GraphQL APIs#
This document will guide you through the process of building GraphQL APIs using FastAPI, a modern, fast (high-performance) web framework for building APIs with Python.
Requirements: - Python 3.8+ - FastAPI - Strawberry (GraphQL library for Python)
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Setting Up the Project#
First, install FastAPI, Uvicorn (ASGI server), and Strawberry for GraphQL support:
pip install fastapi uvicorn
pip install 'strawberry-graphql[fastapi]'
Creating the FastAPI Application#
Define a GraphQL Schema: Using Strawberry, define a schema for API.
Integrate with FastAPI: Add a route in FastAPI to serve the GraphQL API.
Defining the Schema#
Start by defining a schema using Strawberry. We will create a Book type and a query for retrieving a list of books.
# main.py
from typing import List
import strawberry
@strawberry.type
class Book:
title: str
author: str
books = [
Book(title="The Great Gatsby", author="F. Scott Fitzgerald"),
Book(title="1984", author="George Orwell"),
Book(title="To Kill a Mockingbird", author="Harper Lee")
]
@strawberry.type
class Query:
@strawberry.field
def get_books(self) -> List[Book]:
return books
schema = strawberry.Schema(query=Query)
Integrating with FastAPI#
Once the schema is defined, integrate it with FastAPI by adding the route to serve the GraphQL API.
from fastapi import FastAPI
from strawberry.asgi import GraphQL
app = FastAPI()
graphql_app = GraphQL(schema)
app.add_route("/graphql", graphql_app)
app.add_websocket_route("/graphql", graphql_app)
Running the Application#
Run the application using Uvicorn:
uvicorn main:app --reload
FastAPI server will be available at http://127.0.0.1:8000. You can access the GraphQL Playground at http://127.0.0.1:8000/graphql.
Testing the GraphQL API#
In the GraphQL Playground, test the get_books query:
query {
getBooks {
title
author
}
}
Expected response:
{
"data": {
"getBooks": [
{
"title": "The Great Gatsby",
"author": "F. Scott Fitzgerald"
},
{
"title": "1984",
"author": "George Orwell"
},
{
"title": "To Kill a Mockingbird",
"author": "Harper Lee"
}
]
}
}
Adding Mutations#
Next, we will add a mutation for creating a new book. This requires an update to the Book and Mutation classes.
from typing import Optional
@strawberry.type
class Mutation:
@strawberry.mutation
def add_book(self, title: str, author: str) -> Book:
new_book = Book(title=title, author=author)
books.append(new_book)
return new_book
schema = strawberry.Schema(query=Query, mutation=Mutation)
Testing the Mutation#
To test the add_book mutation, use the following query in the GraphQL Playground:
mutation {
addBook(title: "The Catcher in the Rye", author: "J.D. Salinger") {
title
author
}
}
Expected response:
{
"data": {
"addBook": {
"title": "The Catcher in the Rye",
"author": "J.D. Salinger"
}
}
}
Update and Delete#
Update#
Add a mutation for updating a book’s details. The mutation will accept the current title and the new details.
@strawberry.type
class Mutation:
@strawberry.mutation
def update_book(self, title: str, new_title: str, new_author: str) -> Optional[Book]:
for book in books:
if book.title == title:
book.title = new_title
book.author = new_author
return book
return None
Testing Update#
mutation {
updateBook(title: "1984", newTitle: "1984 (Updated)", newAuthor: "George Orwell (Updated)") {
title
author
}
}
Expected response:
{
"data": {
"updateBook": {
"title": "1984 (Updated)",
"author": "George Orwell (Updated)"
}
}
}
Delete#
Add a mutation to delete a book by title. This will remove the book from the list.
@strawberry.type
class Mutation:
@strawberry.mutation
def delete_book(self, title: str) -> bool:
for book in books:
if book.title == title:
books.remove(book)
return True
return False
Testing Delete#
mutation {
deleteBook(title: "To Kill a Mockingbird")
}
Expected response:
{
"data": {
"deleteBook": false
}
}
Conclusion#
Building GraphQL APIs with FastAPI and Strawberry provides a seamless and efficient way to create high-performance, scalable APIs with modern Python frameworks. By following the steps outlined, you can implement robust CRUD functionality, enabling dynamic interactions with your data through queries and mutations. This approach ensures flexibility, maintainability, and an excellent developer experience, making it ideal for modern API development.
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