Branch	Version	Status	Python
master
develop

KP Astrology Dashboard

A high-precision Krishnamurti Paddhati (KP) astrology calculator with convenient UI and Excel export functionality.

Overview

This project implements a KP (Krishnamurti Paddhati) Astrology Dashboard that generates accurate horary charts with precise sub-lord divisions. The application was built to address limitations in existing KP astrology platforms that often have poor design, paywalls, or present data in difficult-to-read formats.

The dashboard provides detailed astrological calculations with high precision for personal use and calculations, specifically designed for serious practitioners who need reliable KP Nanchang data.

Features

• Horary Chart Generation: Calculate precise horary charts based on horary numbers and exact ascendant timing
• Multiple Ayanamsa Support: Includes various ayanamsa options (Krishnamurti, Lahiri, Raman, Yukteshwar, etc.)
• Sub-Lord Calculations: High-precision sub-lord divisions based on KP astrology principles
• Vedic Horoscope Integration: Comprehensive Vedic astrological data integrated with KP system
• Excel Export: Clean data export to Excel for better readability and analysis
• Utility Functions: Conversion utilities for degrees, minutes, seconds, dates and time calculations
• Swiss Ephemeris Integration: Uses the Swiss Ephemeris for accurate planetary positions
• Automatic Updates: The application checks for updates on startup and can download and install new versions automatically

Technical Details

The application is built with Python and uses the following key components:

• Swiss Ephemeris (pyswisseph): For accurate planetary calculations
• Polars: For efficient data manipulation
• DateTime & DateUtil: For precise date-time handling
• Custom KP Sub-Lord Divisions: Preloaded from KP_SL_Divisions.csv for accurate subdivision calculations

Installation

# Clone the repository
git clone https://github.com/cryptekbits/KPAstroDashboard.git
cd KPAstroDashboard

# Install dependencies
pip install -r requirements.txt

# Run the application
python main.py

Dependencies

The application requires the following key dependencies:

• Python 3.13.2 or higher
• pyswisseph 2.10.3.2 or higher (Swiss Ephemeris library)
• PyQt5 5.15.0 or higher (GUI framework)
• polars-lts-cpu 1.23.0 or higher (Data processing)
• Other dependencies as listed in requirements.txt

Building from Source

The application can be built into standalone executables for Windows and macOS:

Windows Build (using py2exe)

# Install dependencies
pip install -r requirements.txt

# Create a Windows executable
python build_win.py --clean

The Windows executable will be created in the dist directory and copied to release_artifacts.

macOS Build (using py2app)

# Install dependencies
pip install -r requirements.txt

# Create a macOS application bundle
python build_mac.py clean py2app

The macOS application bundle will be created in the dist directory and copied to release_artifacts.

Build Process and Releases

Our build process follows these rules:

1. Development builds: The develop branch is automatically built when changes are pushed to it, but no release is created.
2. Production builds: The master branch is only built when a tag is pushed (e.g., v1.2.0).
3. Releases: GitHub releases are automatically created when:
   • A tag is pushed to the repository
   • A manual build is triggered via GitHub Actions UI (except for develop branch)

To create a release:

# Tag the commit
git tag v1.2.0
# Push the tag
git push origin v1.2.0

This will trigger a build and automatically create a release with Windows and macOS executables.

Building Windows Executable

To build a Windows executable using PyInstaller, follow these steps:

1. Install PyInstaller and all dependencies:

   pip install -r requirements.txt
   pip install pyinstaller
   

2. Run the build script:

   python tools/build_windows_exe.py
   

   This will create a standalone executable in the dist directory.

3. For a single-file executable, use the --onefile option:

   python tools/build_windows_exe.py --onefile
   

4. For debugging build issues, use the --debug option:

   python tools/build_windows_exe.py --debug
   

The executable will be created in the dist directory with the name KPAstrologyDashboard-{VERSION}.exe.

Automatic Builds

Windows executables are automatically built by GitHub Actions when a new release is created. The executable is included in the GitHub release assets.

To create a new release with the Windows executable:

1. Run the release creation script:

   python tools/create_release.py
   

2. Follow the prompts to create a new release.

3. The GitHub Actions workflow will build the Windows executable and add it to the release.

Usage

from horary_chart import find_exact_ascendant_time

# Example: Generate a horary chart for the given parameters
year = 2024
month = 2
day = 5
horary_number = 34
latitude, longitude, utc = 11.020085773931049, 76.98319647719487, "+5:30"  # Coimbatore
ayanamsa = "Krishnamurti"

# Get the exact time when ascendant matches the horary number's degree
matched_time, houses_chart, houses_data = find_exact_ascendant_time(
    year, month, day, utc, latitude, longitude, horary_number, ayanamsa
)

# Display the houses data
print(houses_data)

Project Roadmap

• Basic horary chart calculation with precise sub-lord divisions
• Multiple ayanamsa support
• Excel export functionality
• Build into a deployable web app (Heroku/PythonAnywhere)
• Add dynamically updating Excel and webapp
• Calculate important aspects for user-defined timeframes
• Implement Kundli charting as per Lahiri ayanamsa
• Draw inferences of astrological data for financial markets
• Find correlations between planets, signs, houses, and Nakshatras with financial data
• Predict major market moves for commodities, currency, and equities based on correlations

Dependencies

• polars
• swisseph (pyswisseph)
• prettytable
• python-dateutil
• datetime

Contribution

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

License

MIT License

Acknowledgements

• Thanks to Swiss Ephemeris for providing accurate astronomical data
• Thanks to the KP astrology community for documentation on sub-lord divisions

Building the Application

Prerequisites

• Python 3.13.2 or higher
• PyQt5
• Required Python packages (see requirements.txt)

Install Dependencies

pip install -r requirements.txt

Building the Application

# Build for the current platform
python build.py --clean

# Build for all supported platforms (requires Docker)
python build.py --clean --all-platforms

Cross-Compilation Issues

When cross-compiling the application (especially on Apple Silicon Macs), you might encounter issues with certain dependencies:

Common Issues:

1. PyQt5 Installation: PyQt5 requires Qt libraries to be installed on the system.
2. Native Extensions: Packages like pyswisseph require a C compiler and appropriate build tools.
3. Platform-specific Packages: Some packages like polars and numpy may have issues when cross-compiled.

Solutions:

1. Install Build Tools:

   • Windows: Install Microsoft Visual C++ Build Tools
   • macOS: Install Xcode Command Line Tools (xcode-select --install)
   • Linux: Install build-essential package (apt install build-essential)

2. Use Docker with Proper Dependencies:

   python build.py --clean --target-platform windows --target-arch x64 --alt-win-image

3. Build on Native Platforms: For best results, build each platform's executable on that platform:

   • Windows: Build on a Windows machine
   • Linux: Build on a Linux machine
   • macOS: Build on a Mac

Latest Version

Current Version: 1.3.0 (Ephemeris Handling & UX Improvements Release) Build Date: 2025-06-13

Repository Information

• GitHub Repository: https://github.com/cryptekbits/KPAstroDashboard

License

[License information here]

System Requirements

• Windows 10/11 or macOS 12+
• Python 3.13.2 or higher