pymartini
polars
Our great sponsors
| pymartini | polars | |
|---|---|---|
| 1 | 144 | |
| 76 | 26,218 | |
| - | 6.7% | |
| 0.0 | 10.0 | |
| over 1 year ago | 3 days ago | |
| Python | Rust | |
| MIT License | 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.
pymartini
-
Modern Python Performance Considerations
They can! Numpy exposes a C API to other Python programs [0]. It's not hard to write a Cython library that uses the Numpy C API directly and does not cross into Python [1].
[0]: https://numpy.org/doc/stable/reference/c-api/index.html
[1]: https://github.com/kylebarron/pymartini/blob/4774549ffa2051c...
polars
-
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
https://github.com/pola-rs/polars/releases/tag/py-0.19.0
-
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?
pydantic-core - Core validation logic for pydantic written in rust
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 🚀
cannoli - Cannoli Programming Language
modin - Modin: Scale your Pandas workflows by changing a single line of code
uvloop - Ultra fast asyncio event loop.
datafusion - Apache DataFusion SQL Query Engine
DataFrames.jl - In-memory tabular data in Julia
yaegi - Yaegi is Another Elegant Go Interpreter
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