Computer Science 15-112, Fall 2011
Class Notes: Data and Expressions
Excerpts from:
Python
Standard Library, Ch 2 (Built-In Functions)
(just these functions:
abs,
bin,
bool,
complex,
dir,
eval,
float,
help,
hex,
int,
long,
max,
min,
oct,
pow,
round,
type)
The Python interpreter has a number of functions built into it that are always available. They are listed here in alphabetical order.
def all(iterable):
for element in iterable:
if not element:
return False
return True
New in version 2.5.
def any(iterable):
for element in iterable:
if element:
return True
return False
New in version 2.5.
New in version 2.3.
New in version 2.6.
New in version 2.2.1.
Changed in version 2.3: If no argument is given, this function returns False.
The optional source parameter can be used to initialize the array in a few different ways:
Without an argument, an array of size 0 is created.
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.
New in version 2.2.
Changed in version 2.4: Function decorator syntax added.
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 other 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 code in 'single' or 'eval' mode, input must be terminated by at least one newline character. This is to facilitate detection of incomplete and complete statements in the code module.
Changed in version 2.3: The flags and dont_inherit arguments were added.
Changed in version 2.6: Support for compiling AST objects.
Changed in version 2.7: Allowed use of Windows and Mac newlines. Also input in 'exec' mode does not have to end in a newline anymore.
The complex type is described in Numeric Types — int, float, long, complex.
For other containers see the built in list, set, and tuple classes, and the collections module.
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:
The resulting list is sorted alphabetically. For example:
>>> import struct
>>> dir() # show the names in the module namespace
['__builtins__', '__doc__', '__name__', 'struct']
>>> dir(struct) # show the names in the struct module
['Struct', '__builtins__', '__doc__', '__file__', '__name__',
'__package__', '_clearcache', 'calcsize', 'error', 'pack', 'pack_into',
'unpack', 'unpack_from']
>>> class Shape(object):
def __dir__(self):
return ['area', 'perimeter', 'location']
>>> s = Shape()
>>> dir(s)
['area', 'perimeter', 'location']
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.
Changed in version 2.3: Using divmod() with complex numbers is deprecated.
>>> seasons = ['Spring', 'Summer', 'Fall', 'Winter']
>>> list(enumerate(seasons))
[(0, 'Spring'), (1, 'Summer'), (2, 'Fall'), (3, 'Winter')]
>>> list(enumerate(seasons, start=1))
[(1, 'Spring'), (2, 'Summer'), (3, 'Fall'), (4, 'Winter')]
Equivalent to:
def enumerate(sequence, start=0):
n = start
for elem in sequence:
yield n, elem
n += 1
New in version 2.3.
Changed in version 2.6: The start parameter was added.
Changed in version 2.4: formerly locals was required to be a dictionary.
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 __builtin__ 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
>>> print 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 mode argument, eval()‘s return value will be None.
Hints: dynamic execution of statements is supported by the exec statement. Execution of statements from a file is supported by the execfile() 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 execfile().
See ast.literal_eval() for a function that can safely evaluate strings with expressions containing only literals.
The arguments are a file name and two optional dictionaries. The file is parsed and evaluated as a sequence of Python statements (similarly to a module) using the globals and locals dictionaries as global and local namespace. If provided, locals can be any mapping object.
Changed in version 2.4: formerly locals was required to be a dictionary.
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 execfile() is called. The return value is None.
Note
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 execfile() returns. execfile() cannot be used reliably to modify a function’s locals.
When opening a file, it’s preferable to use open() instead of invoking this constructor directly. file is more suited to type testing (for example, writing isinstance(f, file)).
New in version 2.2.
Note that filter(function, iterable) is equivalent to [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.ifilter() and itertools.ifilterfalse() for iterator versions of this function, including a variation that filters for elements where the function returns false.
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, long, complex.
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.
Note
format(value, format_spec) merely calls value.__format__(format_spec).
New in version 2.6.
For other containers see the built in dict, list, and tuple classes, and the collections module.
New in version 2.4.
This function is added to the built-in namespace by the site module.
New in version 2.2.
Note
To obtain a hexadecimal string representation for a float, use the float.hex() method.
Changed in version 2.4: Formerly only returned an unsigned literal.
Note
This function does not catch user errors. It expects a valid Python expression as input. If the input is not syntactically valid, a SyntaxError will be raised. Other exceptions may be raised if there is an error during evaluation.
If the readline module was loaded, then input() will use it to provide elaborate line editing and history features.
Consider using the raw_input() function for general input from users.
The integer type is described in Numeric Types — int, float, long, complex.
Changed in version 2.2: Support for a tuple of type information was added.
Changed in version 2.3: Support for a tuple of type information was added.
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 the readline() method returns an empty string:
with open('mydata.txt') as fp:
for line in iter(fp.readline, ''):
process_line(line)
New in version 2.2.
list is a mutable sequence type, as documented in Sequence Types — str, unicode, list, tuple, bytearray, buffer, xrange. For other containers see the built in dict, set, and tuple classes, and the collections module.
Note
The contents of this dictionary should not be modified; changes may not affect the values of local and free variables used by the interpreter.
The long type is described in Numeric Types — int, float, long, complex.
The optional key argument specifies a one-argument ordering function like that used for list.sort(). The key argument, if supplied, must be in keyword form (for example, max(a,b,c,key=func)).
Changed in version 2.5: Added support for the optional key argument.
The optional key argument specifies a one-argument ordering function like that used for list.sort(). The key argument, if supplied, must be in keyword form (for example, min(a,b,c,key=func)).
Changed in version 2.5: Added support for the optional key argument.
New in version 2.6.
New in version 2.2.
Changed in version 2.3: This function does not accept any arguments. Formerly, it accepted arguments but ignored them.
Changed in version 2.4: Formerly only returned an unsigned literal.
The first two arguments are the same as for stdio‘s fopen(): name is the file name to be opened, and mode is a string indicating how the file is to be opened.
The most commonly-used values of mode are 'r' for reading, '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). If mode is omitted, it defaults to 'r'. The default is to use text mode, which may convert '\n' characters to a platform-specific representation on writing and back on reading. Thus, when opening a binary file, you should append 'b' to the mode value to open the file in binary mode, which will improve portability. (Appending 'b' is useful even on systems that don’t treat binary and text files differently, where it serves as documentation.) See below for more possible values of mode.
The optional buffering argument specifies the file’s desired buffer size: 0 means unbuffered, 1 means line buffered, any other positive value means use a buffer of (approximately) that size. A negative buffering means to use the system default, which is usually line buffered for tty devices and fully buffered for other files. If omitted, the system default is used. [2]
Modes 'r+', 'w+' and 'a+' open the file for updating (note that 'w+' truncates the file). Append 'b' to the mode to open the file in binary mode, on systems that differentiate between binary and text files; on systems that don’t have this distinction, adding the 'b' has no effect.
In addition to the standard fopen() values mode may be 'U' or 'rU'. Python is usually built with universal newline support; supplying 'U' opens the file as a text file, but lines may be terminated by any of the following: the Unix end-of-line convention '\n', the Macintosh convention '\r', or the Windows convention '\r\n'. All of these external representations are seen as '\n' by the Python program. If Python is built without universal newline support a mode with 'U' is the same as normal text mode. Note that file objects so opened also have an attribute called newlines which has a value of None (if no newlines have yet been seen), '\n', '\r', '\r\n', or a tuple containing all the newline types seen.
Python enforces that the mode, after stripping 'U', begins with 'r', 'w' or 'a'.
Python provides many file handling modules including fileinput, os, os.path, tempfile, and shutil.
Changed in version 2.5: Restriction on first letter of mode string introduced.
The arguments must have numeric types. With mixed operand types, the coercion rules for binary arithmetic operators apply. For int and long 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. (This last feature was added in Python 2.2. In Python 2.1 and before, if both arguments were of integer types and the second argument was negative, an exception was raised.) 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. (This restriction was added in Python 2.2. In Python 2.1 and before, floating 3-argument pow() returned platform-dependent results depending on floating-point rounding accidents.)
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.
Note
This function is not normally available as a built-in since the name print is recognized as the print statement. To disable the statement and use the print() function, use this future statement at the top of your module:
from __future__ import print_function
New in version 2.6.
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 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
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.
New in version 2.2.
Changed in version 2.5: Use fget‘s docstring if no doc given.
Changed in version 2.6: The getter, setter, and deleter attributes were added.
>>> range(10)
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
>>> range(1, 11)
[1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
>>> range(0, 30, 5)
[0, 5, 10, 15, 20, 25]
>>> range(0, 10, 3)
[0, 3, 6, 9]
>>> range(0, -10, -1)
[0, -1, -2, -3, -4, -5, -6, -7, -8, -9]
>>> range(0)
[]
>>> range(1, 0)
[]
>>> s = raw_input('--> ')
--> Monty Python's Flying Circus
>>> s
"Monty Python's Flying Circus"
If the readline module was loaded, then raw_input() will use it to provide elaborate line editing and history features.
When reload(module) is executed:
There are a number of other caveats:
If a module is syntactically correct but its initialization fails, the first import statement for it does not bind its name locally, but does store a (partially initialized) module object in sys.modules. To reload the module you must first import it again (this will bind the name to the partially initialized module object) before you can reload() it.
When a module is reloaded, its dictionary (containing the module’s global variables) is retained. Redefinitions of names will override the old definitions, so this is generally not a problem. If the new version of a module does not define a name that was defined by the old version, the old definition remains. This feature can be used to the module’s advantage if it maintains a global table or cache of objects — with a try statement it can test for the table’s presence and skip its initialization if desired:
try:
cache
except NameError:
cache = {}
It is legal though generally not very useful to reload built-in or dynamically loaded modules, except for sys, __main__ and __builtin__. In many cases, however, extension modules are not designed to be initialized more than once, and may fail in arbitrary ways when reloaded.
If a module imports objects from another module using from ... import ..., calling reload() for the other module does not redefine the objects imported from it — one way around this is to re-execute the from statement, another is to use import and qualified names (module.*name*) instead.
If a module instantiates instances of a class, reloading the module that defines the class does not affect the method definitions of the instances — they continue to use the old class definition. The same is true for derived classes.
New in version 2.4.
Changed in version 2.6: Added the possibility to write a custom __reversed__() method.
Note
The behavior of round() for floats can be surprising: for example, round(2.675, 2) gives 2.67 instead of the expected 2.68. This is not a bug: it’s a result of the fact that most decimal fractions can’t be represented exactly as a float. See Floating Point Arithmetic: Issues and Limitations for more information.
For other containers see the built in dict, list, and tuple classes, and the collections module.
New in version 2.4.
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]. See itertools.islice() for an alternate version that returns an iterator.
The optional arguments cmp, key, and reverse have the same meaning as those for the list.sort() method (described in section Mutable Sequence Types).
cmp specifies a custom comparison function of two arguments (iterable elements) which should return a negative, zero or positive number depending on whether the first argument is considered smaller than, equal to, or larger than the second argument: cmp=lambda x,y: cmp(x.lower(), y.lower()). The default value is None.
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 (compare the elements directly).
reverse is a boolean value. If set to True, then the list elements are sorted as if each comparison were reversed.
In general, the key and reverse conversion processes are much faster than specifying an equivalent cmp function. This is because cmp is called multiple times for each list element while key and reverse touch each element only once. Use functools.cmp_to_key() to convert an old-style cmp function to a key function.
For sorting examples and a brief sorting tutorial, see Sorting HowTo.
New in version 2.4.
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++. Also see classmethod() for a variant that is useful for creating alternate class constructors.
For more information on static methods, consult the documentation on the standard type hierarchy in The standard type hierarchy.
New in version 2.2.
Changed in version 2.4: Function decorator syntax added.
For more information on strings see Sequence Types — str, unicode, list, tuple, bytearray, buffer, xrange which describes sequence functionality (strings are sequences), and also the string-specific methods described in the String Methods section. To output formatted strings use template strings or the % operator described in the String Formatting Operations section. In addition see the String Services section. See also unicode().
For some use cases, there are good alternatives to sum(). The preferred, fast way to concatenate a sequence of strings is by calling ''.join(sequence). To add floating point values with extended precision, see math.fsum(). To concatenate a series of iterables, consider using itertools.chain().
New in version 2.3.
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).
Note
super() only works for new-style classes.
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(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 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.
For practical suggestions on how to design cooperative classes using super(), see guide to using super().
New in version 2.2.
tuple is an immutable sequence type, as documented in Sequence Types — str, unicode, list, tuple, bytearray, buffer, xrange. For other containers see the built in dict, list, and set classes, and the collections module.
Return the type of an object. The return value is a type object. The isinstance() built-in function is recommended for testing the type of an object.
With three arguments, type() functions as a constructor as detailed below.
>>> class X(object):
... a = 1
...
>>> X = type('X', (object,), dict(a=1))
New in version 2.2.
New in version 2.0.
If encoding and/or errors are given, unicode() will decode the object which can either be an 8-bit 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.
If no optional parameters are given, unicode() will mimic the behaviour of str() except that it returns Unicode strings instead of 8-bit strings. More precisely, if object is a Unicode string or subclass it will return that Unicode string without any additional decoding applied.
For objects which provide a __unicode__() method, it will call this method without arguments to create a Unicode string. For all other objects, the 8-bit string version or representation is requested and then converted to a Unicode string using the codec for the default encoding in 'strict' mode.
For more information on Unicode strings see Sequence Types — str, unicode, list, tuple, bytearray, buffer, xrange which describes sequence functionality (Unicode strings are sequences), and also the string-specific methods described in the String Methods section. To output formatted strings use template strings or the % operator described in the String Formatting Operations section. In addition see the String Services section. See also str().
New in version 2.0.
Changed in version 2.2: Support for __unicode__() added.
With a module, class or class instance object as argument (or anything else that has a __dict__ attribute), return that attribute.
Note
The returned dictionary should not be modified: the effects on the corresponding symbol table are undefined. [3]
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() in conjunction with the * operator can be used to unzip a list:
>>> x = [1, 2, 3]
>>> y = [4, 5, 6]
>>> zipped = zip(x, y)
>>> zipped
[(1, 4), (2, 5), (3, 6)]
>>> x2, y2 = zip(*zipped)
>>> x == list(x2) and y == list(y2)
True
New in version 2.0.
Changed in version 2.4: Formerly, zip() required at least one argument and zip() raised a TypeError instead of returning an empty list.
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 __builtin__ module and assigning to __builtin__.__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 call __import__() and then look it up in sys.modules:
>>> import sys
>>> name = 'foo.bar.baz'
>>> __import__(name)
<module 'foo' from ...>
>>> baz = sys.modules[name]
>>> baz
<module 'foo.bar.baz' from ...>
Changed in version 2.5: The level parameter was added.
Changed in version 2.5: Keyword support for parameters was added.
There are several built-in functions that are no longer essential to learn, know or use in modern Python programming. They have been kept here to maintain backwards compatibility with programs written for older versions of Python.
Python programmers, trainers, students and book writers should feel free to bypass these functions without concerns about missing something important.
Deprecated since version 2.3: Use the extended call syntax with *args and **keywords instead.
Changed in version 2.3: Interned strings are not immortal (like they used to be in Python 2.2 and before); you must keep a reference to the return value of intern() around to benefit from it.
Footnotes
[1] | It is used relatively rarely so does not warrant being made into a statement. |
[2] | 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. |
[3] | 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. |
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