Today I spent some time exploring modules in Python. Structuring and organizing code is a very important aspect of development. As of now, we have structuring code in Python by using named functions and creating classes to organize functionality. However, when the size of the project increases, it is quite difficult to keep all code in a single file as it grows pretty big in size to read and understand the functionality. This problem is solved by using modules. A module in Python is a Python file (with .py extension) that contains some Python code. Using modules, a single file can be split into multiple files or modules based on functionality or features. Modules are a great way to organize and reuse code. Modules can then be used inside another module or the interactive Python interpreter using the import keyword
Suppose we have two files in our project. main.py and utilities.py. main.py is the file that will be run by the interpreter.
The utilities.py shall have a function.
def tagify(content, tag):
return f'<{tag}>{content}</{tag}>'
def emojifier(content, emoji):
return f'{emoji} {content} {emoji}'
This function can then be used in the main.py file like this
import utilities
result = utilities.tagify('hello world', 'p')
emoji_result = utilities.emojifier('python', '😍')
print(result) # <p>hello world</p>
print(emoji_result) # 😍 python 😍
Thus these utility functions can be imported and reused in any file hence improving code organization.
Ways of importing
There are different ways in which the import syntax can be used for importing modules
- Import with renaming
import utilities as utils
result = utils.tagify('hello world', 'p')
emoji_result = utils.emojifier('python', '😍')
print(result) # <p>hello world</p>
print(emoji_result) # 😍 python 😍
- from.. import statement
To import specific names from a module without importing the entire module
from utilities import tagify, emojifier
result = tagify('hello world', 'p')
emoji_result = emojifier('python', '😍')
print(result) # <p>hello world</p>
print(emoji_result) # 😍 python 😍
- Importing all names using *
from utilities import *
result = tagify('hello world', 'p')
emoji_result = emojifier('python', '😍')
print(result) # <p>hello world</p>
print(emoji_result) # 😍 python 😍
The above way of importing is not considered as good programming practice as it impacts readability and can lead to duplicate definitions for an identifier.
__name__
There is a special dunder attribute__name__ in Python to check the name of the module.
# utilities.py
print(__name__) # utilities
def tagify(content, tag):
return f'<{tag}>{content}</{tag}>'
def emojifier(content, emoji):
return f'{emoji} {content} {emoji}'
# main.py
from utilities import tagify, emojifier
print(__name__) # __main__
result = tagify('hello world', 'p')
emoji_result = emojifier('python', '😍')
print(result) # <p>hello world</p>
print(emoji_result) # 😍 python 😍
Note: The __name__ returns __main__ for the file which is run by the interpreter. Here coincidentally the file name is also main. However, the filename can be anything. There is a common practice in Python to execute a block of code based on the condition of whether the module is the main module or not.
# main.py
from utilities import tagify, emojifier
print(__name__)
result = tagify('hello world', 'p')
emoji_result = emojifier('python', '😍')
print(result) # <p>hello world</p>
print(emoji_result) # 😍 python 😍
if (__name__ == '__main__'):
print('This is the main module'
) # This line gets printed as its the main module
Packages
A package is simply a group of modules placed in a folder. Packages are used to group together modules with similar functionality just like how we keep all music files in a music folder, all videos in a videos folder to better organize files. Every Python module needs to contain a __init.py__ file. This lets the Python interpreter know that the directory is a Python package.
Let's place the utilities module inside a directory named helper. This helper directory needs to have a __init.py__ file to make it a package. This package can then be imported in the main file as
# main.py
import helper.utilities
result = helper.utilities.tagify('hello world', 'p')
emoji_result = helper.utilities.emojifier('python', '😍')
print(result) # <p>hello world</p>
print(emoji_result) # 😍 python 😍
if (__name__ == '__main__'):
print('This is the main module')
The above import can be made more convenient like this
from helper.utilities import tagify, emojifier
result = tagify('hello world', 'p')
emoji_result = emojifier('python', '😍')
print(result) # <p>hello world</p>
print(emoji_result) # 😍 python 😍
if (__name__ == '__main__'):
print('This is the main module')
Built-in modules
Python comes with a lot of built-in modules. These modules are downloaded along with the Python interpreter while installing Python. In some other programming languages, these are also known as standard libraries. These modules are developed and maintained by the Python core team and provide the out of the box functionality to do lot of cool things such as reading files, manipulate audio data, manipulating email and much more. List of all Python standard modules
These modules can be imported just like any other user-created module.
Let's use a built-in module time to create a higher-order function that estimates the time it takes to run a function.
import time # built-in Python module
def list_maker(max_items):
result = []
for item in range(max_items):
result.append(item)
return result
def higher_order(func):
def wrapper(item):
time_start = time.time()
list_maker(item)
time_end = time.time()
time_diff = time_end - time_start
print(f'took {time_diff} seconds')
return wrapper
res = higher_order(list_maker)
print(res(100000))
Note: The result will vary based on the system configuration.
In the functional programming section, we earlier also used a built-in module functools to import reduce function.
That's all for today. Tomorrow will explore the remaining concepts related to modules in Python such as using external Python packages and more.
Have a great one!
Top comments (7)
I really love your articles. Short and clean explanations and good structured. Specially important for us who do not use python daily. Whenever I forget something I can find explanation very quickly. Apriciate to find similar articles for javascript too
Thank you :) I will try to compile a JavaScript series in future.
I love your article because it has given me some insight into Python. Please, recently I got admission at WorldQuant University (WQU) Scientific Computing and Python for Data Science Unit. I have no basis or foundations in Python. The first phase of the course is expected to last for 8 weeks. After reading your article, I realized I have to have a strong foundation in Python, but I do not have. Please, any advice would be much appreciated. Thank You.
Good to hear about your admission :)
First thing I would say is the articles which I am posting are meant for reference and it is not a very in-depth course of Python or such. I am trying to compile the important concepts of Python in a 30-day challenge which could be referenced later on just like a journal.
You can get a roadmap from this series and then explore more on those topics. I would recommend practice coding in Python as much as possible, it will make the concepts more clear.
Here are some good free resources for learning Python according to me:
There are a ton of resources available as the Python community is pretty huge. However, it is better not to procrastinate over lot of tutorials and resources initially. Stick to one. Try understanding the basics.
Soon you will get the tricks up your sleeve :)
Hope that helps!
Thank You, Sir, I really appreciate your time.
Great course, but the included code samples don’t confirm to PEP8. Please, could you look into it?
Thanks for pointing it out. I have formatted the code samples for this post. I'll do it for the other posts as well :)