrary index sets. The subscript notation `a[k]` selects the item indexed by `k` from the mapping `a`; this can be used in expressions and as the target of assignments or `del` statements. The built-in function `len()` returns the number of items in a mapping.
There is currently a single intrinsic mapping type:
Dictionaries These represent finite sets of objects indexed by nearly arbitrary values. The only types of values not acceptable as keys are values containing lists or dictionaries or other mutable types that are compared by value rather than by object identity the reason being that the efficient implementation of dictionaries requires a key's value to remain constant. Numeric types used for keys obey the normal rules for numeric comparison: if two numbers compare equal (e.g. 1 and 1.0) then they can be used interchangeably to index the same dictionary entry.
Dictionaries are mutable; they are created by the `{...}`notation. (See "Dictionary displays" on page28. (ref5.html#REF27031))
The optional library modules dbm, gdbm and bsddb provide additional examples of mapping types.
Callable types These are the types to which the function call operation (for invocation, See "Calls" on page31. (ref5.html#REF41934)) is applied:
User-defined functions A user-defined function object is created by a function definition. (See "Function definitions" on page48. (ref7.html#REF27502))
Special read-only attributes: func_doc or __doc__ is the function's documentation string, or None if unavailable; func_name or __name__ is the function's name; func_defaults is a tuple containing default argument values for those arguments that have defaults, or None if no arguments have a default value; `func_code` is the code object representing the compiled function body; `func_globals` is (a reference to) the dictionary that holds the function's global variables it defines the global name space of the module in which the function was defined. Additional information about a function's definition can be retrieved from its code object; see the description of internal types below.
User-defined methods A user-defined method object (a.k.a. object closure) combines a class, a class instance (or None) and a user-defined function. Special read-only attributes: `im_self` is the instance object; `im_func` is the function object; im_class is the class that defined the method (which may be a base class of the class of which im_self is an instance); __doc__ is the method's documentation (same as im_func.__doc__); __name__ is the method name (same as im_func.__name__).
User-defined method objects are created in two ways: when getting an attribute of a class that is a user-defined function object, or when getting an attributes of a class instance that is a user-defined function object. In the former case (class attribute), the im_self attribute is None, and the method object is said to be unbound; in the latter case (instance attribute), im_self is the instance, and the method object is said to be bound. For instance, when C is a class which contains a definition for a function f, C.f does not yield the function object f; rather, it yields an unbound method object m where m.im_class is C, m.im_function is f, and m.im_self is None. When x is a C instance, x.f yields a bound method object m where m.im_class is C, m.im_function is f, and m.im_self is x.
When an unbound user-defined method object is called, the underlying function (im_func) is called, with the restriction that the first argument must be an instance of the proper class (im_class) or of a derived class thereof.
When a bound user-defined method object is called, the underlying function (im_func) is called, inserting the class instance (im_self) in front of the argument list. For instance, when C is a class which contains a definition for a function f, and x is an instance of C, calling x.f(1) is equivalent to calling C.f(x, 1).
Note that the transformation from function object to (unbound or bound) method object happens each time the attribute is retrieved from the class or instance. In some cases, a fruitful optimization is to assign the attribute to a local variable and call that local variable. Also notice that this transformation only happens for user-defined functions; other callable objects (and all non-callable objects) are retrieved without transformation.
Built-in functions A built-in function object is a wrapper around a C function. Examples of built-in functions are `len` and `math.sin` (math is a standard built-in module). The number and type of the arguments are determined by the C function. Special read-only attributes: __doc__ is the function's documentation string, or None if unavailable; __name__ is the function's name; __self__ is set to None (but see the next paragraph).
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 `list.append`, assuming `list` is a list object. In this case, the special read-only attribute __self__ is set to the object denoted by list.
Classes Class objects are described below. When a class object is called, a new class instance (also described below) is created and returned. This implies a call to the class's `__init__` method if it has one. Any arguments are passed on to the `__init__`method if there is no `__init__` method, the class must be called without arguments.
Class instances Class instances are described below. Class instances can be called as a function only when the class has a __call__ method; in this case, x(arguments) is a shorthand for x.__call__(arguments).
Modules Modules are imported by the `import` statement. (See "The import statement" on page43. (ref6.html#REF17806)) A module object has a name space implemented by a dictionary object (this is the dictionary referenced by the `func_globals` attribute of functions defined in the module). Attribute references are translated to lookups in this dictionary, e.g. m.x is equivalent to m.__dict__["x"]. A module object does not contain the code object used to initialize the module (since it isn't needed once the initialization is done).
Attribute assignment update the module's name space dictionary, e.g. ``m.x=1'' is equivalent to ``m.__dict__["x"] = 1''.
Special read-only attribute: `__dict__` is the dictionary object that is the module's name space.
Predefined (writable) attributes: `__name__`is the module name; `__doc__` is the module's documentation string, or `None` if unavailable; __file__ is the pathname of the file from which the module was loaded, if it was loaded from a file. The __file__ attribute is not present for C modules that are statically linked into the interpreter; for extension modules loaded dynamically from a shared library, it is the pathname of the shared library file.
Classes Class objects are created by class definitions (See "Class definitions" on page49. (ref7.html#REF23237)). A class has a name space implemented by a dictionary object. Class attribute references are translated to lookups in this dictionary, e.g. ``C.x'' is translated to ``C.__dict__["x"]''. When the attribute name is not found there, the attribute search continues in the base classes. The search is depth-first, left-to-right in the order of their occurrence in the base class list. When a class attribute reference would yield a user-defined function object, it is transformed into an unbound user-defined method object (see above). The im_class attribute of this method object is the class in which the function object was found, not necessarily the class for which the attribute reference was initiated.
Class attribute assignments update the class's dictionary, never the dictionary of a base class.
A class object can be called as a function (see above) to yield a class instance (see below).
Special read-only attributes: `__dict__` is the dictionary that is the class's name space; __name__ is the class name; `__bases__` is a tuple (possibly empty or a singleton) containing the base classes, in the order of their occurrence in the base class list.
Predefined (writable) attribute: __doc__ is the class's documentation string, or None if undefined.
Class instances A class instance is created by calling a class object as a function (see above). A class instance has a name space implemented as a dictionary, which is the first place where instance attributes are searched. When an attribute is not found there, the search continues with the class attributes. If a class attribute is found that is a user-defined function object (and in no other case), it is transformed into an unbound user-defined method object (see above). The im_class attribute of this method object is the class in which the function object was found, not necessarily the class of the instance for which the attribute reference was initiated. If no class attribute is found, and the object's class has a __getattr__ method, that is called to satisfy the lookup.
Attribute assignments and deletions update the instance's dictionary, never a class's dictionary. If the class has a __setattr__ or __delattr__ method, this is called instead of updating the instance dictionary directly.
Class instances can pretend to be numbers, sequences, mappings, or callable objects, and override various other special operations, if they have methods with certain special names. See "Special method names" on page18 (ref3.html#REF32560).
Special read-only attributes: `__dict__` yields the attribute dictionary; `__class__` yields the instance's class.
FilesA file object represents an open file. It is a wrapper around a C standard I/O (stdio) file pointer. File objects are created by the `open()` built-in function, and also by `posix.popen()`, `posix.fdopen()` and the `makefile` method of socket objects. The objects `sys.stdin`, `sys.stdout` and `sys.stderr` are initialized to file objects corresponding to the interpreter's standard input, output and error streams. See the Python Library Reference for methods of file objects and other details.
Internal types A few types used internally by the interpreter are exposed to the user. Their definitions may change with future versions of the interpreter, but they are mentioned here for completeness.
Code objects Code objects represent byte-compile executable Python code, or bytecode. The difference between a code object and a function object is that the function object contains an explicit reference to the function's globals (the name space dictionary of the module in which it was defined), while a code object contains no context; also the default argument values are stored in the function object, not in the code object (because they represent values calculated at run-time). Unlike function objects, code objects are immutable and contain no references (directly or indirectly) to mutable objects.
Special read-only attributes: co_argcount is the number of positional arguments (including arguments with default values); co_nlocals is the number of local variables used by the function (including arguments); co_varnames is a tuple containing the names of the local variables (starting with the argument names); `co_code` is a string representing the sequence of bytecode instructions; `co_consts` is a tuple containing the literals used by the bytecode; `co_names` is a tuple containing the names used by the bytecode; `co_filename` is the filename from which the code was compiled; co_flags is an integer encoding a number of flags for the interpreter. The following flag bits are defined: bit 2 is set if the function uses the "*arguments'' syntax to accept an arbitrary number of positional arguments; bit 3 is set if the function uses the ``**keywords'' syntax to accept arbitrary keyword arguments; other bits are used internally or reserved for future use. The first item in co_consts is the documentation string of the function, or None if undefined. To find out the first line number of a function, you have to disassemble the bytecode instructions; the standard library module `codehack` defines a function getlineno() that returns the first line number of a code object.
Frame objects Frame objects represent execution frames. They may occur in traceback objects (see below).
Special read-only attributes: `f_back` is to the previous stack frame (towards the caller), or `None` if this is the bottom stack frame; `f_code` is the code object being executed in this frame; `f_locals` is the dictionary used to look up locals variables; `f_globals` is used for global variables; f_builtins is used for built-in (intrinsic) names; f_restricted is a flag indicating whether the function is executing in restricted execution mode; f_owner is the class or module that defined the code, if any; `f_lineno` gives the current line number and `f_lasti` gives the precise instruction (this is an index into the instruction string of the code object).
Special writable attributes: f_trace, if not None, is a function called at the start of each source code line (this is used by the debugger).
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, (See "The `try` statement" on page47. (ref7.html#REF13811)), the stack trace is made available to the program as `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 also made available to the user as `sys.last_traceback`.
Special read-only attributes: `tb_next` is the next level in the stack trace (towards the frame where the exception occurred), or `None` if there is no next level; `tb_frame` points to the execution frame of the current level; `tb_lineno` gives the line number where the exception occurred; `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 `try` statement with no matching `except` clause or with a `finally` clause.
Slice objects Slice objects are used to represent slices when extended slice syntax is used (this is a slice using two colons, or multiple slices or ellipses separated by commas, e.g. a[i:j:step], a[i:j,k:l], or a[...,i:j]). They are also created by the built-in slice() function.
Special read-only attributes: start is the lowerbound; stop is the upperbound; step is the step value; each is None if omitted. These attributes can have any type.
### 3.3 Special method names
This section describes how user-defined classes can customize their behavior or emulate the behavior of other object types. In the following, if a class defines a particular method, any class derived from it is also understood to define that method (implicitly).
A class can implement certain operations that are invoked by special syntax (such as arithmetic operations or subscripting and slicing) by defining methods with special names. For instance, if a class defines a method named `__getitem__`, and `x` is an instance of this class, then `x[i]` is equivalent to `x.__getitem__(i)`. (The reverse is not true; e.g. if `x` is a list object, `x.__getitem__(i)` is not equivalent to `x[i]`.) Except where mentioned, attempts to execute an operation raise an exception when no appropriate method is defined.
#### 3.3.1 Basic customization
`__init__(self, [args...])`Called when the instance is created. The arguments are those that were passed to the class constructor expression. If a base class has an __init__ method the derived class's __init__ method must explicitly call it to ensure proper initialization of the base class part of the instance, e.g.``BaseClass.__init__(self,[args...])''.
`__del__(self)`Called when the instance is about to be destroyed. If a base class has a __del__ method the derived class's __del__ method must explicitly call it to ensure proper deletion of the base class part of the instance. e.g. ``BaseClass.__del__(self)''. Note that it is possible (though not recommended!) for the __del__ method to postpone destruction of the instance by creating a new reference to it. It may then be called at a later time when this new reference is deleted. It is not guaranteed that __del__ methods are called for objects that still exist when the interpreter exits.
Note that ``del x'' doesn't directly call x.__del__() the former decrements the reference count for x by one, and the latter is only called when its reference count reaches zero. Some common situations that may prevent the reference count of an object to go to zero include: circular references between objects (e.g. a doubly-linked list or a tree data structure with parent and child pointers); a reference to the object on the stack frame of a function that caught an exception (the traceback stored in sys.exc_traceback keeps the stack frame alive); or a reference to the object on the stack frame that raised an unhandled exception in interactive mode (the traceback stored in sys.last_traceback keeps the stack frame alive). The first situation can only be remedied by explicitly breaking the cycles; the latter two situations can be resolved by storing None in sys.exc_traceback or sys.last_traceback.
Warning: due to the precarious circumstances under which __del__ methods are invoked, exceptions that occur during their execution are ignored, and a warning is printed to sys.stderr instead. Also, when __del__ is invoked is response to a module being deleted (e.g. when execution of the program is done), other globals referenced by the __del__ method may already have been deleted. For this reason, __del__ methods should do the absolute minimum needed to maintain external invariants.
`__repr__(self)`Called by the `repr()` built-in function and by string conversions (reverse quotes) to compute the "official" string representation of an object. This should normally look like a valid Python expression that can be used to recreate an object with the same value.
`__str__(self)`Called by the `str()` built-in function and by the `print`statement compute the ``informal'' string representation of an object. This differs from __repr__ in that it doesn't have to look like a valid Python expression: a more convenient or concise representation may be used instead.
`__cmp__(self, other)`Called by all comparison operations. Should return a negative integer if `self``<``other`, zero if `self``==``other`, a positive integer if `self``>``other`. If no __cmp__ method is defined, class instances are compared by object identity ("address"). (Implementation note: due to limitations in the interpreter, exceptions raised by comparisons are ignored, and the outcome will be random in this case.)
`__hash__(self)`Called for the key object for dictionary operations, and by the built-in function hash(). Should return a 32-bit integer usable as a hash value for dictionary operations. The only required property is that objects which compare equal have the same hash value; it is advised to somehow mix together (e.g. using exclusive or) the hash values for the components of the object that also play a part in comparison of objects. If no __hash__ method is defined, class instances are hashed by object identity (``address''). If a class does not define a __cmp__ method it should not define a __hash__ method either; if it defines __cmp__ but not __hash__ its instances will not be usable as dictionary keys. If a class defines mutable objects and implements a __cmp__ method it should not implement __hash__ since the dictionary implementation requires that a key's hash value is immutable (if the object's hash value changes, it will be in the wrong hash bucket).`__nonzero__(self)`Called to implement truth value testing; should return 0 or 1. When this method is not defined, `__len__` is called, if it is defined (see below). If a class defines neither `__len__` nor `__nonzero__`, all its instances are considered true.
#### 3.3.2 Customizing attribute access
The following methods can be defined to customize the meaning of attribute access (use of, assignment to, or deletion of x.name) for class instances. For performance reasons, these methods are cached in the class object at class definition time; therefore, they cannot be changed after the class definition is executed.
`__getattr__(self, name)`Called when an attribute lookup has not found the attribute in the usual places (i.e. it is not an instance attribute nor is it found in the class tree for self). name is the attribute name. This method should return the (computed) attribute value or raise an AttributeError exception.
Note that if the attribute is found through the normal mechanism, `__getattr__` is not called. (This is an asymmetry between `__getattr__` and `__setattr__`.) This is done both for efficiency reasons and because otherwise `__setattr__` would have no way to access other attributes of the instance. Note that at least for instance variables, you can fake total control by not inserting any values in the instance attribute dictionary (but instead inserting them in another object).
`__setattr__(self, name, value)`Called whenever an attribute assignment is attempted. This is called instead of the normal mechanism (i.e. instead of storing the value in the instance dictionary). name is the attribute name, value is the value to be assigned to it.
If __setattr__ wants to assign to an instance attribute, it should not simply execute ``self.name = value'' this would cause a recursive call to itself. Instead, it should insert the value in the dictionary of instance attributes, e.g.``self.__dict__[name]=value''.
`__delattr__(self, name)`Like __setattr__ but for attribute deletion instead of assignment.
#### 3.3.3 Emulating callable objects
`__call__(self, [args...])`Called when the instance is "called" as a function; if this method is defined, x(arg1, arg2, ...) is a shorthand for x.__call__(arg1, arg2, ...).
#### 3.3.4 Emulating sequence and mapping types
The following methods can be defined to emulate sequence or mapping objects. The first set of methods is used either to emulate a sequence or to emulate a mapping; the difference is that for a sequence, the allowable keys should be the integers k for which 0 <= k < N where N is the length of the sequence, and the method __getslice__ (see below) should be defined. It is also recommended that mappings provide methods keys, values and items behaving similar to those for Python's standard dictionary objects; mutable sequences should provide methods append, count, index, insert, sort, remove and reverse like Python standard list objects. Finally, sequence types should implement addition (meaning concatenation) and multiplication (meaning repetition) by defining the methods __add__, __radd__, __mul__ and __rmul__ described below; they should not define __coerce__ or other numerical operators.
`__len__(self)`Called to implement the built-in function `len()`. Should return the length of the object, an integer `>=` 0. Also, an object that doesn't define a __nonzero__() method and whose `__len__()` method returns zero is considered to be false in a Boolean context.
`__getitem__(self, key)`Called to implement evaluation of `self[key]`. Note that the special interpretation of negative keys (if the class wishes to emulate a sequence type) is up to the `__getitem__` method.
`__setitem__(self, key, value)`Called to implement assignment to `self[key]`. Same note as for `__getitem__`.
`__delitem__(self, key)`Called to implement deletion of `self[key]`. Same note as for `__getitem__`.
##### 3.3.4.1 Additional methods for emulation of sequence types
The following methods can be defined to further emulate sequence objects. For immutable sequences methods, only __getslice__ should be defined; for mutable sequences, all three methods should be defined.
`__getslice__(self, i, j)`Called to implement evaluation of `self[i:j]`. The returned object should be of the same type as self. Note that missing `i` or `j` in the slice expression are replaced by 0 or `len(self)`, respectively, and `len(self)` has been added (once) to originally negative `i` or `j` by the time this function is called (unlike for `__getitem__`).
`__setslice__(self, i, j, sequence)`Called to implement assignment to `self[i:j]`. The sequence argument can have any type. The return value should be None. Same notes for i and j as for `__getslice__`.
`__delslice__(self, i, j)`Called to implement deletion of `self[i:j]`. Same notes for i and j as for `__getslice__`.
Notice that these methods are only invoked when a single slice with a single colon is used. For slice operations involving extended slice notation, __getitem__, __setitem__ or __delitem__ is called.
#### 3.3.5 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, right)`
`__sub__(self, right)`
`__mul__(self, right)`
`__div__(self, right)`
`__mod__(self, right)`
`__divmod__(self, right)`
`__pow__(self, right)`
`__lshift__(self, right)`
`__rshift__(self, right)`
`__and__(self, right)`
`__xor__(self, right)`
__or__(self, right)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.
`__radd__(self, left)`
`__rsub__(self, left)`
`__rmul__(self, left)`
`__rdiv__(self, left)`
`__rmod__(self, left)`
`__rdivmod__(self, left)`
`__rpow__(self, left)`
`__rlshift__(self, left)`
`__rrshift__(self, left)`
`__rand__(self, left)`
`__rxor__(self, left)`
`__ror__(self, left)` These functions are called to implement the binary arithmetic operations (`+`, `-`, `*`, `/`, `%`, `divmod()`, `pow()`, `<<`, `>>`, `&`, `^`, `|`) with reversed operands. These functions are only called if the left operand does not support the corresponding operation (possibly after coercion). For instance: to evaluate the expression x+y, where x is an instance of a class that does not have an __add__ method, y.__radd(x) is called. If the class defines a __coerce__ method that coerces its arguments to a common type, these methods will never be called and thus needn't be defined. They are useful for classes that implement semi-numerical data types (types that have some numerical behavior but don't adhere to all invariants usually assumed about numbers).
`__neg__(self)`
`__pos__(self)`
`__abs__(self)`
`__invert__(self)` Called to implement the unary arithmetic operations (`-`, `+`, `abs()` and `~`).
`__int__(self)`
`__long__(self)`
`__float__(self)` Called to implement the built-in functions `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 no conversion is possible. 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 (see [Ref:XXX]) 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.
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Chapter 4: Execution model

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## Chapter 4: Execution model
### 4.1 Code blocks, execution frames, and name spaces
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 string argument passed to the built-in function `eval` and to the `exec` statement are code blocks. The file read by the built-in function execfile 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 name spaces, the local and the global name space, that affect execution of the code block.
A name space is a mapping from names (identifiers) to objects. A particular name space may be referenced by more than one execution frame, and from other places as well. Adding a name to a name space is called binding a name (to an object); changing the mapping of a name is called rebinding; removing a name is unbinding. Name spaces are functionally equivalent to dictionaries (and often implemented as dictionaries).
The local name space of an execution frame determines the default place where names are defined and searched. The global name space 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 specified 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 name space; global names are searched only in the global and built-in namespace.(1) (ref4.html#FN1)
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 name space, it is searched in the built-in namespace. The built-in namespace associated with the execution of a code block is actually found by looking up the name __builtins__ is its global name space; 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, see [Ref:XXX]. When a name is not found at all, a `NameError` exception is raised.
The following table lists the local and global name space used for all types of code blocks. The name space for a particular module is automatically created when the module is first imported. Note that in almost all cases, the global name space is the name space of the containing module scopes in Python do not nest! Notes:
Table 3: Name Spaces for Various Code Blocks (ref4.tbl_1.ps)
```text

---------------------------------------------------------------------------------------------------
Code block type Global name space Local name space Notes
---------------------------------------------------------------------------------------------------
Module n.s. for this module same as global
Script (file or command) n.s. for
__main__
same as global (1)
Interactive command n.s. for
__main__
same as global
Class definition global n.s. of containing block new n.s.
Function body global n.s. of containing block new n.s.
String passed to global n.s. of containing block local n.s. of containing (2), (3)

exec
statement block
String passed to
eval()
global n.s. of caller local n.s. of caller (2), (3)
File read by
execfile()
global n.s. of caller local n.s. of caller (2), (3)
Expression read by
input
global n.s. of caller local n.s. of caller
---------------------------------------------------------------------------------------------------
```
n.s.means name space
(1)The main module for a script is always called __main__; ``the filename don't enter into it.''
(2)The global and local name space 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 name space, respectively. The effect of modifications to this dictionary on the name space are undefined.(2) (ref4.html#FN2)
### 4.2 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 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 this case, the interpreter normally prints a stack backtrace.
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` and `raise` statements in "Compound statements" on page45 (ref7.html#REF24886).
---
### Footnotes
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Chapter 5: Expressions

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## Chapter 5: 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
```text

name: othername
```
and no semantics are given, the semantics of this form of name are the same as for othername.
### 5.1 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 (ref3.html#REF19057). If both arguments are standard numeric types, the following coercions are applied:
Some additional rules apply for certain operators (e.g. a string left argument to the `%' operator). Extensions can define their own coercions.
### 5.2 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:
```text

atom: identifier | literal | enclosure
enclosure: parenth_form|list_display|dict_display|string_conversion
```
#### 5.2.1 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).
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
#### 5.2.2 Literals
Python supports string literals and various numeric literals:
```text

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 "Literals" on page6 (ref2.html#REF40553) 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.
(In the original implementation, all literals in the same code block with the same type and value yield the same object.)
#### 5.2.3 Parenthesized forms
A parenthesized form is an optional expression list enclosed in parentheses:
```text

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.
#### 5.2.4 List displays
A list display is a possibly empty series of expressions enclosed in square brackets:
```text

list_display: "[" [expression_list] "]"
```
A list display yields a new list object. If it has no expression list, the list object has no items. Otherwise, the elements of the expression list are evaluated from left to right and inserted in the list object in that order.
#### 5.2.5 Dictionary displays
A dictionary display is a possibly empty series of key/datum pairs enclosed in curly braces:
```text

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 "The standard type hierarchy" on page12 (ref3.html#REF22319) (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.
#### 5.2.6 String conversions
A string conversion is an expression list enclosed in reverse (a.k.a. backward) quotes:
```text

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.
### 5.3 Primaries
Primaries represent the most tightly bound operations of the language. Their syntax is:
```text

primary: atom | attributeref | subscription | slicing | call
```
#### 5.3.1 Attribute references
An attribute reference is a primary followed by a period and a name:
```text

attributeref: primary "." identifier
```
The primary must evaluate to an object of a type that supports attribute references. 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.
#### 5.3.2 Subscriptions
A subscription selects an item of a sequence (string, tuple or list) or mapping (dictionary) object:
```text

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.
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.
#### 5.3.3 Slicings
A slicing selects a range of items in a sequence (string, tuple or list) object. Slicings may be used as expressions or as targets in assignment or del statements. The syntax for a slicing:
```text

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 | ellipses
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
ellipses: "..."
```
There's an 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 declaring 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 sequence's length, 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 ellipses slice item is the built-in Ellipses object. The conversion of a proper slice is a slice object (see page17 (ref3.html#REF18920)) 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.
#### 5.3.4 Calls
A call calls a callable object (e.g. a function) with a possibly empty series of arguments:
```text

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 "Function definitions" on page48 (ref7.html#REF27502) 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"Function definitions" on page48 (ref7.html#REF27502). 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 library reference manual 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.
### 5.4 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:
```text

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: 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.
### 5.5 Unary arithmetic operations
All unary arithmetic (and bit-wise) operations have the same priority:
```text

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.
### 5.6 Binary arithmetic operations
The remaining 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:
```text

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 a plain integer 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 a similar identity holds where x/y is replaced by floor(x/y)) orfloor((x/y).real), respectively.
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.
### 5.7 Shifting operations
The shifting operations have lower priority than the arithmetic operations:
```text

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 this 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.
### 5.8 Binary bit-wise operations
Each of the three bitwise operations has a different priority level:
```text

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 bit-wise 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.
### 5.9 Comparisons
Contrary to C, all comparison operations in Python have the same priority, which is lower than that of any arithmetic, shifting or bitwise operation. Also contrary to C, expressions like a < b < c have the interpretation that is conventional in mathematics:
```text

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 implied.
The operators "<", ">", "==", ">=", "<=", and "!=" compare the values of two objects. The objects needn't have the same type. If both are numbers, they are converted to a common type. Otherwise, objects of different types always compare unequal, and are ordered consistently but arbitrarily. (This unusual definition of comparison is done to simplify the definition of operations like sorting and the in and not in operators.)
Comparison of objects of the same type depends on the type:
The operators in and not in test for sequence membership: if y is a sequence, x in y is true if and only if there exists an index i such that x = y[i]. x not in y yields the inverse truth value. The exception TypeError is raised when y is not a sequence, or when y is a string and x is not a string of length one.(2) (ref5.html#FN2)
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.
### 5.10 Boolean operations
Boolean operations have the lowest priority of all Python operations:
```text

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
```text

def name (arguments):
return expression
```
See "Function definitions" on page48 (ref7.html#REF27502) for the syntax of parameter lists. Note that functions created with lambda forms cannot contain statements.
### 5.11 Expression lists
```text

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 single); it is optional in all other cases. A single expression without a trailing comma doesn't create a tuple, but rather yields the value of that expression. (To create an empty tuple, use an empty pair of parentheses: ().)
### 5.12 Summary
The following table summarizes the operator precedences in Python, from lowest precedence (least binding) to highest precedence (most binding). Operators in the same box have the same precedence. Unless the syntax is explicitly given, operators are binary. Operators in the same box group left to right (except for comparisons, which chain from left to right see above).
Table 4: Operator Precedence (ref5.tbl_1.ps)
```text

------------------------------------------------------------

or
Boolean OR

and
Boolean AND

not
x
Boolean NOT

in, not in Membership tests
is, is not Identity tests
<, <=, >, >=, <>, !=, =
Comparisons

|
Bitwise OR

^
Bitwise XOR

&
Bitwise AND

<<, >>
Shifts

+, -
Addition and subtraction

*, /, %
Multiplication, division, remainder

+x, -x Positive, negative
~x
Bitwise not

x.attribute Attribute reference
x
[
index
] Subscription

x
[
index:index
] Slicing

f
(
arguments
, ...) Function call
(
expressions
. . .) Binding or tuple display
[
expressions
. . .] List display
{
key:datum
, . . .} Dictionary display
`
expression
` String conversion
------------------------------------------------------------
```
---
### Footnotes
Table of Contents (ref.book.html)
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Chapter 6: Simple statements

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This file was created with the fm2html filter.
The filter is copyright Norwegian Telecom Research and
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## Chapter 6: Simple statements
Simple statements are comprised within a single logical line. Several simple statements may occur on a single line separated by semicolons. The syntax for simple statements is:
```text

simple_stmt: expression_stmt
| assignment_stmt
| pass_stmt
| del_stmt
| print_stmt
| return_stmt
| raise_stmt
| break_stmt
| continue_stmt
| import_stmt
| global_stmt
| exec_stmt
```
### 6.1 Expression statements
Expression statements are used (mostly interactively) to compute and write a value, or (usually) to call a procedure (a function that returns no meaningful result; in Python, procedures return the value `None`). Other uses of expression statements are allowed and occasionally useful. The syntax for an expression statement is:
```text

expression_stmt: expression_list
```
An expression statement evaluates the expression list (which may be a single expression). In interactive mode, if the value is not `None`, it is converted to a string using the built-in repr() function and the resulting string is written to standard output (see "The print statement" on page41 (ref6.html#REF25905)) on a line by itself. (Expression statements yielding None are not written, so that procedure calls do not cause any output.)
### 6.2 Assignment statements
Assignment statements are used to (re)bind names to values and to modify attributes or items of mutable objects:
```text

assignment_stmt: (target_list "=")+ expression_list
target_list: target ("," target)* [","]
target: identifier | "(" target_list ")" | "[" target_list "]"
| attributeref | subscription | slicing
```
(See "Primaries" on page29 (ref5.html#REF30293) for the syntax definitions for the last three symbols.)
An assignment statement evaluates the expression list (remember that this can be a single expression or a comma-separated list, the latter yielding a tuple) and assigns the single resulting object to each of the target lists, from left to right.
Assignment is defined recursively depending on the form of the target (list). When a target is part of a mutable object (an attribute reference, subscription or slicing), the mutable object must ultimately perform the assignment and decide about its validity, and may raise an exception if the assignment is unacceptable. The rules observed by various types and the exceptions raised are given with the definition of the object types (See "The standard type hierarchy" on page12. (ref3.html#REF22319))
Assignment of an object to a target list is recursively defined as follows.
Assignment of an object to a single target is recursively defined as follows.
If the name does not occur in a `global` statement in the current code block: the name is bound to the object in the current local name space.
Otherwise: the name is bound to the object in the current global name space.
(In the current implementation, the syntax for targets is taken to be the same as for expressions, and invalid syntax is rejected during the code generation phase, causing less detailed error messages.)
WARNING: Although the definition of assignment implies that overlaps between the left-hand side and the right-hand side are `safe' (e.g. ```a,` `b` `=` `b,` `a`'' swaps two variables), overlaps within the collection of assigned-to variables are not safe! For instance, the following program prints ``[0,2]'':
```text

x = [0, 1]
i = 0
i, x[i] = 1, 2
print x
```
### 6.3 The `pass` statement
```text

pass_stmt: "pass"
```
pass is a null operation when it is executed, nothing happens. It is useful as a placeholder when a statement is required syntactically, but no code needs to be executed, for example:
```text

def f(arg): pass # a function that does nothing (yet)
class C: pass # a class with no methods (yet)
```
### 6.4 The `del` statement
```text

del_stmt: "del" target_list
```
Deletion is recursively defined very similar to the way assignment is defined. Rather that spelling it out in full details, here are some hints.
Deletion of a target list recursively deletes each target, from left to right.
Deletion of a name removes the binding of that name (which must exist) from the local or global name space, depending on whether the name occurs in a `global` statement in the same code block.
Deletion of attribute references, subscriptions and slicings is passed to the primary object involved; deletion of a slicing is in general equivalent to assignment of an empty slice of the right type (but even this is determined by the sliced object).
### 6.5 The `print` statement
```text

print_stmt: "print" [ expression ("," expression)* [","] ]
```
print evaluates each expression in turn and writes the resulting object to standard output (see below). If an object is not a string, it is first converted to a string using the rules for string conversions. The (resulting or original) string is then written. A space is written before each object is (converted and) written, unless the output system believes it is positioned at the beginning of a line. This is the case: (1) when no characters have yet been written to standard output; or (2) when the last character written to standard output is `\n`; or (3) when the last write operation on standard output was not a `print` statement. (In some cases it may be functional to write an empty string to standard output for this reason.)
A `"\n"` character is written at the end, unless the `print` statement ends with a comma. This is the only action if the statement contains just the keyword `print`. Standard output is defined as the file object named `stdout`in the built-in module `sys`. If no such object exists, or if it is not a writable file, a `RuntimeError` exception is raised. (The original implementation attempts to write to the system's original standard output instead, but this is not safe, and should be fixed.)
### 6.6 The `return` statement
```text

return_stmt: "return" [expression_list]
```
return may only occur syntactically nested in a function definition, not within a nested class definition.
If an expression list is present, it is evaluated, else `None`is substituted.
`return` leaves the current function call with the expression list (or `None`) as return value.
When `return` passes control out of a `try` statement with a `finally` clause, that finally clause is executed before really leaving the function.
### 6.7 The `raise` statement
```text

raise_stmt: "raise" expression ["," expression ["," expression]]
```
raise evaluates its first expression, which must yield a string, class, or instance object. If there is a second expression, this is evaluated, else `None` is substituted. If the first expression is a class object, then the second expression must be an instance of that class or one of its derivatives. If the first expression is an instance object, the second expression must be `None`.
If the first object is a class or string, it then raises the exception identified by the first object, with the second one (or `None`) as its parameter. If the first object is an instance, it raises the exception identified by the class of the object, with the instance as its parameter (and there should be no second object, or the second object should be `None`).
If a third object is present, and it is not `None`, it should be a traceback object (see page17 (ref3.html#REF27144) traceback objects), and it is substituted instead of the current location as the place where the exception occurred. This is useful to re-raise an exception transparently in an except clause.
### 6.8 The `break` statement
```text

break_stmt: "break"
```
break may only occur syntactically nested in a `for`or `while` loop, but not nested in a function or class definition within that loop.
It terminates the nearest enclosing loop, skipping the optional `else` clause if the loop has one.
If a `for` loop is terminated by `break`, the loop control target keeps its current value.
When `break` passes control out of a `try` statement with a `finally` clause, that finally clause is executed before really leaving the loop.
### 6.9 The `continue` statement
```text

continue_stmt: "continue"
```
continue may only occur syntactically nested in a `for` or `while` loop, but not nested in a function or class definition or `try` statement within that loop.(1) (ref6.html#FN1) It continues with the next cycle of the nearest enclosing loop.
### 6.10 The `import` statement
```text

import_stmt: "import" identifier ("," identifier)*
| "from" identifier "import" identifier ("," identifier)*
| "from" identifier "import" "*"
```
Import statements are executed in two steps: (1) find a module, and initialize it if necessary; (2) define a name or names in the local name space (of the scope where the `import` statement occurs). The first form (without `from`) repeats these steps for each identifier in the list, the `from` form performs them once, with the first identifier specifying the module name.
The system maintains a table of modules that have been initialized, indexed by module name. (The current implementation makes this table accessible as `sys.modules`.) When a module name is found in this table, step (1) is finished. If not, a search for a module definition is started. This first looks for a built-in module definition, and if no built-in module if the given name is found, it searches a user-specified list of directories for a file whose name is the module name with extension `".py"`. (The current implementation uses the list of strings `sys.path` as the search path; it is initialized from the shell environment variable `$PYTHONPATH`, with an installation-dependent default.)
If a built-in module is found, its built-in initialization code is executed and step (1) is finished. If no matching file is found, `ImportError` is raised. If a file is found, it is parsed, yielding an executable code block. If a syntax error occurs, `SyntaxError` is raised. Otherwise, an empty module of the given name is created and inserted in the module table, and then the code block is executed in the context of this module. Exceptions during this execution terminate step (1).
When step (1) finishes without raising an exception, step (2) can begin.
The first form of `import` statement binds the module name in the local name space to the module object, and then goes on to import the next identifier, if any. The `from` form does not bind the module name: it goes through the list of identifiers, looks each one of them up in the module found in step (1), and binds the name in the local name space to the object thus found. If a name is not found, `ImportError` is raised. If the list of identifiers is replaced by a star (`*`), all names defined in the module are bound, except those beginning with an underscore(`_`).
Names bound by import statements may not occur in `global` statements in the same scope.
The `from` form with `*` may only occur in a module scope.
(The current implementation does not enforce the latter two restrictions, but programs should not abuse this freedom, as future implementations may enforce them or silently change the meaning of the program.)
### 6.11 The `global` statement
```text

global_stmt: "global" identifier ("," identifier)*
```
The `global` statement is a declaration which holds for the entire current code block. It means that the listed identifiers are to be interpreted as globals. While using global names is automatic if they are not defined in the local scope, assigning to global names would be impossible without `global`.
Names listed in a `global` statement must not be used in the same code block before that `global` statement is executed.
Names listed in a `global` statement must not be defined as formal parameters or in a `for` loop control target, `class`definition, function definition, or `import` statement.
(The current implementation does not enforce the latter two restrictions, but programs should not abuse this freedom, as future implementations may enforce them or silently change the meaning of the program.)
Note: the `global` is a directive to the parser. Therefore, it applies only to code parsed at the same time as the `global`statement. In particular, a `global` statement contained in an `exec` statement does not affect the code block containing the `exec` statement, and code contained in an `exec`statement is unaffected by `global` statements in the code containing the `exec` statement. The same applies to the `eval()`, `execfile()` and `compile()` functions.
### 6.12 The `exec` statement
```text

exec_stmt: "exec" expression ["in" expression ["," expression]]
```
This statement supports dynamic execution of Python code. The first expression should evaluate to either a string, an open file object, or a code object. If it is a string, the string is parsed as a suite of Python statements which is then executed (unless a syntax error occurs). If it is an open file, the file is parsed until EOF and executed. If it is a code object, it is simply executed.
In all cases, if the optional parts are omitted, the code is executed in the current scope. If only the first expression after `in` is specified, it should be a dictionary, which will be used for both the global and the local variables. If two expressions are given, both must be dictionaries and they are used for the global and local variables, respectively.
Hints: dynamic evaluation of expressions is supported by the built-in function `eval()`. The built-in functions `globals()` and `locals()` return the current global and local dictionary, respectively, which may be useful to pass around for use by `exec`.
---
### Footnotes
Table of Contents (ref.book.html)
Next Chapter (ref7.html)