Feature/movies db

.gitignore

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+.idea/

README.md

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-# GroupProjectTemplate
-Please make sure to modify this readme file as well as the "about" property of the project!
+# Team Blockbuster - Top Movies API
+
+#### BU MET CS673 O1: Software Engineering, Fall 2024 - Team 6
+
+## Project Description
+
+Team Blockbuster is creating a microservice Data Science application which will provide the ability to query and display 
+movie data based on various user inputs using the Kaggle IMDB Top 250 Movies dataset: 
+<https://www.kaggle.com/datasets/rajugc/imdb-top-250-movies-dataset>
+
+## Motivation
+
+This application provides information for people who are curious about movie trends such as movies ratings across 
+different countries, movie durations, or specific movie genres and categories, etc. This information can help people 
+working in the film industry or similar industries in making important movie development choices.
+
+## Framework
+
+This microservice based application is built using a **Python Flask** framework where **ReactJS** will be used to create 
+a frontend web-page where the user can input data points and **Python** will be used to manage backend operations that 
+generate the movie data based on the input data received. **SQLite** will be used as the application's database. 
+
+Overview:
+
+- **Frontend:** ReactJS 
+- **Backend:** Python
+- **Database:** SQLite
+
+## Tools Used
+
+The following technologies will be used for our project:
+
+- PyCharm Community (**2024.2.2**)
+- GitHub Actions
+- Python (**v3.12**)
+- pip (**v24.2**)
+    * Python Flask
+    * PyLint
+    * Pandas
+- Docker (**v27.2.0**)
+    * Docker Compose (**v2.29.2-desktop.2**)
+- Podman (**5.2.2**)
+- nodeJS (**v20.17.0**)
+- SQLite (**v3**)
+
+## Installation and Set Up
+
+##### Please install the specific versions mentioned in the **Tools Used** section above.
+
+**PyCharm Community**
+
+Please follow download and installation instructions from the link: 
+https://www.jetbrains.com/pycharm/download/ depending on OS.
+
+**Docker**
+
+Please follow download and installation instructions from the link: https://www.docker.com/ depending on OS.
+
+**Docker Compose**
+
+Docker Compose is part of the Docker installation process.
+
+**nodeJS**
+
+Please follow download and installation instructions from the link: https://nodejs.org/en depending on OS. 
+
+**Python**
+
+Please follow download and installation instructions from the link: https://www.python.org/ depending on OS.
+
+**pip**
+
+pip should be installed with the Python downloaded from https://www.python.org/.
+
+**Python Flask**
+
+Using the Python version installed along with pip, please follow the instructions at the link: 
+https://flask.palletsprojects.com/en/3.0.x/installation/.
+
+**Pandas**
+Using the Python version that is installed along with, please use pip to install: Pandas pip3 install pandas
+
+**SQLite**
+
+sqlite3 is part of the Python library when Python was downloaded and installed.
+
+For more information please refer to this link: https://docs.python.org/3/library/sqlite3.html
+
+## How to Run Software
+
+1. Open a command line console and clone the main branch of this repository (SSH approach) in location of choice using 
+   the command below:
+
+    `git clone git@github.com:BUMETCS673/seprojects-cs673olf24team6.git`
+
+    Note: SSH approach was used for the command above. Please follow the appropriate GitHub guidelines to set up SSH 
+    keys before cloning this repository.
+
+2. Using either file manager or a terminal window navigate to the code directory.
+
+3. To run this application the services must be started in the correct order or an error may occur. The first service to 
+   start is Python Flask
+   - `cd backend` or navigate to backend directory
+   - To run the application using Python use `python3 backend.py`
+   - To run the application using Docker or Podman run the commands below
+     - docker build -t flask_backend .
+     - docker run -p 5000:5000 -t flask_backend
+
+4. To Run the frontend application you need be in the /code/frontend directory.
+     - To run the application using Node use `npm start`
+     - To run the application using Docker or Podman run the commands below
+       - docker build -t node-frontend .
+       - docker run -p 3000:3000 -t node-frontend
+
+5. At this stage in the project you will need to allow a web-browser to open or open web-browser and navigate to 
+   localhost:3000 where you will be able to view the frontend application 
+
+## How to Run Tests
+
+### Frontend
+1. From frontend directory
+2. Podman/Docker build -t node_frontend .
+3. Podman/Docker run -idt --name node_frontend node_frontend
+4. Podman/Docker exec -it node_frontend /bin/bash
+5. ` npm test`
+
+
+### Backend
+1. From backend directory
+2. Podman/Docker build -t flask_backend .
+3. Podman/Docker run -idt --name flask_backend flask_backend
+4. Podman/Docker exec -it flask_backend /bin/bash
+5. `cd tests`
+6. `pytest process_query_request_test.py`
+
+### Database
+1. From database directory
+2. Podman/Docker build -t database .
+3. Podman/Docker run -idt --name database database
+4. Podman/Docker exec -it database /bin/bash
+5. `cd tests`
+6. `pytest movies_unit_test.py`
+
+## Credits
+
+**Course Instructor:** Yuting Zhang
+
+**Facilitators:** Steve Chin, Trevor Michelson
+
+**Tools Installation Information**
+* Docker: https://www.docker.com/ 
+    - Docker Compose
+* Podman
+* nodeJS: https://nodejs.org/en
+* Python: https://www.python.org/
+    - pip
+    - flask
+    - pandas
+    - pylint
+* SQLite: https://docs.python.org/3/library/sqlite3.html
+
+**Dataset Information**
+* Kaggle IMDB Top 250 Movies dataset: <https://www.kaggle.com/datasets/rajugc/imdb-top-250-movies-dataset>, 
+* By Chidambara Raju G (2022)
+
+## Meet the Team
+
+**Team Leader:** Joshua Shilts
+
+**Requirements Leader:** Elizabeth Tyree
+
+**Design and Implementation Leader:** Elizabeth Tyree
+
+**Configuration Leader:** Ricky Zheng
+
+**QA Leader:** Alex Flinchum
+
+**Security Leader:** James Zheng
+
+[Contributors Information](./team.md)

code/backend/.gitignore

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+.pytestcache
+.idea
+src/__pycache__
+tests/__pycache__

code/backend/Dockerfile

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+FROM python:3.11-slim
+
+WORKDIR /app
+
+COPY . /app
+
+# Copy requirements file first to leverage Docker cache if requirements haven't changed
+COPY requirements.txt .
+
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Set PYTHONPATH environment variable
+ENV PYTHONPATH=/app
+
+RUN pip install -r requirements.txt
+
+EXPOSE 5000
+
+CMD ["python", "src/backend.py"]

code/backend/requirements.txt

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+Flask~=3.0.3
+flask-cors~=5.0.0
+pytest~=7.4.0

code/backend/src/backend.py

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+from flask_cors import CORS
+from flask import Flask, request, jsonify
+import json
+
+app = Flask(__name__)
+CORS(app)
+
+# TODO Remove when Alex changes have merged
+@app.route('/api/getData', methods=['POST'])
+def get_data():
+    data = request.json
+    input1 = data.get('input1')
+    input2 = data.get('input2')
+
+    # Example logic using the inputs
+    response_message = f"Received input1: {input1}, input2: {input2}"
+
+    return jsonify({'message': response_message})
+
+
+@app.route('/processQueryRequest', methods=['POST'])
+def process_data_request():
+    data = request.json
+
+    # Add error handling for invalid or missing JSON
+    if not data:
+        return jsonify({"error": "Invalid or missing JSON data"}), 400
+
+    app.logger.info(f"Received: {json.dumps(data)})")
+
+    data_diction = db_query(data)
+
+    response_message = (f"Rank: {data.get('rank')}, \n"
+                            f"Title: {data.get('title')}, \n"
+                            f"Release start: {data.get('release_start')}, \n"
+                            f"Release end: {data.get('release_end')}, \n"
+                            f"Score: {data.get('score')}, \n"
+                            f"Genre: {data.get('genre_select')}, \n"
+                            f"Rating: {data.get('rating_select')}, \n"
+                            f"Budget: {data.get('budget')}, \n"
+                            f"Box Office: {data.get('box_office')}, \n"
+                            f"Cast: {data.get('cast_select')}, \n"
+                            f"Director: {data.get('director_select')}, \n"
+                            f"Writer: {data.get('writer_select')}")
+
+    return jsonify({'Python Received': response_message}), 200
+
+def db_query(data):
+    #conn(db)
+    return "Select * {data.get('rank')}"
+
+
+if __name__ == '__main__':
+    # Run this application on local host on port 5000
+    app.run(host='0.0.0.0', port=5000, debug=True)

code/backend/tests/process_query_request_test.py

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+from src import backend
+import pytest
+import json
+
+
+@pytest.fixture
+def test_client():
+    with backend.app.test_client() as client:
+        yield client
+
+
+def test_process_data_request(test_client):
+
+        incoming_request = {
+            'rank': 1,
+            'title': 'Monty Python',
+            'release_start': '1955-07-16',
+            'release_end': '1999-09-10',
+            'score': 10.0,
+            'genre_select': 'Legend',
+            'rating_select': 'R?',
+            'budget': 20,
+            'box_office': 829895144000,
+            'cast_select': 'All dead',
+            'director_select': 'Monty Python?',
+            'writer_select': 'Monty Python?'
+        }
+
+        response = test_client.post('/processQueryRequest',
+                               data=json.dumps(incoming_request),
+                               content_type='application/json')
+
+        # Verify that respose is ok type
+        assert response.status_code == 200
+
+        # Check if the response contains expected data
+        expected_message = (f"Rank: 1, \n"
+                            f"Title: Monty Python, \n"
+                            f"Release start: 1955-07-16, \n"
+                            f"Release end: 1999-09-10, \n"
+                            f"Score: 10.0, \n"
+                            f"Genre: Legend, \n"
+                            f"Rating: R?, \n"
+                            f"Budget: 20, \n"
+                            f"Box Office: 829895144000, \n"
+                            f"Cast: All dead, \n"
+                            f"Director: Monty Python?, \n"
+                            f"Writer: Monty Python?")
+
+        response_data = json.loads(response.data)
+
+        # Test to ensure the response it correctly formatted
+        assert 'Python Received' in response_data
+        # Verify test has the expected data
+        assert response_data['Python Received'] == expected_message

code/database/Dockerfile

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+FROM python:3.11-slim
+
+# Allows use to access database from shell
+RUN apt-get update && apt-get install -y sqlite3
+
+WORKDIR /app
+
+COPY . /app
+
+# Copy requirements file first to leverage Docker cache if requirements haven't changed
+COPY requirements.txt .
+
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Set PYTHONPATH environment variable
+#ENV PYTHONPATH=/app
+
+RUN python /app/src/start_movies.py
+
+CMD [ "tail", "-f", "/dev/null"]

code/database/requirements.txt

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+pandas==2.2.3
+pytest==7.4.0