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Tivadar Danka cosmic-cortex

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@cosmic-cortex
cosmic-cortex / docker-compose.test.yaml
Created Jan 29, 2020
Docker compose config for unit testing
View docker-compose.test.yaml
version: "3"
services:
fastapi-ml-quickstart:
build: .
ports:
- 8000:8000
entrypoint: ["pytest"]
@cosmic-cortex
cosmic-cortex / ci.yaml
Created Jan 29, 2020
Automated testing using GitHub actions
View ci.yaml
# This GitHub action describes the continuous integration workflow for pull requests to master.
name: ci
on:
pull_request:
branches:
- master
push:
branches:
@cosmic-cortex
cosmic-cortex / docker-compose.yaml
Last active Jan 29, 2020
docker-compose file for the FastAPI app
View docker-compose.yaml
version: "3"
services:
fastapi-ml-quickstart:
build: .
ports:
- 8000:8000
@cosmic-cortex
cosmic-cortex / Dockerfile
Created Jan 28, 2020
Dockerfile for our FastAPI application
View Dockerfile
FROM ubuntu:19.10
COPY ./api /api/api
COPY requirements.txt /requirements.txt
RUN apt-get update \
&& apt-get install python3-dev python3-pip -y \
&& pip3 install -r requirements.txt
ENV PYTHONPATH=/api
@cosmic-cortex
cosmic-cortex / predict_csv.py
Last active Jan 28, 2020
predict_csv endpoint
View predict_csv.py
import pandas as pd
from fastapi import File, UploadFile, HTTPException
from starlette.status import HTTP_422_UNPROCESSABLE_ENTITY
@app.post("/predict_csv")
def predict_csv(csv_file: UploadFile = File(...), model: Model = Depends(get_model)):
try:
df = pd.read_csv(csv_file.file).astype(float)
@cosmic-cortex
cosmic-cortex / test_predict_with_wrong_input.py
Created Jan 27, 2020
Testing the API endpoint with invalid user data
View test_predict_with_wrong_input.py
from itertools import product
from starlette.status import HTTP_422_UNPROCESSABLE_ENTITY
@pytest.mark.parametrize(
"n_instances, test_data_n_features",
product(range(1, 10), [n for n in range(1, 20) if n != n_features]),
)
def test_predict_with_wrong_input(
@cosmic-cortex
cosmic-cortex / test_predict.py
Created Jan 27, 2020
Testing the API endpoint
View test_predict.py
import pytest
import random
from starlette.testclient import TestClient
from starlette.status import HTTP_200_OK
from api.ml.model import n_features
@pytest.mark.parametrize("n_instances", range(1, 10))
@cosmic-cortex
cosmic-cortex / conftest.py
Created Jan 27, 2020
Configurations and fixtures for API testing
View conftest.py
import pytest
from starlette.testclient import TestClient
from ..main import app
from ..ml.model import get_model
from .mocks import MockModel
def get_model_override():
@cosmic-cortex
cosmic-cortex / mocks.py
Created Jan 27, 2020
Mock for unit testing the API
View mocks.py
import numpy as np
class MockModel:
def __init__(self, model_path: str = None):
self._model_path = None
self._model = None
def predict(self, X: np.ndarray) -> np.ndarray:
n_instances = len(X)
@cosmic-cortex
cosmic-cortex / predictrequest_final.py
Created Jan 27, 2020
Additional validation for the PredictRequest model
View predictrequest_final.py
from pydantic import BaseModel, ValidationError, validator
from .ml.model import n_features
class PredictRequest(BaseModel):
data: List[List[float]]
@validator("data")
def check_dimensionality(cls, v):