Get started learning Python with DataCamp's free Intro to Python tutorial. Learn Data Science by completing interactive coding challenges and watching videos by expert instructors. Start Now!
This site is generously supported by DataCamp. DataCamp offers online interactive Python Tutorials for Data Science. Join 11 million other learners and get started learning Python for data science today!
Good news! You can save 25% off your Datacamp annual subscription with the code LEARNPYTHON23ALE25 - Click here to redeem your discount
Modules and Packages
In programming, a module is a piece of software that has a specific functionality. For example, when building a ping pong game, one module may be responsible for the game logic, and another module draws the game on the screen. Each module consists of a different file, which may be edited separately.
Writing modules
Modules in Python are just Python files with a .py extension. The name of the module is the same as the file name. A Python module can have a set of functions, classes, or variables defined and implemented. The example above includes two files:
mygame/
-
mygame/game.py
-
mygame/draw.py
The Python script game.py
implements the game. It uses the function draw_game
from the file draw.py
,
or in other words, the draw
module that implements the logic for drawing the game on the screen.
Modules are imported from other modules using the import
command. In this example, the game.py
script may
look something like this:
# game.py
# import the draw module
import draw
def play_game():
...
def main():
result = play_game()
draw.draw_game(result)
# this means that if this script is executed, then
# main() will be executed
if __name__ == '__main__':
main()
The draw
module may look something like this:
# draw.py
def draw_game():
...
def clear_screen(screen):
...
In this example, the game
module imports the draw
module, which enables it to use functions implemented
in that module. The main
function uses the local function play_game
to run the game, and then
draws the result of the game using a function implemented in the draw
module called draw_game
. To use
the function draw_game
from the draw
module, we need to specify in which module the function is
implemented, using the dot operator. To reference the draw_game
function from the game
module,
we need to import the draw
module and then call draw.draw_game()
.
When the import draw
directive runs, the Python interpreter looks for a file in the directory in which the script was executed with the module name and a .py
suffix. In this case it will look for draw.py
. If it is found, it will be imported. If it's not found, it will continue looking for built-in modules.
You may have noticed that when importing a module, a .pyc
file is created. This is a compiled Python file.
Python compiles files into Python bytecode so that it won't have to parse the files each time modules are loaded. If a .pyc
file exists, it gets loaded instead of the .py
file. This process is transparent to the user.
Importing module objects to the current namespace
A namespace is a system where every object is named and can be accessed in Python. We import the function draw_game
into the main script's namespace by using the from
command.
# game.py
# import the draw module
from draw import draw_game
def main():
result = play_game()
draw_game(result)
You may have noticed that in this example, the name of the module does not precede draw_game
, because we've specified the module name using the import
command.
The advantages of this notation is that you don't have to reference the module over and over. However, a namespace cannot have two objects with the same name, so the import
command may replace an existing object in the namespace.
Importing all objects from a module
You can use the import *
command to import all the objects in a module like this:
# game.py
# import the draw module
from draw import *
def main():
result = play_game()
draw_game(result)
This might be a bit risky as changes in the module may affect the module which imports it, but it is shorter, and doesn't require you to specify every object you want to import from the module.
Custom import name
Modules may be loaded under any name you want. This is useful when importing a module conditionally to use the same name in the rest of the code.
For example, if you have two draw
modules with slighty different names, you may do the following:
# game.py
# import the draw module
if visual_mode:
# in visual mode, we draw using graphics
import draw_visual as draw
else:
# in textual mode, we print out text
import draw_textual as draw
def main():
result = play_game()
# this can either be visual or textual depending on visual_mode
draw.draw_game(result)
Module initialization
The first time a module is loaded into a running Python script, it is initialized by executing the code in the module once. If another module in your code imports the same module again, it will not be loaded again, so local variables inside the module act as a "singleton," meaning they are initialized only once.
You can then use this to initialize objects. For example:
# draw.py
def draw_game():
# when clearing the screen we can use the main screen object initialized in this module
clear_screen(main_screen)
...
def clear_screen(screen):
...
class Screen():
...
# initialize main_screen as a singleton
main_screen = Screen()
Extending module load path
There are a couple of ways to tell the Python interpreter where to look for modules, aside from the
default local directory and built-in modules. You can use the environment variable PYTHONPATH
to specify additional directories to look for modules like this:
PYTHONPATH=/foo python game.py
This executes game.py
, and enables the script to load modules from the foo
directory, as well
as the local directory.
You may also use the sys.path.append
function. Execute it before running the import
command:
sys.path.append("/foo")
Now the foo
directory has been added to the list of paths where modules are looked for.
Exploring built-in modules
Check out the full list of built-in modules in the Python standard library here.
Two very important functions come in handy when exploring modules in Python - the dir
and help
functions.
To import the module urllib
, which enables us to create read data from URLs, we import
the module:
# import the library
import urllib
# use it
urllib.urlopen(...)
We can look for which functions are implemented in each module by using the dir
function:
>>> import urllib
>>> dir(urllib)
['ContentTooShortError', 'FancyURLopener', 'MAXFTPCACHE', 'URLopener', '__all__', '__builtins__',
'__doc__', '__file__', '__name__', '__package__', '__version__', '_ftperrors', '_get_proxies',
'_get_proxy_settings', '_have_ssl', '_hexdig', '_hextochr', '_hostprog', '_is_unicode', '_localhost',
'_noheaders', '_nportprog', '_passwdprog', '_portprog', '_queryprog', '_safe_map', '_safe_quoters',
'_tagprog', '_thishost', '_typeprog', '_urlopener', '_userprog', '_valueprog', 'addbase', 'addclosehook',
'addinfo', 'addinfourl', 'always_safe', 'basejoin', 'c', 'ftpcache', 'ftperrors', 'ftpwrapper', 'getproxies',
'getproxies_environment', 'getproxies_macosx_sysconf', 'i', 'localhost', 'main', 'noheaders', 'os',
'pathname2url', 'proxy_bypass', 'proxy_bypass_environment', 'proxy_bypass_macosx_sysconf', 'quote',
'quote_plus', 'reporthook', 'socket', 'splitattr', 'splithost', 'splitnport', 'splitpasswd', 'splitport',
'splitquery', 'splittag', 'splittype', 'splituser', 'splitvalue', 'ssl', 'string', 'sys', 'test', 'test1',
'thishost', 'time', 'toBytes', 'unquote', 'unquote_plus', 'unwrap', 'url2pathname', 'urlcleanup', 'urlencode',
'urlopen', 'urlretrieve']
When we find the function in the module we want to use, we can read more about it with the help
function, using the Python interpreter:
help(urllib.urlopen)
Writing packages
Packages are namespaces containing multiple packages and modules. They're just directories, but with certain requirements.
Each package in Python is a directory which MUST contain a special file called __init__.py
. This file, which can be empty, indicates that the directory it's in is a Python package. That way it can be imported the same way as a module.
If we create a directory called foo
, which marks the package name, we can then create a module inside that
package called bar
. Then we add the __init__.py
file inside the foo
directory.
To use the module bar
, we can import it in two ways:
import foo.bar
or:
from foo import bar
In the first example above, we have to use the foo
prefix whenever we access the module bar
. In the second example, we don't, because we've imported the module to our module's namespace.
The __init__.py
file can also decide which modules the package exports as the API, while keeping other modules internal, by overriding the __all__
variable like so:
__init__.py:
__all__ = ["bar"]
Exercise
In this exercise, print an alphabetically sorted list of all the functions in the re
module containing the word find
.
import re
# Your code goes here
find_members = []
import re
# Your code goes here
find_members = []
for member in dir(re):
if "find" in member:
find_members.append(member)
print(sorted(find_members))
test_object('find_members')
success_msg('Great work!')
This site is generously supported by DataCamp. DataCamp offers online interactive Python Tutorials for Data Science. Join over a million other learners and get started learning Python for data science today!
Previous Tutorial Next Tutorial Take the Test