Polars
Blazingly fast DataFrames in Rust, Python & Node.js
Polars is a blazingly fast DataFrames library implemented in Rust using Apache Arrow Columnar Format as the memory model.
- Lazy | eager execution
- Multi-threaded
- SIMD
- Query optimization
- Powerful expression API
- Rust | Python | ...
To learn more, read the User Guide.
>>>
>>> =
# embarrassingly parallel execution
# very expressive query language
>>>
:
┌──────────┬──────────┬──────────────┬─────┬─────────────┬─────────────┬─────────────┬─────────────┐
│ ┆ ┆ ┆ ┆ ┆ ┆ ┆ │
│ --- ┆ --- ┆ ┆ --- ┆ ┆ ┆ ┆ │
│ ┆ ┆ --- ┆ ┆ --- ┆ --- ┆ --- ┆ --- │
│ ┆ ┆ ┆ ┆ ┆ ┆ ┆ │
╞══════════╪══════════╪══════════════╪═════╪═════════════╪═════════════╪═════════════╪═════════════╡
│ ┆ ┆ ┆ 11 ┆ 4 ┆ 7 ┆ 4 ┆ 4 │
├╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌┤
│ ┆ ┆ ┆ 11 ┆ 4 ┆ 7 ┆ 3 ┆ 3 │
├╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌┤
│ ┆ ┆ ┆ 11 ┆ 4 ┆ 8 ┆ 5 ┆ 5 │
├╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌┤
│ ┆ ┆ ┆ 11 ┆ 2 ┆ 8 ┆ 2 ┆ 2 │
├╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌┤
│ ┆ ┆ ┆ 11 ┆ 4 ┆ 8 ┆ 1 ┆ 1 │
└──────────┴──────────┴──────────────┴─────┴─────────────┴─────────────┴─────────────┴─────────────┘
Performance 🚀🚀
Polars is very fast. In fact, it is one of the best performing solutions available. See the results in h2oai's db-benchmark.
Python setup
Install the latest polars version with:
$ pip3 install -U 'polars[pyarrow]'
Releases happen quite often (weekly / every few days) at the moment, so updating polars regularly to get the latest bugfixes / features might not be a bad idea.
Rust setup
You can take latest release from crates.io
, or if you want to use the latest features / performance improvements
point to the master
branch of this repo.
= { = "https://github.com/pola-rs/polars", = "<optional git tag>" }
Rust version
Required Rust version >=1.58
Documentation
Want to know about all the features Polars supports? Read the docs!
Python
- Installation guide:
$ pip3 install polars
- Python documentation
- User guide
Rust
Node
- Installation guide:
$ yarn add nodejs-polars
- Node documentation
- User guide
Contribution
Want to contribute? Read our contribution guideline.
[Python]: compile polars from source
If you want a bleeding edge release or maximal performance you should compile polars from source.
This can be done by going through the following steps in sequence:
- Install the latest Rust compiler
- Install maturin:
$ pip3 install maturin
- Choose any of:
- Fastest binary, very long compile times:
&&
- Fast binary, Shorter compile times:
&&
- Fastest binary, very long compile times:
Note that the Rust crate implementing the Python bindings is called py-polars
to distinguish from the wrapped
Rust crate polars
itself. However, both the Python package and the Python module are named polars
, so you
can pip install polars
and import polars
.
Arrow2
Polars has transitioned to arrow2. Arrow2 is a faster and safer implementation of the Apache Arrow Columnar Format. Arrow2 also has a more granular code base, helping to reduce the compiler bloat.
Use custom Rust function in python?
See this example.
Going big...
Do you expect more than 2^32
~4,2 billion rows? Compile polars with the bigidx
feature flag.
Or for python users install $ pip install -U polars-u64-idx
.
Don't use this unless you hit the row boundary as the default polars is faster and consumes less memory.
Acknowledgements
Development of Polars is proudly powered by