Python Modules Tutorial
Table Of Contents
This tutorial was developed using Python version 3.6.
Larger Python projects require larger degrees of order and sub-dividing your project up into logical blocks can greatly improve the readability of your codebase. In Python we can do this sub-division using a concept using modules.
Say for instance you have a program that bought and sold widgets on the stock market. This project does a number of things:
- It performs analysis of the widgets and returns recommendations as to whether to buy or sell these widgets
- It performs the buying and selling of said widgets
- It produces reports of the widgets it has bought and sold
In this scenario the code would be far too much for one file and as such breaking it up into multiple modules would make sense in this instance. We could have an
analysis module, a
trader module and a
Our Python project structure would then look something like this:
widgettrader - widgettrader/ - - analysis/ - - trader/ - - reports/ - - widgettrader.py - setup.py - requirements.txt ...
What is a Module in Python
Before we go on to creating our own Python Modules, it’s important to know exactly what a
module is in Python.
A module can be defined as a file containing Python definitions and statements. The file name is the module name with the suffix
Defining a Simple Module
We’ll start off by defining a very simple module that will exist in a
.py file within the same directory as our
main.py script that we’ll be writing.
directory - main.py - testmodule.py
testmodule.py file we’ll define a very simple function
test() that will simply print
Hey, I'm a test! like so:
# testmodule.py def test(): print("Hey, I'm a test!")
main.py file we can then import this
testmodule as a module and use our newly defined
test() method like so:
# main.py import testmodule def main(): testmodule.test() if __name__ == '__main__': main()
That is all we need to define a very simple python module within our Python programs.
Defining a Module Within a Sub-Directory
In order to define a module that exists within a sub-directory in Python we need to follow a number of steps, in this example we’ll be creating a module named
- Create the
- Within the
analysis/directory add a new
- Create a new
analysis.pyfile within the same
Once we have done this we would then define all of our
analysis module’s code within the
# analysis/analysis.py def my_analysis_func(): print("Executing Analysis")
We could then chose to either import this module directly in our
main.py file like so:
# main.py import analysis.analysis analysis.analysis.my_analysis_func()
Notice that when we call import we have to specify
analysis.analysis. This is because our
analysis.py file lives within the
analysis/ sub-directory. If we wanted to truncate this to just
import analysis we could add the following line to our
# analysis/__init__.py from analysis.analysis import my_analysis_func
main.py code would then look like the following:
# main.py import analysis analysis.my_analysis_func()
Which, I’m sure you’ll agree is more succinct and cleaner to read overall.
Difference Between a Python Module and a Python Package
It has to be noted that there is a difference between a
Python module and a
Python package. The key thing to remember is that a
package is a module that contains multiple modules. Whilst a normal
Python module may be a single file or multiple files that are imported under one import.
- A good example of a Python module would be our the
analysismodule that we defined in the previous section of this tutorial.
- A good example of a Python package would be the
xmlpackage. This include multiple sub modules such as the
xml.etreemodule and an even deeper
Relative Path Imports
Importing modules using their full path can be an arduous task and thankfully Python offers us the ability to import modules from using relative paths. If we continue our
analysis module example from above, we could modify the
analysis/__init__.py file to use relative imports like so:
# This would import the module which was from .analysis import my_analysis_func
This would mean that it would try and resolve the module from the relative path of the
__init__.py file instead of having to specify the absolute path of the module like
analysis.analysis as we had before.