N2R-31

.github/workflows/main.yml

@@ -51,6 +51,17 @@ jobs:
           python3 generator.py ../changed_notebooks/
           echo "Generated services:"
           ls -la services/ || echo "No services directory"
+
+      - name: Install Test Dependencies
+        run: |
+            pip install pytest pytest-cov httpx fastapi starlette
+
+      - name: Run Tests on Generated Service
+        run: |
+          cd ../
+          export PYTHONPATH=$PYTHONPATH:$(pwd):$(pwd)/src
+          python -m pytest --cov=src --cov-report=term-missing -s 
+          cd src/
 
       - name: Configure AWS credentials
         uses: aws-actions/configure-aws-credentials@v2

.github/workflows/tests.yml

@@ -0,0 +1,40 @@
+name: Run Tests
+
+on: 
+  push:
+    branches:
+      - N2R-31
+  workflow_dispatch:
+
+jobs:
+  test:
+    runs-on: ubuntu-latest
+
+    steps:
+    - name: Checkout code
+      uses: actions/checkout@v4
+
+    - name: Set up Python
+      uses: actions/setup-python@v5
+      with:
+        python-version: "3.12"
+
+    - name: Run generator (create Dockerfile, main.py and requirements.txt)
+      run: |
+        pip install nbformat
+        rm -rf src/services/
+        cd src/
+        python3 generator.py ../notebooks/
+        echo "Generated services:"
+        ls -la services/ || echo "No services directory"
+
+    - name: Install dependencies
+      run: |
+        python -m pip install --upgrade pip
+        pip install pytest pytest-cov httpx nbformat fastapi papermill uvicorn pandas lxml
+
+    - name: Run tests with coverage
+      run: |
+        cd ../
+        export PYTHONPATH=$PYTHONPATH:$(pwd):$(pwd)/src
+        python -m pytest --cov=src --cov-report=term-missing -s 

.gitignore

@@ -1,8 +1,11 @@
 .DS_Store
+.coverage
 
 .terraform/
 *.tfstate
 *.tfstate.backup
 *.auto.tfvars
 
-/src/services
+/src/services
+
+__pycache__

notebooks/dataframe/dataframe_output.ipynb

@@ -0,0 +1,112 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df = pd.DataFrame({\n",
+    "    \"user\": [\"A\", \"B\", \"C\"],\n",
+    "    \"score\": [10, 15, 8]\n",
+    "})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>user</th>\n",
+       "      <th>score</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>A</td>\n",
+       "      <td>10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>B</td>\n",
+       "      <td>15</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>C</td>\n",
+       "      <td>8</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "  user  score\n",
+       "0    A     10\n",
+       "1    B     15\n",
+       "2    C      8"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.13.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}

notebooks/error/error_output.ipynb

@@ -0,0 +1,46 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "ZeroDivisionError",
+     "evalue": "division by zero",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[31m---------------------------------------------------------------------------\u001b[39m",
+      "\u001b[31mZeroDivisionError\u001b[39m                         Traceback (most recent call last)",
+      "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[1]\u001b[39m\u001b[32m, line 1\u001b[39m\n\u001b[32m----> \u001b[39m\u001b[32m1\u001b[39m \u001b[32;43m1\u001b[39;49m\u001b[43m \u001b[49m\u001b[43m/\u001b[49m\u001b[43m \u001b[49m\u001b[32;43m0\u001b[39;49m\n",
+      "\u001b[31mZeroDivisionError\u001b[39m: division by zero"
+     ]
+    }
+   ],
+   "source": [
+    "1 / 0"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.10"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

notebooks/linearRegression/docs.md

@@ -0,0 +1,2 @@
+# Description
+This example notebook runs linear regression on Kaggle advertising dataset. Contains longer running process and combination of outputs (text,images,dataframe)