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Pydantic Models Py by gabrielmoreira

Name: Pydantic Models Py
Rating: 4.2 (5 reviews)
Author: gabrielmoreira

Pydantic Models Py

Create Pydantic models following the multi-model pattern with Base, Create, Update, Response, and InDB variants. Use when defining API request/response schemas, database models, or data validation in Python applications using Pydantic v2.

gabrielmoreira Updated Sep 9, 2026 17 repo stars

File contents

Pydantic Models

Create Pydantic models following the multi-model pattern for clean API contracts.

Quick Start

Copy the template from assets/template.py and replace placeholders:

{{ResourceName}} → PascalCase name (e.g., Project)
{{resource_name}} → snake_case name (e.g., project)

Multi-Model Pattern

Model	Purpose
`Base`	Common fields shared across models
`Create`	Request body for creation (required fields)
`Update`	Request body for updates (all optional)
`Response`	API response with all fields
`InDB`	Database document with `doc_type`

camelCase Aliases

from datetime import datetime

from pydantic import BaseModel, ConfigDict, Field

class MyModel(BaseModel):
    model_config = ConfigDict(populate_by_name=True)

    workspace_id: str = Field(..., alias="workspaceId")
    created_at: datetime = Field(..., alias="createdAt")

Optional Update Fields

class MyUpdate(BaseModel):
    model_config = ConfigDict(populate_by_name=True)

    name: Optional[str] = Field(None, min_length=1)
    description: Optional[str] = None

Database Document

class MyInDB(MyResponse):
    doc_type: str = "my_resource"

Integration Steps

Create models in src/backend/app/models/
Export from src/backend/app/models/__init__.py
Add corresponding TypeScript types

Reference Files

File	Contents
references/capabilities.md	Additional non-hero capabilities, operation-group coverage, and production checklists.

---name: pydantic-models-pydescription: Create Pydantic models following the multi-model pattern with Base, Create, Update, Response, and InDB variants. Use when defining API request/response schemas, database models, or data validation in Python applications using Pydantic v2.license: MIT--- # Pydantic Models Create Pydantic models following the multi-model pattern for clean API contracts. ## Quick Start Copy the template from [assets/template.py](assets/template.py) and replace placeholders: - `{{ResourceName}}` → PascalCase name (e.g., `Project`) - `{{resource_name}}` → snake_case name (e.g., `project`) ## Multi-Model Pattern | Model | Purpose | |-------|---------| | `Base` | Common fields shared across models | | `Create` | Request body for creation (required fields) | | `Update` | Request body for updates (all optional) | | `Response` | API response with all fields | | `InDB` | Database document with `doc_type` | ## camelCase Aliases ```python from datetime import datetime from pydantic import BaseModel, ConfigDict, Field class MyModel(BaseModel): model_config = ConfigDict(populate_by_name=True) workspace_id: str = Field(..., alias="workspaceId") created_at: datetime = Field(..., alias="createdAt") ``` ## Optional Update Fields ```python class MyUpdate(BaseModel): model_config = ConfigDict(populate_by_name=True) name: Optional[str] = Field(None, min_length=1) description: Optional[str] = None ``` ## Database Document ```python class MyInDB(MyResponse): doc_type: str = "my_resource" ``` ## Integration Steps 1. Create models in `src/backend/app/models/` 2. Export from `src/backend/app/models/__init__.py` 3. Add corresponding TypeScript types ## Reference Files | File | Contents | |------|----------| | [references/capabilities.md](references/capabilities.md) | Additional non-hero capabilities, operation-group coverage, and production checklists. |

Frequently asked questions