HTTP.jl VS DaemonMode.jl

The req.url field contains the URL of the received request, the req.method field contains request method, like GET or POST, the req.body field contains the POST body of the request in binary format. HTTP request object contains much other information. All this you can find in HTTP.jl documentation. Our web application will only check the request method. If the received request is a POST request, it will parse req.body to JSON object and send the data from this object to the isSurvived function to make a prediction and return it to the client browser. For all other request types, it will just return the content of the index.html file, to display the web interface. This is how the whole source of titanic.jl web service looks:

If you want to just get the html of a website whose url you already have you can make requests from the http.jl package. https://juliaweb.github.io/HTTP.jl/stable/

HTTP.jl and Gumbo.jl for web-scraping

I haven't seen that tutorial, but I agree that HTTP.jl, Gumbo.jl, and Cascadia.jl are the way. I used them to export public wishlists from bookdepository, which has no API nor a built in exporting tool.

I find some of the library documentation hard to understand. Compare http.jl with python's requests, for example. Something as core as HTTP requests should have clear docs with tonnes of examples. Part of this is also a personal dislike of documenter.jl styling. Idk why the contrast is so low – would prefer a standard readthedocs theme.

Thats for an entry point, you can search `Base.@main` to see a little summary of it. Later it will be able to be callable with `juliax` and `juliac` i.e. `~juliax test.jl` in shell.

DynamicalSystems looks like a heavy project. I don't think you can do much more on your own. There have been recent features in 1.10 that lets you just use the portion you need (just a weak dependency), and there is precompiletools.jl but these are on your side.

You can also look into https://github.com/dmolina/DaemonMode.jl for running a Julia process in the background and do your stuff in the shell without startup time until the standalone binaries are there.

> If I were to use e.g. Rust with polars, load time would be virtually none.

Because you're compiling...

And if you need to do the same in Julia, you should also pre-compile or some other method like https://github.com/dmolina/DaemonMode.jl (their demo shows loading a database, with subsequent loads after the first one taking roughly ~0.2% of the first)

Well, not nicely certainly, but:

https://github.com/dmolina/DaemonMode.jl

> portable

Neither is python - it just relies on universal availability. Over time…

You can get around a lot of these problems with DaemonMode.jl though.

You might want DaemonMode.jl

https://github.com/dmolina/DaemonMode.jl can possibly help in the future. Leaving it here so that people know this is planned.

If you strongly prefer to run scripts though, then you can use the package https://github.com/dmolina/DaemonMode.jl in order to re-use a Julia session between multiple scripts, saving you recompilation time.