Skip to main content

The easiest, fastest python GraphQL framework.

Project description

Documentation

FastGQL

FastGQL is a python GraphQL library that uses Pydantic models to build GraphQL types. Think FastAPI for GraphQL.

from fastapi import FastAPI
from fastgql import GQL, build_router

class User(GQL):
    name: str
    age: int

class Query(GQL):
    def user_by_name(self, name: str) -> User:
        return User(name=name, age=27)

router = build_router(query_models=[Query])

app = FastAPI()

app.include_router(router, prefix="/graphql")

I built FastGQL because I wanted a GraphQL framework that

  1. let me use pydantic.BaseModel objects to define my schema
  2. let me build dynamic database queries based on incoming requests

We are now using FastGQL in production and have experienced a massive (10x) speedup in average response times because of 2).

You can find out more about how we build dynamic database queries in the Advanced Tutorial section of the docs.

Installation

$ pip install fastgql
---> 100%
Successfully installed fastgql

Example

All you need to do is create objects that inherit from fastgql.GQL, which is a simple subclass of pydantic.BaseModel. For this example, I am creating a mock schema based on movies. For the functions, you'd usually use a database but I hardcoded the data for this example.

This code generates a GraphQL schema, reading the object fields and functions. Functions can be sync or async.

Code it

  • Create a file main.py with:
from uuid import UUID, uuid4
from fastapi import FastAPI
from fastgql import GQL, build_router

class Account(GQL):  # (4)!
    id: UUID
    username: str

    def watchlist(self) -> list["Movie"]:  # (1)!
        # Usually you'd use a database to get the user's watchlist. For this example, it is hardcoded.
        return [
            Movie(id=uuid4(), title="Barbie", release_year=2023),
            Movie(id=uuid4(), title="Oppenheimer", release_year=2023),
        ]

    def _secret_function(self) -> str:  # (2)!
        return "this is not exposed!"

class Person(GQL):
    id: UUID
    name: str

    def filmography(self) -> list["Movie"]:
        return [
            Movie(id=uuid4(), title="Barbie", release_year=2023),
            Movie(id=uuid4(), title="Wolf of Wallstreet", release_year=2013),
        ]

class Movie(GQL):
    id: UUID
    title: str
    release_year: int

    def actors(self) -> list["Person"]:
        return [
            Person(id=uuid4(), name="Margot Robbie"),
            Person(id=uuid4(), name="Ryan Gosling"),
        ]

class Query(GQL):
    def account_by_username(self, username: str) -> Account:  # (5)!
        # Usually you'd use a database to get this account. For this example, it is hardcoded.
        return Account(id=uuid4(), username=username)

router = build_router(query_models=[Query])

app = FastAPI()  # (3)!

app.include_router(router, prefix="/graphql")
  1. Usually this would be a database call. There is an advanced tutorial showing this.
  2. Functions that start with _ are not included in the GraphQL schema.
  3. This is just a normal FastAPI app. fastgql.build_router returns a router that can be included on any FastAPI app.
  4. These objects are subclasses of pydantic.BaseModel, so anything you'd want to do with a BaseModel you can do with these. You'll see how this comes in handy in future tutorials.
  5. All of these functions can be sync or async. In a future tutorial I'll use an async database call to get data.

Run it

Run the server with:

$ uvicorn main:app --reload

INFO:     Uvicorn running on http://127.0.0.1:8000 (Press CTRL+C to quit)
INFO:     Started reloader process [28720]
INFO:     Started server process [28722]
INFO:     Waiting for application startup.
INFO:     Application startup complete.
(Taken from FastAPI docs) About the command uvicorn main:app --reload...

The command uvicorn main:app refers to:

  • main: the file main.py (the Python "module").
  • app: the object created inside of main.py with the line app = FastAPI().
  • --reload: make the server restart after code changes. Only do this for development.

Check it

Open your browser at http://127.0.0.1:8000/graphql.

You will see a GraphiQL UI. This is your homebase for creating GraphQL queries and checking the schema.

You can see the schema, build queries, and access query history from the icons in the top left respectivly. Here is an example query:

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

fastgql-0.6.3.tar.gz (28.4 kB view details)

Uploaded Source

Built Distribution

fastgql-0.6.3-py3-none-any.whl (36.8 kB view details)

Uploaded Python 3

File details

Details for the file fastgql-0.6.3.tar.gz.

File metadata

  • Download URL: fastgql-0.6.3.tar.gz
  • Upload date:
  • Size: 28.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.5.1 CPython/3.10.10 Darwin/23.0.0

File hashes

Hashes for fastgql-0.6.3.tar.gz
Algorithm Hash digest
SHA256 fdc5e50cefc316b9616f7d85c6a259ab33cd592e2db754a8196a7d62a6e578d4
MD5 44e2e789f20f32361260a1932a6b64cc
BLAKE2b-256 c9e3249345a54826926e84d7f15a74e61699c7edfe8028ea1105a09a7498a2d5

See more details on using hashes here.

Provenance

File details

Details for the file fastgql-0.6.3-py3-none-any.whl.

File metadata

  • Download URL: fastgql-0.6.3-py3-none-any.whl
  • Upload date:
  • Size: 36.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.5.1 CPython/3.10.10 Darwin/23.0.0

File hashes

Hashes for fastgql-0.6.3-py3-none-any.whl
Algorithm Hash digest
SHA256 fbc9e7a70dd309d0bd0eb068ee2de19a4d009ea413495a4c75b2a95ebc3f479c
MD5 0ff26c68c1e4bf3ee9d7a1ae73d38169
BLAKE2b-256 3c6d4c652d0c8a2837e52296a0a5d4ac002f55f30b1b2af59330b4f5933a07d6

See more details on using hashes here.

Provenance

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page