astrokundali 0.2.2

Generate and plot North-Indian Lagna Kundali charts using pyswisseph. Flexible astrokundali package with Different house calculation methods and interpretation JSONs

astrokundali

• version = "0.1.2"
• description = "Flexible astrokundali package with Different house calculation methods and interpretation JSONs"
• authors = name="Mirjan Ali Sha"
• requires-python = ">=3.7"

Request: If anyone would like to collaborate or discuss new features, please send me an email. I will get in touch with you.
If you want access to this project's source code, please do the same. I am planning to make this project fully open source in the near future.

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USER OPTIONS

Ayanāṃśa Options

• fagan_bradley
  Fagan–Bradley Ayanāṃśa: a Western sidereal offset fixed at 24°02′31″ (January 1 1950) and widely used in Western sidereal astrology.

• lahiri (default)
  Lahiri (Chitra‑Paksha/Rohini) Ayanāṃśa: India’s official Vedic ayanāṃśa, zeroed at Spica (Chitra), and by far the most prevalent in Hindu astrology.

• deluce
  de Luce Ayanāṃśa: proposed by Robert DeLuce (1877–1964), theoretically set to 1 CE but in practice anchored to ~26°24′47″ (1900) using Newcomb’s precession theory.

• raman
  Raman Ayanāṃśa: introduced by B. V. Raman to better align with traditional nakṣatra positions, favored by his school of Vedic astrology.

• krishnamurti
  Krishnamurti (KP) Ayanāṃśa: developed by K. S. Krishnamurti for the KP system, emphasizing precise divisional‑chart timing.

• sassanian
  Sassanian Ayanāṃśa: reconstructs pre‑Islamic Persian/Sassanian zodiac data (via Al‑Biruni), often used with whole‑sign houses for ancient chart revival.

• aldebaran
  Aldebaran Ayanāṃśa: fixes zero at the bright star Aldebaran (15° Taurus), popular in fixed‑star and esoteric charting.

• galcenter
  Galcenter Ayanāṃśa: anchors the zodiac at the Milky Way’s center (~5° Sagittarius), used in modern “galactic” sidereal astrology.

House‑System Options

• equal
  Equal Houses: twelve 30° houses measured from the exact Ascendant degree, offering simplicity and uniformity across latitudes.

• whole_sign (default)
  Whole‑Sign: the sign containing the Ascendant becomes the 1st house, the next sign the 2nd, etc.; the oldest division from Hellenistic to Vedic traditions.

• porphyry
  Porphyry: each quadrant (Ascendant→MC, MC→Descendant, etc.) is trisected into three equal parts, creating houses by trisection of angle arcs; described by Vettius Valens in the 2nd CE.

• placidus
  Placidus: the most common Western quadrant system, trisecting diurnal/nocturnal arcs between the four angles to set cusps; can fail near polar circles.

• koch
  Koch: a time‑based quadrant method dividing right‑ascension arcs equally between angles; popular in research and German circles, defined only within ~66° latitude.

• campanus
  Campanus: divides the prime vertical into twelve equal segments, projecting them onto the ecliptic; emphasizes Earth‑centered spatial divisions.

• regiomontanus
  Regiomontanus: splits the celestial equator into twelve equal arcs then projects those onto the ecliptic; a medieval Renaissance favorite attributed to Johann Müller.

Example Usage

  pip install astrokundali
  or
  !pip install astrokundali [Notebook]
    

Configure AstroData

    from astrokundali import AstroData
    data = AstroData(2009,3,30,9,36,0,5,30,19.0760,72.8777,ayanamsa='lahiri')
  

Plot Lagna Chart

    from astrokundali import plot_lagna_chart
    houses = plot_lagna_chart(data, house_system= 'whole_sign') 
      or 
    houses = plot_lagna_chart(data) 
  

Plot Moon/Chandra Chart

from astrokundali import plot_moon_chart
houses = plot_moon_chart(data, house_system= 'whole_sign')
or
houses = plot_moon_chart(data)

Plot Navamsa/Navamsha/D9 Chart

    from astrokundali import plot_navamsa_chart
    houses = plot_navamsa_chart(data, house_system= 'whole_sign') 
      or 
    houses = plot_navamsa_chart(data)
  

Read Astrokundali House Objects

   from astrokundali import format_houses        
   import json
   readable = format_houses(houses) 
   print(json.dumps(readable, indent=2))
  

Get Planetary Positions and Dispositions

    from astrokundali import get_dispositions
    import json
    disp = get_dispositions(data, house_system= 'whole_sign')
      or
    disp = get_dispositions(data)
    print(json.dumps(report, ensure_ascii=False, indent=2)) 
  

Get Interpretation Report

    from astrokundali import generate_report, json_sanitize
    import json
    report  = json_sanitize(generate_report(data, house_system= 'whole_sign'))
      or
    report  = json_sanitize(generate_report(data))
    print(json.dumps(report, ensure_ascii=False, indent=2))
  

• to use json_sanitize function please install ftfy using pip install ftfy
  Marriage Matching

    from astrokundali import AstroData, match_kundli
    boy = AstroData(1990,1,1,10,0,0,5,30,19.07,72.88)
    girl = AstroData(1992,6,15,16,30,0,5,30,28.61,77.23)
    from pprint import pprint
    pprint(match_kundli(boy, girl))
      or
    from astrokundali import AstroData, match_kundli
    boy = AstroData(1990,1,1,10,0,0,5,30,19.07,72.88,ayanamsa='lahiri')
    girl = AstroData(1992,6,15,16,30,0,5,30,28.61,77.23,ayanamsa='lahiri')
    from pprint import pprint
    pprint(match_kundli(boy, girl, house_system= 'whole_sign')) [Version should be >=0.2.1]
  

Format Match Table in Pandas DataFrame

    from astrokundali import AstroData, match_kundli
    boy = AstroData(1990,1,1,10,0,0,5,30,19.07,72.88)
    girl = AstroData(1992,6,15,16,30,0,5,30,28.61,77.23)
    astro_match = match_kundli(boy, girl)
    print(astro_match['interpretation'])
    import pandas as pd
    df = pd.DataFrame(astro_match['table'])
    df