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.

This 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.

This type has a single value. There is a single object with this value. This object is accessed through the built-in name NotImplemented. Numeric methods and rich comparison methods may return this value if they do not implement the operation for the operands provided. (The interpreter will then try the reflected operation, or some other fallback, depending on the operator.) Its truth value is true.

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.

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, floating point numbers, and complex numbers:

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 would fall 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 processor 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.

These represent finite ordered sets indexed by non-negative 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-1. 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.

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 collection of objects directly referenced by an immutable object cannot change.)

The following types are immutable sequences:

The 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.

(On systems whose native character set is not ASCII, strings may use EBCDIC in their internal representation, provided the functions chr() and ord() implement a mapping between ASCII and EBCDIC, and string comparison preserves the ASCII order. Or perhaps someone can propose a better rule?)

The items of a Unicode object are Unicode characters. A Unicode character is represented by a Unicode object of one item and can hold a 16-bit value representing a Unicode ordinal. The built-in functions unichr() and ord() convert between characters and nonnegative integers representing the Unicode ordinals as defined in the Unicode Standard 3.0. Conversion from and to other encodings are possible through the Unicode method encode and the built-in function unicode() 

The 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 an empty pair of 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:

The 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 extension module array provides an additional example of a mutable sequence type.

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:

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 hash 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 section 5.2.5, ``Dictionary Displays'').

The extension modules dbm  gdbm  bsddb provide additional examples of mapping types.

Callable types
These are the types to which the function call operation (see section 5.3.4, ``Calls'') can be applied:

User-defined functions
A user-defined function object is created by a function definition (see section 7.5, ``Function definitions''). It should be called with an argument list containing the same number of items as the function's formal parameter list.

Special 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 namespace of the module in which the function was defined; func_dict or __dict__ contains the namespace supporting arbitrary function attributes; func_closure is None or a tuple of cells that contain binding for the function's free variables.

Of these, func_code, func_defaults, func_closure, func_doc/__doc__, and func_dict/__dict__ may be writable; the others can never be changed. Additional information about a function's definition can be retrieved from its code object; see the description of internal types below.

In Python 2.1, the func_closure slot is always None unless nested scopes are enabled. (See the appendix.)


User-defined methods
A user-defined method object combines a class, a class instance (or None) and any callable object (normally a user-defined function).

Special read-only attributes: im_self is the class instance object, im_func is the function object; im_class is the class of im_self for bound methods, or the class that asked for the method for unbound methods); __doc__ is the method's documentation (same as im_func.__doc__); __name__ is the method name (same as im_func.__name__). Changed in version 2.2: im_self used to refer to the class that defined the method.  

Methods also support accessing (but not setting) the arbitrary function attributes on the underlying function object.

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 attribute of a class instance that is a user-defined function object defined by the class of the instance. 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 has a method 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_func 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_func 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. It is also important to note that user-defined functions which are attributes of a class instance are not converted to bound methods; this only happens when the function is an attribute of the class.

Generator functions 
A function or method which uses the yield statement (see section 6.8, ``The yield statement'') is called a generator function. Such a function, when called, always returns an iterator object which can be used to execute the body of the function: calling the iterator's next() method will cause the function to execute until it provides a value using the yield statement. When the function executes a return statement or falls off the end, a StopIteration exception is raised and the iterator will have reached the end of the set of values to be returned.

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 item).

Built-in methods
This is really a different disguise of a built-in function, this time containing an object passed to the C function as an implicit extra argument. An example of a built-in method is 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.

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 are callable only when the class has a __call__() method; x(arguments) is a shorthand for x.__call__(arguments).

Modules are imported by the import statement (see section 6.12, ``The import statement''). A module object has a namespace 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 updates the module's namespace dictionary, e.g., "m.x = 1" is equivalent to "m.__dict__["x"] = 1".

Special read-only attribute: __dict__ is the module's namespace as a dictionary object.  

Predefined (writable) attributes: __name__ is the module's 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.   

Class objects are created by class definitions (see section 7.6, ``Class definitions''). A class has a namespace 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 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 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 (see above) to yield a class instance (see below).

Special attributes: __name__ is the class name; __module__ is the module name in which the class was defined; __dict__ is the dictionary containing the class's namespace; __bases__ is a tuple (possibly empty or a singleton) containing the base classes, in the order of their occurrence in the base class list; __doc__ is the class's documentation string, or None if undefined.  

Class instances
A class instance is created by calling a class object (see above). A class instance has a namespace implemented as a dictionary which is the first place in which attribute references are searched. When an attribute is not found there, and the instance's class has an attribute by that name, 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 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, or mappings if they have methods with certain special names. See section 3.3, ``Special method names.''

Special attributes: __dict__ is the attribute dictionary; __class__ is the instance's class.  

A file object represents an open file. File objects are created by the open() built-in function, and also by  os.popen(), os.fdopen(), and the makefile() method of socket objects (and perhaps by other functions or methods provided by extension modules). 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 complete documentation of file objects.  

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-compiled 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 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_name gives the function name; 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_cellvars is a tuple containing the names of local variables that are referenced by nested functions; co_freevars is a tuple containing the names of local variables that are neither local nor global; 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_firstlineno is the first line number of the function; co_lnotab is a string encoding the mapping from byte code offsets to line numbers (for details see the source code of the interpreter); co_stacksize is the required stack size (including local variables); co_flags is an integer encoding a number of flags for the interpreter.

The co_cellvars and co_freevars are present in Python 2.1 when nested scopes are not enabled, but the code itself does not use or create cells.


The following flag bits are defined for co_flags: bit 0x04 is set if the function uses the "*arguments" syntax to accept an arbitrary number of positional arguments; bit 0x08 is set if the function uses the "**keywords" syntax to accept arbitrary keyword arguments; other bits are used internally or reserved for future use; bit 0x10 is set if the function was compiled with nested scopes enabled. If a code object represents a function, the first item in co_consts is the documentation string of the function, or None if undefined.

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 local 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_lineno gives the line number and f_lasti gives the precise instruction (this is an index into the bytecode 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); f_exc_type, f_exc_value, f_exc_traceback represent the most recent exception caught in this frame.  

Traceback objects
Traceback objects represent a stack trace of an exception. A traceback object is created when an exception occurs. When the search for an exception handler unwinds the execution stack, at each unwound level a traceback object is inserted in front of the current traceback. When an exception handler is entered, the stack trace is made available to the program. (See section 7.4, ``The try statement.'') It is accessible as sys.exc_traceback, and also as the third item of the tuple returned by sys.exc_info(). The latter is the preferred interface, since it works correctly when the program is using multiple threads. 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 lower bound; stop is the upper bound; step is the step value; each is None if omitted. These attributes can have any type.  

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