HTTP.jl
TailRec.jl
Our great sponsors
HTTP.jl | TailRec.jl | |
---|---|---|
7 | 3 | |
619 | 16 | |
0.5% | - | |
7.7 | 0.0 | |
4 days ago | over 3 years ago | |
Julia | Julia | |
GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
HTTP.jl
-
Machine learning with Julia - Solve Titanic competition on Kaggle and deploy trained AI model as a web service
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:
-
Automate the boring stuff with Julia?
HTTP.jl and Gumbo.jl for web-scraping
- PyTorch: Where we are headed and why it looks a lot like Julia (but not exactly)
-
Recommendations on how to start web scraping with julia for price updates? (if possible)
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.
-
Why not Julia?
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.
- Julia 1.6: what has changed since Julia 1.0?
TailRec.jl
-
PyTorch: Where we are headed and why it looks a lot like Julia (but not exactly)
Here is one:
https://github.com/TakekazuKATO/TailRec.jl
It works by inspecting the code and rewriting a function to turn tail calls into loops.
The interesting bit is that it was very easy to write because of the strong macros in Julia.
What are some alternatives?
DaemonMode.jl - Client-Daemon workflow to run faster scripts in Julia
geni-performance-benchmark
julia - The Julia Programming Language
JET.jl - An experimental code analyzer for Julia. No need for additional type annotations.
PackageCompiler.jl - Compile your Julia Package
Gumbo.jl - Julia wrapper around Google's gumbo C library for parsing HTML
BinaryBuilder.jl - Binary Dependency Builder for Julia
Cython - The most widely used Python to C compiler
hebigo - 蛇語(HEH-bee-go): An indentation-based skin for Hissp.
py2many - Transpiler of Python to many other languages
Cascadia.jl - A CSS Selector library in Julia
OffsetArrays.jl - Fortran-like arrays with arbitrary, zero or negative starting indices.