Python Module vs. Library: Understanding the Difference and Best Practices

In Python, module and library are related but have slightly different meaning. First, let’s discuss the module.

A module is a python file that contains code that define functions, classes and variables. It is a way to organize code and reuse them by grouping the functionality together. Modules can be imported and used in your file to reuse predefined functions, classes and variables. Python has a lot of predefined modules like math, random and datetime which provide functionalities for basic tasks. Let’s use a built-in module:

import math

print(math.sqrt(16))  # Output: 4.0
print(math.pi)        # Output: 3.141592653589793

Here, the built-in module math is imported using import keyword. Using the module to find the square root of a number, a function named sqrt() is used by accessing the module. Again, the constant value of PI is accessed using math module and dot operator.

On the other hand, a library is the collection of modules working together for a specific feature or to solve a certain problem. It provides functionalities beyond Python libraries and are usually developed by third party developers or organizations that can be installed on your device using package manager i.e. pip command.

For example, NumPy is a widely used popular library for mathematical computation. It provides features and functionalities like managing huge data set, matrix operation and powerful and faster arrays. For it to be installed in the device, we can enter the given command in terminal using a tool like pip manager:

pip install numpy

Once the installation process is over, you can import it into your project similar to library:

import numpy as np

arr = np.array([1, 2, 3, 4, 5])
print(np.mean(arr))  # Output: 3.0

In this example, NumPy is imported as np using alias for convenience. An array named arr is made with five items using array() function. np.mean() is used to find the average of the array.

Best Practices While Using Them

Here are the tips and guides to remember while dealing with python libraries and modules:

1. Read The Documentation

Before using any libraries, it is a must for you to go through the documentation of the library in the official website. You can see YouTube videos if available as an alternative for this. Documentation includes usage of functions with understandable examples with references which will help you use the library more effectively.

2. Import only what you need

When importing any library, it is a good practice to import only the functionalities you need. It is more clean and increase the speed of the execution of the program. Another merit is that it avoids possible naming conflicts inside the program.

# Bad practice: Importing everything from a module
from math import * # * means importing everything

# Good practice: Importing only what is needed
from math import sqrt, pi

3. Use Clear And Consistent Names

When naming the variable, it is important to remember that it should be named in a meaningful manner which makes accessing it later easier and hassle-free. This improves code readability and helps to understand how code works.

import random
num= random.randint(0,100) # bad naming
randNum =random.randint(0,100) # good naming
rand_number =random.randint(0,100) # better naming

4. Keep Dependencies Updated

Libraries are constantly updated and improved to fix bugs and improve performance. New functionalities may even be added to it. So, it is better idea to keep your libraries updated using tools like pip package manager to get the merits.

5. Handle Exceptions

When integrating a library into our project, we may encounter few errors and exceptions which must be handled for better performance of the program. Libraries come with built-in exceptions which can be used in our program. Otherwise, we can raise the exception ourselves.

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