.github/workflows/build.yml

@@ -0,0 +1,66 @@
+name: Example
+
+
+on:
+  push
+
+permissions:
+  contents: read
+
+jobs:
+  test:
+    name: run-tests
+    runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        python-version:
+          - "3.10"
+          - "3.11"
+          - "3.12"
+
+
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Install uv
+        uses: astral-sh/setup-uv@v5
+        with:
+          # Install a specific version of uv.
+          version: "0.6.14"
+          enable-cache: true
+          cache-dependency-glob: "uv.lock"
+          python-version: ${{ matrix.python-version }}
+
+      - name: Install dependencies
+        run: uv sync --all-extras --dev
+
+      - name: Run tests
+        run: uv run poe tests
+
+  publish:
+    name: publish
+    runs-on: ubuntu-latest
+    if: startsWith(github.ref, 'refs/tags/v')
+    needs: [test]
+
+    steps:
+      - uses: actions/checkout@v4
+        with:
+          fetch-depth: 0
+
+      - name: Install uv
+        uses: astral-sh/setup-uv@v5
+        with:
+          # Install a specific version of uv.
+          version: "0.6.14"
+          enable-cache: true
+          cache-dependency-glob: "uv.lock"
+
+      - name: Set up Python
+        run: uv python install
+
+      - name: Build
+        run: uv build
+
+      - name: Publish
+        run: uv publish -t ${{ secrets.PYPI_TOKEN }}

jambo/parser/_type_parser.py

@@ -1,5 +1,8 @@
 from abc import ABC, abstractmethod
-from typing import Generic, Self, TypeVar
+from typing import Generic, TypeVar
+from typing_extensions import Self
+
+from pydantic import Field
 
 T = TypeVar("T")
 
@@ -17,7 +20,7 @@ class GenericTypeParser(ABC, Generic[T]):
     @abstractmethod
     def from_properties(
         name: str, properties: dict[str, any]
-    ) -> tuple[type[T], dict[str, any]]: ...
+    ) -> tuple[type[T], Field]: ...
 
     @classmethod
     def get_impl(cls, type_name: str) -> Self:

jambo/parser/array_type_parser.py

@@ -0,0 +1,32 @@
+from jambo.parser._type_parser import GenericTypeParser
+
+from typing import TypeVar
+
+from jambo.utils.properties_builder.mappings_properties_builder import (
+    mappings_properties_builder,
+)
+
+V = TypeVar("V")
+
+
+class ArrayTypeParser(GenericTypeParser):
+    mapped_type = list
+
+    json_schema_type = "array"
+
+    @classmethod
+    def from_properties(cls, name, properties):
+        _item_type, _item_args = GenericTypeParser.get_impl(
+            properties["items"]["type"]
+        ).from_properties(name, properties["items"])
+
+        _mappings = {
+            "maxItems": "max_length",
+            "minItems": "min_length",
+        }
+
+        wrapper_type = set if properties.get("uniqueItems", False) else list
+
+        return wrapper_type[_item_type], mappings_properties_builder(
+            properties, _mappings
+        )

jambo/parser/boolean_type_parser.py

@@ -1,4 +1,4 @@
-from jambo.types._type_parser import GenericTypeParser
+from jambo.parser._type_parser import GenericTypeParser
 
 
 class BooleanTypeParser(GenericTypeParser):
@@ -8,4 +8,4 @@ class BooleanTypeParser(GenericTypeParser):
 
     @staticmethod
     def from_properties(name, properties):
-        return bool, {}
+        return bool, {}  # The second argument is not used in this case

jambo/parser/float_type_parser.py

@@ -0,0 +1,12 @@
+from jambo.parser._type_parser import GenericTypeParser
+from jambo.utils.properties_builder.numeric_properties_builder import numeric_properties_builder
+
+
+class FloatTypeParser(GenericTypeParser):
+    mapped_type = float
+
+    json_schema_type = "number"
+
+    @staticmethod
+    def from_properties(name, properties):
+        return float, numeric_properties_builder(properties)

jambo/parser/int_type_parser.py

@@ -0,0 +1,12 @@
+from jambo.parser._type_parser import GenericTypeParser
+from jambo.utils.properties_builder.numeric_properties_builder import numeric_properties_builder
+
+
+class IntTypeParser(GenericTypeParser):
+    mapped_type = int
+
+    json_schema_type = "integer"
+
+    @staticmethod
+    def from_properties(name, properties):
+        return int, numeric_properties_builder(properties)

jambo/parser/object_type_parser.py

@@ -1,4 +1,4 @@
-from jambo.types._type_parser import GenericTypeParser
+from jambo.parser._type_parser import GenericTypeParser
 
 
 class ObjectTypeParser(GenericTypeParser):
@@ -10,5 +10,7 @@ class ObjectTypeParser(GenericTypeParser):
     def from_properties(name, properties):
         from jambo.schema_converter import SchemaConverter
 
-        _type = SchemaConverter.build_object(name, properties)
+        return (
-        return _type, {}
+            SchemaConverter.build_object(name, properties),
+            {},  # The second argument is not used in this case
+        )

jambo/parser/string_type_parser.py

@@ -0,0 +1,20 @@
+from jambo.parser._type_parser import GenericTypeParser
+from jambo.utils.properties_builder.mappings_properties_builder import (
+    mappings_properties_builder,
+)
+
+
+class StringTypeParser(GenericTypeParser):
+    mapped_type = str
+
+    json_schema_type = "string"
+
+    @staticmethod
+    def from_properties(name, properties):
+        _mappings = {
+            "maxLength": "max_length",
+            "minLength": "min_length",
+            "pattern": "pattern",
+        }
+
+        return str, mappings_properties_builder(properties, _mappings)

jambo/schema_converter.py

@@ -1,4 +1,4 @@
-from jambo.types import GenericTypeParser
+from jambo.parser import GenericTypeParser
 
 from jsonschema.exceptions import SchemaError
 from jsonschema.protocols import Validator
@@ -7,27 +7,47 @@ from pydantic.fields import Field
 
 from typing import Type
 
+from jambo.types.json_schema_type import JSONSchema
+
 
 class SchemaConverter:
-    @staticmethod
+    """
-    def build(schema):
+    Converts JSON Schema to Pydantic models.
-        try:
-            Validator.check_schema(schema)
-        except SchemaError as e:
-            raise ValueError(f"Invalid JSON Schema: {e}")
 
-        if schema["type"] != "object":
+    This class is responsible for converting JSON Schema definitions into Pydantic models.
-            raise TypeError(
+    It validates the schema and generates the corresponding Pydantic model with appropriate
-                f"Invalid JSON Schema: {schema['type']}. Only 'object' can be converted to Pydantic models."
+    fields and types. The generated model can be used for data validation and serialization.
-            )
+    """
+
+    @staticmethod
+    def build(schema: JSONSchema) -> Type:
+        """
+        Converts a JSON Schema to a Pydantic model.
+        :param schema: The JSON Schema to convert.
+        :return: A Pydantic model class.
+        """
+        if "title" not in schema:
+            raise ValueError("JSON Schema must have a title.")
 
         return SchemaConverter.build_object(schema["title"], schema)
 
     @staticmethod
     def build_object(
         name: str,
-        schema: dict,
+        schema: JSONSchema,
-    ):
+    ) -> Type:
+        """
+        Converts a JSON Schema object to a Pydantic model given a name.
+        :param name:
+        :param schema:
+        :return:
+        """
+
+        try:
+            Validator.check_schema(schema)
+        except SchemaError as e:
+            raise ValueError(f"Invalid JSON Schema: {e}")
+
         if schema["type"] != "object":
             raise TypeError(
                 f"Invalid JSON Schema: {schema['type']}. Only 'object' can be converted to Pydantic models."
@@ -60,7 +80,7 @@ class SchemaConverter:
     @staticmethod
     def _build_field(
         name, properties: dict, required_keys: list[str]
-    ) -> tuple[type, Field]:
+    ) -> tuple[type, dict]:
         _field_type, _field_args = GenericTypeParser.get_impl(
             properties["type"]
         ).from_properties(name, properties)

jambo/types/array_type_parser.py

@@ -1,19 +0,0 @@
-from jambo.types._type_parser import GenericTypeParser
-
-from typing import TypeVar
-
-V = TypeVar("V")
-
-
-class ArrayTypeParser(GenericTypeParser):
-    mapped_type = list
-
-    json_schema_type = "array"
-
-    @classmethod
-    def from_properties(cls, name, properties):
-        _item_type, _item_args = GenericTypeParser.get_impl(
-            properties["items"]["type"]
-        ).from_properties(name, properties["items"])
-
-        return list[_item_type], {}

jambo/types/float_type_parser.py

@@ -1,11 +0,0 @@
-from jambo.types._type_parser import GenericTypeParser
-
-
-class FloatTypeParser(GenericTypeParser):
-    mapped_type = float
-
-    json_schema_type = "number"
-
-    @staticmethod
-    def from_properties(name, properties):
-        return float, {}

jambo/types/int_type_parser.py

@@ -1,11 +0,0 @@
-from jambo.types._type_parser import GenericTypeParser
-
-
-class IntTypeParser(GenericTypeParser):
-    mapped_type = int
-
-    json_schema_type = "integer"
-
-    @staticmethod
-    def from_properties(name, properties):
-        return int, {}

jambo/types/json_schema_type.py

@@ -0,0 +1,80 @@
+from typing import List, Dict, Union, TypedDict, Literal
+
+
+JSONSchemaType = Literal[
+    "string", "number", "integer", "boolean", "object", "array", "null"
+]
+
+
+JSONType = Union[str, int, float, bool, None, Dict[str, "JSONType"], List["JSONType"]]
+
+
+class JSONSchema(TypedDict, total=False):
+    # Basic metadata
+    title: str
+    description: str
+    default: JSONType
+    examples: List[JSONType]
+
+    # Type definitions
+    type: Union[JSONSchemaType, List[JSONSchemaType]]
+
+    # Object-specific keywords
+    properties: Dict[str, "JSONSchema"]
+    required: List[str]
+    additionalProperties: Union[bool, "JSONSchema"]
+    minProperties: int
+    maxProperties: int
+    patternProperties: Dict[str, "JSONSchema"]
+    dependencies: Dict[str, Union[List[str], "JSONSchema"]]
+
+    # Array-specific keywords
+    items: Union["JSONSchema", List["JSONSchema"]]
+    additionalItems: Union[bool, "JSONSchema"]
+    minItems: int
+    maxItems: int
+    uniqueItems: bool
+
+    # String-specific keywords
+    minLength: int
+    maxLength: int
+    pattern: str
+    format: str
+
+    # Number-specific keywords
+    minimum: float
+    maximum: float
+    exclusiveMinimum: float
+    exclusiveMaximum: float
+    multipleOf: float
+
+    # Enum and const
+    enum: List[JSONType]
+    const: JSONType
+
+    # Conditionals
+    if_: "JSONSchema"  # 'if' is a reserved word in Python
+    then: "JSONSchema"
+    else_: "JSONSchema"  # 'else' is also a reserved word
+
+    # Combination keywords
+    allOf: List["JSONSchema"]
+    anyOf: List["JSONSchema"]
+    oneOf: List["JSONSchema"]
+    not_: "JSONSchema"  # 'not' is a reserved word
+
+
+# Fix forward references
+JSONSchema.__annotations__["properties"] = Dict[str, JSONSchema]
+JSONSchema.__annotations__["items"] = Union[JSONSchema, List[JSONSchema]]
+JSONSchema.__annotations__["additionalItems"] = Union[bool, JSONSchema]
+JSONSchema.__annotations__["additionalProperties"] = Union[bool, JSONSchema]
+JSONSchema.__annotations__["patternProperties"] = Dict[str, JSONSchema]
+JSONSchema.__annotations__["dependencies"] = Dict[str, Union[List[str], JSONSchema]]
+JSONSchema.__annotations__["if_"] = JSONSchema
+JSONSchema.__annotations__["then"] = JSONSchema
+JSONSchema.__annotations__["else_"] = JSONSchema
+JSONSchema.__annotations__["allOf"] = List[JSONSchema]
+JSONSchema.__annotations__["anyOf"] = List[JSONSchema]
+JSONSchema.__annotations__["oneOf"] = List[JSONSchema]
+JSONSchema.__annotations__["not_"] = JSONSchema

jambo/types/string_type_parser.py

@@ -1,11 +0,0 @@
-from jambo.types._type_parser import GenericTypeParser
-
-
-class StringTypeParser(GenericTypeParser):
-    mapped_type = str
-
-    json_schema_type = "string"
-
-    @staticmethod
-    def from_properties(name, properties):
-        return str, {}

jambo/utils/properties_builder/mappings_properties_builder.py

@@ -0,0 +1,4 @@
+def mappings_properties_builder(properties, mappings):
+    return {
+        mappings[key]: value for key, value in properties.items() if key in mappings
+    }

jambo/utils/properties_builder/numeric_properties_builder.py

@@ -0,0 +1,15 @@
+from jambo.utils.properties_builder.mappings_properties_builder import (
+    mappings_properties_builder,
+)
+
+
+def numeric_properties_builder(properties):
+    _mappings = {
+        "minimum": "ge",
+        "exclusiveMinimum": "gt",
+        "maximum": "le",
+        "exclusiveMaximum": "lt",
+        "multipleOf": "multiple_of",
+    }
+
+    return mappings_properties_builder(properties, _mappings)

pyproject.toml

@@ -21,7 +21,7 @@ dev = [
 # POE Tasks
 [tool.poe.tasks]
 create-hooks        = "bash .githooks/set-hooks.sh"
-
+tests               = "python -m unittest discover -s tests -v"
 
 # Build System
 [tool.hatch.version]

tests/test_schema_converter.py

@@ -32,7 +32,13 @@ class TestSchemaConverter(TestCase):
             "description": "A person",
             "type": "object",
             "properties": {
-                "name": {"type": "string"},
+                "name": {"type": "string", "maxLength": 4, "minLength": 1},
+                "email": {
+                    "type": "string",
+                    "maxLength": 50,
+                    "minLength": 5,
+                    "pattern": r"^[a-zA-Z0-9_.+-]+@[a-zA-Z0-9-]+\.[a-zA-Z0-9-.]+$",
+                },
             },
             "required": ["name"],
         }
@@ -41,13 +47,29 @@ class TestSchemaConverter(TestCase):
 
         self.assertEqual(model(name="John", age=30).name, "John")
 
+        with self.assertRaises(ValueError):
+            model(name=123, age=30, email="teste@hideyoshi.com")
+
+        with self.assertRaises(ValueError):
+            model(name="John Invalid", age=45, email="teste@hideyoshi.com")
+
+        with self.assertRaises(ValueError):
+            model(name="", age=45, email="teste@hideyoshi.com")
+
+        with self.assertRaises(ValueError):
+            model(name="John", age=45, email="hideyoshi.com")
+
     def test_validation_integer(self):
         schema = {
             "title": "Person",
             "description": "A person",
             "type": "object",
             "properties": {
-                "age": {"type": "integer"},
+                "age": {
+                    "type": "integer",
+                    "minimum": 0,
+                    "maximum": 120,
+                },
             },
             "required": ["age"],
         }
@@ -56,7 +78,11 @@ class TestSchemaConverter(TestCase):
 
         self.assertEqual(model(age=30).age, 30)
 
-        self.assertEqual(model(age="30").age, 30)
+        with self.assertRaises(ValueError):
+            model(age=-1)
+
+        with self.assertRaises(ValueError):
+            model(age=121)
 
     def test_validation_float(self):
         schema = {
@@ -64,7 +90,11 @@ class TestSchemaConverter(TestCase):
             "description": "A person",
             "type": "object",
             "properties": {
-                "age": {"type": "number"},
+                "age": {
+                    "type": "number",
+                    "minimum": 0,
+                    "maximum": 120,
+                },
             },
             "required": ["age"],
         }
@@ -73,7 +103,11 @@ class TestSchemaConverter(TestCase):
 
         self.assertEqual(model(age=30).age, 30.0)
 
-        self.assertEqual(model(age="30").age, 30.0)
+        with self.assertRaises(ValueError):
+            model(age=-1.0)
+
+        with self.assertRaises(ValueError):
+            model(age=121.0)
 
     def test_validation_boolean(self):
         schema = {
@@ -98,14 +132,28 @@ class TestSchemaConverter(TestCase):
             "description": "A person",
             "type": "object",
             "properties": {
-                "friends": {"type": "array", "items": {"type": "string"}},
+                "friends": {
+                    "type": "array",
+                    "items": {"type": "string"},
+                    "minItems": 1,
+                    "maxItems": 2,
+                    "uniqueItems": True,
+                },
             },
             "required": ["friends"],
         }
 
         model = SchemaConverter.build(schema)
 
-        self.assertEqual(model(friends=["John", "Jane"]).friends, ["John", "Jane"])
+        self.assertEqual(
+            model(friends=["John", "Jane", "John"]).friends, {"John", "Jane"}
+        )
+
+        with self.assertRaises(ValueError):
+            model(friends=[])
+
+        with self.assertRaises(ValueError):
+            model(friends=["John", "Jane", "Invalid"])
 
     def test_validation_object(self):
         schema = {

tests/test_type_parser.py

@@ -1,4 +1,4 @@
-from jambo.types import (
+from jambo.parser import (
     ArrayTypeParser,
     FloatTypeParser,
     GenericTypeParser,
@@ -21,21 +21,65 @@ class TestTypeParser(unittest.TestCase):
 
     def test_int_parser(self):
         parser = IntTypeParser()
-        expected_definition = (int, {})
 
-        self.assertEqual(parser.from_properties("placeholder", {}), expected_definition)
+        type_parsing, type_validator = parser.from_properties(
+            "placeholder",
+            {
+                "type": "integer",
+                "minimum": 0,
+                "exclusiveMinimum": 1,
+                "maximum": 10,
+                "exclusiveMaximum": 11,
+                "multipleOf": 2,
+            },
+        )
+
+        self.assertEqual(type_parsing, int)
+        self.assertEqual(type_validator["ge"], 0)
+        self.assertEqual(type_validator["gt"], 1)
+        self.assertEqual(type_validator["le"], 10)
+        self.assertEqual(type_validator["lt"], 11)
+        self.assertEqual(type_validator["multiple_of"], 2)
 
     def test_float_parser(self):
         parser = FloatTypeParser()
-        expected_definition = (float, {})
 
-        self.assertEqual(parser.from_properties("placeholder", {}), expected_definition)
+        type_parsing, type_validator = parser.from_properties(
+            "placeholder",
+            {
+                "type": "number",
+                "minimum": 0,
+                "exclusiveMinimum": 1,
+                "maximum": 10,
+                "exclusiveMaximum": 11,
+                "multipleOf": 2,
+            },
+        )
+
+        self.assertEqual(type_parsing, float)
+        self.assertEqual(type_validator["ge"], 0)
+        self.assertEqual(type_validator["gt"], 1)
+        self.assertEqual(type_validator["le"], 10)
+        self.assertEqual(type_validator["lt"], 11)
+        self.assertEqual(type_validator["multiple_of"], 2)
 
     def test_string_parser(self):
         parser = StringTypeParser()
-        expected_definition = (str, {})
 
-        self.assertEqual(parser.from_properties("placeholder", {}), expected_definition)
+        type_parsing, type_validator = parser.from_properties(
+            "placeholder",
+            {
+                "type": "string",
+                "maxLength": 10,
+                "minLength": 1,
+                "pattern": "[a-zA-Z0-9]",
+            },
+        )
+
+        self.assertEqual(type_parsing, str)
+        self.assertEqual(type_validator["max_length"], 10)
+        self.assertEqual(type_validator["min_length"], 1)
+        self.assertEqual(type_validator["pattern"], "[a-zA-Z0-9]")
 
     def test_object_parser(self):
         parser = ObjectTypeParser()
@@ -69,18 +113,26 @@ class TestTypeParser(unittest.TestCase):
         parser = ArrayTypeParser()
 
         properties = {
+            "type": "array",
             "items": {
                 "type": "object",
                 "properties": {
                     "name": {"type": "string"},
                     "age": {"type": "integer"},
                 },
-            }
+            },
+            "maxItems": 10,
+            "minItems": 1,
+            "uniqueItems": True,
         }
 
-        _type, _args = parser.from_properties("placeholder", properties)
+        type_parsing, type_validator = parser.from_properties("placeholder", properties)
 
-        Model = get_args(_type)[0]
+        self.assertEqual(type_parsing.__origin__, set)
+        self.assertEqual(type_validator["max_length"], 10)
+        self.assertEqual(type_validator["min_length"], 1)
+
+        Model = get_args(type_parsing)[0]
         obj = Model(name="name", age=10)
 
         self.assertEqual(obj.name, "name")