Python Modules

Python module concepts of creation and importing.

Python - Modules:

In Python, modules are files containing Python code that can be imported and used in other Python files or programs. They help in organizing code, making it more manageable, reusable, and scalable. Here are some key types and concepts related to Python modules:

1. Creating Modules: You can create your own modules by writing Python code in separate '.py' files. Any Python file can be imported as a module in another Python script using the 'import' statement. For example, if you have a file named '' containing some functions, you can import it in another script using 'import my_module'.

Creating Modules: You can create a module by saving a Python script with functions, classes, or variables in a '.py' file. For example, if you have a file named '', it can be considered a module.

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def greet(name):
    print(f"Hello, {name}!")

def add(a, b):
    return a + b

Importing Modules: You can create a module by saving a Python script with functions, classes, or variables in a '.py' file. For example, if you have a file named '', it can be considered a module.

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# Importing Modules
import my_module

result = mymodule.add(3, 5)
Hello, Ayan!

You can also import specific functions or variables from a module:

from my_module import greet
greet("Ayan")  # Output: Hello, Ayan!

2. Module Aliasing: You can give an alias to a module while importing it using the as keyword. This is useful when you want to refer to a module with a different name to avoid conflicts or for brevity.

import mymodule as mm
mm.greet("Sanvi")  # Output: Hello, Sanvi!

3. Built-in Modules: Python comes with a rich standard library that provides many modules for various purposes. Some commonly used built-in modules include 'os', 'sys', 'math', 'random', 'datetime', 'json', 're', etc.

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import datetime
current_datetime =
print("Current date and time:", current_datetime)
Current date and time: 2024-03-16 07:39:59.882335

4. Creating Packages: Packages are a way of organizing modules hierarchically. A package is a directory that contains a special file called '' along with other modules or sub-packages.


You can import modules from packages using dot notation:

from mypackage import module1

4. Third-Party Modules: These are modules developed by the Python community or third-party developers to extend Python's capabilities beyond the standard library, and they can be installed using package managers like 'pip'.

Popular third-party modules include 'numpy' for numerical computing, 'pandas' for data manipulation and analysis, 'matplotlib' for data visualization, 'requests' for making HTTP requests, etc.

pip install module_name

Here's a simple program using NumPy to generate random numbers and perform some basic operations:

First-Thing-First: Open your terminal or command prompt and execute the following command to install the NumPy: pip install numpy

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import numpy as np

def main():
    # Generate an array of 5 random integers between 0 and 9
    random_array = np.random.randint(0, 10, size=5)
    print("Random Array:", random_array)

    # Calculate the mean of the random array
    mean_value = np.mean(random_array)
    print("Mean:", mean_value)

    # Calculate the sum of the random array
    sum_value = np.sum(random_array)
    print("Sum:", sum_value)

    # Sort the random array
    sorted_array = np.sort(random_array)
    print("Sorted Array:", sorted_array)

if __name__ == "__main__":
Random Array: [8 5 0 9 5]
Mean: 5.4
Sum: 27
Sorted Array: [0 5 5 8 9]


Understanding modules is essential for organizing code effectively and leveraging the power of Python's modular design. By creating, importing, and using modules appropriately, you can write cleaner, more maintainable, and scalable Python code.

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