gql-pygen 0.2.0

GraphQL to Python code generator - generates typed Pydantic models and sync/async clients

gql-pygen

GraphQL to Python Code Generator — Generate typed Pydantic models and async clients from GraphQL schemas.

Features

• 🎯 Typed Pydantic Models — All GraphQL types, inputs, and enums become Pydantic models with full IDE autocomplete
• 🔗 Nested Client — Access operations via intuitive paths like client.policy.firewall.add_rule(...)
• ⚡ Async & Sync Support — Generate async clients (default) or sync clients with --sync flag
• ✅ Response Parsing — Responses are automatically validated and converted to typed models
• 🎛️ Field Selection — Request ALL fields, MINIMAL fields, or custom field sets
• 📦 Archive Support — Works with .graphqls files, directories, .zip, .tar.gz, and .tgz archives
• 🔌 Extensible — Custom auth, templates, scalar handlers, and generation hooks

Installation

pip install gql-pygen

Or with uv:

uv add gql-pygen

Quick Start

1. Generate Pydantic Models

gql-pygen generate -s ./schema.graphqls -o ./generated

This creates:

• generated/models/ — Pydantic models for all types
• generated/enums.py — All GraphQL enums
• generated/scalars.py — Custom scalar definitions

2. Generate Typed Client

gql-pygen client -s ./schema.graphqls -o ./client.py --client-name MyAPIClient

This creates a single file with:

• Nested client classes matching your schema structure
• Typed async methods for all queries and mutations
• Automatic response parsing with model_validate()

3. Use the Client

import asyncio
from generated.client import MyAPIClient
from generated.models import CreateUserInput

async def main():
    async with MyAPIClient(url="https://api.example.com/graphql", api_key="...") as client:
        # Full IDE autocomplete on nested paths
        result = await client.users.create_user(
            input=CreateUserInput(name="Alice", email="[e-mail]")
        )

        # Response is already typed — no manual parsing needed
        print(f"Created user: {result.user.id}")

asyncio.run(main())

CLI Reference

gql-pygen generate

Generate Pydantic models from a GraphQL schema.

gql-pygen generate [OPTIONS]

Options:
  -s, --schema PATH        Path to schema file, directory, or archive [required]
  -o, --output PATH        Output directory for generated code [required]
  -t, --templates PATH     Custom template directory (overrides built-in templates)
  --async                  Generate async clients (async def + await). Default: sync
  -v, --verbose            Enable verbose output

Examples:

# From a directory of .graphqls files (sync mode, default)
gql-pygen generate -s ./schema -o ./generated

# Generate async clients
gql-pygen generate -s ./schema -o ./generated --async

# From an archive
gql-pygen generate -s ./schema-bundle.tgz -o ./generated

# With custom templates
gql-pygen generate -s ./schema -o ./generated --templates ./my_templates

gql-pygen client

Generate a typed client with all operations. By default generates async clients.

gql-pygen client [OPTIONS]

Options:
  -s, --schema PATH        Path to schema file, directory, or archive [required]
  -o, --output PATH        Output file for generated client [required]
  -n, --client-name TEXT   Client class name (default: GraphQLClient)
  --async                  Generate async clients (default: True)
  --sync                   Generate sync clients instead of async
  -v, --verbose            Enable verbose output

Examples:

# Generate async client (default)
gql-pygen client -s ./schema.tgz -o ./client.py

# Generate sync client
gql-pygen client -s ./schema.tgz -o ./client.py --sync

# Generate with custom class name
gql-pygen client -s ./schema.tgz -o ./client.py --client-name CatoClient

Generated Client Usage

Async Context Manager

async with MyAPIClient(url=API_URL, api_key=API_KEY) as client:
    result = await client.namespace.operation(...)

Field Selection

Control which fields are requested:

from generated.client import FieldSelection

# Request all fields (default)
result = await client.users.get_user(id="123", fields=FieldSelection.ALL)

# Request minimal fields (just IDs and __typename)
result = await client.users.get_user(id="123", fields=FieldSelection.MINIMAL)

# Request specific fields
result = await client.users.get_user(
    id="123",
    fields=FieldSelection.custom(["id", "name", "email"])
)

Error Handling

from generated.client import GraphQLError

try:
    result = await client.users.create_user(input=user_input)
except GraphQLError as e:
    print(f"GraphQL error: {e.message}")
    for error in e.errors:
        print(f"  - {error}")

Extensibility

gql-pygen is designed to be extensible. You can customize authentication, templates, scalar handling, and code generation without modifying the package.

Custom Authentication

The generated client supports pluggable authentication:

from gql_pygen.core import BearerAuth, BasicAuth, HeaderAuth, ApiKeyAuth

# Bearer token (OAuth, JWT)
async with MyClient(url=URL, auth=BearerAuth("your-token")) as client:
    result = await client.users.get_user(id="123")

# Basic auth
async with MyClient(url=URL, auth=BasicAuth("user", "pass")) as client:
    ...

# Custom headers
async with MyClient(url=URL, auth=HeaderAuth({"X-Custom": "value"})) as client:
    ...

# API key (default, backward compatible)
async with MyClient(url=URL, auth=ApiKeyAuth("key", header_name="x-api-key")) as client:
    ...

You can also implement your own auth by following the Auth protocol:

class MyCustomAuth:
    def get_headers(self) -> dict[str, str]:
        return {"Authorization": f"Custom {self.token}"}

Custom Templates

Override built-in Jinja2 templates to customize generated code:

gql-pygen generate -s ./schema -o ./generated --templates ./my_templates

Templates in your directory take precedence. Available templates to override:

• models.py.j2 — Pydantic model generation
• enums.py.j2 — Enum generation
• scalars.py.j2 — Scalar type definitions

Custom Scalar Handlers

Define how GraphQL custom scalars map to Python types:

from gql_pygen.core import ScalarHandler, ScalarRegistry

class MoneyHandler:
    python_type = "Decimal"
    import_statement = "from decimal import Decimal"

    def serialize(self, value):
        return str(value)

    def deserialize(self, value):
        from decimal import Decimal
        return Decimal(value)

# Register custom scalars
registry = ScalarRegistry()
registry.register("Money", MoneyHandler())

Built-in handlers: DateTimeHandler, DateHandler, UUIDHandler, JSONHandler

Generation Hooks

Transform the IR before generation or modify generated code after:

from gql_pygen.core import HookRunner, FilterTypesHook, AddHeaderHook

runner = HookRunner()

# Pre-generation: filter out internal types
runner.add_pre_hook(FilterTypesHook(exclude_prefix="_"))

# Post-generation: add license header
runner.add_post_hook(AddHeaderHook("# Copyright 2024 My Company"))

Custom hooks follow the PreGenerateHook and PostGenerateHook protocols:

class MyPreHook:
    def pre_generate(self, ir):
        # Modify IR
        return ir

class MyPostHook:
    def post_generate(self, filename: str, content: str) -> str:
        # Transform generated code
        return content

How It Works

1. Parse — Reads GraphQL schema files using graphql-core
2. Transform — Converts to an intermediate representation (IR)
3. Generate — Renders Pydantic models and client code via Jinja2 templates

The generated client:

• Uses httpx for async HTTP requests
• Validates responses with Pydantic's model_validate()
• Handles lists, optionals, and nested types correctly

Development

# Clone the repository
git clone https://github.com/your-org/gql-pygen.git
cd gql-pygen

# Install with dev dependencies
uv sync

# Run tests
uv run pytest tests/ -v

# Run a specific test file
uv run pytest tests/test_client_generator.py -v

License

MIT