Debugging Dependency Issues with Plotly Dash App

Type errors in Python only surface when the faulty code path actually executes at runtime. A function that receives the wrong argument type can pass an entire test suite — then fail in production on a condition nobody anticipated. mypy catches that class of error before any code runs. But many articles stop at "add annotations and run mypy." The mechanics of how it actually works stay opaque. The article linked below (on PythonCodeCrack) goes further: — The full analysis pipeline: AST parse → import resolution → type inference → contract checking, with no execution involved — How gradual typing works in practice, including what the Any type actually does to mypy's analysis downstream — A precise look at type narrowing and control flow analysis — with an interactive diagram showing how isinstance() resolves str | int into concrete types per branch — The difference between # type: ignore and cast() — and why using the wrong one silently breaks your type guarantees for all code that follows — What mypy 1.20 changed: the narrowing engine rewrite, fixed-format cache as the new default, and the experimental Ruff-based parser — How pyright and ty differ from mypy architecturally — not just in speed benchmarks, but in evaluation strategy and what that means for unannotated legacy code Written for developers who want to understand the tool, not just run it. https://lnkd.in/e838Mdu5 #Python #SoftwareEngineering #TypeHints

Your Django API is not slow because of your database. It's slow because of serialization. A 17-field serializer on 1,000 records = 17,000 Python calls. Just to produce JSON. We hit this in a rental platform in Stockholm. 80ms → 3 seconds at 2,000 users. So we built ClaraX — Rust serialization for Django. One line. No rewrites. No Rust knowledge. Results: → 475ms → 14ms (33x) → 506ms → 10ms (50x) pip install clarax-django python manage.py clarax_doctor https://lnkd.in/dgmZgnK5

My biggest mistake early in my Python journey wasn’t bad code. It was ignoring the small tools that make systems reliable. After 4+ years building automation projects, I found a handful of libraries that quietly transformed my side projects into production-ready products. I wrote about the exact 8 libraries I rely on today. Check out the full breakdown on my Medium account.

📱 Ever wondered how to send SMS messages with just a few lines of Python? It’s simpler than you might think - and we’ve built a quick tutorial to prove it. 🐍 Our latest blog post guides you through creating a simple SMS-sending app with Python, Flask, and the Vonage Messages API. Whether you want to add two-factor authentication (2FA) to your app, send notifications, or flex your dev skills, this is a great place to start. Here's what you'll learn: ✅ Setting up your Vonage API account ✅ Installing the Vonage Python SDK ✅ Building a mini Flask web app with a send-SMS form ✅ Deploying it and hitting "Send" for real 🚀 And the most exciting part? You get a ready-to-clone GitHub repo with the tutorial, so you can dive right into the fun! Text messages have been around forever - but building the tech behind them? That never gets old. 😄 👉 Give it a try: https://vonage.dev/426OrMT

Just shipped stup 🚀 A python package that scaffolds production-ready Python projects in seconds. 🛠️ Every time I started a new project, I was doing the same thing: init uv, pin Python, create venv, wire up requirements.txt, set up folders. 10 minutes of setup before writing a single line of actual code. ⏳ stup kills that loop. One command, full scaffold⚡ → `stup django` : Django + DRF + Celery + Redis + PostgreSQL, ready to go → `stup lang-agent` : LangGraph agent with tools, memory, Ollama config → `stup react-fastapi` : Full-stack with Docker Compose and CORS pre-wired → `stup ml` : MLflow + PyTorch + scikit-learn experiment structure → `stup cli` : PyPI-ready package with Typer + Rich, entry_points set All templates build on top of `stup uv` which handles uv init, Python pinning, and venv in one shot. Install once: `pip install stup` source code: https://lnkd.in/duGUCXVH

Python scope is one of those topics that separates developers who debug fast from those who don't. The language gives you no warning when a variable resolves to an unexpected value. It simply executes, returns a result, and moves on. Tracking down the source of that behaviour - without a solid mental model of how Python resolves names - can cost hours. The LEGB rule isn't complicated. But it's rarely taught with the depth it deserves. I wrote a free guide to change that: → How Python's name resolution actually works under the hood → The LEGB lookup chain with concrete, practical examples → Enclosing scopes and closure behaviour explained clearly → When global and nonlocal are appropriate - and when they signal a design problem → The scope patterns most likely to introduce silent bugs in real codebases Download it free: https://lnkd.in/djp6HJdD #Python #SoftwareEngineering #PythonDevelopment #BackendDevelopment

Built my first Python API using FastAPI! Coming from a MERN background, I decided to explore Python backend development—and it’s been an eye-opening experience. What I built: A simple REST API with GET & POST endpoints Request validation using Pydantic models Auto-generated API docs (Swagger UI) Key Learnings: How FastAPI handles routing (similar to Express but cleaner) Request body validation without extra libraries Importance of virtual environments (and debugging them the hard way) Running production-ready APIs using Uvicorn One thing that really stood out: FastAPI feels like TypeScript + Express, but with built-in validation and performance advantages. Example: Created a POST /user endpoint that validates incoming data using a schema and returns structured responses. GitHub Repo: https://lnkd.in/gF4FFR2u Would love feedback from the community #Python #FastAPI #BackendDevelopment #LearningInPublic #100DaysOfCode

🚀 Just Published My First Python Library on PyPI! Excited to share that I’ve built and published "common-fun" — a modular Python utility library designed to simplify everyday development tasks. 📦 Install: pip install common-fun 🖥️ Try CLI: common-fun help 🔗 GitHub: https://lnkd.in/gjWRyhpq 🔧 What it includes: • Number utilities (prime, gcd, factorial, etc.) • String processing (palindrome, slugify, etc.) • Array helpers (flatten, chunk, rotate) • Validators (email, URL, password) • File utilities • Performance decorators (timer, retry, caching) • 🔥 CLI support for direct terminal usage 💡 Why I built this: While working on multiple projects, I realized I was repeatedly writing similar utility functions. So I decided to consolidate everything into a clean, reusable, and structured library. ⚙️ Key highlights: • Fully modular architecture • Optimized implementations • CLI tool for quick access • PyPI-ready packaging • Clean documentation This project helped me understand: ✔️ Library design ✔️ Packaging & publishing ✔️ CLI development ✔️ Clean code practices Would love your feedback and suggestions! #Python #OpenSource #Developer #Programming #PyPI #SoftwareDevelopment

If you're a Python developer and you're not using tools like ruff, black, pytest, mypy, py-spy and pre-commit, then you're probably behind the curve. All these tools are free to download and use in your projects, and WILL make your code better and less buggy. My latest article on Towards Data Science goes into more depth on all the above-mentioned tools and shows how to download and use each one. A link to the article is in the first comment.

PySpector v0.1.8 is out🚀 Me and the PySpector Core Team worked really hard to deploy this version, so here's what changed: - A new vulnerability leading to arbitrary code execution via plugin bypass was patched (and its #GHSA was published) - Docs were updated and improved🫡 - We fixed a bug preventing the generation of html reports, as well as 2 other bugs preventing the --wizard and -- supply-chain flag from working properly - We expanded error messages during #AST file parsing and added a new #CLI flag to enable Python SyntaxWarnings during code scanning - And last we (finally) expanded support for Python up to the latest #Python3.14 (while before v.0.1.8, Python support stopped at #Python3.12) Thanks to all the #contributors and the awesome SecurityCert community who made this possible🫶 Repo: https://lnkd.in/d7CppftJ