vedic-panchang 0.1.1

Open-source Vedic panchang and planetary position calculator. No API. No credits.

vedic-panchang

A fast, precise Vedic panchang and planetary position library for Python. Built on Swiss Ephemeris (JPL DE431 data). No API calls. No subscriptions. No limits.

pip install vedic-panchang

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What it computes

Everything is derived mathematically from planetary positions. No hardcoded almanac tables.

Element	Method
Planet longitudes (all 9)	Swiss Ephemeris + JPL DE431
Nakshatra (name, id, pada, lord)	moon_lon / 13.333°
Tithi (name, id, paksha, % elapsed)	(moon − sun) / 12°
Yoga (name, id)	(sun + moon) / 13.333°
Karana (name, id)	half-tithi division
Rasi (sign) for all 9 planets	longitude / 30°
Retrograde status	planet speed < 0
Moon phase angle	(moon − sun) % 360
Is Purnima / Amavasya	tithi index 14 or 29
Moon waxing / waning	tithi < 15
Gandanta	moon at water→fire sign junction
Nakshatra / Tithi / Yoga end time	bisection search on ephemeris
Sunrise / Sunset	Swiss Ephemeris rise_trans
Ayanamsa value	Swiss Ephemeris (Lahiri, Raman, KP, …)

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Quick start

from vedic_panchang import Panchang
from datetime import date

p = Panchang(
    date=date(2026, 1, 1),
    time=9.25,          # 09:15 local time
    lat=19.076,
    lon=72.877,
    tz=5.5,             # IST (default)
    ayanamsa="lahiri",  # default
)

Panchang elements

p.nakshatra          # "Purva Ashadha"
p.nakshatra_id       # 20
p.nakshatra_pada     # 3
p.nakshatra_lord     # "Venus"
p.nakshatra_degree   # 6.8421   (degrees into current nakshatra)
p.nakshatra_ends_at  # "2026-01-01T14:30:15+05:30"

p.tithi              # "Amavasya"
p.tithi_id           # 30
p.tithi_pct          # 87.4     (% of tithi elapsed)
p.paksha             # "Krishna"
p.tithi_ends_at      # "2026-01-02T07:45:22+05:30"

p.yoga               # "Vyaghata"
p.yoga_id            # 13
p.yoga_ends_at       # "2026-01-01T18:22:00+05:30"

p.karana             # "Kimstughna"
p.karana_id          # 11

p.vaara              # "Thursday"
p.sunrise            # "2026-01-01T07:14:00+05:30"
p.sunset             # "2026-01-01T18:18:00+05:30"

Planet positions

p.sun_longitude      # 266.200251
p.moon_longitude     # 261.542149
p.mercury_longitude  # 242.821571
p.venus_longitude    # 230.816996
p.mars_longitude     # 250.685927
p.jupiter_longitude  # 11.600357
p.saturn_longitude   # 310.006534
p.rahu_longitude     # 356.147849
p.ketu_longitude     # 176.147849

p.sun_rasi           # "Dhanu"
p.moon_rasi          # "Dhanu"
# all 9 planets have _rasi and _rasi_id

Retrograde & Moon

p.mercury_retrograde  # False
p.venus_retrograde    # False
p.mars_retrograde     # False
p.jupiter_retrograde  # False
p.saturn_retrograde   # False
p.retrograde_count    # 0

p.moon_phase_angle    # 355.34  (0=new moon, 180=full moon)
p.moon_waxing         # False
p.is_purnima          # False
p.is_amavasya         # True
p.moon_gandanta       # False

Export

p.to_dict()      # full snapshot as dict — 55+ fields
p.to_series()    # pandas.Series (requires pandas)

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Ayanamsa options

Panchang(..., ayanamsa="lahiri")        # default — Indian standard
Panchang(..., ayanamsa="raman")
Panchang(..., ayanamsa="krishnamurti")  # KP system
Panchang(..., ayanamsa="fagan_bradley")
Panchang(..., ayanamsa="de_luce")

p.ayanamsa        # "Lahiri"
p.ayanamsa_value  # 24.1983

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Performance

Fields use @cached_property — computed once, only when first accessed. Full to_dict() (55+ fields including boundary times) runs in < 5ms.

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Requirements

• Python 3.9+
• pyswisseph — installed automatically
• pandas — optional, only needed for to_series()

Swiss Ephemeris covers 5400 BCE to 5400 CE.

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License

MIT