Text Analyzer Project

Project Overview

A comprehensive Flask-based text analysis application with advanced natural language processing capabilities, database integration, and robust architecture.

Features

• Advanced text analysis metrics
• Word count and character analysis
• Readability score calculation
• Sentiment analysis
• Word frequency distribution
• JWT authentication
• Database persistence
• Docker containerization

Technology Stack

• Python 3.8+
• Flask
• SQLAlchemy
• PostgreSQL
• NLTK
• TextBlob
• Docker
• JWT Authentication

Project Structure

text-analyzer/
│
├── app/
│   ├── services/
│   ├── models/
│   ├── routes/
│   └── utils/
│
├── config/
├── tests/
└── requirements.txt

Setup Instructions

Local Development

# Clone repository
git clone https://github.com/zahidhasann88/text-analyzer.git
cd text-analyzer

# Create virtual environment
python3 -m venv venv
source venv/bin/activate    #gitbash
venv\Scripts\activate   #cmd
.\venv\Scripts\activate  #powershall

# Install dependencies
pip install -r requirements.txt

# Configure database
createdb textanalyzer

# Run migrations
flask db upgrade

# Start application
python run.py

# test application
pytest tests

Docker Deployment

# Build and run
docker-compose up --build

API Endpoints

• POST /api/analyze: Text analysis endpoint
  • Requires JWT authentication
  • Payload: {"text": "Sample text to analyze"}

Key Analysis Metrics

• Total word count
• Unique words
• Sentence count
• Readability scores
• Word frequency
• Sentiment analysis

Testing

# Run tests
pytest tests/

# Check coverage
coverage run -m pytest
coverage report

Authentication

• JWT-based authentication
• Secure token management

Logging

• Rotating file handlers
• Console and file logging
• Configurable log levels