If you quit from the Python interpreter and enter it again, the definitions you
have made (functions and variables) are lost. Therefore, if you want to write a
somewhat longer program, you are better off using a text editor to prepare the
input for the interpreter and running it with that file as input instead. This
is known as creating a script. As your program gets longer, you may want to
split it into several files for easier maintenance. You may also want to use a
handy function that you’ve written in several programs without copying its
definition into each program.
To support this, Python has a way to put definitions in a file and use them in a
script or in an interactive instance of the interpreter. Such a file is called a
module; definitions from a module can be imported into other modules or into
the main module (the collection of variables that you have access to in a
script executed at the top level and in calculator mode).
A module is a file containing Python definitions and statements. The file name
is the module name with the suffix .py appended. Within a module, the
module’s name (as a string) is available as the value of the global variable
__name__. For instance, use your favorite text editor to create a file
called fibo.py in the current directory with the following contents:
# Fibonacci numbers module def fib(n): # write Fibonacci series up to n a, b = 0, 1 while b < n: print(b, end=' ') a, b = b, a+b print() def fib2(n): # return Fibonacci series up to n result =  a, b = 0, 1 while b < n: result.append(b) a, b = b, a+b return result
Now enter the Python interpreter and import this module with the following
>>> import fibo
This does not enter the names of the functions defined in fibo directly in
the current symbol table; it only enters the module name fibo there. Using
the module name you can access the functions:
>>> fibo.fib(1000) 1 1 2 3 5 8 13 21 34 55 89 144 233 377 610 987 >>> fibo.fib2(100) [1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89] >>> fibo.__name__ 'fibo'
If you intend to use a function often you can assign it to a local name:
>>> fib = fibo.fib >>> fib(500) 1 1 2 3 5 8 13 21 34 55 89 144 233 377
6.1. More on Modules
A module can contain executable statements as well as function definitions.
These statements are intended to initialize the module. They are executed only
the first time the module is imported somewhere. 
Each module has its own private symbol table, which is used as the global symbol
table by all functions defined in the module. Thus, the author of a module can
use global variables in the module without worrying about accidental clashes
with a user’s global variables. On the other hand, if you know what you are
doing you can touch a module’s global variables with the same notation used to
refer to its functions, modname.itemname.
Modules can import other modules. It is customary but not required to place all
import statements at the beginning of a module (or script, for that
matter). The imported module names are placed in the importing module’s global
There is a variant of the import statement that imports names from a
module directly into the importing module’s symbol table. For example:
>>> from fibo import fib, fib2 >>> fib(500) 1 1 2 3 5 8 13 21 34 55 89 144 233 377
This does not introduce the module name from which the imports are taken in the
local symbol table (so in the example, fibo is not defined).
There is even a variant to import all names that a module defines:
>>> from fibo import * >>> fib(500) 1 1 2 3 5 8 13 21 34 55 89 144 233 377
This imports all names except those beginning with an underscore (_).
In most cases Python programmers do not use this facility since it introduces
an unknown set of names into the interpreter, possibly hiding some things
you have already defined.
Note that in general the practice of importing * from a module or package is
frowned upon, since it often causes poorly readable code. However, it is okay to
use it to save typing in interactive sessions.
For efficiency reasons, each module is only imported once per interpreter
session. Therefore, if you change your modules, you must restart the
interpreter – or, if it’s just one module you want to test interactively,
use imp.reload(), e.g. import imp; imp.reload(modulename).
6.1.1. Executing modules as scripts¶
When you run a Python module with
python fibo.py <arguments>
the code in the module will be executed, just as if you imported it, but with
the __name__ set to "__main__". That means that by adding this code at
the end of your module:
if __name__ == "__main__": import sys fib(int(sys.argv))
you can make the file usable as a script as well as an importable module,
because the code that parses the command line only runs if the module is
executed as the “main” file:
$ python fibo.py 50 1 1 2 3 5 8 13 21 34
If the module is imported, the code is not run:
>>> import fibo >>>
This is often used either to provide a convenient user interface to a module, or
for testing purposes (running the module as a script executes a test suite).
6.1.2. The Module Search Path
When a module named spam is imported, the interpreter searches for a file
named spam.py in the current directory, and then in the list of
directories specified by the environment variable PYTHONPATH. This
has the same syntax as the shell variable PATH, that is, a list of
directory names. When PYTHONPATH is not set, or when the file is not
found there, the search continues in an installation-dependent default path; on
Unix, this is usually .:/usr/local/lib/python.
Actually, modules are searched in the list of directories given by the variable
sys.path which is initialized from the directory containing the input script
(or the current directory), PYTHONPATH and the installation- dependent
default. This allows Python programs that know what they’re doing to modify or
replace the module search path. Note that because the directory containing the
script being run is on the search path, it is important that the script not have
the same name as a standard module, or Python will attempt to load the script as
a module when that module is imported. This will generally be an error. See
section Standard Modules for more information.
6.1.3. “Compiled” Python files
As an important speed-up of the start-up time for short programs that use a lot
of standard modules, if a file called spam.pyc exists in the directory
where spam.py is found, this is assumed to contain an
already-“byte-compiled” version of the module spam. The modification time
of the version of spam.py used to create spam.pyc is recorded in
spam.pyc, and the .pyc file is ignored if these don’t match.
Normally, you don’t need to do anything to create the spam.pyc file.
Whenever spam.py is successfully compiled, an attempt is made to write
the compiled version to spam.pyc. It is not an error if this attempt
fails; if for any reason the file is not written completely, the resulting
spam.pyc file will be recognized as invalid and thus ignored later. The
contents of the spam.pyc file are platform independent, so a Python
module directory can be shared by machines of different architectures.
Some tips for experts:
When the Python interpreter is invoked with the -O flag, optimized
code is generated and stored in .pyo files. The optimizer currently
doesn’t help much; it only removes assert statements. When
-O is used, all bytecode is optimized; .pyc files are
ignored and .py files are compiled to optimized bytecode.
Passing two -O flags to the Python interpreter (-OO) will
cause the bytecode compiler to perform optimizations that could in some rare
cases result in malfunctioning programs. Currently only __doc__ strings are
removed from the bytecode, resulting in more compact .pyo files. Since
some programs may rely on having these available, you should only use this
option if you know what you’re doing.
A program doesn’t run any faster when it is read from a .pyc or
.pyo file than when it is read from a .py file; the only thing
that’s faster about .pyc or .pyo files is the speed with which
they are loaded.
When a script is run by giving its name on the command line, the bytecode for
the script is never written to a .pyc or .pyo file. Thus, the
startup time of a script may be reduced by moving most of its code to a module
and having a small bootstrap script that imports that module. It is also
possible to name a .pyc or .pyo file directly on the command
It is possible to have a file called spam.pyc (or spam.pyo
when -O is used) without a file spam.py for the same module.
This can be used to distribute a library of Python code in a form that is
moderately hard to reverse engineer.
6.2. Standard Modules
Python comes with a library of standard modules, see https://docs.python.org/3/library/
Some modules are built into the interpreter; these provide access to operations that
are not part of the core of the language but are nevertheless built in, either
for efficiency or to provide access to operating system primitives such as
system calls. The set of such modules is a configuration option which also
depends on the underlying platform For example, the winreg module is only
provided on Windows systems. One particular module deserves some attention:
sys, which is built into every Python interpreter. The variables
sys.ps1 and sys.ps2 define the strings used as primary and secondary
>>> import sys >>> sys.ps1 '>>> ' >>> sys.ps2 '... ' >>> sys.ps1 = 'C> ' C> print('Yuck!') Yuck! C>
These two variables are only defined if the interpreter is in interactive mode.
The variable sys.path is a list of strings that determines the interpreter’s
search path for modules. It is initialized to a default path taken from the
environment variable PYTHONPATH, or from a built-in default if
PYTHONPATH is not set. You can modify it using standard list
>>> import sys >>> sys.path.append('/ufs/guido/lib/python')
6.3. The dir() Function
The built-in function dir() is used to find out which names a module
defines. It returns a sorted list of strings:
>>> import fibo, sys >>> dir(fibo) ['__name__', 'fib', 'fib2'] >>> dir(sys) ['__displayhook__', '__doc__', '__excepthook__', '__name__', '__stderr__', '__stdin__', '__stdout__', '_getframe', 'api_version', 'argv', 'builtin_module_names', 'byteorder', 'callstats', 'copyright', 'displayhook', 'exc_info', 'excepthook', 'exec_prefix', 'executable', 'exit', 'getdefaultencoding', 'getdlopenflags', 'getrecursionlimit', 'getrefcount', 'hexversion', 'maxint', 'maxunicode', 'meta_path', 'modules', 'path', 'path_hooks', 'path_importer_cache', 'platform', 'prefix', 'ps1', 'ps2', 'setcheckinterval', 'setdlopenflags', 'setprofile', 'setrecursionlimit', 'settrace', 'stderr', 'stdin', 'stdout', 'version', 'version_info', 'warnoptions']
Without arguments, dir() lists the names you have defined currently:
>>> a = [1, 2, 3, 4, 5] >>> import fibo >>> fib = fibo.fib >>> dir() ['__builtins__', '__doc__', '__file__', '__name__', 'a', 'fib', 'fibo', 'sys']
Note that it lists all types of names: variables, modules, functions, etc.
>>> import builtins >>> dir(builtins) ['ArithmeticError', 'AssertionError', 'AttributeError', 'BaseException', 'Buffer Error', 'BytesWarning', 'DeprecationWarning', 'EOFError', 'Ellipsis', 'Environme ntError', 'Exception', 'False', 'FloatingPointError', 'FutureWarning', 'Generato rExit', 'IOError', 'ImportError', 'ImportWarning', 'IndentationError', 'IndexErr or', 'KeyError', 'KeyboardInterrupt', 'LookupError', 'MemoryError', 'NameError', 'None', 'NotImplemented', 'NotImplementedError', 'OSError', 'OverflowError', 'P endingDeprecationWarning', 'ReferenceError', 'RuntimeError', 'RuntimeWarning', ' StopIteration', 'SyntaxError', 'SyntaxWarning', 'SystemError', 'SystemExit', 'Ta bError', 'True', 'TypeError', 'UnboundLocalError', 'UnicodeDecodeError', 'Unicod eEncodeError', 'UnicodeError', 'UnicodeTranslateError', 'UnicodeWarning', 'UserW arning', 'ValueError', 'Warning', 'ZeroDivisionError', '__build_class__', '__deb ug__', '__doc__', '__import__', '__name__', '__package__', 'abs', 'all', 'any', 'ascii'#39;, 'bin', 'bool', 'bytearray', 'bytes', 'chr', 'classmethod', 'compile', ' complex', 'copyright', 'credits', 'delattr', 'dict', 'dir', 'divmod', 'enumerate ', 'eval', 'exec', 'exit', 'filter', 'float', 'format', 'frozenset', 'getattr', 'globals', 'hasattr', 'hash', 'help', 'hex', 'id', 'input', 'int', 'isinstance', 'issubclass', 'iter', 'len', 'license', 'list', 'locals', 'map', 'max', 'memory view', 'min', 'next', 'object', 'oct', 'open', 'ord', 'pow', 'print', 'property' , 'quit', 'range', 'repr', 'reversed', 'round', 'set', 'setattr', 'slice', 'sort ed', 'staticmethod', 'str', 'sum', 'super', 'tuple', 'type', 'vars', 'zip']
Packages are a way of structuring Python’s module namespace by using “dotted
module names”. For example, the module name A.B designates a submodule
named B in a package named A. Just like the use of modules saves the
authors of different modules from having to worry about each other’s global
variable names, the use of dotted module names saves the authors of multi-module
packages like NumPy or the Python Imaging Library from having to worry about
each other’s module names.
Suppose you want to design a collection of modules (a “package”) for the uniform
handling of sound files and sound data. There are many different sound file
formats (usually recognized by their extension, for example: .wav,
.aiff, .au), so you may need to create and maintain a growing
collection of modules for the conversion between the various file formats.
There are also many different operations you might want to perform on sound data
(such as mixing, adding echo, applying an equalizer function, creating an
artificial stereo effect), so in addition you will be writing a never-ending
stream of modules to perform these operations. Here’s a possible structure for
your package (expressed in terms of a hierarchical filesystem):
sound/ Top-level package __init__.py Initialize the sound package formats/ Subpackage for file format conversions __init__.py wavread.py wavwrite.py aiffread.py aiffwrite.py auread.py auwrite.py ... effects/ Subpackage for sound effects __init__.py echo.py surround.py reverse.py ... filters/ Subpackage for filters __init__.py equalizer.py vocoder.py karaoke.py ...
When importing the package, Python searches through the directories on
sys.path looking for the package subdirectory.
The __init__.py files are required to make Python treat the directories
as containing packages; this is done to prevent directories with a common name,
such as string, from unintentionally hiding valid modules that occur later
on the module search path. In the simplest case, __init__.py can just be
an empty file, but it can also execute initialization code for the package or
set the __all__ variable, described later.
Users of the package can import individual modules from the package, for
This loads the submodule sound.effects.echo. It must be referenced with
its full name.
sound.effects.echo.echofilter(input, output, delay=0.7, atten=4)
An alternative way of importing the submodule is:
from sound.effects import echo
This also loads the submodule echo, and makes it available without its
package prefix, so it can be used as follows:
echo.echofilter(input, output, delay=0.7, atten=4)
Yet another variation is to import the desired function or variable directly:
from sound.effects.echo import echofilter
Again, this loads the submodule echo, but this makes its function
echofilter() directly available:
echofilter(input, output, delay=0.7, atten=4)
Note that when using from package import item, the item can be either a
submodule (or subpackage) of the package, or some other name defined in the
package, like a function, class or variable. The import statement first
tests whether the item is defined in the package; if not, it assumes it is a
module and attempts to load it. If it fails to find it, an ImportError
exception is raised.
Contrarily, when using syntax like import item.subitem.subsubitem, each item
except for the last must be a package; the last item can be a module or a
package but can’t be a class or function or variable defined in the previous
6.4.1. Importing * From a Package
Now what happens when the user writes from sound.effects import *? Ideally,
one would hope that this somehow goes out to the filesystem, finds which
submodules are present in the package, and imports them all. This could take a
long time and importing sub-modules might have unwanted side-effects that should
only happen when the sub-module is explicitly imported.
The only solution is for the package author to provide an explicit index of the
package. The import statement uses the following convention: if a package’s
__init__.py code defines a list named __all__, it is taken to be the
list of module names that should be imported when from package import * is
encountered. It is up to the package author to keep this list up-to-date when a
new version of the package is released. Package authors may also decide not to
support it, if they don’t see a use for importing * from their package. For
example, the file sounds/effects/__init__.py could contain the following
__all__ = ["echo", "surround", "reverse"]
This would mean that from sound.effects import * would import the three
named submodules of the sound package.
If __all__ is not defined, the statement from sound.effects import *
does not import all submodules from the package sound.effects into the
current namespace; it only ensures that the package sound.effects has
been imported (possibly running any initialization code in __init__.py)
and then imports whatever names are defined in the package. This includes any
names defined (and submodules explicitly loaded) by __init__.py. It
also includes any submodules of the package that were explicitly loaded by
previous import statements. Consider this code:
import sound.effects.echo import sound.effects.surround from sound.effects import *
In this example, the echo and surround modules are imported in the
current namespace because they are defined in the sound.effects package
when the from...import statement is executed. (This also works when
__all__ is defined.)
Although certain modules are designed to export only names that follow certain
patterns when you use import *, it is still considered bad practise in
Remember, there is nothing wrong with using from Package import
specific_submodule! In fact, this is the recommended notation unless the
importing module needs to use submodules with the same name from different
6.4.2. Intra-package References
When packages are structured into subpackages (as with the sound package
in the example), you can use absolute imports to refer to submodules of siblings
packages. For example, if the module sound.filters.vocoder needs to use
the echo module in the sound.effects package, it can use from
sound.effects import echo.
You can also write relative imports, with the from module import name form
of import statement. These imports use leading dots to indicate the current and
parent packages involved in the relative import. From the surround
module for example, you might use:
from . import echo from .. import formats from ..filters import equalizer
Note that relative imports are based on the name of the current module. Since
the name of the main module is always "__main__", modules intended for use
as the main module of a Python application must always use absolute imports.
6.4.3. Packages in Multiple Directories
Packages support one more special attribute, __path__. This is
initialized to be a list containing the name of the directory holding the
package’s __init__.py before the code in that file is executed. This
variable can be modified; doing so affects future searches for modules and
subpackages contained in the package.
While this feature is not often needed, it can be used to extend the set of
modules found in a package.
|||In fact function definitions are also ‘statements’ that are ‘executed’; the
execution of a module-level function enters the function name in the module’s
global symbol table.