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Foundations
- Install Python and set up an IDE (PyCharm, VSCode with Python extensions).
- Learn syntax, data types, operators, loops, and functions.
Example Commands:
Check Python version python --version Install VSCode extensions for Python code --install-extension ms-python.python
Data Structures & Algorithms
- Master lists, tuples, sets, dictionaries, stacks, queues, and trees.
Example Code:
Stack implementation
stack = []
stack.append('a') Push
stack.pop() Pop
OOP (Object-Oriented Programming)
- Learn classes, inheritance, polymorphism, and decorators.
Example Code:
class Animal: def <strong>init</strong>(self, name): self.name = name class Dog(Animal): def bark(self): return "Woof!"
Advanced Concepts
- Functional programming (
lambda,map,filter), error handling (try-except), file I/O.
Example Code:
Lambda function square = lambda x: x 2 print(square(5)) Output: 25
Standard Library
- Use
os,sys,datetime,collections, and `re` (regex).
Example Commands:
List files in a directory (Linux) ls -l
Python Equivalent:
import os
print(os.listdir('.'))
Web Development (Flask/Django)
- Build RESTful APIs.
Example Flask Code:
from flask import Flask
app = Flask(<strong>name</strong>)
@app.route('/')
def home():
return "Hello, World!"
if <strong>name</strong> == '<strong>main</strong>':
app.run()
Data Science & Machine Learning
- Use NumPy, Pandas, Scikit-learn, TensorFlow.
Example Code:
import pandas as pd
data = pd.read_csv('data.csv')
print(data.head())
DevOps & Deployment
- Git, Docker, CI/CD (GitHub Actions).
Example Commands:
Dockerize a Python app docker build -t python-app . docker run -p 5000:5000 python-app
Best Practices
- Follow PEP 8, optimize performance, secure coding.
Security Tip:
Check for vulnerable Python packages pip-audit
You Should Know:
- Linux Commands for Python Devs:
Monitor Python process top -p $(pgrep python) Run a Python script in the background nohup python script.py &
-
Windows Equivalent:
Check running Python processes Get-Process python
-
Debugging Python:
Debug with pdb python -m pdb script.py
-
Performance Profiling:
import cProfile cProfile.run('my_function()')
What Undercode Say:
Mastering Python requires hands-on practice. Automate tasks, contribute to open-source, and experiment with security tools like `bandit` for code analysis.
Install bandit for security scanning pip install bandit bandit -r my_project/
Expected Output:
[bash] INFO Profile include: [bash] INFO Profile exclude: [bash] INFO CLI args: ...
Prediction:
Python will remain dominant in AI/ML, with increased adoption in cybersecurity automation (e.g., scripting penetration tests).
Relevant URLs:
References:
Reported By: Habib Shaikh – Hackers Feeds
Extra Hub: Undercode MoN
Basic Verification: Pass ✅


