An opinionated list of Python frameworks, libraries, tools, and resources
We're all learning how to ship more side projects. If you're "in the bubble" it can feel like everyone is repo-maxxing. Shipping weekly. Spinning up agents to scaffold full apps overnight. New OSS dropped every Friday. The reality I see with most developers is much more normal: They have six or seven repos sitting in various states of half-attention. A side project from last year that still gets a
You've likely heard that "Data is the new oil". But raw oil is useless without a refinery. In the world of Big Data, Apache Spark is that refinery. Whether it's millisecond-level fraud detection or processing terabytes of logs, Spark's ability to handle massive scale with in-memory speed is why it remains a core skill for every ML & Data Engineer. Here are 5 real-world problems and exactly how Spa
Hey dev.to community! I just launched CodeLens AI — an AI-powered code review tool that automatically reviews every pull request. Connect your GitHub repo Open a PR AI automatically reviews the code Detailed review comment posted on PR Bugs and logic errors SQL injection and security vulnerabilities Performance issues Code quality improvements Next.js + TypeScript NextAuth + GitHub OAuth Supabase
Why We Open-Sourced Our AI Safety Layer When we built the AI safety layer for As You Wish (AYW), we faced a choice: keep it proprietary or open-source it to help the community. Here's why we chose the latter (and why it made our platform stronger). If you're building AI-assisted development tools, you need: Input validation (sanitizing prompts, preventing injection) Output filtering (catching u
If you want to Automate GitHub PRs, the real goal is not just adding another bot comment to a pull request. The goal is to give reviewers the context they usually have to gather manually: who owns the service, whether it is deployed, whether basic repository standards are in place, and whether the change looks safe to merge. A useful AI pull request workflow can do exactly that. When a PR opens, i
Data is no longer treated as a byproduct of business operations and has become one of the most valuable organizational assets. Every interaction on a banking application, e-commerce platform, hospital system, logistics network or social media service generates data continuously. As organizations increasingly adopt digital workflows, cloud platforms, machine learning systems and real-time applicati
In modern data-driven organizations, managing and analyzing data efficiently is critical. OLAP (Online Analytical Processing) and OLTP (Online Transaction Processing) are both integral parts of data management, but they have different functionalities. Understanding how they differ, and how they complement each other is essential for anyone working with data systems. Online Transaction Processing (