#Pythonic

Python Quiz: What is the Output? x = 10 if x == 10: print("Hello")

Python vs Cython: The Same Logic, Over 100× Faster! Did you know that Cython can dramatically speed up Python code? In this benchmark: Pure Python: 7.37 seconds With Cython: 59.5 milliseconds That's approximately 124× faster! What makes the difference? ✅ C-level variable declarations with cdef ✅ Compiled code instead of relying entirely on Python's runtime ✅ Reduced overhead in performance-critical loops Pro tip: If your Python code spends significant time in numerical loops, Cython is worth exploring. Results depend on the code, types, compiler settings, and hardware. Not every Python program will achieve this speedup. Would you try Cython to optimize your Python applications? Repost to help other Python developers discover this! Follow @clcoding for more Python tips, coding challenges, and developer resources. Blog:

In response to the eMudhra / emSign certificate security incident we've published guidance for Python users to update CA certificates: #security #Python #pki

Algorithms — Free PDF (472 Pages!) Want to strengthen your problem-solving skills and become a better programmer? This 472-page Algorithms book is a great resource for anyone interested in understanding how algorithms work and how to solve computational problems efficiently. What you can learn: ✅ Algorithm design and problem-solving ✅ Time and space complexity ✅ Efficient approaches to computational problems ✅ A stronger foundation for Data Structures & Algorithms (DSA) ✅ Skills useful for coding interviews and competitive programming Perfect for Python developers, computer science students, software engineers, and aspiring programmers! Get the free PDF here:

You may have heard about the Model Context Protocol and wondered how it lets AI tools connect to other tools, APIs, and systems. Well, it's all thanks to MCP servers. In this guide, @manishmshiva explains how MCP servers work and helps you build your own with Python and the FastMCP library.

The future of software is code that reasons. And learning Python is your first step in this direction. In this video course, you'll learn Python fundamentals, NumPy, Pandas, SQL, Flask, LLMs, and everything else you need to dive into AI Agent development.

Want to learn Python for Data Science? Turn raw data into meaningful insights with Python! Explore essential libraries used in data analysis and visualization: ✅ NumPy – Numerical computing ✅ Pandas – Data manipulation and analysis ✅ Matplotlib – Data visualization ✅ Seaborn – Statistical data visualization Build practical skills, analyze datasets, and take your first steps toward becoming a Data Scientist. Perfect for Python developers, students, and aspiring data analysts. Detailed Explanation:

63 Python Built-in Functions Every Developer Should Know From beginner to advanced, these functions will help you write cleaner code, solve problems faster, and prepare for Python interviews. A practical Python thread

🚨 CRITICAL SECURITY ALERT PHP, GitLab & Node.js were already facing serious security vulnerabilities. Now, Linux, Python & Java are also in the spotlight. The potential impact across the tech stack is huge.

Which Programming Language Is the Easiest to Learn? If you're a beginner, choosing your first programming language can feel confusing. Here’s a quick comparison of 11 popular programming languages using the classic “Hello, World!” program: My recommendation: Start with Python if you're new to programming. Its readable syntax lets you focus on problem-solving before dealing with too many language-specific details. Remember, the easiest language depends on your goals and background! Which programming language did you learn first? Save this guide and share it with a beginner! Follow @CLCODING for more coding tips and programming tutorials.

The field of Cryptography is all about securing both data and communication between systems. And in this course, you'll learn the basics like hashing, symmetric and asymmetric encryption, and more. By the end, you'll have built a fully-functioning Python-based command line cryptography tool.

Today, I'm launching - SO Powerful than any other Traditional Mathematics tool out there - Draw any shape by hand, and spinning circles redraw it. - Zoom into the Mandelbrot set billions of times and it stays sharp. - See step-by-step solutions, each checked before it's shown to you. - Factor, solve and simplify expressions exactly, not just as decimals. - Find derivatives, integrals, limits and Taylor series. - Write notebooks that mix text, maths, live graphs and Python code. - Leave comments and roll back to any earlier version of your work. - Get answers to 50 digits when you need extreme precision. - Calculate with units: 9.81 m/s² × 3 s gives 29.43 m/s. - Export animations as GIF or video, plus PNG, SVG, PDF and LaTeX. - Bring your graphs over from Desmos and GeoGebra in one step. - Tricky curves are checked pixel by pixel, so nothing is missed or faked.

Explore 15 essential Pandas operations for data analysis in Python, from loading and cleaning datasets to filtering, grouping, merging, handling missing values, and visualizing results. A practical reference for everyday analysis. #Python #Pandas #DataAnalysis #DataScience #DataAnalytics #DataCleaning #PythonProgramming

Python Quiz: Comment your answer 😦

Python Quiz: Comment your answers below!

Top 4 Python patterns ✍️

FlyDSL, an open source Python kernel DSL, now plugs into PyTorch on @AMD MI350-series GPUs via torch.compile and eager mode. Up to 1.68x geomean scaled GEMM kernel speedups and up to 3.01x end-to-end #vLLM serving speedups. Read more:

80 Python Projects: From Beginner to Advanced Want to improve your Python skills? Stop watching tutorials and start building projects! Here’s a roadmap of 80 Python project ideas to help you practice coding, solve real problems, and build a strong portfolio.

SQL vs Python vs PySpark: 50 essential data operations compared side by side. From filtering, joins, and aggregations to window functions and data transformations, learn how the same tasks work across three powerful data technologies. #SQL #Python #PySpark #DataEngineering #DataAnalytics #BigData #DataScience

Types of Data Professionals