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Foundations
- Set up Python & IDE (e.g., PyCharm, VSCode).
- Learn basics: syntax, data types, operators, control flow, functions.
Data Structures & Algorithms
- Master lists, tuples, sets, dictionaries.
- Learn advanced structures (stacks, queues, trees) and algorithms (searching, sorting).
OOP (Object-Oriented Programming)
- Understand classes, objects, inheritance, polymorphism, encapsulation, decorators, and magic methods.
Advanced Concepts
- Explore functional programming, error handling, file I/O, modules, and packages.
Standard Library
- Get familiar with modules like
os,sys,datetime,collections,itertools,re.
Web Development
- Learn HTML/CSS basics, frameworks (Flask, Django, FastAPI), and build RESTful APIs.
Data Science & ML
- Learn NumPy, Pandas, Matplotlib, Scikit-learn, TensorFlow/PyTorch.
Testing & Debugging
- Master testing with
unittest/pytestand debugging tools.
DevOps & Deployment
- Learn Git, Docker, CI/CD with GitHub Actions.
Best Practices
- Follow PEP 8, optimize performance, and learn security basics.
Specializations
- Web scraping, GUI, game dev, networking.
Continuous Learning
- Build projects, contribute to open-source, attend conferences.
# You Should Know:
Essential Python Commands & Practices
1. Virtual Environment Setup:
python -m venv myenv source myenv/bin/activate # Linux/Mac myenv\Scripts\activate # Windows
2. Installing Packages:
pip install numpy pandas flask django
3. Running a Python Script:
python script.py
4. Debugging with `pdb`:
import pdb; pdb.set_trace() # Add breakpoint
5. File Handling:
with open('file.txt', 'r') as file:
content = file.read()
6. List Comprehensions:
squares = [x2 for x in range(10)]
7. Git Basics:
git init git add . git commit -m "Initial commit" git push origin main
8. Dockerizing a Python App:
FROM python:3.9 WORKDIR /app COPY requirements.txt . RUN pip install -r requirements.txt COPY . . CMD ["python", "app.py"]
9. Running a Flask App:
export FLASK_APP=app.py # Linux/Mac set FLASK_APP=app.py # Windows flask run
10. Data Analysis with Pandas:
import pandas as pd
df = pd.read_csv('data.csv')
print(df.head())
# What Undercode Say:
Mastering Python requires structured learning and hands-on practice. Start with fundamentals, then explore specialized fields like web development, data science, or automation. Use version control (Git), containerization (Docker), and cloud platforms for real-world applications. Contribute to open-source projects and stay updated with Python’s evolving ecosystem.
# Expected Output:
A well-structured Python learning path with practical commands, DevOps integration, and best practices for aspiring developers.
References:
Reported By: Habib Shaikh – Hackers Feeds
Extra Hub: Undercode MoN
Basic Verification: Pass ✅
