Python modules are an essential component of the language, helping to structure and organize code. Regardless of development experience, writing scalable and efficient Python programs necessitates a knowledge of modules. Let’s go over the fundamentals of modules in Python step by step.
What are Modules in Python?
Modules are just Python files, as the introduction explains. By importing the module with the import keyword, one Python file’s functionalities can be utilized by another. This method works with other languages as well, like C, Ruby, Java, Javascript, etc.
Benefits of Modules in Python
- Reusability: Different sections of the assignment may easily access functions created in a specific module (through a suitably established API). Duplicate code is therefore no longer required.
- Scoping: To prevent identifier collisions between sections of a program, modules usually define a different namespace. (Namespaces are one incredibly brilliant idea—let’s do more of those!) This is one of the tenets of the Zen of Python.
- Simplification: Rather than focusing on the entire task, a module typically focuses on a relatively narrow portion of the larger issue. If we focus on just one module, we will have a more manageable design problem to consider. Now, creating programs is much easier and less prone to errors.
- Flexibility: It is common practice to create conceptual divisions between different problem areas using modules. If modules are built with less interconnectedness, there is less chance that modifications to one will affect other parts of the program. (We may even be familiar with the program beyond it, but we may not be able to edit a module.) It makes it more likely that multiple developers will be able to work together on a large project.
How to Create a Modules in Python?
- Make a folder in which to keep your codes.
- Inside this folder, create a Python file. Verify that the file was saved as a Python file. Any IDLE will work for this. The file check.py will be called.
- In the new file, write some code: def print_msg(name): print(‘Hello’, name, ‘, welcome to H2k Infosys!’)
- In the folder, make another Python file. Call the print_mg() function from the base module after importing it.
Import a Class in Python
Not only can we create functions, but we can also import and create classes. Let’s develop a class that accepts student entities. The student class will collect essential data such as age, email address, and name.
#create a class that stores student information
class Student:
def __init__(self, f_name, l_name, age):
”’This constructor takes the basic information of the student”’
self.f_name = f_name
self.l_name = l_name
self.email = self.f_name.lower() + self.l_name.lower() + ‘@gmail.com’
self.age = age
def display_info(self):
”’ This function displays the student info”’
print(f”This student’s full name is {self.f_name} {self.l_name}.”)
print(f”Their email address is {self.email}.”)
print(f”They are {self.age} years old.”)
def study(self):
print(f”{self.f_name} is studying.”)
def rest(self):
print(f”{self.f_name} is resting.”)
We can instantiate an object in this class and call its various functions once it has been created. Here are a few instances.
Let’s build a class instance and give it the name student1.
#create an instance of the class
student1 = Student(‘Rohit’, ‘David’, 24)
All of the functions in the class that were created for this object can be called.
This student’s full name is Rohit David.
Their email address is Rohitdavid123@gmail.com.
They are 25 years old.
Python Modules
- sys-(module): Functions and variables for modifying various aspects of the Python Runtime Environment are available in the Python Sys module. It provides us with access to system-specific features and parameters.
- Sys.argv: The command line parameters that were supplied to the Python script are returned as a list.
- Sys.modules: This function offers pre-existing, imported Python modules.
- sys.path: The Python Path is displayed by this function in the running system. All of the Python modules can be found using this environment variable as a search path.
- sys.exit: In addition to exiting the program in the event of an exception, this function can be used to exit the Python console or the command prompt.
- Sys.platform: We can determine the platform we are working on by using this function.
- os-(module): It offers several ways to communicate with the operating system. Python’s standard utility modules include OS. This module makes it possible to use operating system-dependent functionality in a portable manner. Numerous functions for interacting with the system are included in the *os* and *os. path* modules.
- os.name: It determines whether or not specific OS modules are available. It provides the name of the imported operating system-dependent module. such as “posix,” “nt,” “os2,” and “ce.”
- os.getcwd: The current working directory (CWD) of the file used to run the code is returned by this function; the value varies depending on the system.
- os.listdir(‘.’): Printing files and directories from the current directory is its intended use.
- os.error: Every function in this module raises an OSError when an argument is of the correct type but the operating system rejects it, or when file names or paths are invalid or unavailable. An alias for the built-in OSError exceptions is os. error.
- json-(Module): It might be the data exchange and storage syntax. Text written in JavaScript object notation is called JSON. To work with JSON data, Python comes with a built-in package called JSON. Use the “import JSON” statement to import this module.
- Platform: Python specifies an integrated module platform that offers system data. To gather as much information as possible about the platform that the program is currently running on, the Platform module is utilized. It provides details about the device, including its OS, node, version of Python, and OS.
- CSV Module: One of the Python modules that offers classes for reading and writing tabular data in CSV file format is the CSV module.
Reading the CSV file format in python
import csv
with open(‘Giants.csv’, mode =’r’)as file:
CSV file = csv.reader(file)
for lines in CSV file:
print(lines)
Conclusion
Modules in Python are essential for code organization and reuse. They improve scoping, simplify design issues, and increase flexibility in large projects. Creating and utilizing modules enables efficient code management, reducing development complexity and errors. Modules are the foundation of scalable Python programming.
