evcxr
polars
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evcxr | polars | |
---|---|---|
75 | 144 | |
5,168 | 25,837 | |
1.9% | 5.3% | |
8.7 | 10.0 | |
about 1 month ago | 6 days ago | |
Rust | Rust | |
GNU General Public License v3.0 or later | 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.
evcxr
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Scriptisto: "Shebang interpreter" that enables writing scripts in compiled langs
Emacs didn't invent REPL, and it's common everywhere. For Rust: https://github.com/evcxr/evcxr/blob/main/evcxr_repl/README.m.... But heck, the compiler is reasonably fast enough that any IDE can REPL by compiling the code.
The value here is more in being able to read a script before you run it, then have it run fast, maybe tweaking something here and there. And a compiled script will run 10,000 times faster than LISP, which can be important.
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Go: What We Got Right, What We Got Wrong
https://github.com/evcxr/evcxr can run Rust in a Jupyter notebook. It's not Golang but close enough.
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The Hallucinated Rows Incident
The engine uses rust_decimal::Decimal to represent high precision decimal numbers, like the weight property. Serialization of RocksDB keys is done by the storekey crate. To know how Yumi's machine stores diffs, we can now ask- How does storekey serialize rust_decimal? Well, using evcxr to run Rust in Jupyter, the answer is as a null-terminated string:
- TermiC: Terminal C, Interactive C/C++ REPL shell created with BASH
- Exploring Options for Dynamic Code Changes in Rust without Recompilation (hot reloading)
- Go 1.21 will (likely) have a static toolchain on Linux
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What’s an actual use case for Rust
In theory you should be able to create Rust notebooks (Jupyter notebook) using evcxr so maybe some AI, data analysis, prototyping make sense if you aim for good performance in final application (protype in evcxr and use notebook as reference to implement final application in Rust for speed and safety).
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would you use rust for scripting?
You should check out evcxr
- Nannou – An open-source creative-coding framework for Rust
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Rust vs. Haskell
There is also implementations of rust REPLs, like the beautifully named evcxr.
polars
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Why Python's Integer Division Floors (2010)
This is because 0.1 is in actuality the floating point value value 0.1000000000000000055511151231257827021181583404541015625, and thus 1 divided by it is ever so slightly smaller than 10. Nevertheless, fpround(1 / fpround(1 / 10)) = 10 exactly.
I found out about this recently because in Polars I defined a // b for floats to be (a / b).floor(), which does return 10 for this computation. Since Python's correctly-rounded division is rather expensive, I chose to stick to this (more context: https://github.com/pola-rs/polars/issues/14596#issuecomment-...).
- Polars
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Stuff I Learned during Hanukkah of Data 2023
That turned out to be related to pola-rs/polars#11912, and this linked comment provided a deceptively simple solution - use PARSE_DECLTYPES when creating the connection:
- Polars 0.20 Released
- Segunda linguagem
- Polars: Dataframes powered by a multithreaded query engine, written in Rust
- Summing columns in remote Parquet files using DuckDB
- Polars 0.34 is released. (A query engine focussing on DataFrame front ends)
What are some alternatives?
vscode-jupyter - VS Code Jupyter extension
vaex - Out-of-Core hybrid Apache Arrow/NumPy DataFrame for Python, ML, visualization and exploration of big tabular data at a billion rows per second 🚀
jupyter-rust - a docker container for jupyter notebooks for rust
modin - Modin: Scale your Pandas workflows by changing a single line of code
rust-script - Run Rust files and expressions as scripts without any setup or compilation step.
arrow-datafusion - Apache DataFusion SQL Query Engine
bincode - A binary encoder / decoder implementation in Rust.
DataFrames.jl - In-memory tabular data in Julia
cargo-script - Cargo script subcommand
datatable - A Python package for manipulating 2-dimensional tabular data structures
iron.nvim - Interactive Repl Over Neovim
Apache Arrow - Apache Arrow is a multi-language toolbox for accelerated data interchange and in-memory processing