Daft
Distributed DataFrame for Python designed for the cloud, powered by Rust (by Eventual-Inc)
polars
Dataframes powered by a multithreaded, vectorized query engine, written in Rust (by ritchie46)
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Daft | polars | |
---|---|---|
7 | 144 | |
1,684 | 26,218 | |
38.2% | 6.7% | |
9.8 | 10.0 | |
3 days ago | 2 days ago | |
Rust | Rust | |
Apache License 2.0 | MIT License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.
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.
Daft
Posts with mentions or reviews of Daft.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2024-02-29.
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Daft: Distributed DataFrame for Python
There are benchmarks here - https://github.com/Eventual-Inc/Daft?tab=readme-ov-file#benc.... Seems to outperform Dask by a fair bit.
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Daft: A High-Performance Distributed Dataframe Library for Multimodal Data
Hi (one of the maintainers here), that is a good suggestion! I wasn't aware of that project. I went ahead and made an issue to add `export DO_NOT_TRACK=1` as one of the variables we track! https://github.com/Eventual-Inc/Daft/issues/1015
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Daft: The Distributed Python Dataframe
We are looking at supporting other distributed backends as well - please drop by our discussion forums (https://github.com/Eventual-Inc/Daft/discussions) and drop us a message if you have any suggestions! We’d love to hear from you :)
polars
Posts with mentions or reviews of polars.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2024-01-08.
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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)