ihp-datasync-demo
PyCall.jl
Our great sponsors
| ihp-datasync-demo | PyCall.jl | |
|---|---|---|
| 1 | 28 | |
| 1 | 1,438 | |
| - | 1.2% | |
| 0.0 | 6.1 | |
| over 2 years ago | about 2 months ago | |
| Haskell | Julia | |
| - | MIT License |
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.
ihp-datasync-demo
-
Why Co–Star Uses Haskell
On the backend we use Postgres Row-level-security Policies to make sure that a user can only access his own data.
Here's a demo react component that uses the new JS APIs: https://github.com/digitallyinduced/ihp-datasync-demo/blob/m...
Docs are still in progress, but here's a draft https://github.com/digitallyinduced/ihp/commit/39baa4aa23cc6... :)
PyCall.jl
-
I just started into Julia for ML
For point 3 you can use https://github.com/cjdoris/PythonCall.jl or https://github.com/JuliaPy/PyCall.jl (and their respective Python sister packages).
- The Mojo Programming Language: A Python Superset Drawing from Rust's Strengths
-
Calling Chapel, Carbon, and zig code in Julia
PyCall.jl is really handy. Are there any similar projects for calling Chapel code, or Carbon/zig?
-
Am I dumb in thinking I can use Rust as a Fast Python and leave it at that?
Julia and Python interop should not be a problem at all. Actually Julia has one of the best interops I’ve ever seen, so much that swift copied it. https://github.com/JuliaPy/PyCall.jl
- Which tools do you use for python + Data Science?
-
I don't want to abandon Rust for Julia
One small note, julia also has great python interop via PyCall.jl
- Faster Python calculations with Numba: 2 lines of code, 13× speed-up
-
Interoperability in Julia
It is possible to call Python from Julia using PyCall. Then to install PyCall, run the command in the Julia REPL.
-
Why is Python so used in the machine learning?
That said, you can run python modules in Julia. So you can just export your code as a module and then use it in Julia via the PyCall package. short description here github here <— you’d just add the pacakge via the really nice package manager built into julia, but for link for more detailed documentation
- Use rust code in Python with pyo3
What are some alternatives?
expressive-java - Example of matching Scala's case class expressiveness in Java 8, Java 15 and Java 17
py2many - Transpiler of Python to many other languages
ihp - 🔥 The fastest way to build type safe web apps. IHP is a new batteries-included web framework optimized for longterm productivity and programmer happiness
Revise.jl - Automatically update function definitions in a running Julia session
julia - The Julia Programming Language
Genie.jl - 🧞The highly productive Julia web framework
are-we-fast-yet - Are We Fast Yet? Comparing Language Implementations with Objects, Closures, and Arrays
fast-ruby - :dash: Writing Fast Ruby :heart_eyes: -- Collect Common Ruby idioms.
libffi - A portable foreign-function interface library.
RCall.jl - Call R from Julia
typeshed - Collection of library stubs for Python, with static types
Slick - Slick (Scala Language Integrated Connection Kit) is a modern database query and access library for Scala