Python API Debugging Saga: PowerShell Syntax Error Fix

n8n is a powerhouse for workflow automation, offering the perfect balance between a user-friendly UI and the flexibility to inject custom logic where it’s needed most. Self-hosting n8n gives you incredible control, but things get interesting the moment you try to bring Python into the mix. I recently spent some time navigating the complexities of adding a Python runner to a self-hosted setup. While it sounds straightforward, the reality of Docker permissions and environment pathing can lead to a fair share of troubleshooting. I’ve documented the exact roadblocks I hit and the final fix that actually works. If you’re looking to supercharge your n8n workflows with custom Python scripts without the headache, this is for you. Check out the full guide here: https://lnkd.in/gwK4bvjH #n8n #Python #SelfHosting #Automation #DevOps #LowCode #DataEngineering

I put together a local text-to-speech project using Qwen3-TTS, wrapped in a C# console app and run inside Docker. It takes text from the command line, generates MP3 or WAV files, supports custom output names, and lets you override the voice and speaking style for each run. The repo is set up with the source folder mounted into the container, so code changes are available on the next run without rebuilding the image unless dependencies change. It’s a practical example of combining .NET, Python, Docker, and local AI in a development workflow. Repository: https://lnkd.in/eDuDbjdf #dotnet #csharp #python #docker #ai #tts #machinelearning #opensource

I replaced 3 Python tools with 1 and my CI pipeline got 10x faster. The tools I dropped: black, isort, flake8. The replacement: Ruff. I've now migrated 7 repositories to Ruff (totaling 800+ Python files) and here's my honest take after 3 months. What's great: - Speed. Ruff lints my entire monorepo in under 2 seconds. The old stack took 20-30 seconds. In CI, that compounds fast across matrix builds. - One config block. Instead of [tool.black], [tool.isort], [tool.flake8] scattered across pyproject.toml, it's just [tool.ruff] and [tool.ruff.lint]. Select the rule codes you want, done. - Auto-fix. Ruff can fix most import sorting and unused import issues on save. I have it wired as a post-tool hook in my editor — every file save auto-formats. What's not perfect: - Rule parity isn't 100%. A few flake8 plugins I relied on (like flake8-bugbear's B950 line length) don't have exact equivalents. You adapt. - The error messages are sometimes less descriptive than flake8's. When a rule fires that you haven't seen before, you're reading docs more often. - If your team has muscle memory around black's opinionated formatting, Ruff's formatter makes slightly different choices in edge cases. Minor, but it can cause noisy diffs during migration. Bottom line: I'd never go back. The speed alone justifies the switch, and consolidating 3 config sections into 1 removes a real source of drift. If you're still running black + isort + flake8 separately, try `ruff check . --fix` on your repo. You'll feel the difference immediately. Have you switched to Ruff yet? What held you back (or convinced you)? #Python #DevTools #Ruff #DeveloperExperience #CodeQuality

Continuing my learning-in-public exploration of the Claude Agent SDK. Part 7 is live today. It's almost done after this one. In Part 6, I added permission hooks to control dangerous tool use. This post is about the next step - exposing my own Python functions as tools Claude can call directly. This one covers:  - Creating an in-process MCP server with @tool, create_sdk_mcp_server(), and ClaudeAgentOptions  - Why Claude immediately rewound to the wrong checkpoint - and reusing the permission hooks from Part 6 to fix it  - Some scoping problems - @tool can decorate at import time, but your runtime state doesn't exist yet.. Post here: https://lnkd.in/dmFgwRRw

✅ Create Virtual Environment Using Ctrl + Shift + P (VS Code) 🔹 Step 1: Open Your Project Folder in VS Code Make sure your project contains: Your Python files (Optional) requirements.txt 🔹 Step 2: Open Command Palette Press: Ctrl + Shift + P 🔹 Step 3: Type Python: Create Environment Click it ✅ 🔹 Step 4: Choose Environment Type You will see options like: Venv Conda Choose Venv. 🔹 Step 5: Choose Python Interpreter Select the Python version you want (for example Python 3.10). VS Code will: ✔ Create .venv folder ✔ Automatically activate it ✔ Select interpreter 📦 Install From requirements.txt Automatically If your project has requirements.txt, VS Code will usually detect it and ask: “Install dependencies from requirements.txt?” Click Yes ✅ It will install all packages for you.

I spent some time today working on Min Stack (155) from the NeetCode 150. At first glance, the problem looks simple, but the requirement to retrieve the minimum element in constant time makes it trickier than it appears. The key insight I found is that using a single variable to track the minimum does not work when elements are popped from the stack. Instead, maintaining a second stack that keeps the minimum value at each level allows all operations: push, pop, top, and getMin to run in O(1) time. It’s a great reminder that “easy-looking” problems often test how well you think through edge cases and data structure design. Read more here: https://lnkd.in/g_dmANd4 #LeetCode #DSA #Python #ProblemSolving

🧠 Python Feature That Makes Functions Pluggable: functools.partial 💻 Pre-fill arguments once… 💻 Reuse the function forever 😌 ❌ Repeating Yourself def power(base, exp): return base ** exp square = lambda x: power(x, 2) cube = lambda x: power(x, 3) Works, but feels hacky 😬 ✅ Pythonic Way from functools import partial power = lambda base, exp: base ** exp square = partial(power, exp=2) cube = partial(power, exp=3) Clean. Reusable. Intentional ✨ 🧒 Simple Explanation Imagine a juice shop 🧃 You decide orange once 🍊 Every glass after that is just “size?” That’s partial. 💡 Why This Is Powerful ✔ Reduces duplicate functions ✔ Cleaner callbacks ✔ Great for functional programming ✔ Used in real frameworks ⚡ Common Use Case from functools import partial import logging debug = partial(logging.log, logging.DEBUG) 🐍 Python lets you lock in decisions early. 🐍 functools.partial turns functions into reusable tools #Python #PythonTips #PythonTricks #Functools #AdvancedPython #CleanCode #LearnPython #Programming #DeveloperLife #DailyCoding #100DaysOfCode

🤔 Flask vs FastAPI: Which Python framework should you choose in 2024? After building APIs with both frameworks, here's my honest breakdown: 🐍 Flask - The Veteran: • Mature ecosystem with tons of resources • Complete flexibility and control • Perfect for complex, custom architectures • Steeper learning curve for beginners ⚡ FastAPI - The Speed Demon: • Built-in async support for high performance • Automatic API documentation with Swagger • Type hints make code more maintainable • Modern Python features out of the box My take: FastAPI wins for new projects requiring speed and modern features. Flask remains king for legacy systems and when you need maximum customization. The real winner? Learning both! Each has its place in different scenarios. What's your experience? Are you team Flask or FastAPI? Share your thoughts below! 👇 #Python #WebDevelopment #API #Flask #FastAPI #Programming #TechTips #SoftwareDevelopment #Coding

The first of many retiring Hack the Box challenge writeups is now live on my personal site. Exploit Python format string injection to extract bytecode constants from a hidden function, then reverse a leet speak dictionary to reconstruct the flag. Vipère is a Python TCP socket server challenge where user input is passed directly to str.format() with a whitelisted command dispatcher. The whitelist only covers top-level command names but does not restrict attribute traversal through Python's object model. By navigating from the whitelisted whoami function through __globals__ and sys.modules to a hidden database module, we extract the bytecode constants of an unreachable get_credentials() method. Disassembling the bytecode reveals the flag construction logic and a leet speak dictionary. The critical insight is recognizing the direction of the dictionary operation as the bytecode shows decoding logic (digits to letters), but the flag is stored in encoded format (letters to digits). Reversing the dictionary produces the correct flag. https://lnkd.in/egageGQw

Currently working through a Flask tutorial. At this stage, I’ve been learning and implementing: • Flask routing and request handling (GET vs POST) • User authentication and session management • Extending data models and handling migrations • Server-side forms with validation • Tracking user activity with UTC timestamps • Using Jinja templates and template inheritance It’s been helpful in understanding how backend logic, database state, and templates come together in a real Flask application. #Python #Flask #WebDevelopment #BackendDevelopment #LearningInPublic