Web Scraping Learning Roadmap with Python

I've just published a new guide: "BeautifulSoup Web Scraper: A Beginner’s Guide to Scraping Web Data to CSV". Whether you're a student or a seasoned developer looking to automate data tasks, this guide shows you how to fetch, parse, and save web data efficiently using modern Python tools like uv.

Behind every "simple" checkout button is a mountain of logic. 🏗️ I’ve spent the last few weeks deep in the world of MedusaJS and Django REST Framework, and if there’s one thing I’ve learned, it’s that the "invisible" parts of an app are often the most important. Whether it’s mapping out a clinical hierarchy for a pharmacy system or building out meeting session modules, the goal is always the same: clean, scalable code that makes the frontend look effortless. It’s been a season of learning, debugging, and building. Onward! 🚀 #BackendDevelopment #Python #Django #MedusaJS #WebDevelopment

🐍 Simplifying Web Data Extraction with BeautifulSoup Recently, I explored how to use BeautifulSoup to quickly extract structured data from websites—and it’s one of the easiest ways to get started with web scraping. Here’s a simple approach: 🔹 Send a request to a webpage using Python 🔹 Parse the HTML content using BeautifulSoup 🔹 Locate elements (tags, classes, IDs) 🔹 Extract useful data (text, links, prices, etc.) 🛠 Tools Used: • Python • BeautifulSoup • Requests library 💡 Key Takeaway: With just a few lines of code, you can turn unstructured web pages into usable datasets—perfect for building data-driven apps, research tools, or automation workflows. ⚠️ Always respect website terms and use scraping responsibly. A great starting point for anyone getting into data extraction and automation. #Python #WebScraping #BeautifulSoup #DataEngineering #Automation #OpenSource

Django vs FastAPI is not a debate. It's a use case question. Django when you need: Admin panel out of the box ORM, auth, migrations all bundled A monolith that ships fast A team that doesn't want to wire things together FastAPI when you need: High throughput async APIs Full control over every layer ML model serving or agentic backends Type safety and auto docs without extra setup Django is a framework that makes decisions for you. FastAPI is a framework that trusts you to make them. Neither is better. Wrong tool for the job is the only mistake. #Python #Django #FastAPI #BackendDevelopment #SoftwareEngineering

If you’ve ever built APIs in Django REST Framework, you know the pain of writing multiple views for the same model — list, detail, create, update, delete. Messy, repetitive, and error-prone. That’s where ViewSets come in. With just a few lines of code, you get all CRUD endpoints automatically, clean URL routing, and a scalable request flow. In my latest Medium article, I break down: What ViewSets are and why they matter How to secure your APIs with get_queryset() Performance boosts using prefetch_related Query parameter filtering with filter_backends Custom endpoints with @action (like cancel or recent orders) Common mistakes to avoid (permissions, redundant filtering, lost prefetch) This isn’t just about making APIs that “work” — it’s about building APIs that are secure, efficient, and production-ready. 👉 Read the full guide here: https://lnkd.in/diM6UCiZ #Django #RESTAPI #Python #BackendDevelopment #SoftwareEngineering #APIs

🚫 I spent hours debugging my API… just because I didn’t understand this one thing in Django REST Framework. I thought Function-Based Views were enough… until my code started getting messy, repetitive, and hard to scale. That’s when I finally understood the real difference between FBVs and CBVs 👇 🔹 What I Learned FBVs feel easy in the beginning. But as soon as your API grows → logic becomes cluttered. CBVs (especially Generic Views & ViewSets) completely changed the game for me: ✔ Cleaner structure ✔ Reusable logic ✔ Scalable architecture 🔹 Example Function-Based View 👇 @api_view(['GET', 'POST']) def product_list(request): if request.method == 'GET': ... elif request.method == 'POST': ... Class-Based View 👇 class ProductView(ListCreateAPIView): queryset = Product.objects.all() serializer_class = ProductSerializer 👉 Same result… but CBVs remove a LOT of manual work. 🔹 What’s Actually Happening? CBVs use: Mixins → handle logic (list, create, update) Generic views → combine mixins ViewSets → full CRUD with routers 👉 You focus on what to build, DRF handles how it works 🔹 Mistakes I Made (and learned from) ❌ Forgot queryset in ViewSet → basename error ❌ Passed Model instead of ViewSet to router ❌ Wrong URL (case-sensitive → 404) ❌ Imported NestedSimpleRouter from wrong module ❌ Didn’t understand router → action mapping 👉 These mistakes actually helped me understand DRF deeply. 🔹 Final Take 👉 FBVs = Good for learning basics 👉 CBVs = Essential for real-world APIs Now I use ViewSets + Routers by default — less code, more clarity 🚀 #Django #Python #BackendDevelopment  #SoftwareEngineering #API #Programming #LearnPython #TechTips  #100DaysOfCode #TechCommunity

🔧 Django REST Framework Serializers — the unsung heroes of your API If you've worked with DRF, you know serializers are more than just "JSON converters." They're the gatekeepers of your entire data layer. Here's what makes them genuinely powerful: 1) Validation built-in — field-level and object-level validation in one place. No extra form logic, no scattered checks. 2) Nested relationships — serialize related models automatically, or override with custom logic when you need it. 3) Read/write separation — use read_only / write_only fields cleanly, without duplicating code. 4) ModelSerializer — auto-generates fields from your model. Less boilerplate, faster iteration. 5) SerializerMethodField — add any computed property to your API response without touching the model. One underrated pattern: using serializers for input validation outside of views — in Celery tasks, management commands, anywhere you're ingesting untrusted data. Serializers are where your API contract actually lives. Treat them with the same care you'd give your models. What's your go-to serializer trick? Comment below! #Django #DRF #Python #BackendDevelopment #WebDevelopment #SoftwareEngineering

🚀 From Static Data to an Interactive Web App! 🚀 I recently decided to take my programming skills to the next level by heavily upgrading one of my data analysis projects. What started as a simple Python script to process the famous Superstore dataset is now a fully interactive, live web dashboard! 📊 Here is what I accomplished:  🧠 Learned how to structure data using Python and Pandas (specifically using .groupby() to manipulate data dynamically). 🛠️ Rebuilt static charts into interactive ones using Streamlit. ⚙️ Mastered version control by resolving conflicts via Git terminal commands. 🌐 Deployed the final application to the cloud so anyone in the world can interact with the data! I am incredibly proud of how much I learned about environments, dependencies, and taking a project from code to the cloud. 🔗 Try the live dashboard here: https://lnkd.in/dapceAK5  💻 Check out the code on my GitHub: https://lnkd.in/det-RQjc #Python #DataAnalysis #DataScience #Streamlit #Pandas #CodingJourney #BuildInPublic

Python is still undefeated for rapid web development in 2026 🔥 Here’s why I keep coming back: • Flask → lightning-fast APIs • Django → full-featured apps with admin panel in minutes • BeautifulSoup + Selenium → scraping & automation heaven • pandas + FastAPI = data-driven backends Built 3 client projects last quarter using just Python + modern front-end. Speed + scalability = win. What’s your favorite Python web framework right now? Tell me below 👇 #Python #WebDevelopment #Flask #Django #FullStack

Day 41 of #60DaysOfMiniProjects Today I built an Unsent Message Web App using Python & Flask Not just another project… This one lets you express what you feel — without actually sending it. Some messages are never meant to be sent… but they still deserve to be written. What this system does: • Write messages to anyone anonymously • Stores messages securely in a file • Adds real-time timestamp • Simple and clean web interface • Built using Flask backend Why this project matters: • Helps you express emotions freely • Works like a personal emotional journal • Great for reflection and mental clarity • Shows how coding can solve real-life problems Concepts used: • Flask (Web Framework) • File Handling (Read/Write) • HTML Templates • Forms & POST requests • Date & Time module From CLI to Web App — leveling up step by step. Next improvements: • Add message viewing page • Add password protection • Store data in database (SQLite) • Improve UI design Building consistently. Learning daily. Improving step by step. #Python #Flask #WebDevelopment #MiniProjects #BuildInPublic #CodingJourney #DeveloperLife #LearningInPublic #60DaysOfCode