v6.1.2: Merge 4 hidden modules from session workspace
Added modules: - ashtottari_dasha.py — 108-year cycle conditional dasha (BPHS Ch.19) - yogini_dasha.py — 36-year cycle, 8 Yoginis dasha system - kalachakra_dasha.py — Savya/Apasavya dual-mode dasha - report_orchestrator.py — 5-theme narrative report generator with cross-validation engine
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#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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kalachakra_dasha.py — Kalachakra Dasha System (Variable Cycle)
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The Kalachakra Dasha is one of the most intricate Nakshatra-based dasha systems.
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It is based on the Moon's Nakshatra and its Pada (quarter) at birth.
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Key Concepts:
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- 27 Nakshatras × 4 Padas = 108 Padas.
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- Each Pada maps to a specific Rashi (Zodiac sign).
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- Two directional modes:
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* Savya (clockwise / forward)
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* Apasavya (anti-clockwise / backward)
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- 9 lords (Navatara-like) govern the periods in a fixed sequence.
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Nakshatra Grouping (per standard texts):
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Savya (forward) Nakshatras:
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Ashwini, Bharani, Krittika, Ashlesha, Magha, Moola,
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Purva Ashadha, Uttara Ashadha, Shravana, Dhanishta, Shatabhisha
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Apasavya (backward) Nakshatras:
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Rohini, Mrigashira, Ardra, Punarvasu, Pushya, Chitra,
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Swati, Vishakha, Anuradha, Jyeshtha, Purva Bhadrapada,
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Uttara Bhadrapada, Revati
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(Note: Some authorities include Abhijit; this implementation uses the 27-Nakshatra scheme.)
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9-Lord Sequence:
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The 9 dasha lords correspond to the Navagraha sequence used in Kalachakra:
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1. Ketu 2. Venus 3. Sun 4. Moon 5. Mars 6. Mercury 7. Jupiter 8. Saturn 9. Rahu
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Their year allotments (one common traditional set):
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Ketu: 7, Venus: 20, Sun: 6, Moon: 10, Mars: 7,
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Mercury: 18, Jupiter: 16, Saturn: 19, Rahu: 17
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Total: 7+20+6+10+7+18+16+19+17 = 120 years
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However, Kalachakra is more commonly implemented with Rashi-based years.
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This module uses a simplified Rashi-year model (see _RASHI_YEARS below).
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Rashi Dasha Sequence and Years (simplified standard model):
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Savya mode (forward through zodiac):
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Capricorn 7 → Aquarius 8 → Pisces 9 → Aries 10 →
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Taurus 11 → Gemini 12 → Cancer 13 → Leo 14 →
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Virgo 15 → Libra 16 → Scorpio 17 → Sagittarius 18
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Total = 150 years
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Apasavya mode (backward through zodiac):
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Cancer 13 → Gemini 12 → Taurus 11 → Aries 10 →
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Pisces 9 → Aquarius 8 → Capricorn 7 → Sagittarius 18 →
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Scorpio 17 → Libra 16 → Virgo 15 → Leo 14
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Total = 150 years
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Each of the 9 lords rules one consecutive Rashi in the sequence.
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The starting point is determined by Moon's Nakshatra Pada.
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Reference: Brihat Parashara Hora Shastra and various classical commentaries on Kalachakra.
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"""
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from datetime import datetime, timedelta
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# ---------------------------------------------------------------------------
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# Constants
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# ---------------------------------------------------------------------------
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NAKSHATRAS = [
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"Ashwini", "Bharani", "Krittika", "Rohini", "Mrigashira", "Ardra",
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"Punarvasu", "Pushya", "Ashlesha", "Magha", "Purva Phalguni",
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"Uttara Phalguni", "Hasta", "Chitra", "Swati", "Vishakha",
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"Anuradha", "Jyeshtha", "Mula", "Purva Ashadha", "Uttara Ashadha",
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"Shravana", "Dhanishta", "Shatabhisha", "Purva Bhadrapada",
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"Uttara Bhadrapada", "Revati"
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]
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RASHIS = [
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"Aries", "Taurus", "Gemini", "Cancer", "Leo", "Virgo",
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"Libra", "Scorpio", "Sagittarius", "Capricorn", "Aquarius", "Pisces"
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]
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# 9 Kalachakra lords in order
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KALA_LORDS = [
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"Ketu", "Venus", "Sun", "Moon", "Mars",
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"Mercury", "Jupiter", "Saturn", "Rahu"
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]
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# Savya Rashi sequence (starting from Capricorn, forward)
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SAVYA_RASHI_SEQ = [9, 10, 11, 0, 1, 2, 3, 4, 5, 6, 7, 8]
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# Apasavya Rashi sequence (starting from Cancer, backward)
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APASAVYA_RASHI_SEQ = [3, 2, 1, 0, 11, 10, 9, 8, 7, 6, 5, 4]
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# Rashi year allotments (index 0-11)
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# Savya: Cap 7, Aqua 8, Pis 9, Ari 10, Tau 11, Gem 12, Can 13, Leo 14, Vir 15, Lib 16, Sco 17, Sag 18
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# Apasavya: Can 13, Gem 12, Tau 11, Ari 10, Pis 9, Aqua 8, Cap 7, Sag 18, Sco 17, Lib 16, Vir 15, Leo 14
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_RASHI_YEARS_SAVYA = {
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9: 7, 10: 8, 11: 9, 0: 10, 1: 11, 2: 12,
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3: 13, 4: 14, 5: 15, 6: 16, 7: 17, 8: 18
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}
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_RASHI_YEARS_APASAVYA = {
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3: 13, 2: 12, 1: 11, 0: 10, 11: 9, 10: 8,
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9: 7, 8: 18, 7: 17, 6: 16, 5: 15, 4: 14
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}
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# Nakshatra → mode mapping (Savya = True, Apasavya = False)
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# Per standard grouping
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SAVYA_NAKSHATRAS = {0, 1, 2, 8, 9, 18, 19, 20, 21, 22, 23}
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APASAVYA_NAKSHATRAS = {3, 4, 5, 6, 7, 13, 14, 15, 16, 17, 24, 25, 26}
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# Pada → starting Rashi offset within the sequence (simplified model)
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# For Savya: Pada 1 → Cap(0), Pada 2 → Aqu(1), Pada 3 → Pis(2), Pada 4 → Ari(3)
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# For Apasavya: Pada 1 → Can(0), Pada 2 → Gem(1), Pada 3 → Tau(2), Pada 4 → Ari(3)
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# The actual classical mapping is more nuanced; this is a practical approximation.
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PADA_OFFSET_MAP = {1: 0, 2: 1, 3: 2, 4: 3}
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# ---------------------------------------------------------------------------
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# Helper Functions
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# ---------------------------------------------------------------------------
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def _get_mode(nakshatra_index: int) -> str:
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"""Return 'savya' or 'apasavya' based on Nakshatra."""
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if nakshatra_index in SAVYA_NAKSHATRAS:
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return "savya"
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elif nakshatra_index in APASAVYA_NAKSHATRAS:
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return "apasavya"
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else:
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# Default fallback (should not happen with valid 0-26 input)
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return "savya"
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def _build_major_periods(mode: str, start_offset: int, birth_date: datetime) -> list:
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"""
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Build major periods for Kalachakra Dasha.
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Args:
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mode: 'savya' or 'apasavya'.
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start_offset: offset into the 12-sign Rashi sequence.
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birth_date: datetime of birth.
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Returns:
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list of period dicts.
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"""
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if mode == "savya":
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rashi_seq = SAVYA_RASHI_SEQ
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years_map = _RASHI_YEARS_SAVYA
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else:
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rashi_seq = APASAVYA_RASHI_SEQ
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years_map = _RASHI_YEARS_APASAVYA
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periods = []
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current_date = birth_date
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seq_len = len(rashi_seq)
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for i in range(seq_len):
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seq_idx = (start_offset + i) % seq_len
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rashi_idx = rashi_seq[seq_idx]
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lord_idx = i % 9 # 9 lords cycle through 12 rashis
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lord = KALA_LORDS[lord_idx]
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years = years_map[rashi_idx]
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end_date = current_date + timedelta(days=years * 365.25)
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periods.append({
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"lord": lord,
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"rashi": RASHIS[rashi_idx],
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"rashi_index": rashi_idx,
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"years": years,
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"start_date": current_date.isoformat(),
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"end_date": end_date.isoformat(),
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})
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current_date = end_date
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return periods
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# ---------------------------------------------------------------------------
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# Core Functions
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# ---------------------------------------------------------------------------
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def calculate_kalachakra_dasha(birth_info: dict) -> dict:
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"""
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Calculate Kalachakra Dasha for a native.
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Args:
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birth_info: dict containing:
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- "moon_nakshatra_index": int (0-26)
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- "moon_pada": int (1-4)
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- "birth_datetime": datetime object or ISO-format string (optional)
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Returns:
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dict with keys:
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- "mode": str — 'savya' or 'apasavya'
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- "major": list of major period dicts
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- "current": dict — the currently running major period
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- "total_cycle": int — sum of years in one full cycle
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- "starting_lord": str
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- "starting_rashi": str
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"""
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nakshatra_idx = birth_info.get("moon_nakshatra_index", 0)
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pada = birth_info.get("moon_pada", 1)
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birth_dt = birth_info.get("birth_datetime")
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if isinstance(birth_dt, str):
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birth_dt = datetime.fromisoformat(birth_dt)
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if birth_dt is None:
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birth_dt = datetime.now()
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# Clamp pada to 1-4
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if not 1 <= pada <= 4:
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pada = ((pada - 1) % 4) + 1
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mode = _get_mode(nakshatra_idx)
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start_offset = PADA_OFFSET_MAP.get(pada, 0)
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major_periods = _build_major_periods(mode, start_offset, birth_dt)
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total_cycle = sum(p["years"] for p in major_periods)
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starting_lord = major_periods[0]["lord"] if major_periods else None
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starting_rashi = major_periods[0]["rashi"] if major_periods else None
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# Determine current period
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now = datetime.now()
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current_period = None
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for p in major_periods:
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p_start = datetime.fromisoformat(p["start_date"])
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p_end = datetime.fromisoformat(p["end_date"])
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if p_start <= now < p_end:
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current_period = p.copy()
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current_period["elapsed_years"] = (now - p_start).days / 365.25
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current_period["remaining_years"] = (p_end - now).days / 365.25
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break
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return {
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"mode": mode,
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"major": major_periods,
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"current": current_period,
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"total_cycle": total_cycle,
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"starting_lord": starting_lord,
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"starting_rashi": starting_rashi,
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}
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# ---------------------------------------------------------------------------
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# Self-test
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# ---------------------------------------------------------------------------
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if __name__ == "__main__":
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# Example 1: Savya mode — Moon in Ashwini (Savya), Pada 1
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test_birth_1 = {
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"moon_nakshatra_index": 0, # Ashwini (Savya)
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"moon_pada": 1,
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"birth_datetime": datetime(1990, 6, 15, 10, 30),
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}
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result_1 = calculate_kalachakra_dasha(test_birth_1)
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print("=" * 70)
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print("Test 1: Moon in Ashwini (Savya), Pada 1")
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print("=" * 70)
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print(f"Mode : {result_1['mode']}")
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print(f"Starting Lord : {result_1['starting_lord']}")
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print(f"Starting Rashi : {result_1['starting_rashi']}")
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print(f"Total Cycle : {result_1['total_cycle']} years")
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print("Major Periods:")
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for p in result_1["major"]:
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print(f" {p['lord']:8s} | {p['rashi']:12s} | {p['years']:2d} years | {p['start_date'][:10]} → {p['end_date'][:10]}")
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print(f"Current Period : {result_1['current']}")
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print()
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# Example 2: Apasavya mode — Moon in Rohini (Apasavya), Pada 2
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test_birth_2 = {
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"moon_nakshatra_index": 3, # Rohini (Apasavya)
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"moon_pada": 2,
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"birth_datetime": datetime(1985, 3, 20, 8, 0),
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}
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result_2 = calculate_kalachakra_dasha(test_birth_2)
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print("=" * 70)
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print("Test 2: Moon in Rohini (Apasavya), Pada 2")
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print("=" * 70)
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print(f"Mode : {result_2['mode']}")
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print(f"Starting Lord : {result_2['starting_lord']}")
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print(f"Starting Rashi : {result_2['starting_rashi']}")
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print(f"Total Cycle : {result_2['total_cycle']} years")
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for p in result_2["major"]:
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print(f" {p['lord']:8s} | {p['rashi']:12s} | {p['years']:2d} years | {p['start_date'][:10]} → {p['end_date'][:10]}")
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print(f"Current Period : {result_2['current']}")
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print()
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# Example 3: Savya mode — Moon in Shravana (Savya), Pada 4
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test_birth_3 = {
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"moon_nakshatra_index": 21, # Shravana (Savya)
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"moon_pada": 4,
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"birth_datetime": datetime(2000, 1, 1, 0, 0),
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}
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result_3 = calculate_kalachakra_dasha(test_birth_3)
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print("=" * 70)
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print("Test 3: Moon in Shravana (Savya), Pada 4")
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print("=" * 70)
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print(f"Mode : {result_3['mode']}")
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print(f"Starting Lord : {result_3['starting_lord']}")
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print(f"Starting Rashi : {result_3['starting_rashi']}")
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print(f"Total Cycle : {result_3['total_cycle']} years")
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for p in result_3["major"]:
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print(f" {p['lord']:8s} | {p['rashi']:12s} | {p['years']:2d} years | {p['start_date'][:10]} → {p['end_date'][:10]}")
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