chore: more misc cleanup

src/patito/__init__.py

@@ -4,12 +4,14 @@
 from patito import exceptions, sql
 from patito.polars import DataFrame, LazyFrame
 from patito.pydantic import Field, Model
+from patito.exceptions import DataFrameValidationError
 
 _CACHING_AVAILABLE = False
 _DUCKDB_AVAILABLE = False
 field = col("_")
 __all__ = [
     "DataFrame",
+    "DataFrameValidationError",
     "Expr",
     "Field",
     "LazyFrame",

src/patito/exceptions.py

@@ -137,9 +137,6 @@ def errors(self) -> List["ErrorDict"]:
             self._error_cache = list(flatten_errors(self.raw_errors))
         return self._error_cache
 
-    # def json(self, *, indent: Union[None, int, str] = 2) -> str:
-    #     return json.dumps(self.errors(), indent=indent, default=pydantic_encoder)
-
     def __str__(self) -> str:
         errors = self.errors()
         no_errors = len(errors)

tests/test_dummy_data.py

@@ -86,11 +86,11 @@ def test_generation_of_unique_data():
 
     class UniqueModel(pt.Model):
         bool_column: bool
-        string_column: str = pt.Field(json_schema_extra={"unique": True})
-        int_column: int = pt.Field(json_schema_extra={"unique": True})
-        float_column: int = pt.Field(json_schema_extra={"unique": True})
-        date_column: date = pt.Field(json_schema_extra={"unique": True})
-        datetime_column: datetime = pt.Field(json_schema_extra={"unique": True})
+        string_column: str = pt.Field(unique=True)
+        int_column: int = pt.Field(unique=True)
+        float_column: int = pt.Field(unique=True)
+        date_column: date = pt.Field(unique=True)
+        datetime_column: datetime = pt.Field(unique=True)
 
     example_df = UniqueModel.examples({"bool_column": [True, False]})
     for column in UniqueModel.columns:

tests/test_model.py

@@ -388,7 +388,7 @@ class MyModel(pt.Model):
 
     ExpandedModel = MyModel.with_fields(
         b=(int, ...),
-        c=(int, None),  # TODO should this be nullable if not specified as optional?
+        c=(int, None),
         d=(int, pt.Field(gt=10)),
         e=(Optional[int], None),
     )

tests/test_polars.py

@@ -159,8 +159,8 @@ def test_correct_columns_and_dtype_on_read(tmp_path):
     """A model DataFrame should aid CSV reading with column names and dtypes."""
 
     class Foo(pt.Model):
-        a: str = pt.Field(json_schema_extra={"derived_from": "column_1"})
-        b: int = pt.Field(json_schema_extra={"derived_from": "column_2"})
+        a: str = pt.Field(derived_from="column_1")
+        b: int = pt.Field(derived_from="column_2")
 
     csv_path = tmp_path / "foo.csv"
     csv_path.write_text("1,2")
@@ -189,9 +189,7 @@ class Foo(pt.Model):
     assert unspecified_column_df.dtypes == [pl.Utf8, pl.Int64, pl.Float64]
 
     class DerivedModel(pt.Model):
-        cents: int = pt.Field(
-            json_schema_extra={"derived_from": 100 * pl.col("dollars")}
-        )
+        cents: int = pt.Field(derived_from=100 * pl.col("dollars"))
 
     csv_path.write_text("month,dollars\n1,2.99")
     derived_df = DerivedModel.DataFrame.read_csv(csv_path)

tests/test_validators.py

@@ -2,14 +2,13 @@
 import enum
 import sys
 from datetime import date, datetime
-from typing import List, Optional, Union
+from typing import List, Optional, Union, Literal
 
 import polars as pl
 import pytest
-from typing_extensions import Literal
 
 import patito as pt
-from patito.exceptions import DataFrameValidationError
+from patito import DataFrameValidationError
 from patito.validators import _dewrap_optional, _is_optional, validate