User Feedback Analysis System

This project collects and analyzes user feedback using Python, Google Cloud Platform (GCP), BigQuery, and sentiment analysis.

Table of Contents

• User Feedback Analysis System
  • Table of Contents
  • Project Overview
  • Features
  • Requirements
  • Setup
  • Usage
  • Project Structure
  • Contributing
  • License

Project Overview

This system is designed to collect user feedback from a CSV file, store it in Google BigQuery, and perform sentiment analysis using the ChatGPT API. It demonstrates skills in data handling, cloud storage, and natural language processing.

Features

• Load user feedback data from CSV into Google BigQuery
• Perform sentiment analysis on feedback text using ChatGPT API
• Store analyzed data back in BigQuery
• Scalable design for handling large datasets
• Modular architecture with separate modules for data, database, and utility operations

Requirements

• Python 3.7+
• Google Cloud Platform account with BigQuery and Cloud Storage enabled
• OpenAI API key

Setup

1. Clone the repository:

   git clone https://github.com/yourusername/user-feedback-analysis.git
   cd user-feedback-analysis

2. Install dependencies:

   pip install -r requirements.txt

3. Set up Google Cloud credentials:

   • Create a service account and download the JSON key
   • Set the environment variable:

     export GOOGLE_APPLICATION_CREDENTIALS="/path/to/your/service-account-key.json"

4. Set up OpenAI API key:

   export OPENAI_API_KEY="your-api-key"

5. Configure the project:

   • Update the config.py file in the src/utils directory with your project-specific settings

Usage

1. Load data into BigQuery:

   from src.data import load_csv_to_bigquery
   
   load_csv_to_bigquery()

2. Set up BigQuery tables:

   from src.database import setup_tables
   
   setup_tables()

3. Perform sentiment analysis:

   from src.sentiment import analyze_sentiment
   
   analyze_sentiment()

Project Structure

user_feedback_analysis/
│
├── src/
│   ├── data/
│   │   ├── __init__.py
│   │   └── collection.py
│   ├── database/
│   │   ├── __init__.py
│   │   ├── connection.py
│   │   ├── operations.py
│   ├── sentiment/
│   │   ├── __init__.py
│   │   └── sentiment_analysis.py
│   └── utils/
│       ├── __init__.py
│       ├── config.py
│       └── logging.py
├── tests/
│   ├── test_sentiment_analysis.py
│   └── ...
├── requirements.txt
└── README.md

• src/data/: Contains modules for data collection and processing
• src/database/: Contains modules for database connection and operations
  • connection.py: Handles connections to BigQuery and Google Cloud Storage
  • operations.py: Provides functions for loading data, setting up tables, inserting rows, and querying data from BigQuery tables
• src/analysis/: Contains modules for sentiment analysis
• src/utils/: Contains utility modules for configuration and logging
  • config.py: Manages configuration settings, including loading environment variables from a .env file
  • logging.py: Provides a singleton logger instance for consistent logging across the project
• tests/: Contains test scripts for various modules

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the MIT License - see the LICENSE file for details.