Module 3 · FastAPI for ML

Module 3: HTTP Methods & CRUD Operations

Build a simulation database CRUD students record system. Learn GET, POST, PUT, DELETE operations, request payloads parsing, and raising HTTP status codes.

⏱ 25 Min Read • Author: GenAIWallah Team • Updated: May 2026

Day 5

FastAPI HTTP Methods & CRUD Operations

Why this matters

HTTP CRUD: REST maps resources to HTTP verbs — CRUD is how ML services expose create/read/update/delete.

REST maps resources to HTTP verbs. FastAPI uses decorators: @app.get, @app.post, etc.

GET — read (safe, idempotent)
POST — create
PUT — replace
DELETE — remove

from fastapi import FastAPI, HTTPException

app = FastAPI()
students = {}

@app.get("/students/{student_id}")
def get_student(student_id: int):
    if student_id not in students:
        raise HTTPException(status_code=404, detail="Not found")
    return students[student_id]

@app.post("/students", status_code=201)
def create_student(student_id: int, name: str):
    students[student_id] = {"id": student_id, "name": name}
    return students[student_id]

Common mistakes

Blocking the event loop with heavy sync code in async routes.
Returning wrong HTTP status codes (200 on validation failure).
Shipping without request/response models for ML endpoints.

Interview checkpoints

Q: Explain http crud in one minute. A: Definition + ML deployment angle.
Q: One FastAPI pitfall? A: Validation, async blocking, or wrong status code.

Practice

Basic: Define HTTP CRUD and give an example.
Intermediate: Implement a minimal snippet for HTTP CRUD.
Advanced: Break it and read the OpenAPI / error response.

Recap

You can explain http crud clearly.
You know one mistake to avoid.
You see how this connects to the next lesson.

Next: Parameters

Day 6

Path vs. Query Parameters and Status Codes

Why this matters

Parameters: Path vs query parameters and correct status codes are interview staples and production requirements.

Path parameters identify a resource (/students/42). Query parameters filter or paginate (?limit=10).

200 OK, 201 Created, 404 Not Found, 422 Validation Error
Return HTTPException for explicit error bodies

Use Pydantic models instead of bare int, name: str for maintainable APIs.

Common mistakes

Blocking the event loop with heavy sync code in async routes.
Returning wrong HTTP status codes (200 on validation failure).
Shipping without request/response models for ML endpoints.

Interview checkpoints

Q: Explain parameters in one minute. A: Definition + ML deployment angle.
Q: One FastAPI pitfall? A: Validation, async blocking, or wrong status code.

Practice

Basic: Define Parameters and give an example.
Intermediate: Implement a minimal snippet for Parameters.
Advanced: Break it and read the OpenAPI / error response.

Recap

You can explain parameters clearly.
You know one mistake to avoid.
You see how this connects to the next lesson.

Next: ML Pipeline

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