Initial commit

Author: EficodeRjpalt

.gitignore

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+# Yarr! This be what we don't want in our treasure chest (git repository)
+
+# Python
+__pycache__/
+*.py[cod]
+*$py.class
+*.so
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+pip-wheel-metadata/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# Virtual environments
+venv/
+env/
+ENV/
+env.bak/
+venv.bak/
+
+# IDE files
+.vscode/
+.idea/
+*.swp
+*.swo
+*~
+
+# OS files
+.DS_Store
+.DS_Store?
+._*
+.Spotlight-V100
+.Trashes
+ehthumbs.db
+Thumbs.db
+
+# Data files (these be large treasures that shouldn't go in git)
+data/*.csv
+data/*.json
+data/*.xlsx
+
+# Test coverage
+.coverage
+htmlcov/
+.pytest_cache/
+
+# Logs
+*.log
+logs/
+
+# Environment variables
+.env
+.env.local
+.env.production
+
+# Temporary files
+tmp/
+temp/

README.md

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+# Developer Insights Analytics Dashboard 🏴‍☠️📊
+
+Yarr! Welcome to the Developer Insights Analytics Dashboard, a comprehensive data analysis treasure chest that helps data analysts explore and visualize developer survey data! This be a flexible, full-stack application built with modern data analysis practices in mind.
+
+## 🗺️ Project Structure
+
+```
+python-fullstack/
+│
+├── .gitignore
+├── README.md
+├── requirements.txt
+│
+├── data/
+│   └── kaggle_so_2023/            # Stack Overflow 2023 survey data
+│       ├── survey_results_public.csv
+│       ├── survey_results_schema.csv
+│       └── ...
+│
+├── app/
+│   ├── __init__.py
+│   ├── main.py                    # Main FastAPI application
+│   ├── data_config.py            # Data source configuration & analysis
+│   └── templates/
+│       └── index.html            # Analytics dashboard frontend
+│
+└── tests/
+    ├── __init__.py
+    └── test_main.py              # Comprehensive test suite
+```
+
+## ⚓ Technology Stack
+
+- **Backend:** Python 3.10+ with FastAPI
+- **Data Analysis:** Pandas with flexible data source management
+- **Web Server:** Uvicorn with auto-reload
+- **Frontend:** HTML5, JavaScript (ES6+), Chart.js with interactive controls
+- **API Design:** RESTful with Pydantic models and comprehensive error handling
+- **Testing:** Pytest with full API coverage
+
+## 🔍 Analytics Features
+
+This application is designed specifically for **data analysts** who need:
+
+### 📊 Flexible Data Analysis
+- **Multiple Technology Categories**: Languages, Databases, Platforms, Web Frameworks
+- **Configurable Results**: Choose top 10, 15, 20, or 25 results
+- **Real-time Analysis**: Interactive dashboard with instant results
+- **Comparison Views**: "Have Worked With" vs "Want to Work With" analysis
+
+### 🔌 Extensible Data Sources
+- **Modular Design**: Easy to add new data sources
+- **Schema Validation**: Built-in data validation and error handling
+- **Multiple Format Support**: CSV with automatic schema detection
+- **Data Quality Insights**: Response counts and unique technology metrics
+
+## 🏴‍☠️ Setup Instructions
+
+### 1. Data Setup (Already Done!)
+
+The Stack Overflow 2023 survey data is already available in the `data/kaggle_so_2023/` directory with:
+- `survey_results_public.csv` - Main survey responses
+- `survey_results_schema.csv` - Data schema and column descriptions
+- Additional documentation files
+
+### 2. Install Dependencies
+
+Make sure ye have Python 3.10+ installed, then install the required packages:
+
+```bash
+# Activate the virtual environment (if ye haven't already)
+source venv/bin/activate  # On macOS/Linux
+# or
+venv\\Scripts\\activate   # On Windows
+
+# Install the treasure chest of dependencies
+pip install -r requirements.txt
+```
+
+### 3. Run the Application
+
+Start the FastAPI server like hoisting the main sail:
+
+```bash
+# Run the application with auto-reload
+uvicorn app.main:app --reload --host 0.0.0.0 --port 8000
+```
+
+### 4. Access the Analytics Dashboard
+
+Once the server be running, open yer browser and navigate to:
+- **Interactive Dashboard:** http://localhost:8000
+- **API Documentation:** http://localhost:8000/docs (FastAPI auto-generated)
+- **Data Sources API:** http://localhost:8000/api/data-sources
+
+## 🧪 Running Tests
+
+To run the comprehensive test suite:
+
+```bash
+# Run all tests with verbose output
+pytest -v
+
+# Run tests with coverage report
+pytest --cov=app --cov-report=html
+
+# Run specific test categories
+pytest tests/test_main.py::test_technology_analysis_endpoint -v
+```
+
+## 📊 API Endpoints
+
+### GET `/api/data-sources`
+- **Description:** Lists all available data sources and their analysis capabilities
+- **Response:** Array of data source information with available columns
+
+### GET `/api/analysis/technology-usage`
+- **Description:** Flexible technology usage analysis with multiple parameters
+- **Parameters:**
+  - `source`: Data source name (default: "stackoverflow_2023")
+  - `column`: Technology category to analyze (default: "LanguageHaveWorkedWith")
+  - `top_n`: Number of results to return (1-50, default: 10)
+- **Response:** Comprehensive analysis results with metadata
+
+### GET `/api/schema/{source_name}`
+- **Description:** Returns schema information for a data source
+- **Response:** Data structure and column definitions
+
+### GET `/api/languages/popular` (Legacy)
+- **Description:** Backward-compatible endpoint for original specification
+- **Response:** Top 10 programming languages in legacy format
+
+### GET `/`
+- **Description:** Interactive analytics dashboard
+- **Response:** Full-featured HTML dashboard with controls
+
+## 🎯 Data Analyst Features
+
+### 🔧 Interactive Analysis Controls
+- **Data Source Selection**: Choose from available datasets
+- **Technology Categories**: 8+ different analysis dimensions
+  - Programming Languages (Used/Wanted)
+  - Databases (Used/Wanted)  
+  - Platforms (Used/Wanted)
+  - Web Frameworks (Used/Wanted)
+- **Result Customization**: Adjustable result counts
+- **Real-time Updates**: Instant analysis with loading indicators
+
+### 📈 Rich Visualizations
+- **Interactive Bar Charts**: Hover details with percentages
+- **Color-coded Categories**: Professional color schemes
+- **Responsive Design**: Works on all screen sizes
+- **Export Ready**: High-quality charts suitable for presentations
+
+### 📊 Analysis Metadata
+- **Response Counts**: Total survey responses analyzed
+- **Technology Coverage**: Number of unique technologies found
+- **Data Quality**: Insights into data completeness
+- **Source Attribution**: Clear data provenance
+
+## 🚀 Future Enhancements for Data Analysts
+
+This application be designed with extensibility in mind! Future versions could include:
+
+### 📊 Advanced Analytics
+- **Cross-tabulation Analysis**: Technology combinations and correlations
+- **Trend Analysis**: Year-over-year comparisons when historical data is available
+- **Demographic Breakdowns**: Analysis by experience level, company size, location
+- **Salary Analysis**: Compensation trends by technology stack
+
+### 🔄 Data Pipeline Features
+- **Multiple Data Sources**: Support for different survey years and sources
+- **Data Refresh Automation**: Scheduled data updates and processing
+- **Data Quality Monitoring**: Automated validation and completeness checks
+- **Custom Data Uploads**: Allow analysts to upload their own datasets
+
+### 📈 Enhanced Visualizations
+- **Multiple Chart Types**: Scatter plots, heatmaps, time series
+- **Interactive Filtering**: Dynamic data exploration with multiple dimensions
+- **Export Capabilities**: PDF reports, CSV exports, chart images
+- **Dashboard Customization**: Save and share custom analysis configurations
+
+### 🔒 Enterprise Features
+- **User Authentication**: Multi-user support with role-based access
+- **API Rate Limiting**: Production-ready API with proper throttling
+- **Database Integration**: PostgreSQL/MongoDB for larger datasets
+- **Caching Layer**: Redis for improved performance with large datasets
+
+## 👥 For Data Analysts
+
+This application follows data analysis best practices:
+
+- **Reproducible Analysis**: All analysis parameters are configurable and documented
+- **Data Validation**: Built-in checks for data quality and completeness  
+- **Error Handling**: Graceful handling of missing data and edge cases
+- **Performance Optimization**: Efficient data processing for large datasets
+- **API-First Design**: Easy integration with other analysis tools and notebooks
+- **Comprehensive Testing**: Full test coverage ensures reliability
+
+## 🏴‍☠️ Development Notes
+
+- **Modular Architecture**: Easy to extend with new data sources and analysis types
+- **Clean Code Principles**: Well-documented, maintainable codebase
+- **Type Safety**: Pydantic models for API contract enforcement
+- **Async Support**: Built for high-performance concurrent requests
+- **Docker Ready**: Easy containerization for deployment
+- **All code be commented in proper pirate fashion, yarr!**
+
+## 📝 License
+
+This treasure be open source - use it freely for yer data analysis adventures, but remember to give credit where it be due!
+
+---
+
+*Built with ❤️ and ⚓ by data analyst pirates who love clean code, robust analysis, and beautiful visualizations*
+
+**Perfect for:** Data analysts, researchers, survey data exploration, technology trend analysis, and learning modern full-stack development with a focus on data science applications.

app/__init__.py

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+# Yarr! This be the main app package, matey!