Ready to take the test? Head onto LearnX and get your Python Certification!
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 would be responsible for the game logic, and
another module would be responsible for drawing the game on the screen. Each module is a different file, which can be edited separately.
Modules in Python are simply Python files with a .py extension. The name of the module will be the name of the file. A Python module can have a set of functions, classes or variables defined and implemented. In the example above, we will have two files, we will have:
mygame/ mygame/game.py mygame/draw.py
The Python script
game.py will implement the game. It will use the function
draw_game from the file
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()
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 would use the local function
play_game to run the game, and then
draw the result of the game using a function implemented in the
draw module called
draw_game. To use
draw_game from the
draw module, we would need to specify in which module the function is
implemented, using the dot operator. To reference the
draw_game function from the
we would need to import the
draw module and only then call
import draw directive will run, the Python interpreter will look for a file in the directory which
the script was executed from, by the name of the module with a
.py suffix, so in our case it will try to
draw.py. If it will find one, it will import it. If not, he will continue to look for built-in modules.
You may have noticed that when importing a module, a
.pyc file appears, which 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.
.pyc file exists, it gets loaded instead of the
.py file, but this process is transparent to the user.
Importing module objects to the current namespace
We may also import the function
draw_game directly into the main script's namespace, by using the
# 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,
draw_game does not precede with the name of the module it is imported
from, because we've specified the module name in the
The advantages of using this notation is that it is easier to use the functions inside the current module because
you don't need to specify which module the function comes from. However, any namespace cannot have two objects
with the exact same name, so the
import command may replace an existing object in the namespace.
Importing all objects from a module
We may also use the
import * command to import all objects from a specific 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 might affect the module which imports it, but it is shorter and also does not require you to specify which objects you wish to import from the module.
Custom import name
We may also load modules under any name we want. This is useful when we want to import 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)
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 twice but once only - so local variables inside the module act as a "singleton" - they are initialized only once.
This is useful to know, because this means that you can rely on this behavior for initializing 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 we could tell the Python interpreter where to look for modules, aside from the
default, which is the local directory and the built-in modules. You could either use the environment
PYTHONPATH to specify additional directories to look for modules in, like this:
PYTHONPATH=/foo python game.py
This will execute
game.py, and will enable the script to load modules from the
foo directory as well
as the local directory.
Another method is the
sys.path.append function. You may execute it before running an
This will add the
foo directory to the list of paths to look for modules in as well.
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
If we want 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
>>> 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 about it more using the
inside the Python interpreter:
Packages are namespaces which contain multiple packages and modules themselves. They are simply directories, but with a twist.
Each package in Python is a directory which MUST contain a special file called
__init__.py. This file can
be empty, and it indicates that the directory it contains is a Python package, so it can be imported the same
way a module can be imported.
If we create a directory called
foo, which marks the package name, we can then create a module inside that
bar. We also must not forget to add the
__init__.py file inside the
To use the module
bar, we can import it in two ways:
from foo import bar
In the first method, we must use the
foo prefix whenever we access the module
bar. In the second method,
we don't, because we import the module to our module's namespace.
__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"]
In this exercise, you will need to print an alphabetically sorted list of all functions in the
which contain the word
import re # Your code goes here
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!
Ready to take the test? Head onto LearnX and get your Python Certification!Previous Tutorial Next Tutorial Take the Test