python tutorial - Python Functions - Built-In Functions - learn python - python programming




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 (or if the iterable is empty). Equivalent to:
def all(iterable):
    for element in iterable:
        if not element:
            return False
    return True
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any(iterable)

  • Return True if any element of the iterable is true. If the iterable is empty, return False. Equivalent to:
def any(iterable):
    for element in iterable:
        if element:
            return True
    return False
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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([source[, 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 . The optional source 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([source[, 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 bytearray().
  • 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:
  • The @classmethod form is a function decorator.
  • 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=0, dont_inherit=False)

  • Compile the source into a code or AST (Abstract Syntax Tree) object.
  • Code objects can be executed by exec() or 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 ('' 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 other than None will be printed).
  • The optional arguments flags and dont_inherit control which future statements 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.

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')
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  • is equivalent to
del x.foobar.
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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])

    • 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']
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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).
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  • For floating point numbers the result is
(q, a % b),
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  • where q is usually math.floor(a / b) but may be 1 less than that.
  • In any case
q * b + a % b
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  • 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]), .... 
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  • For example:
>>> for i, season in enumerate(['Spring', 'Summer', 'Fall', 'Winter']):
...     print(i, season)
0 Spring
1 Summer
2 Fall
3 Winter
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eval(expression, globals=None, locals=None)

  • 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 1:

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

Traceback (most recent call last):
  File "", line 1, in 
    eval('print y')
  File "", line 1
    print y
        ^
SyntaxError: invalid syntax
>>> exec('print y')
2
>>> 
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  • The expression that eval() takes can reference global variables defined outside the eval(). If called within a function, it can reference local variables too.
  • The reason for the error in the eval('print 5') is because the 'print 5' is a statement not an expression. Note that exec() takes a statement.

Example 2:

>>> eval('1 + 1 == 2')
True
>>> eval('1 + 1 == 5')
False
>>> eval('10 + 20 == 30')
True
>>> eval('"O" + "K"')
'OK'
>>> eval('"Python".translate({80: 74})')
'Jython'
>>> eval('"BANANA".count("A")')
3
>>> eval('["*"]*5')
['*', '*', '*', '*', '*']
>>> 
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  • eval() 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.

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.
  • 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().

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.
  • See itertools.filterfalse() for the complementary function that returns elements of iterable for which function returns false.

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.

format(value[, format_spec])

  • Convert a value 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.

frozenset([iterable])

  • Return a frozenset object, optionally with elements taken from iterable.
  • 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 attribute of an object. In other words, it is used to fetch an attribute from an object, using a string object instead of an identifier to identify the attribute.
  • The 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,
value = obj.attribute
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  • is equivalent to
value = getattr(obj, "attribute")
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  • If the named attribute does not exist, default is returned if provided, otherwise AttributeError is raised.
Purpose Usage 1 Usage 2
to get a computed attribute (unconditionally) x.property x.__getattribute__('property')
to get a computed attribute (fallback) x.property x.__getattr__('property')
to set an attribute x.property = value x.__setattr__('property', value)
to delete an attribute del x.property x.__delattr__('property')
to list all attributes and methods dir(x) x.__dir__()
  • If our class defines a __getattribute__() method, Python will call it on every reference to any attribute or method name (except special method names, since that would cause an unpleasant infinite loop).
  • If our class defines a __getattr__() method,
  • Python will call it only after looking for the attribute in all the normal places.
  • If an instance x defines an attribute color, x.color will not call x.__getattr__('color'); it will simply return the already-defined value of x.color.
  • The __setattr__() method is called whenever we assign a value to an attribute.
  • The __delattr__() method is called whenever er delete an attribute. The __dir__() method is useful if we define a __getattr__() or __getattribute__() method.
  • Normally, calling dir(x) would only list the regular attributes and methods. If our __getattr__() method handles a color attribute dynamically, dir(x) would not list color as one of the available attributes.
  • Overriding the __dir__() method allows us to list color as an available attribute, which is helpful for other people who wish to use our class without digging into the internals of it.
  • The distinction between the __getattr__() and __getattribute__() methods:
class SetColors:
    def __getattr__(self, key):
        if key == 'color':
            return 'Maroon'
        else:
            raise AttributeError

        
>>> sc = SetColors()
>>> sc.color
'Maroon'
>>> sc.color = 'Red'
>>> sc.color
'Red'
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  • The attribute name is passed into the __getattr__() method as a string.
  • If the name is color, the method returns a value. (In this case, it's just a hard-coded string, but we would normally do some sort of computation and return the result.)
  • If the attribute name is unknown, the __getattr__() method needs to raise an AttributeError exception, otherwise our code will silently fail when accessing undefined attributes.
  • Actually, if the method doesn't raise an exception or explicitly return a value, it returns None, the Python null value.
  • This means that all attributes not explicitly defined will be None, which is almost certainly not what we want.)
  • At the line:
sc.color
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  • since the sc instance does not have an attribute named color, the __getattr__() method is called to provide a computed value.
  • After explicitly setting sc.color, the __getattr__() method will no longer be called to provide a value for sc.color, because sc.color is already defined on the instance.
  • On the other hand, the __getattribute__() method is absolute and unconditional.
class SettingColors:
    def __getattribute__(self, key):
        if key == 'color':
            return 'Maroon'
        else:
            raise AttributeError

>>> sc = SettingColors()
>>> sc.color
'Maroon'
>>> sc.color = 'Red'
>>> sc.color
'Maroon'
>>> 
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  • The __getattribute__() method is called to provide a value for sc.color.
  • Even after explicitly setting sc.color, the __getattribute__() method is still called to provide a value for sc.color.
  • If present, the __getattribute__() method is called unconditionally for every attribute and method lookup, even for attributes that we explicitly set after creating an instance.
  • If our class defines a __getattribute__() method, we probably also want to define a __setattr__() method and coordinate between them to keep track of attribute values.
  • Otherwise, any attributes we set after creating an instance will disappear.

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 exceptions 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.
  • CPython implementation detail: This is the address of the object.

__import__(name, globals={}, locals={}, fromlist=[], level=0)

  • 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.
  • 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. 0 (the default) 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.
  • spam = __import__('spam', globals(), locals(), [], 0) spam = __import__('spam.ham', globals(), locals(), [], 0) 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'], 0)
eggs = _temp.eggs
saus = _temp.sausage
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  • Here, the spam.ham module is returned from __import__().
  • If you simply want to import a module (potentially within a package) by name, you can call __import__() and then look it up in sys.modules:
>>> import sys
>>> name = 'foo.bar.baz'
>>> __import__(name)

>>> baz = sys.modules[name]
>>> baz
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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"
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  • If the readline module was loaded, then input() will use it to provide elaborate line editing and history features.

int([number | string[, base]])

  • 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 base 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.
  • Base 0 means to interpret exactly as a code literal, so that the actual base 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).

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 exceptions is raised.
Purpose Usage 1 Usage 2
a class constructor x = MyClass() x.__new__()
a class destructor del x x.__del__()
only a specific set of
attributes to be defined
N/A x.__slots__()
a custom hash value hash(x) x.__hash__()
to get a property's value x.color type(x).__dict__['color'].__get__(x, type(x))
to set a property's value x.color = 'Red' type(x).__dict__['color'].__set__(x, 'Red')
to delete a property del x.color type(x).__dict__['color'].__del__(x)
to control whether an object
is an instance of your class
isinstance(x, MyClass) MyClass.__instancecheck__(x)
to control whether a class
is a subclass of your class
issubclass(C, MyClass) MyClass.__subclasscheck__(C)
to control whether a class is a
subclass of your abstract base class
issubclass(C, MyABC) MyABC.__subclasshook__(C)

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 exceptions is raised.

iter(object[, sentinel])

  • Return an iterator object.
  • The first argument is interpreted very differently depending on the presence of the second argument.
  • Without a second argument, object 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 object must be a callable object.
  • The iterator created in this case will call object 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.
  • One useful application of the second form of iter() is to read lines of a file until a certain line is reached.
  • The following example reads a file until "STOP" is reached:
Purpose Usage 1 Usage 2
to iterate through a sequence iter(seq) seq.__iter__()
to get the next value from an iterator next(seq) seq.__next__()
to create an iterator in reverse order reversed(seq) seq.__reversed__()
with open("mydata.txt") as fp:
    for line in iter(fp.readline, "STOP"):
        process_line(line)
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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')
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  • returns
['a', 'b', 'c']
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  • and
list( (1, 2, 3) )
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  • returns
[1, 2, 3].
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  • If no argument is given, returns a new empty list, [].

locals()

  • Update and return a dictionary representing the current local symbol table.
  • Free variables are returned by locals() when it is called in function blocks, but not 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.

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.

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=-1, encoding=None, errors=None, newline=None, closefd=True)

  • Open file and return a corresponding stream.
  • If the file cannot be opened, an IOError is raised.
  • file is either a string or bytes object giving the pathname (absolute or relative to 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.)

ord(c)

  • Given a string of length one, return an integer representing the Unicode code point of the character.
  • For example,
ord('a')
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  • returns the integer
97
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  • and
ord('\u2020')
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  • returns
8224.
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  • 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=None, fset=None, fdel=None, doc=None)

  • 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.")
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  • If then c is an instance of C, c.x will invoke the getter, c.x = value will invoke the setter and del c.x the deleter.
  • 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
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  • 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
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  • 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))
[]
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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.
  • repr literals (backticks)
Python 2.x Python 3.x
`x` repr(x)
`'mystring' + `2`` repr('mystring' + repr(2))
  • x can be anything. It can be a class, a function, a module, a primitive data type, etc
  • The repr() function works on everything. In Python 2, backticks could be nested, leading to this sort of confusing (but valid) expression.

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 taken from iterable.

setattr(object, name, value)

  • This is the counterpart of getattr(object, name).
  • 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)
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  • is equivalent to
x.foobar = 123.
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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, ...): ...
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  • The @staticmethod form is a function decorator.
  • 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++.

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.

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 proxy object that delegates method calls to a parent or sibling class of type.
  • This is useful for accessing inherited methods that have been overridden in a class.
  • The search order is same as that used by getattr(object, name) except that the type itself is skipped.
  • The __mro__ attribute of the type lists the method resolution search order used by both getattr() and super().
  • The attribute is dynamic and can change whenever the inheritance hierarchy is updated.
  • 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 (this is useful for classmethods).
  • 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 inheritance 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 it 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 calls is determined at runtime, because that order adapts to changes in the class hierarchy, and because that order can include sibling classes that are unknown prior to runtime).
  • 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)
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  • 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 getattr(object, name) method for searching 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 form 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.

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))
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vars([object])

  • Without an argument, act like locals().
>>> language = 'Python'
>>> version = 320
>>> vars()
{'language': 'Python', '__builtins__': , 
'__package__': None, 'version': 320, '__name__': '__main__', '__doc__': None}
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  • With a module, class or class instance object as argument (or anything else that has a __dict__ attribute), return that attribute.

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
    sentinel = object()
    iterables = [iter(it) for it in iterables]
    while iterables:
        result = []
        for it in iterables:
            elem = next(it, sentinel)
            if elem is sentinel:
                return
            result.append(elem)
        yield tuple(result)
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  • 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 == list(x2) and y == list(y2)
True
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