Built-in Functions¶

The Python interpreter has a number of functions and types built into it that are always available. They are listed here in alphabetical order.

abs(x)¶

Return the absolute value of a number. The argument may be an integer or a floating point number. If the argument is a complex number, its magnitude is returned.

all(iterable)¶

Return True if all elements of the iterable are true. Equivalent to:

def all(iterable):
    for element in iterable:
        if not element:
            return False
    return True

any(iterable)¶

Return True if any element of the iterable is true. Equivalent to:

def any(iterable):
    for element in iterable:
        if element:
            return True
    return False

ascii(object)¶

As repr(), return a string containing a printable representation of an object, but escape the non-ASCII characters in the string returned by repr() using \x, \u or \U escapes. This generates a string similar to that returned by repr() in Python 2.

bin(x)¶

Convert an integer number to a binary string. The result is a valid Python expression. If x is not a Python int object, it has to define an __index__() method that returns an integer.

bool([x])¶

Convert a value to a Boolean, using the standard truth testing procedure. If x is false or omitted, this returns False; otherwise it returns True. bool is also a class, which is a subclass of int. Class bool cannot be subclassed further. Its only instances are False and True.

bytearray([arg[, encoding[, errors]]])¶

Return a new array of bytes. The bytearray type is a mutable sequence of integers in the range 0 <= x < 256. It has most of the usual methods of mutable sequences, described in Mutable Sequence Types, as well as most methods that the str type has, see Bytes and Byte Array Methods.

The optional arg parameter can be used to initialize the array in a few different ways:

• If it is a string, you must also give the encoding (and optionally, errors) parameters; bytearray() then converts the string to bytes using str.encode().
• If it is an integer, the array will have that size and will be initialized with null bytes.
• If it is an object conforming to the buffer interface, a read-only buffer of the object will be used to initialize the bytes array.
• If it is an iterable, it must be an iterable of integers in the range 0 <= x < 256, which are used as the initial contents of the array.

Without an argument, an array of size 0 is created.

bytes([arg[, encoding[, errors]]])¶

Return a new “bytes” object, which is an immutable sequence of integers in the range 0 <= x < 256. bytes is an immutable version of bytearray – it has the same non-mutating methods and the same indexing and slicing behavior.

Accordingly, constructor arguments are interpreted as for buffer().

Bytes objects can also be created with literals, see String and Bytes literals.

chr(i)¶

Return the string of one character whose Unicode codepoint is the integer i. For example, chr(97) returns the string 'a'. This is the inverse of ord(). The valid range for the argument depends how Python was configured – it may be either UCS2 [0..0xFFFF] or UCS4 [0..0x10FFFF]. ValueError will be raised if i is outside that range.

classmethod(function)¶

Return a class method for function.

A class method receives the class as implicit first argument, just like an instance method receives the instance. To declare a class method, use this idiom:

class C:
    @classmethod
    def f(cls, arg1, arg2, ...): ...

The @classmethod form is a function decorator – see the description of function definitions in Function definitions for details.

It can be called either on the class (such as C.f()) or on an instance (such as C().f()). The instance is ignored except for its class. If a class method is called for a derived class, the derived class object is passed as the implied first argument.

Class methods are different than C++ or Java static methods. If you want those, see staticmethod() in this section.

For more information on class methods, consult the documentation on the standard type hierarchy in The standard type hierarchy.

compile(source, filename, mode[, flags[, dont_inherit]])¶

Compile the source into a code or AST object. Code objects can be executed by an exec statement or evaluated by a call to eval(). source can either be a string or an AST object. Refer to the ast module documentation for information on how to work with AST objects.

The filename argument should give the file from which the code was read; pass some recognizable value if it wasn’t read from a file ('<string>' is commonly used).

The mode argument specifies what kind of code must be compiled; it can be 'exec' if source consists of a sequence of statements, 'eval' if it consists of a single expression, or 'single' if it consists of a single interactive statement (in the latter case, expression statements that evaluate to something else than None will be printed).

The optional arguments flags and dont_inherit control which future statements (see PEP 236) affect the compilation of source. If neither is present (or both are zero) the code is compiled with those future statements that are in effect in the code that is calling compile. If the flags argument is given and dont_inherit is not (or is zero) then the future statements specified by the flags argument are used in addition to those that would be used anyway. If dont_inherit is a non-zero integer then the flags argument is it – the future statements in effect around the call to compile are ignored.

Future statements are specified by bits which can be bitwise ORed together to specify multiple statements. The bitfield required to specify a given feature can be found as the compiler_flag attribute on the _Feature instance in the __future__ module.

This function raises SyntaxError if the compiled source is invalid, and TypeError if the source contains null bytes.

Note

When compiling a string with multi-line statements, line endings must be represented by a single newline character ('\n'), and the input must be terminated by at least one newline character. If line endings are represented by '\r\n', use str.replace() to change them into '\n'.

complex([real[, imag]])¶

Create a complex number with the value real + imag*j or convert a string or number to a complex number. If the first parameter is a string, it will be interpreted as a complex number and the function must be called without a second parameter. The second parameter can never be a string. Each argument may be any numeric type (including complex). If imag is omitted, it defaults to zero and the function serves as a numeric conversion function like int() and float(). If both arguments are omitted, returns 0j.

The complex type is described in Numeric Types — int, float, complex.

delattr(object, name)¶

This is a relative of setattr(). The arguments are an object and a string. The string must be the name of one of the object’s attributes. The function deletes the named attribute, provided the object allows it. For example, delattr(x, 'foobar') is equivalent to del x.foobar.

dict([arg])

Create a new data dictionary, optionally with items taken from arg. The dictionary type is described in Mapping Types — dict.

For other containers see the built in list, set, and tuple classes, and the collections module.

dir([object])¶

Without arguments, return the list of names in the current local scope. With an argument, attempt to return a list of valid attributes for that object.

If the object has a method named __dir__(), this method will be called and must return the list of attributes. This allows objects that implement a custom __getattr__() or __getattribute__() function to customize the way dir() reports their attributes.

If the object does not provide __dir__(), the function tries its best to gather information from the object’s __dict__ attribute, if defined, and from its type object. The resulting list is not necessarily complete, and may be inaccurate when the object has a custom __getattr__().

The default dir() mechanism behaves differently with different types of objects, as it attempts to produce the most relevant, rather than complete, information:

• If the object is a module object, the list contains the names of the module’s attributes.
• If the object is a type or class object, the list contains the names of its attributes, and recursively of the attributes of its bases.
• Otherwise, the list contains the object’s attributes’ names, the names of its class’s attributes, and recursively of the attributes of its class’s base classes.

The resulting list is sorted alphabetically. For example:

>>> import struct
>>> dir()   # doctest: +SKIP
['__builtins__', '__doc__', '__name__', 'struct']
>>> dir(struct)   # doctest: +NORMALIZE_WHITESPACE
['Struct', '__builtins__', '__doc__', '__file__', '__name__',
 '__package__', '_clearcache', 'calcsize', 'error', 'pack', 'pack_into',
 'unpack', 'unpack_from']
>>> class Foo(object):
...     def __dir__(self):
...         return ["kan", "ga", "roo"]
...
>>> f = Foo()
>>> dir(f)
['ga', 'kan', 'roo']

Note

Because dir() is supplied primarily as a convenience for use at an interactive prompt, it tries to supply an interesting set of names more than it tries to supply a rigorously or consistently defined set of names, and its detailed behavior may change across releases. For example, metaclass attributes are not in the result list when the argument is a class.

divmod(a, b)¶

Take two (non complex) numbers as arguments and return a pair of numbers consisting of their quotient and remainder when using integer division. With mixed operand types, the rules for binary arithmetic operators apply. For integers, the result is the same as (a // b, a % b). For floating point numbers the result is (q, a % b), where q is usually math.floor(a / b) but may be 1 less than that. In any case q * b + a % b is very close to a, if a % b is non-zero it has the same sign as b, and 0 <= abs(a % b) < abs(b).

enumerate(iterable[, start=0])¶

Return an enumerate object. iterable must be a sequence, an iterator, or some other object which supports iteration. The __next__() method of the iterator returned by enumerate() returns a tuple containing a count (from start which defaults to 0) and the corresponding value obtained from iterating over iterable. enumerate() is useful for obtaining an indexed series: (0, seq[0]), (1, seq[1]), (2, seq[2]), .... For example:

>>> for i, season in enumerate(['Spring', 'Summer', 'Fall', 'Winter']):
...     print(i, season)
0 Spring
1 Summer
2 Fall
3 Winter

eval(expression[, globals[, locals]])¶

The arguments are a string and optional globals and locals. If provided, globals must be a dictionary. If provided, locals can be any mapping object.

The expression argument is parsed and evaluated as a Python expression (technically speaking, a condition list) using the globals and locals dictionaries as global and local namespace. If the globals dictionary is present and lacks ‘__builtins__’, the current globals are copied into globals before expression is parsed. This means that expression normally has full access to the standard builtins module and restricted environments are propagated. If the locals dictionary is omitted it defaults to the globals dictionary. If both dictionaries are omitted, the expression is executed in the environment where eval() is called. The return value is the result of the evaluated expression. Syntax errors are reported as exceptions. Example:

>>> x = 1
>>> eval('x+1')
2

This function can also be used to execute arbitrary code objects (such as those created by compile()). In this case pass a code object instead of a string. If the code object has been compiled with 'exec' as the kind argument, eval()‘s return value will be None.

Hints: dynamic execution of statements is supported by the exec() function. The globals() and locals() functions returns the current global and local dictionary, respectively, which may be useful to pass around for use by eval() or exec().

exec(object[, globals[, locals]])¶

This function supports dynamic execution of Python code. object must be either a string 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 a code object, it is simply executed. In all cases, the code that’s executed is expected to be valid as file input (see the section “File input” in the Reference Manual). Be aware that the return and yield statements may not be used outside of function definitions even within the context of code passed to the exec() function. The return value is None.

In all cases, if the optional parts are omitted, the code is executed in the current scope. If only globals is provided, it must be a dictionary, which will be used for both the global and the local variables. If globals and locals are given, they are used for the global and local variables, respectively. If provided, locals can be any mapping object.

If the globals dictionary does not contain a value for the key __builtins__, a reference to the dictionary of the built-in module builtins is inserted under that key. That way you can control what builtins are available to the executed code by inserting your own __builtins__ dictionary into globals before passing it to exec().

Note

The built-in functions globals() and locals() return the current global and local dictionary, respectively, which may be useful to pass around for use as the second and third argument to exec().

Warning

The default locals act as described for function locals() below: modifications to the default locals dictionary should not be attempted. Pass an explicit locals dictionary if you need to see effects of the code on locals after function exec() returns.

filter(function, iterable)¶

Construct an iterator from those elements of iterable for which function returns true. iterable may be either a sequence, a container which supports iteration, or an iterator. If function is None, the identity function is assumed, that is, all elements of iterable that are false are removed.

Note that filter(function, iterable) is equivalent to the generator expression (item for item in iterable if function(item)) if function is not None and (item for item in iterable if item) if function is None.

float([x])¶

Convert a string or a number to floating point. If the argument is a string, it must contain a possibly signed decimal or floating point number, possibly embedded in whitespace. The argument may also be '[+|-]nan' or '[+|-]inf'. Otherwise, the argument may be an integer or a floating point number, and a floating point number with the same value (within Python’s floating point precision) is returned. If no argument is given, 0.0 is returned.

Note

When passing in a string, values for NaN and Infinity may be returned, depending on the underlying C library. Float accepts the strings 'nan', 'inf' and '-inf' for NaN and positive or negative infinity. The case and a leading + are ignored as well as a leading - is ignored for NaN. Float always represents NaN and infinity as nan, inf or -inf.

The float type is described in Numeric Types — int, float, complex.

format(value[, format_spec])¶

Convert a string or a number to a “formatted” representation, as controlled by format_spec. The interpretation of format_spec will depend on the type of the value argument, however there is a standard formatting syntax that is used by most built-in types: Format Specification Mini-Language.

Note

format(value, format_spec) merely calls value.__format__(format_spec).

frozenset([iterable])

Return a frozenset object, optionally with elements taken from iterable. The frozenset type is described in Set Types — set, frozenset.

For other containers see the built in dict, list, and tuple classes, and the collections module.

getattr(object, name[, default])¶

Return the value of the named attributed of object. name must be a string. If the string is the name of one of the object’s attributes, the result is the value of that attribute. For example, getattr(x, 'foobar') is equivalent to x.foobar. If the named attribute does not exist, default is returned if provided, otherwise AttributeError is raised.

globals()¶

Return a dictionary representing the current global symbol table. This is always the dictionary of the current module (inside a function or method, this is the module where it is defined, not the module from which it is called).

hasattr(object, name)¶

The arguments are an object and a string. The result is True if the string is the name of one of the object’s attributes, False if not. (This is implemented by calling getattr(object, name) and seeing whether it raises an exception or not.)

hash(object)¶

Return the hash value of the object (if it has one). Hash values are integers. They are used to quickly compare dictionary keys during a dictionary lookup. Numeric values that compare equal have the same hash value (even if they are of different types, as is the case for 1 and 1.0).

help([object])¶

Invoke the built-in help system. (This function is intended for interactive use.) If no argument is given, the interactive help system starts on the interpreter console. If the argument is a string, then the string is looked up as the name of a module, function, class, method, keyword, or documentation topic, and a help page is printed on the console. If the argument is any other kind of object, a help page on the object is generated.

This function is added to the built-in namespace by the site module.

hex(x)¶

Convert an integer number to a hexadecimal string. The result is a valid Python expression. If x is not a Python int object, it has to define an __index__() method that returns an integer.

id(object)¶

Return the “identity” of an object. This is an integer which is guaranteed to be unique and constant for this object during its lifetime. Two objects with non-overlapping lifetimes may have the same id() value. (Implementation note: this is the address of the object.)

input([prompt])¶

If the prompt argument is present, it is written to standard output without a trailing newline. The function then reads a line from input, converts it to a string (stripping a trailing newline), and returns that. When EOF is read, EOFError is raised. Example:

>>> s = input('--> ')
--> Monty Python's Flying Circus
>>> s
"Monty Python's Flying Circus"

If the readline module was loaded, then input() will use it to provide elaborate line editing and history features.

int([number | string[, radix]])¶

Convert a number or string to an integer. If no arguments are given, return 0. If a number is given, return number.__int__(). Conversion of floating point numbers to integers truncates towards zero. A string must be a base-radix integer literal optionally preceded by ‘+’ or ‘-‘ (with no space in between) and optionally surrounded by whitespace. A base-n literal consists of the digits 0 to n-1, with ‘a’ to ‘z’ (or ‘A’ to ‘Z’) having values 10 to 35. The default radix is 10. The allowed values are 0 and 2-36. Base-2, -8, and -16 literals can be optionally prefixed with 0b/0B, 0o/0O, or 0x/0X, as with integer literals in code. Radix 0 means to interpret exactly as a code literal, so that the actual radix is 2, 8, 10, or 16, and so that int('010', 0) is not legal, while int('010') is, as well as int('010', 8).

The integer type is described in Numeric Types — int, float, complex.

isinstance(object, classinfo)¶

Return true if the object argument is an instance of the classinfo argument, or of a (direct or indirect) subclass thereof. If object is not an object of the given type, the function always returns false. If classinfo is not a class (type object), it may be a tuple of type objects, or may recursively contain other such tuples (other sequence types are not accepted). If classinfo is not a type or tuple of types and such tuples, a TypeError exception is raised.

issubclass(class, classinfo)¶

Return true if class is a subclass (direct or indirect) of classinfo. A class is considered a subclass of itself. classinfo may be a tuple of class objects, in which case every entry in classinfo will be checked. In any other case, a TypeError exception is raised.

iter(o[, sentinel])¶

Return an iterator object. The first argument is interpreted very differently depending on the presence of the second argument. Without a second argument, o must be a collection object which supports the iteration protocol (the __iter__() method), or it must support the sequence protocol (the __getitem__() method with integer arguments starting at 0). If it does not support either of those protocols, TypeError is raised. If the second argument, sentinel, is given, then o must be a callable object. The iterator created in this case will call o with no arguments for each call to its __next__() method; if the value returned is equal to sentinel, StopIteration will be raised, otherwise the value will be returned.

len(s)¶

Return the length (the number of items) of an object. The argument may be a sequence (string, tuple or list) or a mapping (dictionary).

list([iterable])¶

Return a list whose items are the same and in the same order as iterable‘s items. iterable may be either a sequence, a container that supports iteration, or an iterator object. If iterable is already a list, a copy is made and returned, similar to iterable[:]. For instance, list('abc') returns ['a', 'b', 'c'] and list( (1, 2, 3) ) returns [1, 2, 3]. If no argument is given, returns a new empty list, [].

list is a mutable sequence type, as documented in Sequence Types — str, bytes, bytearray, list, tuple, range.

locals()¶

Update and return a dictionary representing the current local symbol table.

Warning

The contents of this dictionary should not be modified; changes may not affect the values of local variables used by the interpreter.

Free variables are returned by locals() when it is called in a function block. Modifications of free variables may not affect the values used by the interpreter. Free variables are not returned in class blocks.

map(function, iterable, ...)¶

Return an iterator that applies function to every item of iterable, yielding the results. If additional iterable arguments are passed, function must take that many arguments and is applied to the items from all iterables in parallel. With multiple iterables, the iterator stops when the shortest iterable is exhausted.

max(iterable[, args...], *[, key])¶

With a single argument iterable, return the largest item of a non-empty iterable (such as a string, tuple or list). With more than one argument, return the largest of the arguments.

The optional keyword-only key argument specifies a one-argument ordering function like that used for list.sort().

memoryview(obj)

Return a “memory view” object created from the given argument. See memoryview Types for more information.

min(iterable[, args...], *[, key])¶

With a single argument iterable, return the smallest item of a non-empty iterable (such as a string, tuple or list). With more than one argument, return the smallest of the arguments.

The optional keyword-only key argument specifies a one-argument ordering function like that used for list.sort().

next(iterator[, default])¶

Retrieve the next item from the iterator by calling its __next__() method. If default is given, it is returned if the iterator is exhausted, otherwise StopIteration is raised.

object()¶

Return a new featureless object. object is a base for all classes. It has the methods that are common to all instances of Python classes. This function does not accept any arguments.

Note

object does not have a __dict__, so you can’t assign arbitrary attributes to an instance of the object class.

oct(x)¶

Convert an integer number to an octal string. The result is a valid Python expression. If x is not a Python int object, it has to define an __index__() method that returns an integer.

open(file[, mode='r'[, buffering=None[, encoding=None[, errors=None[, newline=None[, closefd=True]]]]]])¶

Open a file. If the file cannot be opened, IOError is raised.

file is either a string or bytes object giving the name (and the path if the file isn’t in the current working directory) of the file to be opened or an integer file descriptor of the file to be wrapped. (If a file descriptor is given, it is closed when the returned I/O object is closed, unless closefd is set to False.)

mode is an optional string that specifies the mode in which the file is opened. It defaults to 'r' which means open for reading in text mode. Other common values are 'w' for writing (truncating the file if it already exists), and 'a' for appending (which on some Unix systems, means that all writes append to the end of the file regardless of the current seek position). In text mode, if encoding is not specified the encoding used is platform dependent. (For reading and writing raw bytes use binary mode and leave encoding unspecified.) The available modes are:

Character	Meaning
'r'	open for reading (default)
'w'	open for writing, truncating the file first
'a'	open for writing, appending to the end of the file if it exists
'b'	binary mode
't'	text mode (default)
'+'	open a disk file for updating (reading and writing)
'U'	universal newline mode (for backwards compatibility; unneeded for new code)

The default mode is 'rt' (open for reading text). For binary random access, the mode 'w+b' opens and truncates the file to 0 bytes, while 'r+b' opens the file without truncation.

Python distinguishes between files opened in binary and text modes, even when the underlying operating system doesn’t. Files opened in binary mode (appending 'b' to the mode argument) return contents as bytes objects without any decoding. In text mode (the default, or when 't' is appended to the mode argument) the contents of the file are returned as strings, the bytes having been first decoded using a platform-dependent encoding or using the specified encoding if given.

buffering is an optional integer used to set the buffering policy. By default full buffering is on. Pass 0 to switch buffering off (only allowed in binary mode), 1 to set line buffering, and an integer > 1 for full buffering.

encoding is the name of the encoding used to decode or encode the file. This should only be used in text mode. The default encoding is platform dependent, but any encoding supported by Python can be passed. See the codecs module for the list of supported encodings.

errors is an optional string that specifies how encoding errors are to be handled—this argument should not be used in binary mode. Pass 'strict' to raise a ValueError exception if there is an encoding error (the default of None has the same effect), or pass 'ignore' to ignore errors. (Note that ignoring encoding errors can lead to data loss.) See the documentation for codecs.register() for a list of the permitted encoding error strings.

newline controls how universal newlines works (it only applies to text mode). It can be None, '', '\n', '\r', and '\r\n'. It works as follows:

• On input, if newline is None, universal newlines mode is enabled. Lines in the input can end in '\n', '\r', or '\r\n', and these are translated into '\n' before being returned to the caller. If it is '', universal newline mode is enabled, but line endings are returned to the caller untranslated. If it has any of the other legal values, input lines are only terminated by the given string, and the line ending is returned to the caller untranslated.
• On output, if newline is None, any '\n' characters written are translated to the system default line separator, os.linesep. If newline is '', no translation takes place. If newline is any of the other legal values, any '\n' characters written are translated to the given string.

If closefd is False, the underlying file descriptor will be kept open when the file is closed. This does not work when a file name is given and must be True in that case.

See also the file handling modules, such as, fileinput, io (where open() is declared), os, os.path, tempfile, and shutil.

ord(c)¶

Given a string of length one, return an integer representing the Unicode code point of the character. For example, ord('a') returns the integer 97 and ord('\u2020') returns 8224. This is the inverse of chr().

If the argument length is not one, a TypeError will be raised. (If Python was built with UCS2 Unicode, then the character’s code point must be in the range [0..65535] inclusive; otherwise the string length is two!)

pow(x, y[, z])¶

Return x to the power y; if z is present, return x to the power y, modulo z (computed more efficiently than pow(x, y) % z). The two-argument form pow(x, y) is equivalent to using the power operator: x**y.

The arguments must have numeric types. With mixed operand types, the coercion rules for binary arithmetic operators apply. For int operands, the result has the same type as the operands (after coercion) unless the second argument is negative; in that case, all arguments are converted to float and a float result is delivered. For example, 10**2 returns 100, but 10**-2 returns 0.01. If the second argument is negative, the third argument must be omitted. If z is present, x and y must be of integer types, and y must be non-negative.

print([object, ...][, sep=' '][, end='\n'][, file=sys.stdout])¶

Print object(s) to the stream file, separated by sep and followed by end. sep, end and file, if present, must be given as keyword arguments.

All non-keyword arguments are converted to strings like str() does and written to the stream, separated by sep and followed by end. Both sep and end must be strings; they can also be None, which means to use the default values. If no object is given, print() will just write end.

The file argument must be an object with a write(string) method; if it is not present or None, sys.stdout will be used.

property([fget[, fset[, fdel[, doc]]]])¶

Return a property attribute.

fget is a function for getting an attribute value, likewise fset is a function for setting, and fdel a function for del’ing, an attribute. Typical use is to define a managed attribute x:

class C(object):
    def __init__(self):
        self._x = None

    def getx(self):
        return self._x
    def setx(self, value):
        self._x = value
    def delx(self):
        del self._x
    x = property(getx, setx, delx, "I'm the 'x' property.")

If given, doc will be the docstring of the property attribute. Otherwise, the property will copy fget‘s docstring (if it exists). This makes it possible to create read-only properties easily using property() as a decorator:

class Parrot(object):
    def __init__(self):
        self._voltage = 100000

    @property
    def voltage(self):
        """Get the current voltage."""
        return self._voltage

turns the voltage() method into a “getter” for a read-only attribute with the same name.

A property object has getter, setter, and deleter methods usable as decorators that create a copy of the property with the corresponding accessor function set to the decorated function. This is best explained with an example:

class C(object):
    def __init__(self):
        self._x = None

    @property
    def x(self):
        """I'm the 'x' property."""
        return self._x

    @x.setter
    def x(self, value):
        self._x = value

    @x.deleter
    def x(self):
        del self._x

This code is exactly equivalent to the first example. Be sure to give the additional functions the same name as the original property (x in this case.)

The returned property also has the attributes fget, fset, and fdel corresponding to the constructor arguments.

range([start], stop[, step])¶

This is a versatile function to create iterables yielding arithmetic progressions. It is most often used in for loops. The arguments must be integers. If the step argument is omitted, it defaults to 1. If the start argument is omitted, it defaults to 0. The full form returns an iterable of integers [start, start + step, start + 2 * step, ...]. If step is positive, the last element is the largest start + i * step less than stop; if step is negative, the last element is the smallest start + i * step greater than stop. step must not be zero (or else ValueError is raised). Example:

>>> list(range(10))
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
>>> list(range(1, 11))
[1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
>>> list(range(0, 30, 5))
[0, 5, 10, 15, 20, 25]
>>> list(range(0, 10, 3))
[0, 3, 6, 9]
>>> list(range(0, -10, -1))
[0, -1, -2, -3, -4, -5, -6, -7, -8, -9]
>>> list(range(0))
[]
>>> list(range(1, 0))
[]

repr(object)¶

Return a string containing a printable representation of an object. For many types, this function makes an attempt to return a string that would yield an object with the same value when passed to eval(), otherwise the representation is a string enclosed in angle brackets that contains the name of the type of the object together with additional information often including the name and address of the object. A class can control what this function returns for its instances by defining a __repr__() method.

reversed(seq)¶

Return a reverse iterator. seq must be an object which has a __reversed__() method or supports the sequence protocol (the __len__() method and the __getitem__() method with integer arguments starting at 0).

round(x[, n])¶

Return the floating point value x rounded to n digits after the decimal point. If n is omitted, it defaults to zero. Delegates to x.__round__(n).

For the built-in types supporting round(), values are rounded to the closest multiple of 10 to the power minus n; if two multiples are equally close, rounding is done toward the even choice (so, for example, both round(0.5) and round(-0.5) are 0, and round(1.5) is 2). The return value is an integer if called with one argument, otherwise of the same type as x.

set([iterable])

Return a new set, optionally with elements are taken from iterable. The set type is described in Set Types — set, frozenset.

setattr(object, name, value)¶

This is the counterpart of getattr(). The arguments are an object, a string and an arbitrary value. The string may name an existing attribute or a new attribute. The function assigns the value to the attribute, provided the object allows it. For example, setattr(x, 'foobar', 123) is equivalent to x.foobar = 123.

slice([start], stop[, step])¶

Return a slice object representing the set of indices specified by range(start, stop, step). The start and step arguments default to None. Slice objects have read-only data attributes start, stop and step which merely return the argument values (or their default). They have no other explicit functionality; however they are used by Numerical Python and other third party extensions. Slice objects are also generated when extended indexing syntax is used. For example: a[start:stop:step] or a[start:stop, i].

sorted(iterable[, key[, reverse]])¶

Return a new sorted list from the items in iterable.

Has two optional arguments which must be specified as keyword arguments.

key specifies a function of one argument that is used to extract a comparison key from each list element: key=str.lower. The default value is None.

reverse is a boolean value. If set to True, then the list elements are sorted as if each comparison were reversed.

staticmethod(function)¶

Return a static method for function.

A static method does not receive an implicit first argument. To declare a static method, use this idiom:

class C:
    @staticmethod
    def f(arg1, arg2, ...): ...

The @staticmethod form is a function decorator – see the description of function definitions in Function definitions for details.

It can be called either on the class (such as C.f()) or on an instance (such as C().f()). The instance is ignored except for its class.

Static methods in Python are similar to those found in Java or C++. For a more advanced concept, see classmethod() in this section.

For more information on static methods, consult the documentation on the standard type hierarchy in The standard type hierarchy.

str([object[, encoding[, errors]]])¶

Return a string version of an object, using one of the following modes:

If encoding and/or errors are given, str() will decode the object which can either be a byte string or a character buffer using the codec for encoding. The encoding parameter is a string giving the name of an encoding; if the encoding is not known, LookupError is raised. Error handling is done according to errors; this specifies the treatment of characters which are invalid in the input encoding. If errors is 'strict' (the default), a ValueError is raised on errors, while a value of 'ignore' causes errors to be silently ignored, and a value of 'replace' causes the official Unicode replacement character, U+FFFD, to be used to replace input characters which cannot be decoded. See also the codecs module.

When only object is given, this returns its nicely printable representation. For strings, this is the string itself. The difference with repr(object) is that str(object) does not always attempt to return a string that is acceptable to eval(); its goal is to return a printable string. With no arguments, this returns the empty string.

Objects can specify what str(object) returns by defining a __str__() special method.

For more information on strings see Sequence Types — str, bytes, bytearray, list, tuple, range which describes sequence functionality (strings are sequences), and also the string-specific methods described in the String Methods section. To output formatted strings, see the String Formatting section. In addition see the String Services section.

sum(iterable[, start])¶

Sums start and the items of an iterable from left to right and returns the total. start defaults to 0. The iterable‘s items are normally numbers, and are not allowed to be strings. The fast, correct way to concatenate a sequence of strings is by calling ''.join(sequence).

super([type[, object-or-type]])¶

Return a super object that acts as a proxy to superclasses of type.

If the second argument is omitted the super object returned is unbound. If the second argument is an object, isinstance(obj, type) must be true. If the second argument is a type, issubclass(type2, type) must be true. Calling super() without arguments is equivalent to super(this_class, first_arg).

There are two typical use cases for super(). In a class hierarchy with single inheritance, super() can be used to refer to parent classes without naming them explicitly, thus making the code more maintainable. This use closely parallels the use of “super” in other programming languages.

The second use case is to support cooperative multiple inheritence in a dynamic execution environment. This use case is unique to Python and is not found in statically compiled languages or languages that only support single inheritance. This makes in possible to implement “diamond diagrams” where multiple base classes implement the same method. Good design dictates that this method have the same calling signature in every case (because the order of parent calls is determined at runtime and because that order adapts to changes in the class hierarchy).

For both use cases, a typical superclass call looks like this:

class C(B):
    def method(self, arg):
        super().method(arg)    # This does the same thing as: super(C, self).method(arg)

Note that super() is implemented as part of the binding process for explicit dotted attribute lookups such as super().__getitem__(name). It does so by implementing its own __getattribute__() method for searching parent classes in a predictable order that supports cooperative multiple inheritance. Accordingly, super() is undefined for implicit lookups using statements or operators such as super()[name].

Also note that super() is not limited to use inside methods. The two argument specifies the arguments exactly and makes the appropriate references. The zero argument form automatically searches the stack frame for the class (__class__) and the first argument.

tuple([iterable])¶

Return a tuple whose items are the same and in the same order as iterable‘s items. iterable may be a sequence, a container that supports iteration, or an iterator object. If iterable is already a tuple, it is returned unchanged. For instance, tuple('abc') returns ('a', 'b', 'c') and tuple([1, 2, 3]) returns (1, 2, 3). If no argument is given, returns a new empty tuple, ().

tuple is an immutable sequence type, as documented in Sequence Types — str, bytes, bytearray, list, tuple, range.

type(object)¶

Return the type of an object. The return value is a type object and generally the same object as returned by object.__class__.

The isinstance() built-in function is recommended for testing the type of an object, because it takes subclasses into account.

With three arguments, type() functions as a constructor as detailed below.

type(name, bases, dict)

Return a new type object. This is essentially a dynamic form of the class statement. The name string is the class name and becomes the __name__ attribute; the bases tuple itemizes the base classes and becomes the __bases__ attribute; and the dict dictionary is the namespace containing definitions for class body and becomes the __dict__ attribute. For example, the following two statements create identical type objects:

>>> class X(object):
...     a = 1
...
>>> X = type('X', (object,), dict(a=1))

vars([object])¶

Without arguments, return a dictionary corresponding to the current local symbol table. With a module, class or class instance object as argument (or anything else that has a __dict__ attribute), returns a dictionary corresponding to the object’s symbol table. The returned dictionary should not be modified: the effects on the corresponding symbol table are undefined. [1]

zip(*iterables)¶

Make an iterator that aggregates elements from each of the iterables.

Returns an iterator of tuples, where the i-th tuple contains the i-th element from each of the argument sequences or iterables. The iterator stops when the shortest input iterable is exhausted. With a single iterable argument, it returns an iterator of 1-tuples. With no arguments, it returns an empty iterator. Equivalent to:

def zip(*iterables):
    # zip('ABCD', 'xy') --> Ax By
    iterables = map(iter, iterables)
    while iterables:
        result = [it.next() for it in iterables]
        yield tuple(result)

The left-to-right evaluation order of the iterables is guaranteed. This makes possible an idiom for clustering a data series into n-length groups using zip(*[iter(s)]*n).

zip() should only be used with unequal length inputs when you don’t care about trailing, unmatched values from the longer iterables. If those values are important, use itertools.zip_longest() instead.

zip() in conjunction with the * operator can be used to unzip a list:

>>> x = [1, 2, 3]
>>> y = [4, 5, 6]
>>> zipped = zip(x, y)
>>> list(zipped)
[(1, 4), (2, 5), (3, 6)]
>>> x2, y2 = zip(*zip(x, y))
>>> x == x2, y == y2
True

__import__(name[, globals[, locals[, fromlist[, level]]]])¶

Note

This is an advanced function that is not needed in everyday Python programming.

This function is invoked by the import statement. It can be replaced (by importing the builtins module and assigning to builtins.__import__) in order to change semantics of the import statement, but nowadays it is usually simpler to use import hooks (see PEP 302). Direct use of __import__() is rare, except in cases where you want to import a module whose name is only known at runtime.

The function imports the module name, potentially using the given globals and locals to determine how to interpret the name in a package context. The fromlist gives the names of objects or submodules that should be imported from the module given by name. The standard implementation does not use its locals argument at all, and uses its globals only to determine the package context of the import statement.

level specifies whether to use absolute or relative imports. The default is -1 which indicates both absolute and relative imports will be attempted. 0 means only perform absolute imports. Positive values for level indicate the number of parent directories to search relative to the directory of the module calling __import__().

When the name variable is of the form package.module, normally, the top-level package (the name up till the first dot) is returned, not the module named by name. However, when a non-empty fromlist argument is given, the module named by name is returned.

For example, the statement import spam results in bytecode resembling the following code:

spam = __import__('spam', globals(), locals(), [], -1)

The statement import spam.ham results in this call:

spam = __import__('spam.ham', globals(), locals(), [], -1)

Note how __import__() returns the toplevel module here because this is the object that is bound to a name by the import statement.

On the other hand, the statement from spam.ham import eggs, sausage as saus results in

_temp = __import__('spam.ham', globals(), locals(), ['eggs', 'sausage'], -1)
eggs = _temp.eggs
saus = _temp.sausage

Here, the spam.ham module is returned from __import__(). From this object, the names to import are retrieved and assigned to their respective names.

If you simply want to import a module (potentially within a package) by name, you can get it from sys.modules:

>>> import sys
>>> name = 'foo.bar.baz'
>>> __import__(name)
<module 'foo' from ...>
>>> baz = sys.modules[name]
>>> baz
<module 'foo.bar.baz' from ...>

Footnotes

[1]

Specifying a buffer size currently has no effect on systems that don’t have setvbuf. The interface to specify the buffer size is not done using a method that calls setvbuf, because that may dump core when called after any I/O has been performed, and there’s no reliable way to determine whether this is the case.

[2]	In the current implementation, local variable bindings cannot normally be affected this way, but variables retrieved from other scopes (such as modules) can be. This may change.