locust VS TypeScript

Nice!

Have been working on something similar, although my use case is more about learning how code has changed across git commits: https://github.com/bugout-dev/locust

For Javascript/Typescript/React support, like you, I hooked into the Babel toolchain. Can't recommend it highly enough.

There's also a newish project called quick-lint-js which seems to have written their own from-scratch AST parser for JS, but I haven't tried it yet: https://github.com/quick-lint/quick-lint-js

Finally, another project that I know in this space is comby (I believe it is owned/maintained by the folks at Sourcegraph): https://comby.dev/

Don't know why I dumped all those links there. Just figured there may be something useful in them for you. Am also just super passionate about building knowledge about code bases by analyzing their ASTs. Nice to meet a fellow enthusiast. :)

I maintain a free/open source project that does exactly what the author asks for: https://github.com/bugout-dev/locust.

Our tool uses git as the foundation of its functionality. It superimposes git diffs on top of ASTs.

It is insanely powerful.

For example, we use it to power semantic code search and current support Python, Javascript, and Java. We generate a JSON object defining the AST differences between initial and terminal commits on GitHub PRs and doing text search on the JSON objects performs surprisingly well when we want to answer questions like, "When did we add dateutils as a dependency?" or "When did we last change the /journals handler on the API?"

The Python integration currently sees the most use but if you are interested in other languages, we would be happy to support it.

Do drop me a DM if you want help getting started with Locust.

My team has a similar project (Locust: https://github.com/bugout-dev/locust) where the goal is to learn the semantic meanings of code changes in git commits, GitHub PRs, etc.

Since we took git diffs as a target for semantic analysis, we have a different approach to our diffs. We start with line-by-line diffs (specifically using "git diff") and then take a semantic diff by superimposing the git diff information on top of the initial and terminal ASTs.

This makes the diff calculation cheaper because we don't have to do full diff between trees.

Haven't updated the code in a few months, but my team is actively using Locust on public GitHub repos to learn the semantics of those code bases. We do plan to do some work on it soon to make it easier to make Locust easier to use (especially as a library).

Really need to sit down and take a proper look at tree-sitter. We currently support Locust diffs for Python, Javascript, and Java, but each one is custom written and implements the same basic algorithm. It looks like tree sitter might just crush this problem for us.

Regular expressions are part of the language, so it's not so unreasonable that TypeScript should parse them and take their semantics into account. Indeed, TypeScript 5.5 will include [new support for syntax checking of regular expressions](https://github.com/microsoft/TypeScript/pull/55600), and presumably they'll eventually be able to solve the problem the GP highlighted on top of those foundations.

Dedicated syntax for creating unique subsets of a type that denote a particular refinement is a longstanding ask[2] - and very useful, we've experimented with implementations.[3]

I don't think it has any relation to runtime type checking at all. It's refinement types, [4] or newtypes[5] depending on the details and how you shape it.

[1] https://github.com/microsoft/TypeScript/blob/main/src/compil...

GitHub | Website

Learning Curve and Developer Tooling sCrypt is an embedded Domain Specific Language (eDSL) based on TypeScript. It is strictly a subset of TypeScript, so all sCrypt code is valid TypeScript. TypeScript is chosen as the host language because it provides an easy, familiar language (JavaScript), but with type safety. There’s an abundance of learning materials available for TypeScript and thus sCrypt, including online tutorials, courses, documentation, and community support. This makes it relatively easy for beginners to start learning. It also has a vast ecosystem with numerous libraries and frameworks (e.g., React, Angular, Vue) that can simplify development and integration with Web2 applications.

As a JavaScript or TypeScript developer, you might have come across the terms type and interface when working with complex data structures or defining custom types. While both serve similar purposes, they have distinct characteristics that influence when to use them. In this blog post, we'll delve into the differences between types and interfaces in TypeScript, providing examples to aid your understanding.

TypeScript helps you in many ways in the context of a JavaScript app. It makes it easier to consume interfaces of any type.

In this guide, we'll be extracting information from Amazon product pages using the power of TypeScript in combination with the Cheerio and Crawlee libraries. We'll explore how to retrieve and extract detailed product data such as titles, prices, image URLs, and more from Amazon's vast marketplace. We'll also discuss handling potential blocking issues that may arise during the scraping process.

TypeScript

Familiarity with TypeScript, React and Next.js