Automatic update of dependencies

.github/workflows/linting.yml

@@ -1,31 +1,39 @@
 name: Python checks
 
-on: [push]
+on:
+  push:
 
 jobs:
   styles:
     runs-on: ubuntu-latest
-    strategy:
-      matrix:
-        python-version: [3.7, 3.8]
+    # strategy:
+    #   matrix:
+    #     python-version: [3.7, 3.8]
 
     steps:
-      - uses: actions/checkout@v2
-      - name: Set up Python ${{ matrix.python-version }}
-        uses: actions/setup-python@v2
+      - name: Checkout source code from Github
+        uses: actions/checkout@v3
         with:
-          python-version: ${{ matrix.python-version }}
+          fetch-depth: 0
+      # - name: Set up Python ${{ matrix.python-version }}
+      #   uses: actions/setup-python@v2
+        # with:
+          # python-version: ${{ matrix.python-version }}
       - name: Install dependencies
         run: |
           python -m pip install --upgrade pip
-          pip install flake8 pytest mypy
-          if [ -f requirements.txt ]; then pip install -r requirements.txt; fi
+          pip install flake8 mypy
+          if [ -f docker/requirements.txt ]; then pip install -r docker/requirements.txt; fi
+
       - name: Lint with flake8
         run: |
           # stop the build if there are Python syntax errors or undefined names
           flake8 ./src --count --select=E9,F63,F7,F82 --show-source --statistics
           # exit-zero treats all errors as warnings.
           flake8 ./src --count --exit-zero --max-complexity=10 --max-line-length=120 --statistics
       - name: Static typing
-        run: |
-          mypy --no-warn-no-return --ignore-missing-imports ./src
+        run: mypy --no-warn-no-return --ignore-missing-imports ./src
+      - name: Test
+       # env:
+       #   PYTHONPATH: "${PYTHONPATH}:/src"
+        run: cd src && export PYTHONPATH="${PYTHONPATH}:/src" && echo $PYTHONPATH  && pytest tests

.gitignore

@@ -130,5 +130,6 @@ dmypy.json
 
 
 .idea/
-src/ml_pipelines
 .env
+src/ml_pipelines/*
+!src/ml_pipelines/.gitkeep 

docker/requirements.txt

@@ -1,26 +1,11 @@
-click==7.1.2
 fastapi==0.61.2
 flake8==3.8.4
-h11==0.11.0
-importlib-metadata==3.4.0
 joblib==1.0.0
-mccabe==0.6.1
-mypy==0.800
-mypy-extensions==0.4.3
 numpy==1.20.1
 pandas==1.2.1
 psycopg2==2.9.3
-pycodestyle==2.6.0
 pydantic==1.7.2
-pyflakes==2.2.0
-python-dateutil==2.8.1
-pytz==2021.1
 scikit-learn==0.24.1
-scipy==1.6.0
-six==1.15.0
-starlette==0.13.6
-threadpoolctl==2.1.0
-typed-ast==1.4.2
-typing-extensions==3.7.4.3
 uvicorn==0.12.3
-zipp==3.4.0
+pytest==7.1.2
+pytest-asyncio==0.19.0

src/pytest.ini

@@ -0,0 +1,2 @@
+[pytest]
+addopts = -p no:warnings

src/server.py

@@ -73,7 +73,7 @@ async def predict(item: Item, response: Response):
                                 status_code=status.HTTP_404_NOT_FOUND)
 
     # make prediction
-    df = convert_item_to_df(item)
+    df = await convert_item_to_df(item)
     prediction = CACHE['ml_pipeline'].predict(df)[0]
 
     # save features + prediction + pipeline version

src/tests/unit_tests/test_helpers.py

@@ -0,0 +1,33 @@
+import pytest
+import pandas as pd
+from utils.helpers import convert_item_to_df
+from models.item_model import Item
+
+@pytest.mark.asyncio
+async def test_convert_item_to_df():
+    item = Item(
+        CRIM=0.00632, ZN=18.0, INDUS=2.31, CHAS=0, NOX=0.538, RM=6.575, AGE=65.2, 
+        DIS=4.09, RAD=1, TAX=296.0, PTRATIO=15.3, B=396.9, LSTAT=4.98
+    )
+
+    converted_item = await convert_item_to_df(item)
+    expected = {
+        'CRIM': 0.00632,
+        'ZN': 18.0,
+        'INDUS': 2.31,
+        'CHAS': 0,
+        'NOX': 0.538,
+        'RM': 6.575,
+        'AGE': 65.2,
+        'DIS': 4.09,
+        'RAD': 1,
+        'TAX': 296.0,
+        'PTRATIO': 15.3,
+        'B': 396.9,
+        'LSTAT': 4.98
+    }
+
+    assert type(converted_item) == pd.DataFrame
+
+    for key, val in expected.items():
+        assert converted_item[key][0] == val

src/utils/helpers.py

@@ -31,7 +31,7 @@ async def save_prediction(row: list) -> None:
     execute_query(query, row)
 
 
-def convert_item_to_df(item: Item) -> pd.DataFrame:
+async def convert_item_to_df(item: Item) -> pd.DataFrame:
     """Convert Item to the pandas DataFrame"""
     items = {}
     for key, value in item.dict().items():