We’ll start by learning FastAPI’s key features and core use cases. Then we will run our first application and test it out! Finally, we will learn the details of supporting GET and POST operations that include request parameters and build and test those endpoints.

Why FastAPI?

First application

FastAPI vs. Django

GET operations

Hello world

Hello who?

POST operations

Pydantic model

POST operation in action

FastAPI Basics

We’ll start by learning how to support PUT and DELETE operations using FastAPI. Then we will learn how to handle different kinds of errors and always return an appropriate status code in the response. Lastly we'll learn how to use async to enable concurrent requests that can handle higher workloads.

PUT and DELETE operations

PUT operation in action

DELETE operation in action

Handling errors

Status code classification

Handling a client error

Using async for concurrent work

When should we use async?

Asynchronous DELETE operation

FastAPI Advanced topics

We'll start by learning how to write system tests to validate individual FastAPI endpoints. Next we'll build a full JSON CRUD API to manage object lifecycles over HTTP. Finally, we'll learn how to test different application endpoints working together with manual functional tests.

Pengujian otomatis FastAPI

Opsi

Unit test

System test

Unit test vs. system test

from fastapi import FastAPI, HTTPException
from pydantic import BaseModel
from typing import Optional

# define model Item
class Item(BaseModel):
    name: str
    quantity: Optional[int] = 0

app = FastAPI()

items = {"scissors": Item(name="scissors", quantity=100)}


@app.get("/items")
def read(name: str):
    if name not in items:
        raise HTTPException(status_code=404, detail="Item not found")
    return items[name]

# Import TestClient
from fastapi.testclient import ____
from main import app

# Create test client with application context
client = TestClient(____)

def test_main():
    response = client.get("/items?name=scissors")
    assert response.status_code == 200
    assert response.json() == {"name": "scissors",
                               "quantity": ____}

# Import TestClient
from fastapi.testclient import TestClient
from main import app

# Create test client with application context
client = TestClient(app)

def test_main():
    response = client.get("/items?name=scissors")
    assert response.status_code == 200
    assert response.json() == {"name": "scissors",
                               "quantity": 100}

Uji sistem

Membangun API CRUD JSON

Create

Read

Update

Operasi HTTP & langkah CRUD

Respons operasi DELETE

from fastapi import FastAPI, HTTPException
from pydantic import BaseModel
from typing import Optional

# define model Item
class Item(BaseModel):
    name: str
    quantity: Optional[int] = 0

app = FastAPI()

items = {}


@app.____("/items")
def create(item: Item):
    name = item.name
    if name in items:
        raise HTTPException(status_code=409, detail="Item exists")
    items[name] = item
    return {"message": f"Added {name} to items."}
  
@app.____("/items")
def read(name: str):
    if name not in items:
        raise HTTPException(status_code=____, detail="Item not found")
    return items[name]  
  
@app.____("/items")
def update(item: Item):
    name = item.name
    if name not in items:
        raise HTTPException(status_code=____, detail="Item not found")
    items[name] = item
    return {"message": f"Updated {name}."}
  
@app.delete("/items")
def delete(item: Item):
    name = item.name
    if name not in items:
        raise HTTPException(status_code=____, detail="Item not found")
    del items[name]
    return {"message": f"Deleted {name}."}

from fastapi import FastAPI, HTTPException
from pydantic import BaseModel
from typing import Optional

# define model Item
class Item(BaseModel):
    name: str
    quantity: Optional[int] = 0

app = FastAPI()

items = {}


@app.post("/items")
def create(item: Item):
    name = item.name
    if name in items:
        raise HTTPException(status_code=409, detail="Item exists")
    items[name] = item
    return {"message": f"Added {name} to items."}
  
@app.get("/items")
def read(name: str):
    if name not in items:
        raise HTTPException(status_code=404, detail="Item not found")
    return items[name]  
  
@app.put("/items")
def update(item: Item):
    name = item.name
    if name not in items:
        raise HTTPException(status_code=404, detail="Item not found")
    items[name] = item
    return {"message": f"Updated {name}."}
  
@app.delete("/items")
def delete(item: Item):
    name = item.name
    if name not in items:
        raise HTTPException(status_code=404, detail="Item not found")
    del items[name]
    return {"message": f"Deleted {name}."}

Lengkapi JSON CRUD API

Menulis uji fungsional manual

Pengujian Sistem

Pengujian Fungsional

Pengujian sistem vs. pengujian fungsional

import requests

ENDPOINT = "http://localhost:8000/items"

# Create item "rock" without providing quantity
r = requests.post(ENDPOINT, json={"name": "rock"})
assert r.status_code == ____
assert r.json()["message"] == "Added rock to items."

# Verify that item "rock" has quantity 0
r = requests.get(ENDPOINT + "?____=____")
assert r.status_code == 200
assert r.json()["quantity"] == 0

# Update item "rock" with quantity 100
r = requests.put(ENDPOINT, json={"name": "rock", "quantity": 100})
assert r.status_code == 200
assert r.json()["message"] == "Updated rock."

# Verify that item "rock" has quantity 100
r = requests.get(ENDPOINT + "?name=rock")
assert r.status_code == 200
assert r.json()["quantity"] == ____

# Delete item "rock"
r = requests.delete(ENDPOINT, json={____: ____})
assert r.status_code == 200
assert r.json()["message"] == "Deleted rock."

# Verify that item "rock" does not exist
r = requests.get(ENDPOINT + "?name=rock")
assert r.status_code == ____

print("Test complete.")

import requests

ENDPOINT = "http://localhost:8000/items"

# Create item "rock" without providing quantity
r = requests.post(ENDPOINT, json={"name": "rock"})
assert r.status_code == 200
assert r.json()["message"] == "Added rock to items."

# Verify that item "rock" has quantity 0
r = requests.get(ENDPOINT + "?name=rock")
assert r.status_code == 200
assert r.json()["quantity"] == 0

# Update item "rock" with quantity 100
r = requests.put(ENDPOINT, json={"name": "rock", "quantity": 100})
assert r.status_code == 200
assert r.json()["message"] == "Updated rock."

# Verify that item "rock" has quantity 100
r = requests.get(ENDPOINT + "?name=rock")
assert r.status_code == 200
assert r.json()["quantity"] == 100

# Delete item "rock"
r = requests.delete(ENDPOINT, json={"name": "rock"})
assert r.status_code == 200
assert r.json()["message"] == "Deleted rock."

# Verify that item "rock" does not exist
r = requests.get(ENDPOINT + "?name=rock")
assert r.status_code == 404

print("Test complete.")

Uji fungsional

Ringkasan

Building and testing a JSON CRUD API

Kursus ini mengajarkan Anda membangun aplikasi web tingkat produksi menggunakan FastAPI, kerangka kerja Python populer untuk membuat API. Anda akan mempelajari cara menangani keempat operasi HTTP, mendefinisikan skema permintaan dan respons, memvalidasi permintaan API, serta mengembalikan kode status HTTP yang sesuai. Anda juga akan mempelajari eksekusi kode asinkron untuk meningkatkan kinerja, dan pada akhirnya Anda akan mengembangkan API CRUD serta menguji alur kerja dengan modul requests di Python. Dirancang untuk pemrogram Python berpengalaman, kursus ini membekali Anda dengan keterampilan mengelola data dengan FastAPI, mempersiapkan Anda membangun pipeline manajemen data dan penyajian model ML yang tangguh.

<h2>Pengantar FastAPI dan Aplikasinya</h2> API sering digunakan untuk mengelola data di web, dan FastAPI adalah kerangka kerja web populer baru untuk membangun API dengan Python. Insinyur Data dan Machine Learning memanfaatkan FastAPI untuk membangun aplikasi yang berfungsi sebagai transaksi dan pipa data yang sadar konteks di web.<br><br> <h2>Membuat Aplikasi Web Berkelas Produksi dengan FastAPI</h2> Dalam kursus ini, Anda akan belajar cara membangun aplikasi web berkualitas produksi dengan memanfaatkan keterampilan Python Anda menggunakan kerangka kerja FastAPI. Pada akhirnya, Anda akan memahami penggunaan utama FastAPI dibandingkan dengan kerangka kerja web Python lainnya. Anda akan belajar cara membangun API menggunakan keempat jenis operasi HTTP dan mendefinisikan skema permintaan dan respons. Selain itu, Anda akan memvalidasi permintaan API, merespons dengan kode status HTTP yang sesuai dan pesan, serta menjalankan kode secara asinkron untuk meningkatkan kinerja aplikasi. Proyek praktis ini akan membimbing Anda dalam membangun API CRUD (Create, Read, Update, Delete) klasik, serta menguji alur kerja menggunakan modul requests Python.<br><br> <h2>Tujuan Kursus dan Sasaran Peserta</h2> Kursus ini dirancang untuk programmer Python berpengalaman yang ingin membangun aplikasi web yang mengelola data menggunakan FastAPI. Setelah menyelesaikan kursus ini, Anda akan memiliki dasar yang diperlukan untuk membuat proyek FastAPI yang cocok untuk pengelolaan data berkapasitas tinggi dan pipeline penyajian model ML.

Introduction to APIs in Python

Introduction to Object-Oriented Programming in Python

Bangun API andal dengan FastAPI, kuasai operasi HTTP, validasi, dan eksekusi async untuk pipeline data.

Pengantar FastAPI

Bangun API yang andal dan siap produksi dengan FastAPI, kuasai operasi HTTP, validasi, dan eksekusi asinkron untuk menciptakan alur data dan ML yang efisien.


Membuat API dengan Python

Menguji beberapa endpoint secara bersamaan

Pengujian sistem vs. pengujian fungsional

Pengantar FastAPI

Latihan interaktif praktis