Calculating Panchangam

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Inputs

• Latitude and longitude — Observation location (e.g. user’s saved coordinates).
• Timezone — IANA name (e.g. America/Los_Angeles, Asia/Kolkata) used for sunrise/sunset and all displayed times.
• Target date — Optional; if omitted, the current date in that timezone is used.
• Optional — include_transitions (whether to compute tithi/nakshatra/yoga/karana transition times during the day), city_detail (for location name/region in the output).

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Pipeline (how a panchangam is calculated)

1. Location — A single location is represented as an astral.LocationInfo (name, region, timezone, lat, lon). The backend builds this in app.py via create_location_with_timezone(); optionally it uses city_detail from the database for display name and region.
2. Date in timezone — The target date is interpreted in the given timezone (e.g. “today” in the user’s local time). Sunrise, sunset, and day divisions are all in that local time.
3. Sun and moon times — get_sun_moon_times(date, location) in panchangam_main.py uses the astral library to compute sunrise, sunset, solar noon, and (when possible) moonrise and moonset for that date and location.
4. Julian Day — get_julian_day(dt) in calculations.py uses Swiss Ephemeris (swisseph) to get the Julian Day for the given datetime. This is the time base for planetary positions.
5. Planet positions (sidereal) — get_planet_positions(jd) in calculations.py uses Swiss Ephemeris to get Sun and Moon positions, then applies an ayanamsa correction to convert from tropical to sidereal longitudes. The default ayanamsa is set in panchangam/config.py (e.g. Lahiri). Sidereal longitudes are used for all panchangam elements.
6. Panchangam elements — calculate_panchangam_elements(date, jd) in panchangam_main.py uses helpers from calculations.py to derive:
   • Tithi — Lunar day (1–30) from the Moon–Sun angle (each tithi = 12°).
   • Nakshatra — Lunar mansion (1–27) from Moon longitude (each segment ≈ 13°20′).
   • Yoga — From combined Sun+Moon longitude (27 segments).
   • Karana — Half-tithi (11 karanas: 7 variable + 4 fixed).
   • Paksha — Shukla (waxing) or Krishna (waning) from tithi.
   • Samvatsara, Masa, Ritu — Year name (60-year cycle), lunar month, and season from Sun longitude and date.
   Name constants (e.g. TITHI_NAMES, NAKSHATRA_NAMES) come from panchangam/config.py.
7. Day divisions — calculate_day_divisions(date, sunrise, sunset, solar_noon) in panchangam_main.py uses functions in calculations.py to compute:
   • Rahukalam — Weekday-dependent 1/8 of daylight.
   • Yamagandam — Similarly derived.
   • Gulika Kalam — Similarly derived.
   • Abhijit Muhurta — 24 minutes before and after solar noon.
8. Transitions (optional) — If include_transitions is true, find_transitions() in panchangam/transitions.py steps through the day (using Skyfield and segment rules from calculations.get_segment_angle) to find when tithi, nakshatra, yoga, or karana change. Results are attached to the panchangam dict as transitions.
9. Output structure — The result is a single dictionary with keys such as date, location, sun_moon_times, panchangam_elements, day_divisions, and optionally transitions. This is the same structure consumed by messaging.generate_panchangam_template_parameters and generate_panchangam_template_parameters_short to build WhatsApp template body parameters.

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Key files in panchangam/

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Where the backend uses the core logic

• app.py — generate_panchangam_with_timezone(latitude, longitude, timezone_name, target_date=None, include_transitions=True, include_horai=1, city_detail=None) builds the location, resolves the date in the given timezone, then calls panchangam_main.get_sun_moon_times, get_julian_day, calculate_panchangam_elements, calculate_day_divisions, and (if requested) find_transitions, and assembles the panchangam dict. Used by:
  • Webhook location handler (immediate panchangam after user shares location).
  • Test and admin routes (e.g. /test/whatsapp/generate/<phone_number>, /test/whatsapp/generate-coords).
  • tasks.send_for_timezone (daily 6:30 AM send) — which calls this with the user’s lat/lon, timezone, and current local date.
• tasks.py — send_for_timezone runs inside a Celery worker with a Flask app context; for each user in the timezone it calls generate_panchangam_with_timezone (with get_user_local_time(timezone_name) as target_date) and then messaging.send_panchangam_template.
• messaging.py — send_panchangam_template takes the panchangam dict and either uses generate_panchangam_template_parameters (long template, 42 params) or generate_panchangam_template_parameters_short (short template, 24 params). Those functions read from the same dict keys (panchangam_elements, sun_moon_times, day_divisions, transitions, etc.) and call panchangam.output.format_time / format_time_short for time strings. The resulting parameter list is sent via the WhatsApp template message API.