Rahul M.’s Post

Hot take: Python is fast enough for most things. For the other things? 🦀 Rust. Just published a guide on using PyO3 v0.28 + maturin to drop Rust into your Python stack — the same approach Polars, Ruff, and Pydantic v2 use. One function. Native speed. Still pip install-able. 👉 https://lnkd.in/g794MZxa #Rust #Python #PyO3 #Engineering #Performance

Day 19/100 – #100DaysOfCode 🚀 Solved LeetCode #414 – Third Maximum Number (Python). Today I worked on an array problem to find the third distinct maximum number in the array. If it does not exist, return the maximum number. Approach: 1) Remove duplicates by converting the array into a set. 2) Convert it back to a list. 3) Sort the list in ascending order. 4) If the length is ≥ 3, return the third maximum element. 5) Otherwise, return the maximum element. Time Complexity: O(n log n) Space Complexity: O(n) Understanding how sets help remove duplicates efficiently 💪 #LeetCode #Python #DSA #Arrays #ProblemSolving #100DaysOfCode

That simple x = 10 in Python? It’s doing much more than storing the number 10. Under the hood, a Python integer is a full object (implemented in C) that includes: -- The actual value (stored as a dynamic array of digits) -- Type information -- A size field -- A reference count for memory management Unlike C, where an integer is just fixed-size raw bytes, Python stores a reference to an object. This is why a Python list of 1000 integers is actually 1000 separate objects in memory, each with its own overhead. And this is exactly where NumPy shines: -- Fixed-type arrays -- Contiguous memory -- No per-object overhead More flexibility = more memory. That’s the trade-off Python makes for you silently, every single day. #Python #SoftwareEngineering #BackendDevelopment #NumPy #PythonInternals

This article focuses on Google Colab , an increasingly popular, free, and accessible, cloud-based Python environment that is well-suited for prototyping data analysis workflows and experimental code befo... #teachthemachine https://lnkd.in/gbtzKk96

LeetCode #104 – Maximum Depth of Binary Tree | Python Implementation I implemented a recursive DFS approach that calculates tree depth by taking the maximum of left and right subtree depths plus one for the current node. Core Insight: Depth calculation decomposes naturally into subproblems. Each node's depth is determined by its deepest child, making recursion the cleanest solution with minimal code. Time: O(n) | Space: O(h) where h = tree height (recursion stack) #LeetCode #DataStructures #Python #BinaryTree #Recursion #DFS #CodingInterview #SoftwareEngineering

Which Python IDE Is the Best? This is one of the most common questions among Python developers. The honest answer: there is no single "best" IDE. It depends on what you're doing. > PyCharm is great for large Python projects and offers powerful debugging and refactoring tools. > VS Code is extremely popular because it's lightweight, flexible, and has a huge extension ecosystem. > Jupyter Notebook dominates in data science thanks to its interactive workflow - perfect for experiments, visualizations, and quick analysis. In reality, many developers switch between them depending on the task. Different tools for different jobs. P.S. Serious question: does anyone in this world still use Emacs? 😅 #python #ide #pycharm #vs_code #jupyter

When exploring a new dataset in Python, one simple command can save a lot of time: df.describe() It quickly shows key statistics for numerical columns — count, mean, standard deviation, min, max, and quartiles. Instead of manually checking distributions, this gives an instant snapshot of the data and often helps spot outliers or unusual values early in the analysis. Small habits like this make the data exploration phase much faster. #Python #DataAnalytics #MachineLearning #DataScience

LeetCode #98 – Validate Binary Search Tree | Python Implementation I implemented a recursive DFS approach with boundary tracking to validate BST properties. Core Insight: BST validation requires tracking allowable ranges, not just comparing immediate children. Each recursive call narrows the valid interval, ensuring global ordering throughout the entire subtree. Time: O(n) | Space: O(h) where h = tree height (recursion stack) #LeetCode #DataStructures #Python #BinarySearchTree #Recursion #DFS #CodingInterview #SoftwareEngineering

Deploying AI agents just got easier. 💻✨ Check out this framework-agnostic, open-source Python library. It handles everything from HTTP/A2A/MCP deployment to observability and prompt management in one place. 🌐 Web & Docs: https://studio.kiboup.com #Python #OpenSource #AIAgents #ArtificialIntelligence #DeveloperTools #MachineLearning #GitHub #TechCommunity #Coding

Recently I released v2 of immobilus — my small Python library for deterministic time control in tests. The project was completely redesigned and now includes: • thread-safe time freezing • a pytest plugin • flexible time control (tick, jumps, shifts) Feel free to check it out: https://lnkd.in/dTN_ksie #python #testing #pytest #opensource