SShortSingh.
Back to feed

Textparser offers high-performance C parsing engine with Python-compiled grammars

0
·1 views

A developer has introduced Textparser, a hybrid parsing engine that combines JSON, Python, and C to simplify language parsing workflows. The tool aims to bridge the gap between complex traditional parser generators like Flex/Bison and difficult-to-maintain hand-written parsers. Textparser ships with ready-to-use grammar files for over 30 languages, including C, C++, Rust, Python, JavaScript, HTML, and SQL. Each parsed token carries metadata such as code coordinates, structural flags, and syntax styling options. The project is designed for lightweight use cases like terminal text editors, syntax highlighters, and custom linters where full compiler front-ends would be excessive.

Read the full story at DEV Community

This is an AI-generated summary. ShortSingh links to the original source for the complete article.

Discussion (0)

Log in to join the discussion and vote.

Log in

Related stories

0
ProgrammingDEV Community ·

University of Minnesota Scientists Build World's First Fully Synthetic Cell from Scratch

Researchers at the University of Minnesota, led by Associate Professors Kate Adamala and Aaron Engelhart, have created SpudCell, the world's first synthetic cell built entirely from non-living chemical components rather than derived from any existing organism. The cell can grow, feed, replicate its genetic material, and divide — completing a full life cycle driven purely by chemistry. SpudCell's genome is just 90 kilobase pairs, a fraction of the human genome's 3 billion base pairs, and is precisely minimal by design, with every molecular component intentional and fully documented. Because researchers have a complete blueprint and ingredient list, individual components can be swapped out, making the system highly programmable and experimentally flexible. Experts say the breakthrough frees synthetic biology from the evolutionary constraints of natural cells, potentially enabling biological systems to perform functions that living cells cannot easily achieve.

0
ProgrammingDEV Community ·

How Developers Can Break Free From Passive Learning and Start Creating

Many developers fall into a 'learning vacuum' where they endlessly consume tutorials, courses, and articles without producing anything tangible. A DEV Community writer outlines practical steps to shift from passive absorption to active output, starting with simply documenting what you build each day. Taking on small personal projects, even ones with no real-world utility, can reignite motivation and provide hands-on experience that tutorials cannot replicate. Engaging with developer communities — whether online forums, Discord servers, or local meetups — helps transform isolated learning into shared, applied knowledge. Writing about concepts you have recently mastered, no matter how basic they seem, reinforces understanding and builds confidence in your own abilities.

0
ProgrammingHacker News ·

Infracost Seeks Marketing Lead to Drive FinOps Awareness

Infracost, a Y Combinator Winter 2021 alumni company, is currently hiring for a Marketing Lead position. The company focuses on FinOps, a practice that aims to bring cloud cost management earlier into the software development lifecycle. The job listing was posted on Y Combinator's company job board. No further details about the role's requirements or compensation were publicly available in the listing.

0
ProgrammingDEV Community ·

Vercel, Google, and Mistral ship major AI infrastructure updates in same week

Vercel's AI Gateway introduced firewall-style routing rules that let platform teams swap or block models at the credential level without changing application code, reducing model migration to a single config update. Google released Nano Banana 2 Lite, capable of generating 1,000 images in four seconds at low cost, alongside Omni Flash, which enables natural-language video editing within the same API pipeline but is limited to 10-second clips with no audio support. A new suite of MIT-licensed agentic coding models, ranging from 9B to 397B parameters, was released with reinforcement learning training optimized for both solution quality and search scaffolding, supporting 256K context windows. The smaller 9B dense model runs on a single 80GB GPU, making capable agentic coding accessible without multi-GPU infrastructure. Mistral also shipped two production-ready releases in the same cycle, with a text-to-speech offering among them, reflecting a broader industry push toward tighter control over model selection, credentials, and tool integrations.