Optimize Python Code with Profiling by Tom Reid

Frustrated with a Python script that feels sluggish? Instead of guessing where the slowdown is, you can measure it. Tom Reid shares a guide on using cProfile and snakeviz to find and fix the exact parts of your code that are causing delays.

🐍📰 Learn how to build a Model Context Protocol (MCP) server in Python. Connect tools, prompts, and data to AI agents like Cursor for smarter assistants #python

In the Metasploit Wrap-Up from last week, a new Python Site-Specific Hook Persistence module was released. [1] I wrote a detailed blog about this persistence, which I think is pretty cool. [2] If you have never heard of this technique, you might want to read up on it. [1] https://lnkd.in/ei_C5TgQ [2] https://lnkd.in/eYRmWrx8

𝗪𝗵𝗮𝘁 𝗶𝗳 𝘆𝗼𝘂𝗿 𝗣𝘆𝘁𝗵𝗼𝗻 𝗰𝗼𝗱𝗲 𝗰𝗼𝘂𝗹𝗱 𝗿𝘂𝗻 𝟮𝟬× 𝗳𝗮𝘀𝘁𝗲𝗿 — 𝘄𝗶𝘁𝗵𝗼𝘂𝘁 𝘁𝗼𝘂𝗰𝗵𝗶𝗻𝗴 𝘆𝗼𝘂𝗿 𝗹𝗼𝗴𝗶𝗰? Sounds impossible, right? But it’s not. I just published an article that shows how you can dramatically boost Python performance using modern execution techniques like JIT compilation, smarter runtimes, and optimized libraries — all without rewriting your existing code. If you’re working with: ✅ Backend APIs ✅ Data processing ✅ Automation scripts ✅ Performance-critical Python apps …this is a must-read 👉 Read here: https://lnkd.in/gykbHu-z 💡 Faster code 💡 Same logic 💡 Zero pain refactoring #Python #PythonPerformance #JIT #SoftwareEngineering #BackendDevelopment #Developer #ProgrammingTips

This was a great read! 🔥 I liked how it highlights that Python performance bottlenecks are often caused by how we use the language rather than the language itself. Techniques like switching interpreters, relying on optimized C-backed libraries, and profiling hot paths instead of rewriting logic shows that scalability and maintainability don’t have to be trade-offs. Very relevant for real-world backend and automation systems. #Python #PythonProgramming #PythonPerformance #PythonTips #PythonOptimization #PyPy #Programming #Developers #CodingLife

Reduce friction in user interactions by implementing QR codes. This tutorial from Mahnoor Javed shows you how to generate them with Python.

Day 460: 7/1/2026 Why Python Execution Is Slow? Python is expressive, flexible, and easy to use — but when performance matters, it often struggles. This is not because Python is “badly written,” but because of how Python executes code and accesses memory. Let’s break it down. ⚙️ 1. Python Works With Objects, Not Raw Data In Python, data is not stored contiguously like in C or C++. Instead: --> Each value is a Python object --> Objects live at arbitrary locations in memory --> Variables hold pointers to those objects When Python accesses a value: --> The pointer is loaded --> The CPU jumps to that memory location --> The Python object is loaded --> Metadata is inspected --> The actual value is read This pointer-chasing happens for every operation. 🔁 2. Python Is Interpreted, Not Compiled to Machine Code Python source code is not executed directly. Execution flow: --> Python source is compiled into bytecode --> Bytecode consists of many small opcodes --> The Python interpreter: fetches an opcode, decodes it, dispatches it to the corresponding C implementation --> This repeats for every operation --> Each step adds overhead. Even a simple arithmetic operation involves: --> multiple bytecode instructions --> multiple function calls in C --> dynamic type checks at runtime ⚠️ 3. Dynamic Typing Adds Runtime Checks Because Python is dynamically typed: --> Types are not known at compile time --> Every operation checks type compatibility --> Method lookups happen at runtime This flexibility makes Python powerful — but it prevents many low-level optimizations. Stay tuned for more AI insights! 😊 #Python #Performance #SystemsProgramming

Also checkout depyler which does something kind of similar, but actually very different. It single shot CONVERTS python to Rust and compiles it, so it is the ULTIMATE type check a one way PERMANENT conversion to Rust. Current status? 40% of 200 corpus of projects with sklearn, numpy, argparse, etc, "just work", and possible 80% in next few days... https://lnkd.in/ehJeTtvs

From "eliminate flaky tests" to "make them impossible" Waitless v1.0.0 is live! Now with WebSocket tracking, framework hooks (React/Angular/Vue), and iframe support. No more time.sleep(). Ever. pip install waitless --upgrade #Selenium #QualityEngineering #Python #Automation

🐍📰 Python's deque: Implement Efficient Queues and Stacks Use a Python deque to efficiently append and pop elements from both ends of a sequence, build queues and stacks, and set maxlen for history buffers https://lnkd.in/dwJM6in9