A lightweight Python GraphQL server framework with automatic resolver mapping and schema introspection
Project description
pgql
A lightweight Python GraphQL server framework with automatic resolver mapping, schema introspection, and built-in support for Starlette/Uvicorn.
Features
- 🚀 Automatic Resolver Mapping: Map Python class methods to GraphQL fields based on return types
- 📁 Recursive Schema Loading: Organize your
.gqlschema files in nested directories - 🔍 Built-in Introspection: Full GraphQL introspection support out of the box
- 🎯 Instance-based Resolvers: Use class instances for stateful resolvers with dependency injection
- ⚡ Async Support: Built on Starlette and Uvicorn for high-performance async handling
- 🔧 YAML Configuration: Simple YAML-based server configuration
- 📦 Type Support: Full support for
extend type, nested types, and GraphQL type modifiers - 🔐 Authorization System: Intercept resolver calls with
on_authorizefunction - 🍪 Session Management: Built-in session store with automatic cookie handling
- 🌐 CORS Validation: Dynamic origin validation with
on_http_check_origincallback - 🔗 FastAPI Integration: Mount FastAPI apps alongside GraphQL in a single Uvicorn instance
Installation
pip install pgql
Quick Start
1. Define Your GraphQL Schema
Create your schema files in a directory structure:
schema/
├── schema.gql
└── user/
├── types.gql
└── queries.gql
schema/schema.gql:
schema {
query: Query
}
schema/user/types.gql:
type User {
id: ID!
name: String!
email: String!
}
schema/user/queries.gql:
extend type Query {
getUser(id: ID!): User!
getUsers: [User!]!
}
2. Create Resolver Classes
# resolvers/user.py
class User:
def getUser(self, parent, info, id):
# Your logic here
return {'id': id, 'name': 'John Doe', 'email': 'john@example.com'}
def getUsers(self, parent, info):
return [
{'id': 1, 'name': 'John', 'email': 'john@example.com'},
{'id': 2, 'name': 'Jane', 'email': 'jane@example.com'}
]
3. Configure Server
config.yml:
http_port: 8080
debug: true
server:
host: localhost
routes:
- mode: gql
endpoint: /graphql
schema: schema # Path to schema directory
4. Start Server
from pgql import HTTPServer
from resolvers.user import User
# Create resolver instances
user_resolver = User()
# Initialize server
server = HTTPServer('config.yml')
# Map resolvers to GraphQL types
server.gql({
'User': user_resolver
})
# Start server
server.start()
5. Query Your API
curl -X POST http://localhost:8080/graphql \
-H "Content-Type: application/json" \
-d '{"query": "{ getUsers { id name email } }"}'
Response:
{
"data": {
"getUsers": [
{"id": "1", "name": "John", "email": "john@example.com"},
{"id": "2", "name": "Jane", "email": "jane@example.com"}
]
}
}
How It Works
Automatic Resolver Mapping
pgql automatically maps resolver methods to GraphQL fields based on return types:
- If
Query.getUserreturns typeUser, pgql looks for a method namedgetUserin theUserresolver class - The mapping works recursively for nested types (e.g.,
User.company→Company.company)
Example:
type User {
id: ID!
company: Company!
}
type Company {
id: ID!
name: String!
}
type Query {
getUser: User!
}
class User:
def getUser(self, parent, info):
return {'id': 1, 'company': {'id': 1}}
class Company:
def company(self, parent, info):
# parent contains the User object
company_id = parent['id']
return {'id': company_id, 'name': 'Acme Corp'}
# Register both resolvers
server.gql({
'User': User(),
'Company': Company()
})
Resolver Arguments
All resolver methods receive:
self: The resolver instance (for stateful resolvers)parent: The parent object from the previous resolverinfo: GraphQL execution info (field name, context, variables, etc.)**kwargs: Field arguments from the query
def getUser(self, parent, info, id):
# id comes from query arguments
return fetch_user(id)
Introspection
pgql supports full GraphQL introspection out of the box:
curl -X POST http://localhost:8080/graphql \
-H "Content-Type: application/json" \
-d '{"query": "{ __schema { queryType { name } } }"}'
This works with tools like:
- GraphiQL
- GraphQL Playground
- Apollo Studio
- Postman
Advanced Usage
Authorization Interceptor
pgql allows you to intercept every resolver call to implement authorization logic using on_authorize:
from pgql import HTTPServer, AuthorizeInfo
def on_authorize(auth_info: AuthorizeInfo) -> bool:
"""
Intercept every resolver call for authorization
Args:
auth_info.operation: 'query', 'mutation', or 'subscription'
auth_info.src_type: Parent GraphQL type invoking the resolver (e.g., 'User' for User.company)
auth_info.dst_type: GraphQL type being executed (e.g., 'Company' for User.company)
auth_info.resolver: Field/resolver name (e.g., 'getUser', 'company')
auth_info.session_id: Session ID from cookie (None if not present)
Returns:
True to allow execution, False to deny
"""
# Deny access if no session
if not auth_info.session_id:
return False
# Restrict specific field access based on parent type
if auth_info.src_type == "User" and auth_info.resolver == "company":
return auth_info.session_id == "admin123" # Only admin can access User.company
return True
server = HTTPServer('config.yml')
server.on_authorize(on_authorize) # Register authorization function
server.gql({...})
Session Management:
pgql extracts session_id from cookies automatically. Set the cookie in your client:
curl -X POST http://localhost:8080/graphql \
-H "Content-Type: application/json" \
-H "Cookie: session_id=abc123" \
-d '{"query": "{ getUsers { id } }"}'
Authorization Flow Example:
When querying { getUser { id company { name } } }:
- First call:
Query.getUser → User(src_type='Query', dst_type='User', resolver='getUser') - Second call:
User.company → Company(src_type='User', dst_type='Company', resolver='company')
Note: The on_authorize function is optional. If not set, all resolvers execute without authorization checks.
CORS Origin Validation
pgql provides dynamic CORS origin validation using the on_http_check_origin callback:
from pgql import HTTPServer
# Define allowed origins
ALLOWED_ORIGINS = [
"http://localhost:3000",
"https://myapp.com",
"https://app.example.com"
]
def check_origin(origin: str) -> bool:
"""
Validate CORS origin dynamically
Args:
origin: The origin header from the request (e.g., "http://localhost:3000")
Returns:
True to allow the origin, False to deny (returns 403)
"""
return origin in ALLOWED_ORIGINS
server = HTTPServer('config.yml')
server.on_http_check_origin(check_origin) # Register CORS validator
server.gql({...})
Default Behavior:
By default, all origins are allowed (returns True). The validator only runs when you register a callback.
CORS Headers:
When an origin is allowed, pgql automatically adds these headers:
Access-Control-Allow-Origin: The validated originAccess-Control-Allow-Credentials:trueAccess-Control-Allow-Methods:*Access-Control-Allow-Headers:*
Preflight Requests:
OPTIONS preflight requests are handled automatically with the same origin validation.
Testing:
# Allowed origin - returns 200 with CORS headers
curl -X POST http://localhost:8080/graphql \
-H "Content-Type: application/json" \
-H "Origin: http://localhost:3000" \
-d '{"query": "{ getUsers { id } }"}'
# Blocked origin - returns 403
curl -X POST http://localhost:8080/graphql \
-H "Content-Type: application/json" \
-H "Origin: http://malicious-site.com" \
-d '{"query": "{ getUsers { id } }"}'
Note: The on_http_check_origin function is optional. If not set, all origins are permitted (permissive by default).
Session Management
pgql includes a built-in session store for managing user sessions:
from pgql import HTTPServer, Session
server = HTTPServer('config.yml')
# Create a new session
session = server.create_session(max_age=3600) # 1 hour
# Store any data in the session
session.set('user_id', 123)
session.set('username', 'john')
session.set('roles', ['admin', 'user'])
session.set('preferences', {'theme': 'dark'})
# Retrieve session
session = server.get_session(session_id)
user_id = session.get('user_id')
# Delete session (logout)
server.delete_session(session_id)
Using Sessions in Resolvers:
class UserResolver:
def __init__(self, server):
self.server = server
def login(self, parent, info, username, password):
# Create session on successful login
session = self.server.create_session(max_age=7200)
session.set('user_id', 123)
session.set('authenticated', True)
# Mark session to set cookie in response
info.context['new_session'] = session
return {'success': True, 'session_id': session.session_id}
def getUser(self, parent, info):
# Access session data
session = info.context.get('session')
if session and session.get('authenticated'):
return {'id': session.get('user_id'), 'name': 'John'}
return None
Configure cookie name in YAML:
http_port: 8080
cookie_name: my_session_id # Custom cookie name
server:
host: localhost
routes:
- mode: gql
endpoint: /graphql
schema: schema
For complete session documentation, see SESSIONS.md.
Note: The on_authorize function is optional. If not set, all resolvers execute without authorization checks.
Error Handling
pgql provides a structured error system compatible with GraphQL spec and Go's gogql:
from pgql import new_error, new_fatal, new_warning, ErrorDescriptor, LEVEL_FATAL
class User:
def create_user(self, parent, info):
input_data = info.input
# Simple fatal error
if not input_data.get('email'):
raise new_fatal(
message="Email is required",
extensions={'field': 'email'}
)
# Error with ErrorDescriptor
if input_data.get('age', 0) < 18:
error_descriptor = ErrorDescriptor(
message="User must be at least 18 years old",
code="AGE_VALIDATION_FAILED",
level=LEVEL_FATAL
)
raise new_error(
err=error_descriptor,
extensions={'field': 'age', 'minimumAge': 18}
)
# Warning (non-critical)
if input_data.get('age', 0) > 100:
raise new_warning(
message="Unusual age detected",
extensions={'field': 'age', 'value': input_data['age']}
)
return {'id': '1', 'name': input_data['name']}
Error Response Format:
{
"data": null,
"errors": [
{
"message": "User must be at least 18 years old",
"extensions": {
"code": "AGE_VALIDATION_FAILED",
"level": "fatal",
"field": "age",
"minimumAge": 18
}
}
]
}
Error Types:
new_fatal(): Critical error, stops execution (returns null for field)new_warning(): Non-critical warning, execution continuesnew_error(): Generic error (Warning or Fatal based on level)
For complete error handling guide, see ERROR_HANDLING.md.
Nested Schema Organization
Organize your schemas by domain:
schema/
├── schema.gql
├── user/
│ ├── types.gql
│ ├── queries.gql
│ ├── mutations.gql
│ └── inputs.gql
└── company/
├── types.gql
└── queries.gql
pgql recursively loads all .gql files.
Multiple Routes
Configure multiple GraphQL endpoints:
server:
routes:
- mode: gql
endpoint: /graphql
schema: schema
- mode: gql
endpoint: /admin/graphql
schema: admin_schema
Integration with FastAPI
pgql can be integrated with existing FastAPI applications using the mount() method, allowing you to run both frameworks in a single Uvicorn instance:
from fastapi import FastAPI
from pgql import HTTPServer
from resolvers.user import User
# Create your FastAPI app
fastapi_app = FastAPI(title="My API")
@fastapi_app.get("/api/")
async def read_root():
return {"message": "Hello from FastAPI!"}
@fastapi_app.get("/api/users")
async def get_users():
return {"users": [{"id": 1, "name": "Alice"}]}
# Create pygql server
server = HTTPServer('config.yml')
server.gql({'User': User()})
# Mount FastAPI app on /api path
server.mount("/api", fastapi_app, name="fastapi")
# Start single uvicorn server with both apps
server.start()
Available endpoints:
POST http://localhost:8080/graphql- pygql GraphQL endpointGET http://localhost:8080/api/- FastAPI endpointsGET http://localhost:8080/api/users- FastAPI endpoints
Key benefits:
- Single Uvicorn instance: No need to manage multiple servers
- Shared configuration: Use pygql's YAML config for both
- Easy migration: Add GraphQL to existing FastAPI projects without refactoring
- ASGI compatible: Works with any ASGI application (FastAPI, Quart, Starlette apps, etc.)
Method signature:
def mount(self, path: str, app, name: str = None):
"""
Mount an ASGI application (like FastAPI) on a specific path
Args:
path: URL prefix for the mounted app (e.g., "/api")
app: ASGI application instance (FastAPI, etc.)
name: Optional name for the mount point
"""
Documentation
For detailed guides on specific features:
- Error Handling - Complete guide on how to return and handle errors
- Sessions - Session management and cookie handling
- Authorization - Authorization system with
on_authorize - Scalars - Custom scalar types implementation
- Naming Conventions - camelCase/snake_case conversion
- Resolver Info - ResolverInfo object reference
Requirements
- Python >= 3.8
- graphql-core >= 3.2.0
- starlette >= 0.27.0
- uvicorn >= 0.23.0
- pyyaml >= 6.0
License
MIT
Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
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