♻️ 🎨 more projest structure for use in repo template

Author: jmeisele

.DS_Store

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+FROM python:3.7-stretch
+RUN pip install pipenv
+COPY Pipfile* /tmp
+RUN cd /tmp && pipenv lock --requirements > requirements.txt
+RUN pip install -r /tmp/requirements.txt
+COPY . /tmp/myapp
+RUN pip install /tmp/myapp
+CMD ["uvicorn", "fastapi_scaffolding.main:app", "host='0.0.0.0'", "port=3000"]

Dockerfile

@@ -1,2 +1,6 @@
-# fastapi-ml-scaffolding
+# FastAPI Model Serving Scaffolding
+
 Scaffolding for serving ml model APIs using FastAPI
+
+This repo contains the scaffolding which can be used to speed up your next machine learning project.
+

README.md

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+version: '3'
+services: 
+    python1:
+        container_name: ml-api-service-1
+        restart: always
+        build: 
+            context: .
+            dockerfile: Dockerfile
+        ports: 
+            - "3000:3000"
+        volumes: 
+            - ./app1:/app

docker-compose.yml

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+
+from fastapi import APIRouter
+
+from fastapi_scaffolding.models.heartbeat import HearbeatResult
+
+router = APIRouter()
+
+
+@router.get("/heartbeat", response_model=HearbeatResult, name="heartbeat")
+def get_hearbeat() -> HearbeatResult:
+    heartbeat = HearbeatResult(is_alive=True)
+    return heartbeat

fastapi_scaffolding/api/routes/heartbeat.py

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+from fastapi import APIRouter, Depends
+from starlette.requests import Request
+
+from fastapi_scaffolding.core import security
+from fastapi_scaffolding.models.payload import HousePredictionPayload # Incoming payload data model
+from fastapi_scaffolding.models.prediction import HousePredictionResult # Outbound prediction result data model
+from fastapi_scaffolding.services.models import HousePriceModel # ML Model itself
+
+router = APIRouter()
+
+
+@router.post("/predict", response_model=HousePredictionResult, name="predict")
+def post_predict(
+    request: Request,
+    authenticated: bool = Depends(security.validate_request),
+    block_data: HousePredictionPayload = None
+) -> HousePredictionResult:
+
+    model: HousePriceModel = request.app.state.model
+    prediction: HousePredictionResult = model.predict(block_data)
+
+    return prediction

fastapi_scaffolding/api/routes/prediction.py

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+
+
+from fastapi import APIRouter
+
+from fastapi_scaffolding.api.routes import heartbeat, prediction
+
+api_router = APIRouter()
+api_router.include_router(heartbeat.router, tags=["health"], prefix="/health")
+api_router.include_router(prediction.router, tags=[
+                          "prediction"], prefix="/model")

fastapi_scaffolding/api/routes/router.py

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+
+
+from starlette.config import Config
+from starlette.datastructures import Secret
+
+APP_VERSION = "0.0.1"
+APP_NAME = "Machine Learning Prediction Example"
+API_PREFIX = "/api"
+
+config = Config(".env")
+
+API_KEY: Secret = config("API_KEY", cast=Secret)
+IS_DEBUG: bool = config("IS_DEBUG", cast=bool, default=False)
+
+DEFAULT_MODEL_PATH: str = config("DEFAULT_MODEL_PATH")

fastapi_scaffolding/core/config.py

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+
+
+from typing import Callable
+
+from fastapi import FastAPI
+from loguru import logger
+
+from fastapi_scaffolding.core.config import DEFAULT_MODEL_PATH
+from fastapi_scaffolding.services.models import HousePriceModel
+
+
+def _startup_model(app: FastAPI) -> None:
+    model_path = DEFAULT_MODEL_PATH
+    model_instance = HousePriceModel(model_path)
+    app.state.model = model_instance
+
+
+def _shutdown_model(app: FastAPI) -> None:
+    app.state.model = None
+
+
+def start_app_handler(app: FastAPI) -> Callable:
+    def startup() -> None:
+        logger.info("Running app start handler.")
+        _startup_model(app)
+    return startup
+
+
+def stop_app_handler(app: FastAPI) -> Callable:
+    def shutdown() -> None:
+        logger.info("Running app shutdown handler.")
+        _shutdown_model(app)
+    return shutdown

fastapi_scaffolding/core/event_handlers.py

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+NO_API_KEY = "No API key provided."
+AUTH_REQ = "Authentication required."
+HTTP_500_DETAIL = "Internal server error."
+
+# templates
+NO_VALID_PAYLOAD = "{} is not a valid payload."