
A python package for Vedic Astrology, with a particular focus on the Krishnamurthi Paddhati system
VedicAstro is an innovative Python library tailored for those interested in the intricate world of traditional Vedic Astrology. This package focuses on providing users with essential tools to generate chart and planetary position data, particularly utilizing the Krishnamurthi Paddhati (KP) system. By leveraging the sidereal capabilities of the flatlib library alongside data from the Swiss ephemeris, VedicAstro simplifies the complex process of astrological research and practice.
For anyone who aspires to deepen their understanding of Vedic Astrology or explore its practical applications, VedicAstro stands out as an indispensable resource. The library not only offers comprehensive functionalities for chart generation but also ensures an efficient setup process through clear installation instructions.
Chart Generation: Easily generate flatlib.Chart objects based on specific time and location data, making the initial step of astrological analysis straightforward.
Planetary Data: Retrieve detailed planetary data tables from generated chart objects, providing a clearer view of planetary positions.
House Data: Access houses data tables to gain insights into the astrological influences associated with different houses in a chart.
Significators: Generate ABCD significators for both planets and houses, enhancing the interpretative aspects of astrological readings.
Vimshottari Dasa Computation: Compute the Vimshottari Dasa, a crucial element in Vedic astrology, to understand planetary periods and their implications.
Planetary Aspects: Calculate significant aspects like Trine, Sextile, Square, and Conjunction between planets, which are key to interpreting interactions in a chart.
KP Horary Functionality: Special features for computing KP Horary (Prasna) charts, accommodating unique datetime requirements for ascendant calculations.
API Deployment: Easily deploy VedicAstro through FastAPI, enabling seamless integration into local or remote server environments for extended usability.
