WhatsApp is no longer a platform just for chat.

It's an educational goldmine.

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PYTHON INTERVIEW QUESTIONS

1 what is python ?
2 why python ?
3 what are advantage of python ?
4 what is pep 8 ?
5. What do you mean by literal ?
6 explain python function ?
7 what is use of break statement ?
8 what is tuple ?
9 python libraries /module ?
10. What is an in operator in python ?
11 why python interpreted ?
12 how is memory managed in python ?
13 python decorator ?
14 global variable / local variable ?
15 what is iterators in python ?
16 what is slicing in python ?
17 what is a dictionary in python ?
18 what is pass in python ?
19 what isinit ?
20 what is self in python ?

Most important for Technical round interview.

11. Python + BeautifulSoup = Web Scraping
12. Python + Scrapy = Web Scraping and Crawling
13. Python + PySpark = Big Data Processing
14. Python + OpenCV = Computer Vision
15. Python + PyTorch = Deep Learning
16. Python + FastAPI = Web Development (high-performance APIs)
17. Python + SQLAlchemy = Database Management
18. Python + Jupyter Notebook = Interactive Computing and Data Analysis
19. Python + Celery = Distributed Task Queue
20. Python + Pygame = Game Development

#python

21. Python + Ansible = IT Automation and Configuration Management
22. Python + Fabric = Automation and Deployment
23. Python + NLTK = NLP
24. Python + spaCy = Industrial-Strength Natural Language Processing
25. Python + Bokeh = Interactive Web Visualization
26. Python + Dash = Web-Based Data Visualization
27. Python + Scikit-learn = ML
28. Python + NetworkX = Network Analysis and Graph Theory
29. Python + Twisted = Network Programming
30. Python + PyQt = GUI Application Development

#python

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Python is ❤️

⌨️ Useful Python Modules

⌨️ Quick Python cheatsheet.

Python for FinTech Roadmap

Stage 1 – Learn Python (Syntax, OOP, Libraries)
Stage 2 – Understand FinTech Concepts (Finance, Payments, Regulations)
Stage 3 – Data Handling (Pandas, NumPy, CSV, APIs)
Stage 4 – Financial Modeling (Risk Analysis, Pricing Models)
Stage 5 – Automation (Web Scraping, Report Generation)
Stage 6 – Security (Encryption, Compliance)
Stage 7 – Build Financial Tools (Payment Gateways, Trading Bots)
Stage 8 – Deploy FinTech Apps (Cloud, SaaS)

🏆 – Python FinTech Developer

#python

Python for Cloud Computing Roadmap

Stage 1 – Learn Python (Syntax, OOP)
Stage 2 – Understand Cloud Concepts (IaaS, PaaS, SaaS)
Stage 3 – Work with AWS/Azure SDKs (Boto3, Azure SDK)
Stage 4 – Cloud Storage (S3, Blob Storage)
Stage 5 – Deploy with Docker and Kubernetes
Stage 6 – Implement Serverless (Lambda, Functions)
Stage 7 – Automate Infrastructure (Terraform, CloudFormation)
Stage 8 – Monitor and Scale Cloud Apps

🏆 – Python Cloud Developer

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5. https://www.codeabbey.com/index/task_list
6. https://www.pythonchallenge.com/

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DICTIONARY FOR PYTHON DEVELOPER

Python Code to remove Image Background
—————————————————————-
from rembg import remove
from PIL import Image

image_path = 'Image Name' ## ---> Change to Image name

output_image = 'ImageNew' ## ---> Change to new name your image

input = Image.open(image_path)

output = remove(input)

output.save(output_image)

Functions are fundamental in 𝗣𝘆𝘁𝗵𝗼𝗻, reusable blocks of code that streamline our work. Whether you're a beginner or an experienced coder, understanding Normal Functions vs. Lambda Functions can level up your coding efficiency.

Let's break it down:

🔹 𝗡𝗼𝗿𝗺𝗮𝗹 𝗙𝘂𝗻𝗰𝘁𝗶𝗼𝗻
With a name, body, and return statement, this function is ideal for tasks that require multiple lines of code or complex logic.

🔹 𝗟𝗮𝗺𝗯𝗱𝗮 𝗙𝘂𝗻𝗰𝘁𝗶𝗼𝗻
Need a quick, single-use function? Lambda is your friend! It’s anonymous and perfect for concise operations.

While Normal Functions are great for more extensive operations, Lambda Functions are excellent for small, single-use operations where you need simplicity.

Choose the function type that best fits your task’s complexity!

Python for Scientific Computing Roadmap

Stage 1 – Learn Python (Syntax, OOP)
Stage 2 – Use NumPy and SciPy for Mathematical Computing
Stage 3 – Work with Matplotlib for Data Visualization
Stage 4 – Statistical Analysis (Pandas, Statsmodels)
Stage 5 – Use SymPy for Symbolic Mathematics
Stage 6 – Simulate Models (ODE, PDE)
Stage 7 – Learn Jupyter for Scientific Workflows
Stage 8 – Perform Optimization and Numerical Solvers

🏆 – Python Scientific Developer

Happy Diwali guys 🪔🎇