Add table schema validator

.github/workflows/ci_template.yml

@@ -9,7 +9,7 @@ on:
         type: string
       python-version:
         description: 'Python version'
-        default: '["3.9", "3.12"]'
+        default: '["3.10", "3.13"]'
         type: string
 
 jobs:
@@ -38,6 +38,6 @@ jobs:
       run: poetry run pytest
 
     - name: Upload coverage to Codecov
-      if: success() && (matrix.os == 'ubuntu-latest' && matrix.python-version == 3.9)
+      if: success() && (matrix.os == 'ubuntu-latest' && matrix.python-version == 3.10)
       uses: codecov/codecov-action@v5
 

.github/workflows/publish.yml

@@ -12,7 +12,7 @@ jobs:
     uses: ./.github/workflows/ci_template.yml
     with:
       os: '["ubuntu-latest", "windows-latest", "macos-latest"]'
-      python-version: '["3.9", "3.10", "3.11", "3.12"]'
+      python-version: '["3.10", "3.11", "3.12", "3.13"]'
 
   build-wheel:
     needs: test
@@ -37,7 +37,7 @@ jobs:
 
     - uses: actions/setup-python@v5
       with:
-        python-version: 3.9
+        python-version: 3.10
 
     - name: Install Poetry
       uses: abatilo/[email protected]

.pre-commit-config.yaml

@@ -16,7 +16,7 @@ repos:
     rev: "v1.13.0"
     hooks:
       - id: mypy
-        additional_dependencies: [types-PyYAML]
+        additional_dependencies: [types-PyYAML, pydantic]
   - repo: https://github.com/igorshubovych/markdownlint-cli
     rev: v0.43.0
     hooks:

csvy/validators/__init__.py

@@ -0,0 +1,65 @@
+"""Validators for the CSVY format."""
+
+from collections.abc import Mapping
+from typing import Any
+
+from pydantic import BaseModel
+
+from .csv_dialect import CSVDialectValidator  # noqa: F401
+from .registry import VALIDATORS_REGISTRY, register_validator  # noqa: F401
+from .table_schema import SchemaValidator  # noqa: F401
+
+
+def validate_header(header: dict[str, Any]) -> dict[str, Any]:
+    """Run the validators on the header.
+
+    This function runs the validators on the header. It uses the keys of the header to
+    find the validators in the registry and runs them on the corresponding values. As
+    a result, some values in the header may be replaced by the validated values in the
+    form of Pydantic models.
+
+    If the header is an already validated header, the Pydantic models within, if any,
+    are dumped to dictionaries and re-validated, again. This accounts for the case where
+    attributes of the Pydantic models are changed to invalid values.
+
+    Args:
+        header: The header of the CSVY file.
+
+    Returns:
+        The validated header.
+
+    """
+    validated_header: dict[str, Any] = {}
+    for key, value in header.items():
+        value_ = value.model_dump() if isinstance(value, BaseModel) else value
+        if key in VALIDATORS_REGISTRY:
+            if not isinstance(value_, Mapping):
+                raise TypeError(
+                    f"Value for '{key}' must be a mapping, not a '{type(value_)}'."
+                )
+            validator = VALIDATORS_REGISTRY[key]
+            validated_header[key] = validator(**value_)
+        else:
+            validated_header[key] = value_
+    return validated_header
+
+
+def header_to_dict(header: dict[str, Any]) -> dict[str, Any]:
+    """Transform the header into a serializable dictionary.
+
+    Transforms the header with validators to a header with dictionaries that can be
+    saved as yaml.
+
+    Args:
+        header: Dictionary to be saved as the header of the CSVY file.
+
+    Returns:
+        The validated header, as a serializable dictionary.
+
+    """
+    validated_header = {}
+    for key, value in header.items():
+        validated_header[key] = (
+            value.model_dump() if isinstance(value, BaseModel) else value
+        )
+    return validated_header

csvy/validators.py → csvy/validators/csv_dialect.py

@@ -1,99 +1,13 @@
-"""Module that contains validators for the CSVY file format."""
+"""CSV Dialect-related validation."""
+
+from __future__ import annotations
 
 import csv
-from collections.abc import Mapping
-from typing import Any, Callable, Optional, TypeVar
+from typing import TypeVar
 
 from pydantic import BaseModel, Field
 
-VALIDATORS_REGISTRY: dict[str, type[BaseModel]] = {}
-"""Registry of validators to run on the header."""
-
-
-def register_validator(
-    name: str, overwrite: bool = False
-) -> Callable[[type[BaseModel]], type[BaseModel]]:
-    """Register a validator in the registry.
-
-    This function is a decorator that registers a validator in the registry. The name
-    of the validator is used as the key in the registry.
-
-    Args:
-        name: The name of the validator.
-        overwrite: Whether to overwrite the validator if it already exists.
-
-    Returns:
-        The decorator function that registers the validator.
-
-    """
-
-    def decorator(cls: type[BaseModel]) -> type[BaseModel]:
-        if not issubclass(cls, BaseModel):
-            raise TypeError("Validators must be subclasses of pydantic.BaseModel.")
-
-        if name in VALIDATORS_REGISTRY and not overwrite:
-            raise ValueError(f"Validator with name '{name}' already exists.")
-
-        VALIDATORS_REGISTRY[name] = cls
-        return cls
-
-    return decorator
-
-
-def validate_header(header: dict[str, Any]) -> dict[str, Any]:
-    """Run the validators on the header.
-
-    This function runs the validators on the header. It uses the keys of the header to
-    find the validators in the registry and runs them on the corresponding values. As
-    a result, some values in the header may be replaced by the validated values in the
-    form of Pydantic models.
-
-    If the header is an already validated header, the Pydantic models within, if any,
-    are dumped to dictionaries and re-validated, again. This accounts for the case where
-    attributes of the Pydantic models are changed to invalid values.
-
-    Args:
-        header: The header of the CSVY file.
-
-    Returns:
-        The validated header.
-
-    """
-    validated_header: dict[str, Any] = {}
-    for key, value in header.items():
-        value_ = value.model_dump() if isinstance(value, BaseModel) else value
-        if key in VALIDATORS_REGISTRY:
-            if not isinstance(value_, Mapping):
-                raise TypeError(
-                    f"Value for '{key}' must be a mapping, not a '{type(value_)}'."
-                )
-            validator = VALIDATORS_REGISTRY[key]
-            validated_header[key] = validator(**value_)
-        else:
-            validated_header[key] = value_
-    return validated_header
-
-
-def header_to_dict(header: dict[str, Any]) -> dict[str, Any]:
-    """Transform the header into a serializable dictionary.
-
-    Transforms the header with validators to a header with dictionaries that can be
-    saved as yaml.
-
-    Args:
-        header: Dictionary to be saved as the header of the CSVY file.
-
-    Returns:
-        The validated header, as a serializable dictionary.
-
-    """
-    validated_header = {}
-    for key, value in header.items():
-        validated_header[key] = (
-            value.model_dump() if isinstance(value, BaseModel) else value
-        )
-    return validated_header
-
+from .registry import register_validator
 
 # Create a generic variable that can be 'Parent', or any subclass.
 T = TypeVar("T", bound="CSVDialectValidator")
@@ -127,7 +41,7 @@ class CSVDialectValidator(BaseModel):
 
     delimiter: str = Field(default=",")
     doublequote: bool = Field(default=True)
-    escapechar: Optional[str] = Field(default=None)
+    escapechar: str | None = Field(default=None)
     lineterminator: str = Field(default="\r\n")
     quotechar: str = Field(default='"')
     skipinitialspace: bool = Field(default=False)

csvy/validators/registry.py

@@ -0,0 +1,38 @@
+"""Registry of validators to run on the header."""
+
+from collections.abc import Callable
+
+from pydantic import BaseModel
+
+VALIDATORS_REGISTRY: dict[str, type[BaseModel]] = {}
+"""Registry of validators to run on the header."""
+
+
+def register_validator(
+    name: str, overwrite: bool = False
+) -> Callable[[type[BaseModel]], type[BaseModel]]:
+    """Register a validator in the registry.
+
+    This function is a decorator that registers a validator in the registry. The name
+    of the validator is used as the key in the registry.
+
+    Args:
+        name: The name of the validator.
+        overwrite: Whether to overwrite the validator if it already exists.
+
+    Returns:
+        The decorator function that registers the validator.
+
+    """
+
+    def decorator(cls: type[BaseModel]) -> type[BaseModel]:
+        if not issubclass(cls, BaseModel):
+            raise TypeError("Validators must be subclasses of pydantic.BaseModel.")
+
+        if name in VALIDATORS_REGISTRY and not overwrite:
+            raise ValueError(f"Validator with name '{name}' already exists.")
+
+        VALIDATORS_REGISTRY[name] = cls
+        return cls
+
+    return decorator