Feature fix polars are unique (#460)

* Added fix to are unique in polars latest version

* Added new versions

---------

Co-authored-by: Herminio Vazquez <hvazquez-cano@copado.com>

Author: canimus

.gitignore

@@ -10,6 +10,7 @@
 # Cache
 **__pycache__/
 .DS_Store
+uv.lock
 
 # Security
 *.crt

README.md

@@ -35,8 +35,8 @@ Provider | API | Versions
 ![databricks](https://github.com/canimus/cuallee/blob/fbef98f5340279fc726b369a7ce879fd67ea1d1f/logos/databricks.svg?raw=true "PySpark DataFrame API")| `pyspark` & `spark-connect` |`3.5.x`, `3.4.0`, `3.3.x`, `3.2.x`
 ![bigquery](https://github.com/canimus/cuallee/blob/fbef98f5340279fc726b369a7ce879fd67ea1d1f/logos/bigquery.png?raw=true "BigQuery Client API")| `bigquery` | `3.4.1`
 ![pandas](https://github.com/canimus/cuallee/blob/fbef98f5340279fc726b369a7ce879fd67ea1d1f/logos/pandas.svg?raw=true "Pandas DataFrame API")| `pandas`| `2.0.2`, `1.5.x`, `1.4.x`
-![duckdb](https://github.com/canimus/cuallee/blob/fbef98f5340279fc726b369a7ce879fd67ea1d1f/logos/duckdb.png?raw=true "DuckDB API")|`duckdb` | `1.0.0`, ~~`0.10.2`~~,~~`0.9.2`~~,~~`0.8.0`~~
-![polars](https://github.com/canimus/cuallee/blob/fbef98f5340279fc726b369a7ce879fd67ea1d1f/logos/polars.svg?raw=true "Polars API")|`polars`| `1.0.0`, ~~`0.19.6`~~
+![duckdb](https://github.com/canimus/cuallee/blob/fbef98f5340279fc726b369a7ce879fd67ea1d1f/logos/duckdb.png?raw=true "DuckDB API")|`duckdb` | `1.4.0`,~~`1.0.0`~~, ~~`0.10.2`~~,~~`0.9.2`~~,~~`0.8.0`~~
+![polars](https://github.com/canimus/cuallee/blob/fbef98f5340279fc726b369a7ce879fd67ea1d1f/logos/polars.svg?raw=true "Polars API")|`polars`| `1.34.0`, ~~`1.0.0`~~, ~~`0.19.6`~~
 ![daft](https://github.com/canimus/cuallee/blob/fbef98f5340279fc726b369a7ce879fd67ea1d1f/logos/daft.png?raw=true "Daft API")|`daft`| `0.2.24`, ~~`0.2.19`~~
 
  <sub>Logos are trademarks of their own brands.</sub>

cuallee/polars_validation.py

@@ -75,10 +75,7 @@ def is_unique(self, rule: Rule, dataframe: pl.DataFrame) -> Union[bool, int]:
     def are_unique(self, rule: Rule, dataframe: pl.DataFrame) -> Union[bool, int]:
         """Validate absence of duplicate in group of columns"""
         return Compute._result(
-            dataframe.select(
-                [pl.col(c).is_unique().cast(pl.Int8).sum() for c in rule.column]
-            ).sum_horizontal()
-            / len(rule.column)
+            dataframe.select(pl.struct(*rule.column).is_unique().cast(pl.Int8)).sum()
         )
 
     def is_greater_than(self, rule: Rule, dataframe: pl.DataFrame) -> Union[bool, int]:

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "cuallee"
-version = "0.15.2"
+version = "0.15.3"
 
 authors = [
   { name="Herminio Vazquez", email="canimus@gmail.com"},