Day2: The Setup Stop struggling with dependency hell: 3 Django Setup Rules 🛠️ When I first started with Python and Django, I just ran pip install django globally on my main machine. Big mistake. Six months later, I tried to open an old project and nothing worked because a newer project had upgraded a conflicting library. It took hours to fix. If you are setting up your Django environment, here are 3 non-negotiable rules to keep your sanity later: 1️⃣ Virtual Environments are mandatory Never install Django globally. Always create an isolated sandbox for every project. python -m venv venv This ensures that Project A's dependencies never clash with Project B's. It’s the golden rule of Python development. 2️⃣ Freeze your requirements immediately You got it working today, but will it work next month? Don't guess. Once you install your packages inside your virtual environment, run pip freeze > requirements.txt. This locks the exact versions you used, ensuring your teammates (and your production server) use the exact same setup. 3️⃣ The .gitignore file is your best friend Before you make your first commit, set up your .gitignore file. You do not want to push your venv/ folder, your local database (db.sqlite3), or compiled Python files (__pycache__) to GitHub. It bloats your repository and causes massive headaches for collaborators. The Takeaway: A clean development environment isn't just about being tidy; it's about reproducibility. "It works on my machine" is not a valid deployment strategy. How do you manage your Python environments? Are you Team venv, Team Poetry, or do you jump straight to Docker? Let's discuss below! 👇 #Django #Python #WebDevelopment #DevOps #CodingTips #Programming #Day2
Django Setup Rules: Virtual Environments, Freeze Requirements, Gitignore
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Common mistakes I see devs making in Django (and that I’ve made in the past). Some classics I’ve come across: - Putting business logic in views. - Not using select_related (resulting in N+1 queries). - Hardcoding secrets in settings.py. - Leaving DEBUG=True in production (!). Knowing Django isn’t just about coding, it’s about following best practices. What’s the most critical mistake you’ve ever seen or made in Django? hashtag #Django hashtag #Python
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While designing a booking module in a Django application recently, I ran into a common backend design challenge: How do you relate one model to multiple different models without filling your database with nullable foreign keys? Instead of complicating the schema, I used Django’s ContentTypes framework + GenericForeignKey to create flexible, scalable relationships — without constant migrations. In this article, I explain: ✅ When ForeignKeys stop scaling ✅ How ContentTypes solves the problem ✅ How GenericForeignKey works (with a simple mental model + diagram) ✅ Setting up reverse relations using GenericRelation ✅ A small production tip many developers miss If you're designing Django models or building systems expected to grow, this approach can save you from major refactors later. Full medium article — link in comments. #Django #Python #BackendDevelopment #SoftwareArchitecture #WebDevelopment #CleanCode #Programming
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Speed Up Your Dockerized Django Projects with Python Wheels! If you’re building Django/DRF apps with Docker, you’ve probably felt the pain of slow package installations. That’s where Python wheels (.whl) come to the rescue. Why wheels matter: 1.Pre-Built & Ready-to-Install Wheel files are binary packages, so Python doesn’t need to compile them. Install your packages lightning fast. 2. Reliable Builds Packages with C extensions (like numpy, Pillow) often fail to compile from source. Wheels avoid these issues by providing a ready-to-use version. 3. Docker-Friendly Build all your wheels first: pip wheel --no-cache-dir --no-deps --wheel-dir /app/wheels -r requirements.txt Then install from them inside the container: pip install --no-index --find-links=/app/wheels -r requirements.txt
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🚀 A Small Django Mistake That Can Slow Down Your Entire Application While working on my Django project, I noticed something interesting. My code was working perfectly… but the page was loading slower than expected. After checking the queries, I realized I was unknowingly creating the N+1 query problem. I was fetching orders and accessing the related customer for each order. Without optimization, Django was hitting the database again and again for every single customer record. That’s when I understood the importance of select_related() and prefetch_related(). When the relationship is ForeignKey or OneToOne, select_related() performs a SQL JOIN and fetches everything in a single query. When the relationship is ManyToMany or reverse ForeignKey, prefetch_related() works better because it runs separate queries and combines the data efficiently in Python. After applying the correct method, the number of queries reduced significantly — and the performance improved immediately. This experience taught me one important lesson: Writing working code is good. Writing optimized code is better. 🚀 As a backend developer, understanding how the ORM works internally makes a huge difference. #Django #Python #BackendDeveloper #LearningJourney #ORM #PerformanceOptimization
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A Cool Django Fact You Might Not Know 🔧 Technical Django Fact 🧠 Django follows the “fat models, thin views” principle — business logic lives in models, while views stay lightweight. 📦 This leads to cleaner architecture, easier testing, and codebases that scale without becoming messy. 🚀 🌱 Beginner-Friendly Django Fact 🐍 Django helps you write clean code by design. ✨ By encouraging logic in models instead of views, Django makes projects easier to understand, maintain, and grow — even for beginners. 💡 #Django #Python #WebDevelopment #CleanCode #DevelopersOfLinkedIn #DeveloperForHire 🚀
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Python dominates web development, but they often comes with performance and scaling issues. Recently, the Python ecosystem has seen massive performance gains from projects written in Rust, such as uv and ruff. But what other projects are out there to help Python scale thanks to Rust? At Cloudsmith, we achieved 2x throughput on our 10-year-old Django monolith by integrating Rust-based tools and contributed features back upstream We'll look at a number of projects that helped us start bringing Rust into our stack. We'll go over our methodology: establishing performance baselines through load testing, identifying bottlenecks, and scaling issues. We integrated existing Rust-based tools with minimal code changes and tuned application server configuration for maximum throughput, consolidating infrastructure and reducing operational complexity. We'll also share our experience contributing observability features upstream to Granian, ensuring production-ready monitoring that benefits the entire community. You'll leave with actionable strategies for modernising legacy services using existing Rust tools, understanding when this approach makes sense, and maintaining production reliability throughout the transition. https://lnkd.in/dMSMtCUC
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Tip Tuesday for anyone learning Django. One habit that has saved me a lot of confusion is starting my debugging from urls.py. Early on, I used to jump straight into views or templates when something broke. Over time, I realized that if the URL is not mapped correctly, the rest of the code does not even get a chance to run. Now, I trace every issue through the request flow, starting from urls.py, then moving to the view, and finally the template. This simple approach has helped me understand Django’s request response cycle much better. If you’re learning Django backend development, mastering URL routing early can save hours of unnecessary debugging. 👉 When a Django page fails, where do you usually start debugging? 🔗 Helpful resources: Django URL Dispatcher https://lnkd.in/gB52UEMY Django Request and Response Objects https://lnkd.in/ga3py3GT Corey Schafer Django Tutorials https://lnkd.in/gwfMkrT5 #Python #Django #BackendDevelopment #WebDevelopment #LearningInPublic #StudentDeveloper #CodingTips
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January was about removing friction for our users and supporting the many Python shops requesting Tusk Drift support. 𝗧𝘄𝗼 𝗰𝗹𝗶𝗰𝗸𝘀 𝘁𝗼 𝗴𝗲𝗻𝗲𝗿𝗮𝘁𝗲 𝘂𝗻𝗶𝘁 𝘁𝗲𝘀𝘁𝘀 Creating and merging a GitHub workflow to use Tusk can be a blocker. So we built a setup agent that handles setup in two clicks without committing code. Let the agent analyze your repo, create the config, and verify everything works within minutes. 𝗣𝘆𝘁𝗵𝗼𝗻 𝗦𝗗𝗞 𝗳𝗼𝗿 𝗧𝘂𝘀𝗸 𝗗𝗿𝗶𝗳𝘁 Tusk Drift now supports Python repos. Instrumentations include gRPC, aiohttp, urllib3, psycopg, PyJWT, among others. Start recording traffic on your Django, Flask, and FastAPI services to replay as API tests. 𝗙𝗿𝗲𝘀𝗵 𝗨𝗜, 𝘀𝗶𝗺𝗽𝗹𝗲𝗿 𝗯𝗶𝗹𝗹𝗶𝗻𝗴 We shipped a redesigned UI with cleaner navigation. Billing experience is also streamlined to make it easy to manage your subscription. Look out for Launch Week next week. Full changelog in the comments 👇
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