polars-list-math
polars-list-math is a Python/Rust package with list, JSON, and URL expression
helpers for Polars.
Import the package once to register extra methods on Expr.list and Expr.str:
import polars as pl
import polars_list_math # noqa: F401
For type-checked code, import the top-level expression helpers described below.
Install
pip install polars-list-math
# or
uv add polars-list-math
Requires Python 3.12+ and polars>=1.39.3.
Methods
| Method | Result | Docs |
|---|---|---|
Expr.list.zip(...) |
Zip lists into list[struct] |
Polars proposal |
Expr.list.combinations(...) |
Pair items in one list, optionally skipping self-pairs | Combinations |
Expr.list.combinations_to(...) |
Pair each item with each item from another list | Combinations |
Expr.list.similarity(...) |
Weighted similarity between two lists | Similarity |
Expr.list.mean_similarity(...) |
Mean similarity inside a nested-list row | Similarity |
Expr.list.mean_similarity_to(...) |
Mean similarity to reference nested lists | Similarity |
Expr.str.json_object_items(...) |
Convert a JSON object to list[struct[key, value]] |
JSON object items |
Expr.str.json_array_values(...) |
Convert a JSON array to list[str] |
JSON array values |
Top-level expression helpers provide the statically typed API for Pyright, Pylance, and other type checkers:
| Function | Result | Docs |
|---|---|---|
list_zip(...) |
Zip lists into list[struct] |
Examples |
list_combinations(...) |
Pair items in one list | Combinations |
list_combinations_to(...) |
Pair items from two lists | Combinations |
expected_value_of_game(...) |
Expected value of a sequential game | Expected value of a game |
list_similarity(...) |
Weighted similarity between two lists | Similarity |
list_mean_similarity(...) |
Mean similarity inside nested lists | Similarity |
list_mean_similarity_to(...) |
Mean similarity to reference nested lists | Similarity |
json_object_items(expr, strict=False) |
Convert a JSON object to list[struct[key, value]] |
JSON object items |
json_array_values(expr, strict=False) |
Convert a JSON array to list[str] |
JSON array values |
url_query_encode(expr, doseq=False) |
Encode a Struct or key/value list as a URL query string | URL query encoding |
url_build(...) |
Assemble a URL from optional component expressions | URL building |
The Python helper py_list_similarity(...) computes weighted similarity for
plain Python sequences.
The Expr.list and Expr.str methods are registered dynamically and remain
available as convenient runtime syntax. Python type checkers cannot safely
augment Polars' own namespace classes from another installed package, so use
the equivalent top-level functions in code checked by Pylance or Pyright.
If a future Polars release ships native methods with the same names, this package leaves the native implementation untouched.
Quick Examples
from polars_list_math import (
list_combinations,
list_mean_similarity,
list_similarity,
list_zip,
)
df = pl.DataFrame(
{
"a": [[1, 2, 3]],
"b": [[2, 1, 3]],
"groups": [[[1, 2, 3], [1, 2, 3], [4, 5, 6]]],
}
)
df.with_columns(
list_similarity("a", "b").alias("similarity"),
list_mean_similarity("groups").alias("mean_similarity"),
list_combinations("a").alias("pairs"),
list_zip("a", "b", fields=["a", "b"]).alias("zipped"),
)
Convert JSON strings to nested Polars values. String values stay strings, JSON
null stays null, and other values become compact JSON strings. Invalid JSON
returns null by default; pass strict=True to raise instead.
from polars_list_math import json_array_values, json_object_items
json_df = pl.DataFrame(
{
"object": ['{"name":"Ada","active":true,"note":null}'],
"array": ['["python",42,true,null]'],
}
)
json_df.select(
json_object_items("object").alias("items"),
json_array_values("array").alias("values"),
)
Encode query parameters and build URLs from expressions:
from polars_list_math import url_build, url_query_encode
pages = pl.DataFrame(
{
"host": ["example.com"],
"path": ["/search"],
"term": ["rust polars"],
"page": [2],
}
)
query = url_query_encode(pl.struct(q=pl.col("term"), page=pl.col("page")))
pages.select(
url_build(
scheme=pl.lit("https"),
netloc="host",
path="path",
query=query,
).alias("url")
)
More complete, runnable examples are available in the
examples
directory.
Development
make install
make develop
make test
Build and check the package locally:
make check-dist
Release steps are in docs/publishing.md.
1 maintainer
Metadata
1 maintainer
Release files for polars-list-math 0.3.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| polars_list_math-0.3.0.tar.gz | 39.7 kB | With provenance | Details |
Built distributions (wheels)
| File | Reset | |||
|---|---|---|---|---|
| polars_list_math-0.3.0-cp313-cp313-win_amd64.whl | CPython 3.13 | CPython 3.13 | Windows x86-64 | Details |
| polars_list_math-0.3.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl | CPython 3.13 | CPython 3.13 | Linux glibc 2.17+ x86-64 | Details |
| polars_list_math-0.3.0-cp313-cp313-macosx_11_0_arm64.whl | CPython 3.13 | CPython 3.13 | macOS 11.0+ ARM64 | Details |
| polars_list_math-0.3.0-cp313-cp313-macosx_10_12_x86_64.whl | CPython 3.13 | CPython 3.13 | macOS 10.12+ x86-64 | Details |
| polars_list_math-0.3.0-cp312-cp312-win_amd64.whl | CPython 3.12 | CPython 3.12 | Windows x86-64 | Details |
| polars_list_math-0.3.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl | CPython 3.12 | CPython 3.12 | Linux glibc 2.17+ x86-64 | Details |
| polars_list_math-0.3.0-cp312-cp312-macosx_11_0_arm64.whl | CPython 3.12 | CPython 3.12 | macOS 11.0+ ARM64 | Details |
| polars_list_math-0.3.0-cp312-cp312-macosx_10_12_x86_64.whl | CPython 3.12 | CPython 3.12 | macOS 10.12+ x86-64 | Details |
Total release size: 38.9 MB
Release files / polars_list_math-0.3.0.tar.gz
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