When I started programming Edge Python more than six months ago, I was looking for a version of Python that weighed less than 200 kb so it could reach any device, sandboxed by design, built with browsers in mind, decoupled from the operating system and very fast.
Today the closest competitor would be MicroPython. However, it did not solve my real problems or the problems of the people who use the project.
* Managing async and blocking code on the event loop. MicroPython inherits CPython's blocking execution model, designed around the GIL. When I built Edge Python I put the events inside the virtual machine, and that lets you run any operation while handling thousands of connections without blocking the main thread or the worker's thread.
* MicroPython was not built for the web and neither was its stdlib. I have been working to get regex and every other dependency down to a few clean lines, crash free thanks to directed fuzzing.
* Edge Python guarantees parsing everything in linear time, in a single pass, while MicroPython does not. This came from avoiding a syntax tree, which makes programs parse faster.
* MicroPython crosses into JS through PyProxy. Edge Python avoids that entirely with an execution model decoupled from the host, they never have to interact directly.
* I recently added the ability to serialize entire programs, born from an issue. If a user closes the tab, the whole bytecode state gets serialized, stored in the browser cache, and when the user comes back execution continues from the exact same point.
That said, my intention was never to replace CPython and it never will be. It has a gigantic ecosystem and competing with it is not even a priority for me. What I want to enable is this.
* Anyone with business logic written in Python being able to run it on the client side.
* Running lightweight LLM logic on the client side, so you do not need expensive compute just to parse a CSV or do math.
* Building a framework to run lightweight machine learning models entirely on the user's side.
I am still working on all of this and, to be honest, I do not know how long it will take me to reach a real version to build a product around. I just want to say it has been an incredible process, and it has made me realize that with a compiler of barely under 20,000 lines I spend less and less time writing code and more time automating its stability with fuzzing and determinism.
Thanks! Any feedback or experience is appreciated. If you want to take a look, try the demo in the browser at https://edgepython.com/ and edit the code, the compiler is really fast. Try the CLI version too.
dylansuttonc•58m ago
Today the closest competitor would be MicroPython. However, it did not solve my real problems or the problems of the people who use the project.
* Managing async and blocking code on the event loop. MicroPython inherits CPython's blocking execution model, designed around the GIL. When I built Edge Python I put the events inside the virtual machine, and that lets you run any operation while handling thousands of connections without blocking the main thread or the worker's thread.
* MicroPython was not built for the web and neither was its stdlib. I have been working to get regex and every other dependency down to a few clean lines, crash free thanks to directed fuzzing.
* Edge Python guarantees parsing everything in linear time, in a single pass, while MicroPython does not. This came from avoiding a syntax tree, which makes programs parse faster.
* MicroPython crosses into JS through PyProxy. Edge Python avoids that entirely with an execution model decoupled from the host, they never have to interact directly.
* I recently added the ability to serialize entire programs, born from an issue. If a user closes the tab, the whole bytecode state gets serialized, stored in the browser cache, and when the user comes back execution continues from the exact same point.
That said, my intention was never to replace CPython and it never will be. It has a gigantic ecosystem and competing with it is not even a priority for me. What I want to enable is this.
* Anyone with business logic written in Python being able to run it on the client side.
* Running lightweight LLM logic on the client side, so you do not need expensive compute just to parse a CSV or do math.
* Building a framework to run lightweight machine learning models entirely on the user's side.
I am still working on all of this and, to be honest, I do not know how long it will take me to reach a real version to build a product around. I just want to say it has been an incredible process, and it has made me realize that with a compiler of barely under 20,000 lines I spend less and less time writing code and more time automating its stability with fuzzing and determinism.
Thanks! Any feedback or experience is appreciated. If you want to take a look, try the demo in the browser at https://edgepython.com/ and edit the code, the compiler is really fast. Try the CLI version too.