Merge branch 'main' into dependabot/pip/ruff-0.4.8

.pre-commit-config.yaml

@@ -1,6 +1,6 @@
 repos:
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: 'v0.4.7'
+    rev: 'v0.4.8'
     hooks:
       - id: ruff
         files: "^datamodel_code_generator|^tests"

README.md

@@ -16,9 +16,6 @@ and [msgspec.Struct](https://github.com/jcrist/msgspec) from an openapi file and
 ## Help
 See [documentation](https://koxudaxi.github.io/datamodel-code-generator) for more details.
 
-## Sponsors
-[![JetBrains](https://avatars.githubusercontent.com/u/60931315?s=200&v=4)](https://github.com/JetBrainsOfficial)
-
 ## Quick Installation
 
 To install `datamodel-code-generator`:
@@ -236,6 +233,45 @@ class Apis(BaseModel):
 ```
 </details>
 
+## Supported input types
+-  OpenAPI 3 (YAML/JSON, [OpenAPI Data Type](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#data-types));
+-  JSON Schema ([JSON Schema Core](http://json-schema.org/draft/2019-09/json-schema-validation.html)/[JSON Schema Validation](http://json-schema.org/draft/2019-09/json-schema-validation.html));
+-  JSON/YAML/CSV Data (it will be converted to JSON Schema);
+-  Python dictionary (it will be converted to JSON Schema);
+-  GraphQL schema ([GraphQL Schemas and Types](https://graphql.org/learn/schema/));
+
+## Supported output types
+- [pydantic](https://docs.pydantic.dev/1.10/).BaseModel;
+- [pydantic_v2](https://docs.pydantic.dev/2.0/).BaseModel;
+- [dataclasses.dataclass](https://docs.python.org/3/library/dataclasses.html);
+- [typing.TypedDict](https://docs.python.org/3/library/typing.html#typing.TypedDict);
+- [msgspec.Struct](https://github.com/jcrist/msgspec);
+- Custom type from your [jinja2](https://jinja.palletsprojects.com/en/3.1.x/) template;
+
+## Sponsors
+<table>
+  <tr>
+    <td valign="top" align="center">
+    <a href="https://github.com/JetBrainsOfficial">
+      <img src="https://avatars.githubusercontent.com/u/60931315?s=100&v=4" alt="JetBrains Logo" style="width: 100px;">
+      <p>JetBrains</p>
+    </a>
+    </td>
+  <td valign="top" align="center">
+    <a href="https://github.com/astral-sh">
+      <img src="https://avatars.githubusercontent.com/u/115962839?s=200&v=4" alt="Astral Logo" style="width: 100px;">
+      <p>Astral</p>
+    </a>
+  </td>
+  <td valign="top" align="center">
+    <a href="https://github.com/DataDog">
+      <img src="https://avatars.githubusercontent.com/u/365230?s=200&v=4" alt="Datadog, Inc. Logo" style="width: 100px;">
+      <p>Datadog, Inc.</p>
+    </a>
+  </td>
+  </tr>
+</table>
+
 ## Projects that use datamodel-code-generator
  
 These OSS projects use datamodel-code-generator to generate many models. 
@@ -267,21 +303,6 @@ See the following linked projects for real world examples and inspiration.
 - [SeldonIO/MLServer](https://github.com/SeldonIO/MLServer)
   - *[generate-types.sh](https://github.com/SeldonIO/MLServer/blob/master/hack/generate-types.sh)*
 
-## Supported input types
--  OpenAPI 3 (YAML/JSON, [OpenAPI Data Type](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#data-types));
--  JSON Schema ([JSON Schema Core](http://json-schema.org/draft/2019-09/json-schema-validation.html)/[JSON Schema Validation](http://json-schema.org/draft/2019-09/json-schema-validation.html));
--  JSON/YAML/CSV Data (it will be converted to JSON Schema);
--  Python dictionary (it will be converted to JSON Schema);
--  GraphQL schema ([GraphQL Schemas and Types](https://graphql.org/learn/schema/));
-
-## Supported output types
-- [pydantic](https://docs.pydantic.dev/1.10/).BaseModel;
-- [pydantic_v2](https://docs.pydantic.dev/2.0/).BaseModel;
-- [dataclasses.dataclass](https://docs.python.org/3/library/dataclasses.html);
-- [typing.TypedDict](https://docs.python.org/3/library/typing.html#typing.TypedDict);
-- [msgspec.Struct](https://github.com/jcrist/msgspec);
-- Custom type from your [jinja2](https://jinja.palletsprojects.com/en/3.1.x/) template;
-
 ## Installation
 
 To install `datamodel-code-generator`:
@@ -319,6 +340,7 @@ This method needs the [http extra option](#http-extra-option)
 ## All Command Options
 
 The `datamodel-codegen` command:
+
 ```bash
 usage:
   datamodel-codegen [options]

datamodel_code_generator/parser/base.py

@@ -700,6 +700,7 @@ def __change_from_import(
                     from_, import_ = full_path = relative(
                         model.module_name, data_type.full_name
                     )
+                    import_ = import_.replace('-', '_')
 
                 alias = scoped_model_resolver.add(full_path, import_).name
 
@@ -778,8 +779,18 @@ def __apply_discriminator_type(
                                 discriminator_model.path.split('#/')[-1]
                                 != path.split('#/')[-1]
                             ):
-                                # TODO: support external reference
-                                continue
+                                if (
+                                    path.startswith('#/')
+                                    or discriminator_model.path[:-1]
+                                    != path.split('/')[-1]
+                                ):
+                                    t_path = path[str(path).find('/') + 1 :]
+                                    t_disc = discriminator_model.path[
+                                        : str(discriminator_model.path).find('#')
+                                    ].lstrip('../')
+                                    t_disc_2 = '/'.join(t_disc.split('/')[1:])
+                                    if t_path != t_disc and t_path != t_disc_2:
+                                        continue
                             type_names.append(name)
                     else:
                         type_names = [discriminator_model.path.split('/')[-1]]
@@ -1250,6 +1261,7 @@ class Processed(NamedTuple):
                     init = True
                 else:
                     module = (*module[:-1], f'{module[-1]}.py')
+                    module = tuple(part.replace('-', '_') for part in module)
             else:
                 module = ('__init__.py',)
 

docs/index.md

@@ -12,9 +12,6 @@ This code generator creates [pydantic v1 and v2](https://docs.pydantic.dev/) mod
 [![Pydantic v1](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/pydantic/pydantic/main/docs/badge/v1.json)](https://pydantic.dev)
 [![Pydantic v2](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/pydantic/pydantic/main/docs/badge/v2.json)](https://pydantic.dev)
 
-## Sponsors
-[![JetBrains](https://avatars.githubusercontent.com/u/60931315?s=200&v=4)](https://github.com/JetBrainsOfficial)
-
 ## Quick Installation
 
 To install `datamodel-code-generator`:
@@ -232,6 +229,44 @@ class Apis(BaseModel):
 ```
 </details>
 
+## Supported input types
+-  OpenAPI 3 (YAML/JSON, [OpenAPI Data Type](https://github.com/OAI/OpenAPI-Specification/blob/master/versions/3.0.2.md#data-types));
+-  JSON Schema ([JSON Schema Core](http://json-schema.org/draft/2019-09/json-schema-validation.html)/[JSON Schema Validation](http://json-schema.org/draft/2019-09/json-schema-validation.html));
+-  JSON/YAML/CSV Data (it will be converted to JSON Schema);
+-  Python dictionary (it will be converted to JSON Schema);
+-  GraphQL schema ([GraphQL Schemas and Types](https://graphql.org/learn/schema/));
+
+## Supported output types
+- [pydantic](https://docs.pydantic.dev/1.10/).BaseModel;
+- [pydantic_v2](https://docs.pydantic.dev/2.0/).BaseModel;
+- [dataclasses.dataclass](https://docs.python.org/3/library/dataclasses.html);
+- [typing.TypedDict](https://docs.python.org/3/library/typing.html#typing.TypedDict);
+- [msgspec.Struct](https://github.com/jcrist/msgspec);
+- Custom type from your [jinja2](https://jinja.palletsprojects.com/en/3.1.x) template;
+
+## Sponsors
+<table>
+  <tr>
+    <td valign="top" align="center">
+    <a href="https://github.com/JetBrainsOfficial">
+      <img src="https://avatars.githubusercontent.com/u/60931315?s=100&v=4" alt="JetBrains Logo" style="width: 100px;">
+      <p>JetBrains</p>
+    </a>
+    </td>
+  <td valign="top" align="center">
+    <a href="https://github.com/astral-sh">
+      <img src="https://avatars.githubusercontent.com/u/115962839?s=200&v=4" alt="Astral Logo" style="width: 100px;">
+      <p>Astral</p>
+    </a>
+  </td>
+  <td valign="top" align="center">
+    <a href="https://github.com/DataDog">
+      <img src="https://avatars.githubusercontent.com/u/365230?s=200&v=4" alt="Datadog, Inc. Logo" style="width: 100px;">
+      <p>Datadog, Inc.</p>
+    </a>
+  </td>
+  </tr>
+</table>
 ## Projects that use datamodel-code-generator
 
 These OSS projects use datamodel-code-generator to generate many models. 
@@ -263,21 +298,6 @@ See the following linked projects for real world examples and inspiration.
 - [SeldonIO/MLServer](https://github.com/SeldonIO/MLServer)
     - *[generate-types.sh](https://github.com/SeldonIO/MLServer/blob/master/hack/generate-types.sh)*
 
-## Supported input types
--  OpenAPI 3 (YAML/JSON, [OpenAPI Data Type](https://github.com/OAI/OpenAPI-Specification/blob/master/versions/3.0.2.md#data-types));
--  JSON Schema ([JSON Schema Core](http://json-schema.org/draft/2019-09/json-schema-validation.html)/[JSON Schema Validation](http://json-schema.org/draft/2019-09/json-schema-validation.html));
--  JSON/YAML/CSV Data (it will be converted to JSON Schema);
--  Python dictionary (it will be converted to JSON Schema);
--  GraphQL schema ([GraphQL Schemas and Types](https://graphql.org/learn/schema/));
-
-## Supported output types
-- [pydantic](https://docs.pydantic.dev/1.10/).BaseModel;
-- [pydantic_v2](https://docs.pydantic.dev/2.0/).BaseModel;
-- [dataclasses.dataclass](https://docs.python.org/3/library/dataclasses.html);
-- [typing.TypedDict](https://docs.python.org/3/library/typing.html#typing.TypedDict);
-- [msgspec.Struct](https://github.com/jcrist/msgspec);
-- Custom type from your [jinja2](https://jinja.palletsprojects.com/en/3.1.x) template;
-
 ## Installation
 
 To install `datamodel-code-generator`:

tests/data/expected/main/discriminator_with_external_reference/output.py

@@ -0,0 +1,37 @@
+# generated by datamodel-codegen:
+#   filename:  schema.json
+#   timestamp: 2019-07-26T00:00:00+00:00
+
+from __future__ import annotations
+
+from typing import Optional, Union
+
+from pydantic import BaseModel, Field
+from typing_extensions import Literal
+
+
+class Type1(BaseModel):
+    type_: Literal['a'] = Field('a', title='Type ')
+
+
+class Type2(BaseModel):
+    type_: Literal['b'] = Field('b', title='Type ')
+    ref_type: Optional[Type1] = Field(None, description='A referenced type.')
+
+
+class Type4(BaseModel):
+    type_: Literal['d'] = Field('d', title='Type ')
+
+
+class Type5(BaseModel):
+    type_: Literal['e'] = Field('e', title='Type ')
+
+
+class Type3(BaseModel):
+    type_: Literal['c'] = Field('c', title='Type ')
+
+
+class Response(BaseModel):
+    inner: Union[Type1, Type2, Type3, Type4, Type5] = Field(
+        ..., discriminator='type_', title='Inner'
+    )

tests/data/expected/main/discriminator_with_external_references_folder/__init__.py

@@ -0,0 +1,3 @@
+# generated by datamodel-codegen:
+#   filename:  discriminator_with_external_reference
+#   timestamp: 2019-07-26T00:00:00+00:00

tests/data/expected/main/discriminator_with_external_references_folder/inner_folder/__init__.py

@@ -0,0 +1,3 @@
+# generated by datamodel-codegen:
+#   filename:  discriminator_with_external_reference
+#   timestamp: 2019-07-26T00:00:00+00:00

tests/data/expected/main/discriminator_with_external_references_folder/inner_folder/artificial_folder/__init__.py

@@ -0,0 +1,3 @@
+# generated by datamodel-codegen:
+#   filename:  discriminator_with_external_reference
+#   timestamp: 2019-07-26T00:00:00+00:00

tests/data/expected/main/discriminator_with_external_references_folder/inner_folder/artificial_folder/type_1.py

@@ -0,0 +1,12 @@
+# generated by datamodel-codegen:
+#   filename:  inner_folder/artificial_folder/type-1.json
+#   timestamp: 2019-07-26T00:00:00+00:00
+
+from __future__ import annotations
+
+from pydantic import BaseModel, Field
+from typing_extensions import Literal
+
+
+class Type1(BaseModel):
+    type_: Literal['a'] = Field(..., const=True, title='Type ')

tests/data/expected/main/discriminator_with_external_references_folder/inner_folder/schema.py

@@ -0,0 +1,25 @@
+# generated by datamodel-codegen:
+#   filename:  inner_folder/schema.json
+#   timestamp: 2019-07-26T00:00:00+00:00
+
+from __future__ import annotations
+
+from typing import Union
+
+from pydantic import BaseModel, Field
+from typing_extensions import Literal
+
+from .. import type_4
+from ..subfolder import type_5
+from . import type_2
+from .artificial_folder import type_1
+
+
+class Type3(BaseModel):
+    type_: Literal['c'] = Field(..., const=True, title='Type ')
+
+
+class Response(BaseModel):
+    inner: Union[type_1.Type1, type_2.Type2, Type3, type_4.Type4, type_5.Type5] = Field(
+        ..., discriminator='type_', title='Inner'
+    )

tests/data/expected/main/discriminator_with_external_references_folder/inner_folder/type_2.py

@@ -0,0 +1,16 @@
+# generated by datamodel-codegen:
+#   filename:  inner_folder/type-2.json
+#   timestamp: 2019-07-26T00:00:00+00:00
+
+from __future__ import annotations
+
+from typing import Optional
+
+from pydantic import BaseModel, Field
+
+from .artificial_folder import type_1
+
+
+class Type2(BaseModel):
+    type_: Literal['b'] = Field(..., const=True, title='Type ')
+    ref_type: Optional[type_1.Type1] = Field(None, description='A referenced type.')

tests/data/expected/main/discriminator_with_external_references_folder/subfolder/__init__.py

@@ -0,0 +1,3 @@
+# generated by datamodel-codegen:
+#   filename:  discriminator_with_external_reference
+#   timestamp: 2019-07-26T00:00:00+00:00

tests/data/expected/main/discriminator_with_external_references_folder/subfolder/type_5.py

@@ -0,0 +1,11 @@
+# generated by datamodel-codegen:
+#   filename:  subfolder/type-5.json
+#   timestamp: 2019-07-26T00:00:00+00:00
+
+from __future__ import annotations
+
+from pydantic import BaseModel, Field
+
+
+class Type5(BaseModel):
+    type_: Literal['e'] = Field(..., const=True, title='Type ')

tests/data/expected/main/discriminator_with_external_references_folder/type_4.py

@@ -0,0 +1,11 @@
+# generated by datamodel-codegen:
+#   filename:  type-4.json
+#   timestamp: 2019-07-26T00:00:00+00:00
+
+from __future__ import annotations
+
+from pydantic import BaseModel, Field
+
+
+class Type4(BaseModel):
+    type_: Literal['d'] = Field(..., const=True, title='Type ')

tests/data/jsonschema/discriminator_with_external_reference/inner_folder/artificial_folder/type-1.json

@@ -0,0 +1,11 @@
+{
+  "properties": {
+    "type_": {
+      "const": "a",
+      "default": "a",
+      "title": "Type "
+    }
+  },
+  "title": "Type1",
+  "type": "object"
+}