Team: NonNomine2 PR

.github/workflows/ci.yml

@@ -0,0 +1,52 @@
+name: CI Pipeline
+
+on:
+  push:
+    branches:
+      - main
+  pull_request:
+    branches:
+      - main
+
+jobs:
+  test-and-docker:
+    runs-on: ubuntu-latest
+
+    steps:
+      # Checkout the repository
+      - name: Checkout code
+        uses: actions/checkout@v3
+
+      # Setup Python environment
+      - name: Setup Python
+        uses: actions/setup-python@v4
+        with:
+          python-version: '3.10'
+
+      # Install dependencies from both requirements.txt files
+      - name: Install dependencies
+        run: |
+          python -m pip install --upgrade pip
+          pip install -r requirements.txt
+          pip install -r app/requirements.txt
+
+      # Run tests with pytest
+      - name: Run tests
+        run: |
+          export PYTHONPATH=.
+          python3 tests/test.py
+
+      # Run linting with pylint
+      - name: Run pylint
+        run: |
+          pylint app/ || exit 0 # Allow linting to fail without failing the pipeline
+
+      # Build Docker image
+      - name: Build Docker image
+        run: |
+          docker build -t commonassessmenttool .
+
+      # Run Docker container
+      - name: Run Docker container
+        run: |
+          docker run -d -p 8000:8000 --name app-container commonassessmenttool

Dockerfile

@@ -0,0 +1,29 @@
+# Use an official Python image as the base image
+FROM python:3.10-slim
+
+# Install necessary build dependencies
+RUN apt-get update && apt-get install -y \
+    gcc \
+    python3-dev \
+    libffi-dev \
+    build-essential \
+    --no-install-recommends && \
+    apt-get clean && \
+    rm -rf /var/lib/apt/lists/*
+
+# Set the working directory in the container
+WORKDIR /app
+
+# Copy the application code to the container
+COPY . .
+
+# Upgrade pip and install dependencies
+RUN pip install --upgrade pip && \
+    pip install -r requirements.txt && \
+    pip install -r app/requirements.txt
+
+# Expose the port FastAPI will use
+EXPOSE 8000
+
+# Command to start the FastAPI application
+CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "8000"]

README.md

@@ -3,3 +3,86 @@ This will contain the model used for the project that based on the input informa
 The model works off of dummy data of several combinations of clients alongside the interventions chosen for them as well as their success rate at finding a job afterward. The model will be updated by the case workers by inputing new data for clients with their updated outcome information, and it can be updated on a daily, weekly, or monthly basis.
 
 This also has an API file to interact with the front end, and logic in order to process the interventions coming from the front end. This includes functions to clean data, create a matrix of all possible combinations in order to get the ones with the highest increase of success, and output the results in a way the front end can interact with.
+
+## Assessment Tool Documentation
+
+This API provides several endpoints to handle client-related operations, such as predicting outcomes based on input data, adding client information to an SQLite database, retrieving client information, updating client data, and deleting a client from the database.
+
+### Prerequisites
+To run this project, ensure that the following tools are installed on your system:
+
+* Python 3.8 or later
+* FastAPI
+* SQLite
+
+### API Endpoints
+1. POST /clients/predictions  
+This endpoint accepts input data and returns a prediction result by calling the interpret_and_calculate logic.
+
+Request:
+* Method: POST
+* URL: /clients/predictions
+
+2. POST /clients/add  
+This endpoint adds the input data to the SQLite database and returns the newly created client_id along with the prediction result.
+
+Request:
+* Method: POST
+* URL: /clients/add
+* Body: Same as /clients/predictions
+
+3. GET /clients/{client_id}  
+This endpoint retrieves a client's information by client_id from the database.
+
+Request:
+* Method: GET
+* URL: /clients/{client_id}
+
+4. PUT /clients/update/{client_id}  
+This endpoint updates the client information for the provided client_id using the input data.
+
+Request:
+
+* Method: PUT
+* URL: /clients/update/{client_id}
+* Body: Same as /clients/predictions
+
+5. DELETE /clients/delete/{client_id}  
+This endpoint deletes the client record from the database using the provided client_id.
+
+Request:
+* Method: DELETE
+* URL: /clients/delete/{client_id}
+
+### Database Configuration
+This project uses an SQLite database to store client information. The database schema can be defined as follows:
+
+CREATE TABLE clients (
+    id INTEGER PRIMARY KEY AUTOINCREMENT,
+    age INTEGER,
+    gender TEXT,
+    work_experience INTEGER,
+    canada_workex INTEGER,
+    dep_num INTEGER,
+    canada_born BOOLEAN,
+    citizen_status TEXT,
+    level_of_schooling TEXT,
+    fluent_english BOOLEAN,
+    reading_english_scale INTEGER,
+    speaking_english_scale INTEGER,
+    writing_english_scale INTEGER,
+    numeracy_scale INTEGER,
+    computer_scale INTEGER,
+    transportation_bool BOOLEAN,
+    caregiver_bool BOOLEAN,
+    housing TEXT,
+    income_source TEXT,
+    felony_bool BOOLEAN,
+    attending_school BOOLEAN,
+    currently_employed BOOLEAN,
+    substance_use TEXT,
+    time_unemployed INTEGER,
+    need_mental_health_support_bool BOOLEAN
+);
+
+You can create the database by running this SQL command on your SQLite database engine.

app/clients/database.py

@@ -0,0 +1,41 @@
+import sqlite3
+
+def get_db_connection():
+    conn = sqlite3.connect('clients.db')
+    conn.row_factory = sqlite3.Row
+    return conn
+
+
+def create_clients_table():
+    conn = get_db_connection()
+    conn.execute('''
+        CREATE TABLE IF NOT EXISTS clients (
+            id INTEGER PRIMARY KEY AUTOINCREMENT,
+            age INTEGER,
+            gender INTEGER,
+            work_experience INTEGER,
+            canada_workex INTEGER,
+            dep_num INTEGER,
+            canada_born INTEGER,
+            citizen_status INTEGER,
+            level_of_schooling INTEGER,
+            fluent_english INTEGER,
+            reading_english_scale INTEGER,
+            speaking_english_scale INTEGER,
+            writing_english_scale INTEGER,
+            numeracy_scale INTEGER,
+            computer_scale INTEGER,
+            transportation_bool INTEGER,
+            caregiver_bool INTEGER,
+            housing INTEGER,
+            income_source INTEGER,
+            felony_bool INTEGER,
+            attending_school INTEGER,
+            currently_employed INTEGER,
+            substance_use INTEGER,
+            time_unemployed INTEGER,
+            need_mental_health_support_bool INTEGER
+        )
+    ''')
+    conn.commit()
+    conn.close()

app/clients/router.py

@@ -1,8 +1,7 @@
-from fastapi import APIRouter
-from fastapi.responses import HTMLResponse
-
+from fastapi import APIRouter, HTTPException
 from app.clients.service.logic import interpret_and_calculate
 from app.clients.schema import PredictionInput
+from app.clients.database import get_db_connection
 
 router = APIRouter(prefix="/clients", tags=["clients"])
 
@@ -12,4 +11,87 @@ async def predict(data: PredictionInput):
     print(data.model_dump())
     return interpret_and_calculate(data.model_dump())
 
+@router.post("/add")
+async def add(data: PredictionInput):
+    # Input data to SQLite
+    conn = get_db_connection()
+    conn.execute('''INSERT INTO clients 
+                (age, gender, work_experience, canada_workex, dep_num, canada_born,
+                citizen_status, level_of_schooling, fluent_english, reading_english_scale,
+                speaking_english_scale, writing_english_scale, numeracy_scale, computer_scale,
+                transportation_bool, caregiver_bool, housing, income_source, felony_bool,
+                attending_school, currently_employed, substance_use, time_unemployed,
+                need_mental_health_support_bool)
+                VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
+                ''', 
+            (data.age, data.gender, data.work_experience, data.canada_workex, data.dep_num, data.canada_born,
+            data.citizen_status, data.level_of_schooling, data.fluent_english, data.reading_english_scale,
+            data.speaking_english_scale, data.writing_english_scale, data.numeracy_scale, data.computer_scale,
+            data.transportation_bool, data.caregiver_bool, data.housing, data.income_source, data.felony_bool,
+            data.attending_school, data.currently_employed, data.substance_use, data.time_unemployed,
+            data.need_mental_health_support_bool))
+    conn.commit()
+    client_id = conn.execute("SELECT last_insert_rowid()").fetchone()[0]
+    conn.close()
+    return { "client_id": client_id, 
+        "prediction_result": interpret_and_calculate(data.model_dump())}
+
+# get client by id
+@router.get("/{client_id}")
+async def get_client(client_id: int):
+    conn = get_db_connection()
+    client = conn.execute('SELECT * FROM clients WHERE id = ?', (client_id,)).fetchone()
+    conn.close()
+    if client is None:
+        raise HTTPException(status_code=404, detail="Client not found")
+    return dict(client)
+
+# update clients info by id
+@router.put("/update/{client_id}")
+async def update_client(client_id: int, data: PredictionInput):
+    conn = get_db_connection()
+
+    client = conn.execute('SELECT * FROM clients WHERE id = ?', (client_id,)).fetchone()
+    if client is None:
+        conn.close()
+        raise HTTPException(status_code=404, detail="Client not found")
+
+    conn.execute('''
+        UPDATE clients
+        SET age = ?, gender = ?, work_experience = ?, canada_workex = ?, dep_num = ?,
+            canada_born = ?, citizen_status = ?, level_of_schooling = ?, fluent_english = ?,
+            reading_english_scale = ?, speaking_english_scale = ?, writing_english_scale = ?,
+            numeracy_scale = ?, computer_scale = ?, transportation_bool = ?, caregiver_bool = ?,
+            housing = ?, income_source = ?, felony_bool = ?, attending_school = ?,
+            currently_employed = ?, substance_use = ?, time_unemployed = ?, need_mental_health_support_bool = ?
+        WHERE id = ?
+        ''', (
+            data.age, data.gender, data.work_experience, data.canada_workex, data.dep_num,
+            data.canada_born, data.citizen_status, data.level_of_schooling, data.fluent_english,
+            data.reading_english_scale, data.speaking_english_scale, data.writing_english_scale,
+            data.numeracy_scale, data.computer_scale, data.transportation_bool, data.caregiver_bool,
+            data.housing, data.income_source, data.felony_bool, data.attending_school,
+            data.currently_employed, data.substance_use, data.time_unemployed,
+            data.need_mental_health_support_bool, client_id
+    ))
+
+    conn.commit()
+    conn.close()
+
+    return {"message": "Client information updated successfully", "client_id": client_id}
+
+# delete clients info by id
+@router.delete("/delete/{client_id}")
+async def delete_client(client_id: int):
+    conn = get_db_connection()
+
+    client = conn.execute('SELECT * FROM clients WHERE id = ?', (client_id,)).fetchone()
+    if client is None:
+        conn.close()
+        raise HTTPException(status_code=404, detail="Client not found")
+
+    conn.execute('DELETE FROM clients WHERE id = ?', (client_id,))
+    conn.commit()
+    conn.close()
 
+    return {"message": f"Client with id {client_id} deleted successfully."}

app/clients/schema.py

@@ -1,3 +1,4 @@
+
 from pydantic import BaseModel
 
 class PredictionInput(BaseModel):

app/clients/service/logic.py

@@ -28,10 +28,10 @@
 def clean_input_data(data):
     #translate input into wahtever we trained the model on, numerical data in a specific order
     columns = ["age","gender","work_experience","canada_workex","dep_num",	"canada_born",	
-               "citizen_status",	"level_of_schooling",	"fluent_english",	"reading_english_scale",	
-               "speaking_english_scale",	"writing_english_scale",	"numeracy_scale",	"computer_scale",	
-               "transportation_bool",	"caregiver_bool",	"housing",	"income_source",	"felony_bool",	"attending_school",	
-               "currently_employed",	"substance_use",	"time_unemployed",	"need_mental_health_support_bool"]
+        "citizen_status",	"level_of_schooling",	"fluent_english",	"reading_english_scale",	
+        "speaking_english_scale",	"writing_english_scale",	"numeracy_scale",	"computer_scale",	
+        "transportation_bool",	"caregiver_bool",	"housing",	"income_source",	"felony_bool",	"attending_school",	
+        "currently_employed",	"substance_use",	"time_unemployed",	"need_mental_health_support_bool"]
     demographics = {
         'age': data['age'],
         'gender': data['gender'],

app/main.py

@@ -1,8 +1,7 @@
 from fastapi import FastAPI
 from fastapi.middleware.cors import CORSMiddleware
-
 from app.clients.router import router as clients_router
-
+from app.clients.database import create_clients_table  # input from database.py
 
 app = FastAPI()
 
@@ -17,4 +16,9 @@
     allow_headers=["*"],  # Allows all headers
 )
 
+@app.on_event("startup")
+async def startup_event():
+    create_clients_table()
 
+if __name__ == "__main__":
+    create_clients_table()