Functions, Methods, Modules, and Libraries in Python

Here, I have consolidated all the points related to Functions, Methods, Modules and Library in Python. Hope you will find it useful.

Type	Description	Examples
Functions	Standalone blocks of code inside a def.	math.sqrt(), os.path.exists(), json.loads()
Methods	Functions within a class, always linked to objects.	list.append(), str.upper(), dict.items()
Modules	A Python file with a .py extension containing functions, classes, and other code.	import math from ikea import add
Libraries	A collection of modules. Libraries contain similar modules for similar tasks.	import pandas as pd

Importing Modules and Differences

Syntax	Description	Example	Difference
import module	Imports the full module. Use moduleName.functionName to access functions.	import math print(math.sqrt(16))	Keeps the namespace clean, avoids naming conflicts.
from module import function	Imports specific functions directly, no need for the module name prefix.	from ikea import add print(add(1, 2))	Convenient for using specific functions frequently.
from module import *	Imports all functions, classes, and variables from the module directly into the current namespace.	from math import * print(sqrt(16))	Can cause naming conflicts, harder to track where functions/classes come from. Generally not recommended for larger codebases.

Installing Libraries

Command	Description	Example
pip install libraryname	Installs a library from the command prompt or terminal.	pip install pandas
os.system('pip install libraryname')	Installs a library from within your Python code using the os module to run shell commands.	import os os.system('pip install pandas')

Managing Libraries When Sharing Python Code

Step	Description	Example
pip freeze > requirements.txt	Create a requirements.txt file that lists all the libraries your script needs.	pip freeze > requirements.txt
pip install -r requirements.txt	Install dependencies on another system.	pip install -r requirements.txt

Example Workflow

Step	Description	Code
Create the Python script	Write your Python script and save it to a file.	echo "import pandas as pd ... " > data_analysis.py
Install pandas if not installed	Ensure that the pandas library is installed.	pip install pandas
Generate requirements.txt	Create a requirements.txt file listing all required libraries.	pip freeze > requirements.txt
Clone project or copy files	Copy your project files to the target system.	scp user@development_system:/path/to/project/* /path/to/local/directory/
Create virtual environment	(Optional) Create a virtual environment for your project.	python -m venv myenv source myenv/bin/activate
Install required libraries	Install the required libraries on the target system using requirements.txt.	pip install -r requirements.txt
Run the script	Execute your Python script on the target system.	python data_analysis.py