tutorial003_py39.py — fastapi Source File

Architecture documentation for tutorial003_py39.py, a python file in the fastapi codebase. 2 imports, 1 dependents.

File python FastAPI Routing 2 imports 1 dependents 3 functions

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FastAPI→ Routing→ tutorial003_py39.py — fastapi Source File

Dependency Diagram

graph LR
  71f2968e_1af1_02b0_6082_4ff2aceb8912["tutorial003_py39.py"]
  a88eb002_9197_73f3_410d_ee5315767f34["contextlib"]
  71f2968e_1af1_02b0_6082_4ff2aceb8912 --> a88eb002_9197_73f3_410d_ee5315767f34
  534f6e44_61b8_3c38_8b89_6934a6df9802["__init__.py"]
  71f2968e_1af1_02b0_6082_4ff2aceb8912 --> 534f6e44_61b8_3c38_8b89_6934a6df9802
  32fe68d3_95d9_2e66_78d9_f6e43815ee26["test_tutorial003.py"]
  32fe68d3_95d9_2e66_78d9_f6e43815ee26 --> 71f2968e_1af1_02b0_6082_4ff2aceb8912
  style 71f2968e_1af1_02b0_6082_4ff2aceb8912 fill:#6366f1,stroke:#818cf8,color:#fff

Relationship Graph

Source Code

from contextlib import asynccontextmanager

from fastapi import FastAPI


def fake_answer_to_everything_ml_model(x: float):
    return x * 42


ml_models = {}


@asynccontextmanager
async def lifespan(app: FastAPI):
    # Load the ML model
    ml_models["answer_to_everything"] = fake_answer_to_everything_ml_model
    yield
    # Clean up the ML models and release the resources
    ml_models.clear()


app = FastAPI(lifespan=lifespan)


@app.get("/predict")
async def predict(x: float):
    result = ml_models["answer_to_everything"](x)
    return {"result": result}