Revisiting HTML basics for Python upskilling at eMobilis

🚀 Day 15 of #100DaysLearningChallenge Today I built a simple Markdown to HTML converter using Python! 🐍✨ 📄 What it does: ->Reads a .md file ->Converts the content to HTML using the markdown library ->Writes the output to a new .html file 🔍 Why this matters: Markdown is everywhere — from documentation to blogging platforms. Converting it to HTML opens up possibilities for web publishing and automation. #Python #Markdown #WebDev #100DaysChallenge #Day15 #CodingChallenge #100DaysOfCode #100DaysLearningChallenge #MySirG #LearningToCode #TechJourney #DeveloperLife #KeepBuilding #DevJourney 💻 Here's bellow a snippet of my code:

🚀 Day 40 of #100DaysOfCode — Learning FastAPI (Python) Today I explored FastAPI, one of the fastest and most modern frameworks for building APIs in Python ⚡ 🔍 What I learnt today: ✅ How to create a simple FastAPI app ✅ Setting up GET and POST routes ✅ Automatic interactive documentation using Swagger UI ✅ How FastAPI handles data validation with Pydantic ✅ Why it’s much faster and developer-friendly compared to Flask & Django REST 💡 Key takeaway: FastAPI makes building APIs feel effortless — it’s super fast, type-safe, and easy to maintain. Perfect for modern backend development! 🧠 Next, I’ll explore CRUD operations and database integration using FastAPI + SQLAlchemy. #Python #FastAPI #BackendDevelopment #100DaysOfCode #LearningJourney #APIDevelopment

🚀 In 2025, writing Python code without 𝘁𝘆𝗽𝗲 𝗵𝗶𝗻𝘁𝘀 feels outdated. Type hints aren’t “𝗻𝗶𝗰𝗲 𝘁𝗼 𝗵𝗮𝘃𝗲” anymore — they’re a must for clean, maintainable code. Here’s why: 🧠 Catch bugs before runtime using static type checkers like MyPy, Pyright (and even Ruff) 💡 Make intent clear without extra docs ⚙️ Unlock smarter autocompletion & refactoring 🤝 Enable safer, faster collaboration 📈 Align with modern frameworks like FastAPI, Django Typing doesn’t slow you down — it helps future you move faster with confidence. Would you still merge untyped code in 2025? 🤔 #Python #TypeHints #CleanCode #SoftwareEngineering #BestPractices

⚙️ Day 10 — #90DaysDisciplineDiaries 🚀 Just built a Simple Interactive Calculator using Python & Tkinter! 🧮 While it may look like a small project, it helped me strengthen my understanding of GUI design, functions, and event handling in Python. Here’s what it does 👇 ✅ Performs Addition, Subtraction, Multiplication, and Division ✅ Each operation has its own function (clean & modular) ✅ Interactive Tkinter-based interface (no console needed!) ✅ Handles invalid inputs and division by zero gracefully ✅ Works smoothly in VS Code or any Python environment 💻 Tech Used: Python, Tkinter 🎯 Concepts Practiced: Functions, Error Handling, GUI Events, Input Validation 🐍 Python Progress: ✅ Completed my weekly quizzes 🧮 Built a Calculator Project using Python — applying loops, conditionals, and functions all together! It’s such a satisfying feeling to see concepts turn into something real and working. 💻💡 These small projects might look simple, but they build the foundation for much bigger things ahead. Day 10 ✅ 80 more to go — learning, building, and staying consistent! 🔥 #90DaysDisciplineDiaries #Python #LearningJourney #CodingJourney #PersonalGrowth #DisciplineOverMotivation #PythonProjects #Day10 #Consistency

Ever feel like your Python code just refuses to cooperate when things get heavy? Imagine you’ve crafted the perfect string matching algorithm. It works fine with small data, but when you scale up, everything slows to a crawl. Frustrating, right? That’s when I remembered an old trick: offloading critical parts to C. Turns out, a little C integration can make your Python programs run up to 150 times faster. I’ve tried subprocess calls, ctypes, and even full C extensions, and the speed gains are staggering. It’s like giving your code a turbo boost without abandoning Python’s simplicity. The key takeaway? 🧩 Use subprocess for quick wins—compile C code to executable and call from Python. 🚀 Load your C functions directly into Python with ctypes for seamless speed. 🎯 For the fastest performance, write Python C extensions to get native-like speed. When your code hits a wall, consider whether a C shortcut can get you across faster. Are we just coding in Python, or starting to think like data scientists with a performance edge? What’s your favorite way to speed up Python? #DataScience #PythonTips #Performance #CodingHacks

🚀 Reviving My 2020 Archives – Advanced Python Tutorials (Part 1) Back in 2020, I created a series of in-depth Python tutorials covering topics many developers overlook — but every engineer should master. I’m bringing them back, polished for 2025 🧩 Today’s Topic — Decorators in Python They may look simple, but decorators form the foundation of some of the most powerful frameworks we use daily — FastAPI, Flask, Django, and Airflow. 💻 Here’s one of the examples from my GitHub repo: 👉 https://lnkd.in/gbw7Txec ``` def be_polite(fn): def wrapper(): print("What a pleasure to meet you") fn() print("Have a great day") return wrapper def greet(): print("My name is Aman") Output : What a pleasure to meet you! My name is Aman Have a great day! ``` 🎯 This is where Python’s elegance truly shines — functions enhancing other functions seamlessly. 🧠 Why it matters: Decorators let you wrap shared logic (like logging, retries, validation) around multiple functions — without repeating code. 🧠 In real-world data systems, decorators enable logging, authentication, retries, caching, and orchestration — powering tools like Airflow DAGs and FastAPI routes. 🔗 Full tutorial with explanations and multiple examples here: 👉 https://lnkd.in/gbw7Txec #Python #DataEngineering #AmanpreetSingh #AdvancedPython #FastAPI #Flask #Django #Airflow #CleanCode #DataSolutions #LinkedInLearning #100DaysOfCode #SoftwareEngineering #BackendDevelopment #ProgrammingTips #LearningSeries #DeveloperCommunity #GitHubProjects

🧩 Understanding Jinja2 — The Engine Behind Dynamic HTML Most beginners think Python frameworks like Flask or Django “serve HTML directly.” But in reality, Jinja2 is what transforms your Python data into real, dynamic web pages. Here’s what you’ll learn in this post 👇 🔹 What Jinja2 is and why we use it 🔹 Core syntax — variables, loops, and conditionals If you’re building your own WSGI app or learning how frameworks render templates, understanding Jinja2 will make everything click — it’s where backend logic meets frontend presentation. #Python #WebDevelopment #Backend #Flask #Django #Jinja2 #FullStack #LearningJourney #DeveloperJourney #Programming

🔹 Quick Guide to Start Python (Beginner-Friendly) 1. Install Python – Download from python.org (latest stable version). 2. Choose an Editor – VS Code, PyCharm, or even IDLE to begin. 3. Start With Basics – variables, data types, input/output, conditionals. 4. Learn Core Concepts – loops, functions, lists, dictionaries. 5. Practice Daily – small scripts like calculator, file reader, patterns. 6. Use Libraries – requests, pandas, selenium to explore automation & data. 7. Build Mini Projects – login system, API tester, web scraper, automation scripts. 8. Stay Consistent – 20–30 mins a day is enough to grow fast. Python is simple, powerful, and beginner-friendly — the perfect starting point. Follow Kushal Parikh for more! Happy Testing #python #programming #coding #testing

Stop using square brackets for dict access!   Here’s why dict.get() is the cleaner, safer way in Python. Writing robust Python code means anticipating failures. One of the most common exceptions that can halt your application is the dreaded KeyError when accessing a dictionary. The solution is simple, effective, and makes your code immediately more stable: Use the .get() method. Safety Net: Square brackets (my_dict['key']) will crash if the key doesn't exist. The .get() method, however, safely returns None (or a default value you specify, like my_dict.get('key', 0)). Cleaner Code: Say goodbye to excessive try/except blocks just for simple lookups. This small change is a massive step toward cleaner, production-ready code. See the clear difference in the visual! What is one other Python tip you use every day to prevent errors? Share your wisdom below! #Python #ProgrammingTips #CleanCode #Developer #TechTip #SoftwareEngineering

Day 45 – Packages vs Modules (The Missing Piece) Heard of modules and packages but not sure what’s what? Let’s simplify 👇 📦 Module → A single .py file 📦 Package → A folder that contains multiple modules + an __init__.py file Example: my_package/ __init__.py math_ops.py string_ops.py You can use them like: from my_package import math_ops math_ops.add(5, 10) Packages = modularity + reusability. This is how Python frameworks like Django or Flask are structured internally.💡 👉 Small, modular codebases are easier to grow and maintain. #Python #SoftwareEngineering #CleanCode #100DaysOfCode