ndastro-engine 0.23.0

A modern Vedic astrology calculation engine for Python, providing accurate astronomical calculations for birth charts, planetary positions, and ayanamsa systems.

NDAstro engine

A modern Python library for Vedic astronomical calculations, built on top of Skyfield. NDAstro engine provides a clean, intuitive API for computing planetary positions, sunrise/sunset times, lunar nodes (Rahu/Kethu), ascendant, and other astronomical events for any location on Earth.

Features

• 🪐 Planetary Positions - Calculate positions for Sun, Moon, Mars, Mercury, Jupiter, Venus, and Saturn. Calculations are based on Geocentric - Apparent positions with wobbling True Nodes.
• 🚀 Planetary Velocities - Get speed components (longitude, latitude, distance rates) for all planets
• 🌅 Sunrise & Sunset - Accurate sunrise and sunset times for any location
• 🌙 Lunar Nodes - Rahu (North Node) and Kethu (South Node) calculations
• ⬆️ Ascendant Calculation - Compute rising sign (Lagna) for any time and location
• ⏱️ Dasa Calculations - Multi-level dasa periods (Mahadasa, Antardasa, Pratyantardasa, Sookshmadasa) with Vimshottari system built-in; full extensibility for custom dasa systems
• 🔧 Type-safe Ayanamsa Systems - AyanamsaSystem TypeAlias covering 16 calculation methods (Lahiri, Raman, Krishnamurti, Fagan-Bradley, and more) with IDE autocomplete
• �🔄 16 Ayanamsa Systems - Comprehensive support for Vedic and Western sidereal systems:
  • Lahiri, Raman, Krishnamurti (KP New & Old), Fagan-Bradley
  • Traditional: Kali, Janma, Yukteshwar, Suryasiddhanta, Aryabhatta
  • Star-based: True Citra, True Revati, True Pusya, Ushashasi
  • Additional: Madhava, Vishnu, True ayanamsa
• � House & Nakshatra Enums - Houses with owner lookup; Nakshatras (27 lunar mansions) with lord lookup
• �🌍 WGS84 Coordinates - Support for standard latitude/longitude coordinates
• 📅 Date-based Queries - Calculate astronomical events for any date and time
• 🎯 High Precision - Powered by Skyfield using JPL ephemeris data (DE440s)
• ✅ Verified Accuracy - All ayanamsa values verified against astro-seek.com reference
• 🔧 Easy Configuration - Automatic ephemeris data management
• 🏷️ Type-safe Enum Codes - PlanetCode, HouseCode, NakshatraCode, RasiCode TypeAliases for safe string lookups via .code property and from_code() helpers
• 📦 Modern Python - Full type hints, clean API, and comprehensive test coverage

Installation

Install using pip:

pip install ndastro-engine

For development:

pip install ndastro-engine[dev]

Documentation

Full documentation is available at https://ndastro-engine.dhuruvah.in/

The documentation includes:

• 📖 Getting Started Guide - Installation and quick start tutorials
• 📚 User Guide - Detailed guides on ayanamsa, planets, retrograde, and sunrise/sunset calculations
• 🔍 API Reference - Complete API documentation with examples
• 📝 Contributing Guide - Information for contributors

Quick Start

from datetime import datetime
import pytz
from ndastro_engine.core import get_planet_position, get_planets_position, get_sunrise_sunset
from ndastro_engine.enums import Planets  # Simplified import

# Define location (New York City)
latitude = 40.7128
longitude = -74.0060
time = datetime(2026, 1, 6, 12, 0, 0, tzinfo=pytz.UTC)

# Get Sun's position (returns PlanetPosition named tuple)
position = get_planet_position(Planets.SUN, latitude, longitude, time)
print(f"Sun: Longitude {position.longitude:.2f}°, Latitude {position.latitude:.4f}°")
print(f"     Distance {position.distance:.4f} AU")
print(f"     Speed: {position.speed_longitude:.4f}°/day")

# Get all planetary positions
positions = get_planets_position([], latitude, longitude, time)
for planet, pos in positions.items():
    print(f"{planet.name}: {pos.longitude:.2f}° (moving {pos.speed_longitude:+.4f}°/day)")

# Get sunrise and sunset
sunrise, sunset = get_sunrise_sunset(latitude, longitude, time)
print(f"Sunrise: {sunrise}")
print(f"Sunset: {sunset}")

Usage Examples

Working with Enum Codes

from ndastro_engine.enums import Planets, Rasis, Houses, Nakshatras, PlanetCode, RasiCode

# Each enum exposes a .code property for type-safe string identifiers
print(Planets.SUN.code)        # "SU"
print(Rasis.ARIES.code)        # "AR"
print(Houses.HOUSE1.code)      # "H01"
print(Nakshatras.ASWINNI.code) # "ASW"

# Convert a code back to the enum
planet = Planets.from_code("MA")   # → Planets.MARS
rasi = Rasis.from_code("SC")        # → Rasis.SCORPIO  (returns None if invalid)
house = Houses.from_code("H7")      # → Houses.HOUSE7
nakshatra = Nakshatras.from_code("REV")  # → Nakshatras.REVATHI

# Rasi.from_string() is now safe — returns None instead of raising KeyError
rasi = Rasis.from_string("invalid")  # → None

Ayanamsa Calculation

from datetime import datetime
from ndastro_engine.ayanamsa import get_ayanamsa

# Calculate ayanamsa for a specific date
date = datetime(2026, 1, 15, 12, 0, 0)

lahiri = get_ayanamsa(date, "lahiri")
raman = get_ayanamsa(date, "raman")
kp = get_ayanamsa(date, "krishnamurti_new")
fagan = get_ayanamsa(date, "fagan_bradley")

print(f"Lahiri Ayanamsa: {lahiri:.4f}°")
print(f"Raman Ayanamsa: {raman:.4f}°")
print(f"KP New Ayanamsa: {kp:.4f}°")
print(f"Fagan-Bradley Ayanamsa: {fagan:.4f}°")

Dasa Calculations

from datetime import datetime
import pytz
from ndastro_engine.dasa import DasaContext, DasaQuery, get_dasa_timeline, get_running_dasa

# Create birth context (Vimshottari is default)
context = DasaContext(
    birth_datetime=datetime(1985, 10, 24, 6, 30, 0, tzinfo=pytz.UTC),
    lat=13.08,          # Chennai latitude
    lon=80.27,          # Chennai longitude
    ayanamsa_system="lahiri"
)

# Get 40-year timeline with 4 levels
timeline = get_dasa_timeline(context, DasaQuery(levels=4, years=40))

# Print first mahadasa
maha = timeline[0]
print(f"Mahadasa {maha.lord}: {maha.start_utc.date()} → {maha.end_utc.date()}")

# Find running dasa at a specific date
query_date = datetime(2026, 4, 18, 12, 0, 0, tzinfo=pytz.UTC)
running = get_running_dasa(query_date, context)
print(f"Current Mahadasa: {running.maha.lord if running.maha else 'N/A'}")
print(f"Current Antardasa: {running.antara.lord if running.antara else 'N/A'}")

Planetary Position Calculation

from datetime import datetime
import pytz
from ndastro_engine.core import get_planet_position
from ndastro_engine.enums import Planets
from ndastro_engine.ayanamsa import get_lahiri_ayanamsa

# Location: Mumbai, India
lat = 19.0760
lon = 72.8777
time = datetime(2026, 1, 15, 12, 0, 0, tzinfo=pytz.UTC)

# Get Jupiter's position (tropical)
position = get_planet_position(Planets.JUPITER, lat, lon, time)
print(f"Jupiter (Tropical): {position.longitude:.2f}°")
print(f"  Speed: {position.speed_longitude:+.4f}°/day")

# For sidereal/Vedic positions, calculate ayanamsa separately
ayanamsa = get_lahiri_ayanamsa(time)
sidereal_longitude = position.longitude - ayanamsa
print(f"Jupiter (Sidereal): {sidereal_longitude:.2f}°")

Get All Planetary Positions at Once

from datetime import datetime
import pytz
from ndastro_engine.core import get_planets_position
from ndastro_engine.enums import Planets

lat = 51.5074  # London
lon = -0.1278
time = datetime(2026, 3, 20, 0, 0, 0, tzinfo=pytz.UTC)

# Get positions for all planets including Rahu, Kethu, and Ascendant
positions = get_planets_position([], lat, lon, time)

for planet, pos in positions.items():
    if planet in [Planets.RAHU, Planets.KETHU, Planets.ASCENDANT]:
        print(f"{planet.name}: {pos.longitude:.2f}°")
    else:
        print(f"{planet.name}: {pos.longitude:.2f}° (Distance: {pos.distance:.4f} AU)")
        print(f"  Speed: {pos.speed_longitude:+.4f}°/day")

Basic Sunrise/Sunset Calculation

from datetime import datetime
from ndastro_engine.astro_engine import get_sunrise_sunset

# Location: London, UK
lat = 51.5074
lon = -0.1278

# Calculate for a specific date
date = datetime(2026, 1, 15)
sunrise, sunset = get_sunrise_sunset(lat, lon, date)

print(f"On {date.date()}, sunrise is at {sunrise.strftime('%H:%M:%S')} UTC")
print(f"On {date.date()}, sunset is at {sunset.strftime('%H:%M:%S')} UTC")

Working with Different Time Zones

from datetime import datetime
import pytz
from ndastro_engine.astro_engine import get_sunrise_sunset

# Location: Tokyo, Japan
lat = 35.6762
lon = 139.6503

# Get times in local timezone
date = datetime(2026, 6, 21)
sunrise_utc, sunset_utc = get_sunrise_sunset(lat, lon, date)

# Convert to Tokyo time
tokyo_tz = pytz.timezone('Asia/Tokyo')
sunrise_local = sunrise_utc.replace(tzinfo=pytz.UTC).astimezone(tokyo_tz)
sunset_local = sunset_utc.replace(tzinfo=pytz.UTC).astimezone(tokyo_tz)

print(f"Sunrise (Tokyo): {sunrise_local.strftime('%H:%M:%S %Z')}")
print(f"Sunset (Tokyo): {sunset_local.strftime('%H:%M:%S %Z')}")

Configuration

The library automatically downloads and caches the required JPL ephemeris data (DE441) on first use. The data is stored in your system's application data directory:

• Windows: %APPDATA%\ndastro
• macOS: ~/Library/Application Support/ndastro
• Linux: ~/.local/share/ndastro

This data is approximately 150 MB and only needs to be downloaded once.

API Reference

get_planet_position(planet, lat, lon, given_time)

Calculate the position of a specific planet.

Parameters:

• planet (Planets): The planet enum (e.g., Planets.SUN, Planets.MOON)
• lat (float): Latitude of the observer in decimal degrees
• lon (float): Longitude of the observer in decimal degrees
• given_time (datetime): The datetime of observation in UTC

Returns:

• PlanetPosition: Named tuple with attributes:
  • latitude (float): Planet's ecliptic latitude in degrees
  • longitude (float): Planet's ecliptic longitude in degrees
  • distance (float): Distance from Earth in AU
  • speed_latitude (float): Rate of latitude change in degrees/day
  • speed_longitude (float): Rate of longitude change in degrees/day
  • speed_distance (float): Rate of distance change in AU/day

Example:

from datetime import datetime
import pytz
from ndastro_engine.core import get_planet_position
from ndastro_engine.enums import Planets

position = get_planet_position(
    Planets.MARS, 
    34.0522, -118.2437,  # Los Angeles
    datetime(2026, 3, 20, tzinfo=pytz.UTC)
)
print(f"Mars longitude: {position.longitude:.2f}°")
print(f"Mars speed: {position.speed_longitude:+.4f}°/day")

get_planets_position(planets, lat, lon, given_time)

Calculate positions for all planets, including Rahu, Kethu, and Ascendant.

Parameters:

• planets (list[Planets]): List of planets to calculate (empty list returns all planets)
• lat (float): Latitude of the observer in decimal degrees
• lon (float): Longitude of the observer in decimal degrees
• given_time (datetime): The datetime of observation in UTC

Returns:

• dict[Planets, PlanetPosition]: Dictionary mapping each planet to its PlanetPosition named tuple

Example:

from datetime import datetime
import pytz
from ndastro_engine.core import get_planets_position

positions = get_planets_position(
    [],  # Empty list gets all planets
    12.97, 77.59,  # Bangalore, India
    datetime(2026, 1, 15, tzinfo=pytz.UTC)
)

for planet, pos in positions.items():
    print(f"{planet.name}: {pos.longitude:.2f}° @ {pos.speed_longitude:+.4f}°/day")

get_sunrise_sunset(lat, lon, given_time, elevation=914)

Calculate sunrise and sunset times for a specific location and date.

Parameters:

• lat (float): Latitude of the location in decimal degrees
• lon (float): Longitude of the location in decimal degrees
• given_time (datetime): The date for which to calculate sunrise/sunset
• elevation (float, optional): Elevation in meters (default: 914m)

Returns:

• tuple[datetime, datetime]: (sunrise, sunset) as UTC datetime objects

Example:

from datetime import datetime
import pytz
from ndastro_engine.core import get_sunrise_sunset

sunrise, sunset = get_sunrise_sunset(
    34.0522, -118.2437,  # Los Angeles
    datetime(2026, 3, 20, tzinfo=pytz.UTC)
)

Requirements

• Python 3.10 or higher
• skyfield >= 1.53
• pytz >= 2025.2

Development

Setting Up Development Environment

# Clone the repository
git clone https://github.com/jaganathanb/ndastro-core.git
cd ndastro-core

# Install with development dependencies
pip install -e .[dev]

# Verify installation by running tests
pytest tests/ -v

Development Dependencies Include:

• pytest>=9.0.2 - Testing framework
• pytest-cov>=6.0.0 - Coverage reporting
• pytest-xdist>=3.6.1 - Parallel test execution
• ruff>=0.14.10 - Linting and formatting
• mypy>=1.19.1 - Type checking

Running Tests

The project includes comprehensive test coverage with multiple ways to run tests:

# Run all tests with coverage (recommended)
pytest tests/

# Or using the test runner scripts:
# PowerShell (Windows)
.\run_tests.ps1

# Batch (Windows)
run_tests.bat coverage

# Make (cross-platform)
make test

Test Modes:

# Run only unit tests
pytest -m unit tests/

# Run fast tests (exclude slow tests)
pytest -m "not slow" tests/

# Run with verbose output
pytest tests/ -v

# Run in parallel (faster for large test suites)
pytest -n 4 tests/

# Generate HTML coverage report
pytest tests/ --cov=ndastro_engine --cov-report=html
# Then open htmlcov/index.html in your browser

Test Coverage:

• 69 total unit tests covering all core functionality
• Parametrized tests for comprehensive edge case coverage
• Test markers for easy filtering (unit, integration, slow)
• Automated coverage reporting

For detailed testing documentation, see TESTING.md.

Code Quality

The project uses:

• pytest for testing with coverage reporting
• pytest-cov for coverage analysis
• pytest-xdist for parallel test execution
• ruff for linting and formatting
• mypy for type checking

# Run linter
ruff check ndastro_engine/ tests/

# Run type checker
mypy ndastro_engine/

# Format code
ruff format ndastro_engine/ tests/

# Run all quality checks
make lint && make type-check && make test

Contributing

Contributions are welcome! Please feel free to submit a Pull Request. For major changes, please open an issue first to discuss what you would like to change.

1. Fork the repository
2. Create your feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

License

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

Acknowledgments

• Built on Skyfield by Brandon Rhodes
• Uses JPL ephemeris data (DE440t) for high-precision calculations
• Inspired by the need for a simple, modern astronomical calculation library

Support

• 📫 Email: jaganathan.eswaran at gmail.com
• 🐛 Issues: GitHub Issues
• 📖 Documentation: GitHub Repository

Roadmap

Coming Soon: Vedic Astrology Features 🕉️

The library will soon include comprehensive Vedic (Hindu/Indian) astrology functionalities:

Panchanga Calculations:

• Tithi (Lunar day) - All 30 tithis with precise timing
• Nakshatra (Lunar mansion) - 27 nakshatras with pada divisions
• Yoga - 27 yogas based on Sun-Moon positions
• Karana - Half-tithi divisions
• Vara (Weekday) - Traditional Hindu weekday system

Astrological Timings:

• Rahu Kala (Inauspicious period)
• Gulika Kala
• Yamaganda Kala
• Abhijit Muhurta (Auspicious time)
• Brahma Muhurta (Pre-dawn period)
• Dur Muhurtam (Inauspicious periods)

Planetary Calculations:

• Graha Sphuta (Planetary positions in sidereal zodiac)
• Ayanamsa corrections (Lahiri, Raman, Krishnamurti systems)
• Bhava (House) calculations
• Dasha periods (Vimshottari, Ashtottari, Yogini)
• Planetary strengths (Shadbala, Ashtakavarga)

Hora & Choghadiya:

• Hourly lord calculations
• Choghadiya divisions for day/night
• Auspicious/inauspicious period identification

Festival & Event Calculations:

• Hindu festival dates (Diwali, Holi, Navratri, etc.)
• Ekadashi dates
• Purnima (Full moon) and Amavasya (New moon)
• Sankranti (Solar transitions)
• Vyatipata and Vaidhriti yogas

Birth Chart Features:

• Rashi (Moon sign) calculations
• Lagna (Ascendant) determination
• Navamsa and other divisional charts
• Compatibility matching (Guna Milan)

Other Planned Features

• Moon phase calculations
• Solar and lunar eclipse predictions
• Planetary positions (Western tropical system)
• Twilight times (civil, nautical, astronomical)
• Constellation identification
• Custom observer elevation support

Changelog

See CHANGELOG.md for a list of changes.

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Made with ❤️ by Jaganathan B