5 Free Ways to Host a Python Application

Learn how to build a vector search engine from scratch in Python with embeddings, similarity scoring, and basic retrieval logic.

It’s harder than it might seem to create a stand-alone Python app. It’s also harder than you might think to reliably back up SQLite databases, but Python has the tools for it. And while it’s not easy to install Python on an air-gapped machine, it absolutely can be done. Top picks for Python readers on InfoWorld Why it’s so hard to create stand-alone Python apps Python’s dynamism is one of its most powerful features. It’s also why making stand-alone apps from Python programs is such a bear. How to back up SQLite databases the right way (not by copying them!) SQLite databases are single files, so backing them up just means copying them, right? Wrong. Make backups the proper way by using SQLite’s own backup mechanisms. Python’s new frozendict type, demonstrated A long-desired and -debated core addition to the language: a “frozen” or immutable dictionary, is coming in Python 3.15. See where it’ll be most useful in our live demo. How to set up Python on an air-gapped system Stuck working wi

In this tutorial, we explore CloakBrowser, a Python-friendly browser automation tool that uses Playwright-style APIs within a stealth Chromium environment. We begin by setting up CloakBrowser, preparing the required browser binary, and resolving the common Colab asyncio loop issue by running the sync browser workflow in a separate worker thread. We then move through practical […] The post Build a CloakBrowser Automation Workflow with Stealth Chromium, Persistent Profiles, and Browser Signal Inspection appeared first on MarkTechPost.

A practical guide to modern type annotations in Python for data science The post The Joy of Typing appeared first on Towards Data Science.

Feature engineering is the foundation of strong machine learning systems, but the traditional process is often manual, time-consuming, and dependent on domain expertise. While effective, it can miss deeper signals hidden in unstructured data such as text, logs, and user interactions. Large Language Models change this by helping machines understand language, extract meaning, and generate […] The post Feature Engineering with LLMs: Techniques & Python Examples appeared first on Analytics Vidhya.

Front-end development has never been more capable. Modern frameworks offer fast rendering pipelines, component composition, powerful tooling, and a growing ecosystem of libraries that promise to make building sophisticated applications easier than ever. Yet many teams experience exactly the opposite — increasing difficulty. Applications grow harder to reason about. Features interact in unexpected ways. Simple changes ripple through unrelated parts of the system. Debugging becomes an exercise in tracing invisible dependencies across the application. The tools improved, but the complexity remained. Front-end complexity never ends For many years, front-end complexity was blamed on frameworks. Each generation of tooling promised to fix the limitations of the previous one. The transition from server-rendered pages to client-side frameworks introduced a wave of architectural experimentation. Then came virtual DOM engines, reactive libraries, and increasingly sophisticated component systems.

Stop shifting elements in lists! Discover why collections.deque is the secret to high-performance sliding windows, thread-safe queues, and efficient data streams in your next Python project. The post Beyond Lists: Using Python Deque for Real-Time Sliding Windows appeared first on Towards Data Science.

It's not just you. Hackers and other cybercriminals are complaining about “AI shit” flooding platforms where they discuss cyberattacks and other illegal activity.