InfoWorld AI·
The first beta release of Python 3.15 has arrived. That means it’s time to discover all the best new features in Python, and especially its low-to-no impact profiling tools. Plus, with the recent debut of Mojo 1.0, you can see for yourself how the one-time Python challenger has set out on a path of its very own. Top picks for Python readers on InfoWorld First look: Mojo 1.0 mixes Python and Rust What was once pitched as a potential Python replacement is evolving into a synthesis of Python’s easy syntax and package ecosystem and Rust’s native speed and memory safety. The best new features in Python 3.15 Lazy imports, faster JIT compilations, better error messages, and smarter profiling make Python 3.15 a compelling upgrade. And you can try out beta 1 right now. Hands-on with the new sampling profiler in Python 3.15 Another can’t-miss Python 3.15 feature: its low-impact statistical sampling profiler, for getting visibility into your programs without slowing them down. Profile Python func
Read full articleIn this article, we will dive deep into five must-know Python concepts that will help you transition from writing clunky, slow spaghetti code to constructing lightning-fast, production-grade, and beautifully functional data pipelines.
In this tutorial, we implement a practical use case with Loguru, a powerful, flexible, and production-ready logging library for Python. The post A Coding Implementation on Loguru for Designing Robust, Structured, Concurrent, and Production-Ready Python Logging Pipelines appeared first on MarkTechPost.
AgentTrove is the largest open-source collection of agentic interaction traces, with 1.7M rows in a ShareGPT-style layout. This hands-on Python tutorial shows how to stream the dataset without full downloads, normalize agent turns, extract commands, analyze trajectories, and export successful traces into a clean SFT fine-tuning dataset. The post How to Use AgentTrove: Streaming 1.7M Agentic Traces and Building a Clean ShareGPT SFT Dataset in Python appeared first on MarkTechPost.
This article shows how to use free, open-source tools like Python and its Textstat library to build a script that automates the process of capturing "gatekeeping language" in job descriptions before publishing them.
A single malformed character in a web request can let an unauthenticated attacker slip past the access controls that guard applications built on Starlette, the open-source Python framework that powers FastAPI, researchers said. The flaw, tracked as CVE-2026-48710 could allow attackers to bypass host-validation protections using malformed Host headers, according to an advisory from cybersecurity firm X41 D-Sec. The attacker needs no password and no action from a victim, it said. Starlette’s maintainer released a patch through an official GitHub security advisory after X41 D-Sec disclosed the vulnerability in coordination with the Open Source Technology Improvement Fund (OSTIF). They found the flaw during an unrelated source-code audit, and traced it to Starlette rather than the application under review. “This bug is a classic ‘responsibility gap’ where if this maintainer didn’t patch, thousands of exposed projects would have to individually secure their projects,” OSTIF said. The resear
This article covers Python libraries that make large-scale data processing faster, more scalable, and easier to manage across modern data workflows.
What a recent study on ChatGPT, Python, R, and Stata tells us about AI-assisted coding for causal inference The post Can AI Write Your Code? appeared first on Towards Data Science.
How did semantic search evolve from simple keyword matching into modern transformer-based language understanding? This hands-on article builds four generations of semantic search systems step by step using Python. The post From TF-IDF to Transformers: Implementing Four Generations of Semantic Search appeared first on Towards Data Science.
