HTTP.jl
geni-performance-benchmark
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HTTP.jl | geni-performance-benchmark | |
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7 | 3 | |
623 | 27 | |
1.3% | - | |
7.7 | 4.1 | |
6 days ago | over 3 years ago | |
Julia | Clojure | |
GNU General Public License v3.0 or later | Apache License 2.0 |
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
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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:
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How can I use Julia to search on the web automatically?
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/
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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)
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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.
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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?
geni-performance-benchmark
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PyTorch: Where we are headed and why it looks a lot like Julia (but not exactly)
Clojure has a high performance data frame library that leverages new JVM vector API and high quality apache arrow protocol.
Talk related - https://youtu.be/5mUGu4RlwKE
https://github.com/zero-one-group/geni-performance-benchmark
- LLVM!
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Clojure High Performance Data Processing System
How often have you seen a Clojure system that soundly beats C, Julia, Python, Spark, and R systems in a data processing benchmark?
What are some alternatives?
julia - The Julia Programming Language
jax - Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
DaemonMode.jl - Client-Daemon workflow to run faster scripts in Julia
tablecloth - Dataset manipulation library built on the top of tech.ml.dataset
JET.jl - An experimental code analyzer for Julia. No need for additional type annotations.
tech.ml.dataset - A Clojure high performance data processing system
BinaryBuilder.jl - Binary Dependency Builder for Julia
functorch - functorch is JAX-like composable function transforms for PyTorch.
PackageCompiler.jl - Compile your Julia Package
TailRec.jl - A tail recursion optimization macro for julia.
Gumbo.jl - Julia wrapper around Google's gumbo C library for parsing HTML
geni - A Clojure dataframe library that runs on Spark