After months of work, I'm thrilled to announce the release of the new edition of "Mastering Python Design Patterns"! What's new? This edition dives deep into creational, structural, behavioral, and architectural patterns, plus it introduces concurrency, asynchronous, and performance patterns. What you’ll learn: 👉 Master key design principles and SOLID concepts 👉 Implement Gang of Four (GoF) patterns in Python 👉 Use architectural patterns to build robust systems 👉 Optimize code with concurrency and performance patterns 👉 Scale applications with distributed systems patterns 👉 Ensure reliability with testing patterns 👉 Build modular, decoupled systems and manage dependencies efficiently Stay tuned for more updates! 📘✨ #Python #Coding #DesignPatterns

Shipped the first version of the UX for my LLM → Structured Data Connector. Next work involves advanced ways of providing the data schema input (JSON, CSV).

Shipped the CLI slice for my LLM → Structured Data Connector. Currently, you can define the schema with --col. Note: The --col option might get adjusted. I may also add a preview of the data before writing. Next: Small UX (going to try Gradio first). Would you target the other output stores/formats (SQL, JSON) by using custom code in the package directly or would you delegate that to standard pipeline/ELT/ETL tools?

What's stopping you from using Linux?🐧

Been out of this account for more than a year, spending time elsewhere. Life happens and there is so much to do in this world 🌐 I am back with improved skills and new ideas. Let's reignite/continue the conversations.

The book has now been published!

🐍 Python Tip of the Day: Utilizing Python’s “-m” Option for Module Execution Python's `-m` option is a versatile tool that allows you to run library modules as scripts. This can be incredibly useful for executing modules that contain test code or need to perform initialization tasks. It runs the source file for a module located in the Python module search path. One common use of the `-m` option: Launch Python's built-in HTTP server, which can serve files from the current directory over HTTP. This is very useful for quick tests, sharing files, or local development work. ``` # Serve files from the current directory at http://localhost:8000/ python -m http.server ``` Another popular usage: Run the `pip` installer to ensure that you are using the module corresponding to the Python interpreter you're currently using: ``` # Upgrade the pip installer using the -m option python -m pip install --upgrade pip ``` Benefits: 1️⃣ Flexibility: Offers a straightforward way to execute Python modules from the command line, providing a flexible approach for various Python tasks. 2️⃣ Utility: Great for utility tasks like running a web server, profiling code, testing, or package management, all without additional scripts. 3️⃣ Safe imports: Ensures that the module is imported correctly, potentially avoiding shadowing issues that can occur when a module and a script have the same name.