ux-dataflow
polars
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ux-dataflow | polars | |
---|---|---|
2 | 144 | |
9 | 26,043 | |
- | 6.1% | |
0.0 | 10.0 | |
over 2 years ago | 6 days ago | |
Rust | Rust | |
Mozilla Public License 2.0 | 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.
ux-dataflow
- UX Dataflow is a streaming capable data multiplexer
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Platform-agnostic Charts for HTML5 Canvas and GTK/Cairo Desktop Applications
UX Charts is a drawing library designed for clean charts. UX Charts supports various types of backend including GTK/Cairo and HTML5 Canvas. UX Charts are designed with the concept - "one code for all". It uses the UX Dataflow library as the data source and the UX Animate library as the canvas implementation.
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-...).
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Polars
https://github.com/pola-rs/polars/releases/tag/py-0.19.0
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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?
yew-components - Material Design Components for the Yew framework
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 🚀
yew - Rust / Wasm framework for creating reliable and efficient web applications
modin - Modin: Scale your Pandas workflows by changing a single line of code
utah - Dataframe structure and operations in Rust
datafusion - Apache DataFusion SQL Query Engine
ux-charts - Simple, responsive, modern Charts with zero dependencies
DataFrames.jl - In-memory tabular data in Julia
ux-animate - A simple but powerful tweening, spring physics, animation library for Rust
datatable - A Python package for manipulating 2-dimensional tabular data structures
Apache Arrow - Apache Arrow is a multi-language toolbox for accelerated data interchange and in-memory processing
db-benchmark - reproducible benchmark of database-like ops