Compare commits
5 Commits
| Author | SHA1 | Date | |
|---|---|---|---|
| 73f39e7df8 | |||
| c4a181b810 | |||
| 97ad21d2e4 | |||
| 2dbd3410e9 | |||
| ca458fd741 |
@@ -0,0 +1,19 @@
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name: build
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on:
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push:
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branches: [main]
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jobs:
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build:
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v4
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- name: Login
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run: echo "${{ secrets.REGISTRY_TOKEN }}" | docker login gitea.czernobog.pl -u gitea --password-stdin
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- name: Build & push (data, logic, presentation)
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run: |
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TAG=${GITHUB_SHA::8}
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for SVC in data logic presentation; do
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docker build -t gitea.czernobog.pl/gitea/astrololo-$SVC:$TAG ./services/$SVC
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docker push gitea.czernobog.pl/gitea/astrololo-$SVC:$TAG
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done
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echo "Tag: $TAG"
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@@ -10,6 +10,7 @@ i nie w bazie.
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- `POST /chart/report` → `{when_utc, lat, lon, limit?}` → wynik obliczeń wyszukany w bazie: fasety sygnifikatorów **w znaku / w domu / w aspekcie**, z rozwinięciem skrótów, odsiewaniem duplikatów (ten sam sygnifikator i opis), rankingiem siły (LOG-21) oraz opcją group (grupowanie identycznych opisów)
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- `POST /chart/profections` → `{when_utc, lat, lon, start_age?, count?}` → profekcje roczne: wiek, profektowany Asc, Władca Roku (+MC/Su/Mo) (LOG-10)
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- `POST /chart/return` → `{when_utc, lat, lon, kind, around?}` → Solar/Lunar Return: moment powrotu + pełny horoskop na ten moment (LOG-12)
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- `POST /chart/timeline` → `{when_utc, lat, lon, from_date, to_date, techniques?}` → zbiorcza oś czasu: profekcje + Solar Return + dyrekcje solar-arc, posortowane (technique | significator | start | exact | end); z interpret=true dopina interpretacje z bazy do dat (LOG-14, 1B->2B)
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- `POST /chart/compare` → jak wyżej → raport różnic dwóch silników (LOG-26; wymaga silnika B)
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- `GET /health` (sprawdza też warstwę bazodanową)
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@@ -0,0 +1,136 @@
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"""Zbiorcza tabela dat z technik (LOG-14).
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Spina w jedną, posortowaną oś czasu daty z kilku technik:
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- profekcje roczne (LOG-10) — rok życia,
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- Solar Return (LOG-12) — moment powrotu Słońca,
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- dyrekcje solar-arc — daty dokładnych aspektów kierowanych planet do punktów
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natalnych (wzorzec z notes3: „Profection planet | Aspect | Birth planet |
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Exact Date"). Klucz łuku konfigurowalny; domyślnie Naiboda (0°59'08"/rok).
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Każdy wiersz ma kształt z notes2: technique | significator | start | exact | end.
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"""
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from __future__ import annotations
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from datetime import date, datetime, timedelta, timezone
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from app.engine.aspects import MAJOR, PL_NAME
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from app.engine.profections import DOMICILE_RULERS, profected_sign
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from app.engine.returns import find_return
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NAIBOD_KEY = 0.9856472 # °/rok (0°59'08") — domyślny klucz solar-arc
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DAYS_PER_YEAR = 365.2422
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DIRECTED = ["Sun", "Moon", "Mercury", "Venus", "Mars",
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"Jupiter", "Saturn", "Uranus", "Neptune", "Pluto"]
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def _add_years(birth: datetime, years: float) -> datetime:
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return birth + timedelta(days=years * DAYS_PER_YEAR)
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def _row(technique, significator, start, exact, end) -> dict:
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def iso(x):
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return x.date().isoformat() if isinstance(x, datetime) else x
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return {"technique": technique, "significator": significator,
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"start": iso(start), "exact": iso(exact), "end": iso(end)}
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def solar_arc_directions(
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natal: dict[str, float], birth: datetime, lo: datetime, hi: datetime,
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key: float = NAIBOD_KEY, orb_years: float = 1.0,
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) -> list[dict]:
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"""Daty dyrekcji solar-arc w oknie [lo, hi].
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natal: nazwa punktu -> długość natalna (planety + Asc/MC). Kierowane są planety
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(DIRECTED), celem każdy punkt natalny. Aspekt dokładny gdy łuk = odległość
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kątowa (mod 360). Wiek = łuk/klucz; data = urodziny + wiek.
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"""
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out: list[dict] = []
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lo_age = (lo - birth).days / DAYS_PER_YEAR - orb_years
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hi_age = (hi - birth).days / DAYS_PER_YEAR + orb_years
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for p in DIRECTED:
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if p not in natal:
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continue
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for q, q_lon in natal.items():
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for asp, angle in MAJOR.items():
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for target in ({angle, (360.0 - angle) % 360.0}):
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arc = (q_lon + target - natal[p]) % 360.0
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age = arc / key
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if not (lo_age <= age <= hi_age) or (p == q and arc < 1e-6):
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continue
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exact = _add_years(birth, age)
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row = _row(
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"solar_arc",
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f"dyr. {p} {PL_NAME[asp]} {q}",
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_add_years(birth, age - orb_years),
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exact,
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_add_years(birth, age + orb_years),
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)
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row.update(directed=p, aspect=asp, target=q) # do budowy tokenów (1B->2B)
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out.append(row)
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return out
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def profection_events(natal_asc: float, birth: datetime, lo: datetime, hi: datetime) -> list[dict]:
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"""Lata profekcyjne (LOG-10) nachodzące na okno."""
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out: list[dict] = []
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for age in range((lo.year - birth.year) - 1, (hi.year - birth.year) + 1):
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if age < 0:
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continue
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try:
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start = birth.replace(year=birth.year + age)
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end = birth.replace(year=birth.year + age + 1)
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except ValueError: # 29 lutego
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start = birth.replace(year=birth.year + age, day=28)
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end = birth.replace(year=birth.year + age + 1, day=28)
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if end < lo or start > hi:
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continue
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sign = profected_sign(natal_asc, age)
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lord = DOMICILE_RULERS[sign]
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row = _row(
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"profection", f"Władca Roku: {lord} (Asc {sign}, wiek {age})",
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start, start, end,
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)
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row.update(lord=lord, sign=sign) # do budowy tokenów (1B->2B)
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out.append(row)
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return out
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def solar_return_events(engine, natal_moment, birth: datetime, lo: datetime, hi: datetime) -> list[dict]:
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"""Solariusze w oknie (LOG-12) — jeden na rok."""
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out: list[dict] = []
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for year in range(lo.year, hi.year + 1):
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try:
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around = birth.replace(year=year)
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except ValueError:
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around = birth.replace(year=year, day=28)
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hit = find_return(engine, "solar", natal_moment, around)
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if hit and lo <= hit <= hi:
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out.append(_row("solar_return", "Solar Return", hit, hit, _add_years(hit, 1)))
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return out
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def _as_dt(d) -> datetime:
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if isinstance(d, datetime):
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return d if d.tzinfo else d.replace(tzinfo=timezone.utc)
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if isinstance(d, date):
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return datetime(d.year, d.month, d.day, tzinfo=timezone.utc)
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return datetime.fromisoformat(str(d)).replace(tzinfo=timezone.utc)
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def build_timeline(
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engine, natal_moment, natal_points: dict[str, float],
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from_d, to_d, techniques: list[str] | None = None,
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) -> list[dict]:
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"""Scala wybrane techniki w jedną oś czasu, posortowaną po dacie dokładnej."""
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lo, hi = _as_dt(from_d), _as_dt(to_d)
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birth = natal_moment.when_utc
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want = set(techniques or ["profection", "solar_return", "solar_arc"])
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events: list[dict] = []
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if "profection" in want:
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events += profection_events(natal_points["Asc"], birth, lo, hi)
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if "solar_return" in want:
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events += solar_return_events(engine, natal_moment, birth, lo, hi)
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if "solar_arc" in want:
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events += solar_arc_directions(natal_points, birth, lo, hi)
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events.sort(key=lambda e: e["exact"])
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return events
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@@ -173,6 +173,45 @@ def chart_return(req: ReturnRequest) -> dict:
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"return_utc": hit.isoformat(), **chart}
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class TimelineRequest(BaseModel):
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when_utc: datetime # moment urodzenia (UTC)
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lat: float = 0.0
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lon: float = 0.0
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from_date: str # zakres: YYYY-MM-DD
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to_date: str
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techniques: list[str] | None = None # profection | solar_return | solar_arc
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interpret: bool = False # dopnij interpretacje z bazy (1B->2B)
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@app.post("/chart/timeline")
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def chart_timeline(req: TimelineRequest) -> dict:
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"""Zbiorcza oś czasu z technik (LOG-14): technique | significator | start | exact | end.
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Z interpret=true dopina do zdarzeń interpretacje z warstwy danych (LOG-19, 1B->2B).
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"""
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from app.engine import houses as H
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from app.engine.models import ChartMoment
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from app.engine.timeline import build_timeline
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engine = get_engine()
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natal = ChartMoment(when_utc=req.when_utc, lat=req.lat, lon=req.lon)
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ramc, eps = engine.sidereal(natal)
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points = {"Asc": H.compute_asc(ramc, eps, natal.lat), "MC": H.compute_mc(ramc, eps)}
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for p in engine.positions(natal):
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points[p.name] = p.longitude
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events = build_timeline(engine, natal, points, req.from_date, req.to_date, req.techniques)
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out = {"engine": engine.name, "from": req.from_date, "to": req.to_date}
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if req.interpret:
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from app.significators import interpret_events
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try:
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interpret_events(events, DataClient())
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except httpx.HTTPError as e:
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out["data_error"] = f"Warstwa danych niedostępna: {e}"
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out.update(count=len(events), events=events)
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return out
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@app.get("/health")
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def health() -> dict:
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info = {"status": "ok", "layer": "logic"}
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@@ -195,3 +195,52 @@ def build_report(
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"facets": facets,
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})
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return {"provider": provider, "objects": items}
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def _event_tokens(event: dict) -> list[str]:
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"""Tokeny bazy dla zdarzenia osi czasu (spięcie 1B→2B). Pierwszy = planeta."""
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from app.engine.aspects import DB_TOKEN
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if event.get("technique") == "solar_arc":
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p = PLANET_ABBR.get(event.get("directed"))
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a = DB_TOKEN.get(event.get("aspect"))
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q = PLANET_ABBR.get(event.get("target")) # None dla Asc/MC (nie ma tokenu)
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toks = []
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if p:
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toks.append("[" + p)
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if a:
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toks.append(a)
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if q:
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toks.append("[" + q)
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return toks if p else []
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if event.get("technique") == "profection":
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lord = PLANET_ABBR.get(event.get("lord"))
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sign = SIGN_TO_ABBR.get(event.get("sign"))
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toks = []
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if lord:
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toks.append("[" + lord)
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if sign:
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toks.append("[" + sign)
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return toks if lord else []
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return []
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def interpret_events(events: list[dict], data: DataSource, limit: int = 4,
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per_object_limit: int = 5000) -> list[dict]:
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"""Dopina interpretacje z bazy do zdarzeń osi czasu (predykcyjne 1B → 2B).
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Wyszukuje po tokenie planety zdarzenia i zawęża do wszystkich tokenów
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(aspekt/druga planeta lub znak), z odsiewaniem szumu i duplikatów.
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"""
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for ev in events:
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tokens = _event_tokens(ev)
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if not tokens:
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continue
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raw = data.search(
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key="significator", value=tokens[0], exact=False, limit=per_object_limit,
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fields=["significator", "actioneffect", "topicresult", "bodypart"],
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)
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samples = _facet_samples(raw.get("rows", []), tokens)
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ev["interpretations"] = samples[:limit]
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ev["interpretations_count"] = len(samples)
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return events
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@@ -0,0 +1,71 @@
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"""Zbiorcza oś czasu z technik (LOG-14)."""
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import datetime as dt
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from app.engine.timeline import (
|
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NAIBOD_KEY,
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build_timeline,
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profection_events,
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solar_arc_directions,
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)
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BIRTH = dt.datetime(1984, 4, 30, 7, 35, tzinfo=dt.timezone.utc)
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# natalne długości (z horoskopu referencyjnego)
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NATAL = {
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"Asc": 112.18, "MC": 352.59, "Sun": 40.14, "Moon": 30.55, "Mercury": 27.38,
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"Venus": 27.68, "Mars": 234.54, "Jupiter": 282.96, "Saturn": 223.31,
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"Uranus": 252.81, "Neptune": 271.22, "Pluto": 210.48,
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}
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def _win(y0, y1):
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return (dt.datetime(y0, 1, 1, tzinfo=dt.timezone.utc),
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dt.datetime(y1, 12, 31, tzinfo=dt.timezone.utc))
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def test_profection_events_in_window():
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lo, hi = _win(2024, 2026)
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rows = profection_events(NATAL["Asc"], BIRTH, lo, hi)
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# rok profekcyjny wiek 42 zaczyna się 30.04.2026 -> Asc Capricorn
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ages = [r["significator"] for r in rows]
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assert any("Asc Capricorn" in a and "wiek 42" in a for a in ages)
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|
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|
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def test_solar_arc_exact_matches_arc_over_key():
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lo, hi = _win(2020, 2030)
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rows = solar_arc_directions(NATAL, BIRTH, lo, hi, key=NAIBOD_KEY)
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assert rows, "brak dyrekcji w oknie"
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# dla każdej dyrekcji: łuk = (wiek * klucz), a data = urodziny + wiek -> spójne
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for r in rows[:5]:
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exact = dt.date.fromisoformat(r["exact"])
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age_years = (dt.datetime(exact.year, exact.month, exact.day, tzinfo=dt.timezone.utc)
|
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- BIRTH).days / 365.2422
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assert 36 <= age_years <= 47 # okno 2020-2030 = wiek ~36-46
|
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assert r["technique"] == "solar_arc" and "dyr." in r["significator"]
|
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|
||||
|
||||
def test_directed_sun_conjunct_natal_mc_date():
|
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# Sun natal 40.14 -> MC natal 352.59: łuk koniunkcji = (352.59-40.14)%360 = 312.45
|
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# to > lifespan przy Naibod (~317 lat) -> NIE powinno być w oknie życia
|
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lo, hi = _win(1984, 2084)
|
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rows = solar_arc_directions(NATAL, BIRTH, lo, hi)
|
||||
sun_mc = [r for r in rows if r["significator"] == "dyr. Sun koniunkcja MC"]
|
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assert not sun_mc # łuk 312° = poza życiem
|
||||
|
||||
|
||||
def test_build_timeline_sorted_and_merged():
|
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events = build_timeline(_FakeEngine(), _FakeNatal(), NATAL,
|
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"2025-01-01", "2027-01-01",
|
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techniques=["profection", "solar_arc"])
|
||||
assert events
|
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dates = [e["exact"] for e in events]
|
||||
assert dates == sorted(dates) # posortowane po dacie dokładnej
|
||||
techs = {e["technique"] for e in events}
|
||||
assert "profection" in techs and "solar_arc" in techs
|
||||
|
||||
|
||||
class _FakeNatal:
|
||||
when_utc = BIRTH
|
||||
|
||||
|
||||
class _FakeEngine:
|
||||
"""Silnik-atrapa — build_timeline z solar_return by go użył, tu go pomijamy."""
|
||||
@@ -0,0 +1,46 @@
|
||||
"""Spięcie osi czasu z bazą interpretacji (LOG-14 → 1B→2B)."""
|
||||
from app.significators import _event_tokens, interpret_events
|
||||
|
||||
|
||||
class FakeData:
|
||||
def __init__(self, rows_by_value):
|
||||
self.rows_by_value = rows_by_value
|
||||
|
||||
def search(self, key, value, exact, limit, fields=None):
|
||||
rows = self.rows_by_value.get(value, [])
|
||||
return {"provider": "fake", "total": len(rows), "rows": rows}
|
||||
|
||||
|
||||
def test_event_tokens_solar_arc():
|
||||
ev = {"technique": "solar_arc", "directed": "Venus", "aspect": "conjunction", "target": "North Node"}
|
||||
assert _event_tokens(ev) == ["[Ve", "[conj", "[NN"]
|
||||
|
||||
|
||||
def test_event_tokens_solar_arc_to_angle_has_no_target_token():
|
||||
ev = {"technique": "solar_arc", "directed": "Sun", "aspect": "square", "target": "MC"}
|
||||
assert _event_tokens(ev) == ["[Su", "[sq"] # MC nie ma tokenu planety
|
||||
|
||||
|
||||
def test_event_tokens_profection():
|
||||
ev = {"technique": "profection", "lord": "Saturn", "sign": "Capricorn"}
|
||||
assert _event_tokens(ev) == ["[Sa", "[Cap"]
|
||||
|
||||
|
||||
def test_solar_return_has_no_tokens():
|
||||
assert _event_tokens({"technique": "solar_return"}) == []
|
||||
|
||||
|
||||
def test_interpret_attaches_matches_with_all_tokens():
|
||||
events = [
|
||||
{"technique": "solar_arc", "directed": "Venus", "aspect": "conjunction", "target": "North Node"},
|
||||
{"technique": "solar_return"},
|
||||
]
|
||||
data = FakeData({"[Ve": [
|
||||
{"significator": "[Ve [conj [NN", "actioneffect": "spotkanie losowe"}, # wszystkie tokeny
|
||||
{"significator": "[Ve [conj [Mo", "actioneffect": "inny"}, # brak [NN
|
||||
{"significator": "[Ve [conj [NN", "actioneffect": "spotkanie losowe"}, # duplikat
|
||||
]})
|
||||
interpret_events(events, data)
|
||||
assert events[0]["interpretations_count"] == 1 # duplikat odsiany, tylko z [NN
|
||||
assert events[0]["interpretations"][0]["expanded"] == "Venus conjunction North Node"
|
||||
assert "interpretations" not in events[1] # solar_return pominięty
|
||||
@@ -56,3 +56,17 @@ class LogicClient:
|
||||
r = client.post(f"{self.base_url}/chart/report", json=payload)
|
||||
r.raise_for_status()
|
||||
return r.json()
|
||||
|
||||
def timeline(
|
||||
self, when_utc_iso: str, lat: float, lon: float,
|
||||
from_date: str, to_date: str, interpret: bool = True,
|
||||
) -> dict[str, Any]:
|
||||
"""Oś czasu z technik (+interpretacje z bazy) — woła logic /chart/timeline."""
|
||||
payload = {
|
||||
"when_utc": when_utc_iso, "lat": lat, "lon": lon,
|
||||
"from_date": from_date, "to_date": to_date, "interpret": interpret,
|
||||
}
|
||||
with httpx.Client(timeout=max(settings.http_timeout, 60.0)) as client:
|
||||
r = client.post(f"{self.base_url}/chart/timeline", json=payload)
|
||||
r.raise_for_status()
|
||||
return r.json()
|
||||
|
||||
@@ -132,6 +132,40 @@ def interpret_run(
|
||||
return templates.TemplateResponse(request, "interpret.html", ctx)
|
||||
|
||||
|
||||
# ---------------- Kalendarz (oś czasu z technik + interpretacje) ----------------
|
||||
@app.get("/timeline", response_class=HTMLResponse)
|
||||
def timeline_form(request: Request):
|
||||
return templates.TemplateResponse(request, "timeline.html", {"result": None, "form": {}})
|
||||
|
||||
|
||||
@app.post("/timeline", response_class=HTMLResponse)
|
||||
def timeline_run(
|
||||
request: Request,
|
||||
date: str = Form(...),
|
||||
time: str = Form(...),
|
||||
tz_offset: float = Form(0.0),
|
||||
lat: float = Form(0.0),
|
||||
lon: float = Form(0.0),
|
||||
from_date: str = Form(...),
|
||||
to_date: str = Form(...),
|
||||
):
|
||||
form = {"date": date, "time": time, "tz_offset": tz_offset, "lat": lat, "lon": lon,
|
||||
"from_date": from_date, "to_date": to_date}
|
||||
ctx: dict = {"form": form, "result": None, "error": None, "moment": None}
|
||||
try:
|
||||
iso_utc, label = _build_utc(date, time, tz_offset)
|
||||
ctx["moment"] = label
|
||||
ctx["result"] = logic.timeline(
|
||||
when_utc_iso=iso_utc, lat=lat, lon=lon,
|
||||
from_date=from_date, to_date=to_date, interpret=True,
|
||||
)
|
||||
except httpx.HTTPError as e:
|
||||
ctx["error"] = _logic_error(e)
|
||||
except ValueError as e:
|
||||
ctx["error"] = f"Niepoprawne dane wejściowe: {e}"
|
||||
return templates.TemplateResponse(request, "timeline.html", ctx)
|
||||
|
||||
|
||||
@app.get("/health")
|
||||
def health() -> dict:
|
||||
return {"status": "ok", "layer": "presentation"}
|
||||
|
||||
@@ -13,6 +13,7 @@
|
||||
<nav>
|
||||
<a href="/" class="{% block nav_chart %}{% endblock %}">Horoskop</a>
|
||||
<a href="/interpret" class="{% block nav_interp %}{% endblock %}">Interpretacje</a>
|
||||
<a href="/timeline" class="{% block nav_timeline %}{% endblock %}">Kalendarz</a>
|
||||
<a href="/significators" class="{% block nav_sig %}{% endblock %}">Sygnifikatory</a>
|
||||
</nav>
|
||||
</header>
|
||||
|
||||
@@ -0,0 +1,77 @@
|
||||
{% extends "base.html" %}
|
||||
{% block title %}Kalendarz{% endblock %}
|
||||
{% block nav_timeline %}active{% endblock %}
|
||||
|
||||
{% block content %}
|
||||
<p class="sub">Zbiorcza oś czasu technik predykcyjnych (profekcje, solariusze, dyrekcje solar-arc) z interpretacjami z bazy dla dat.</p>
|
||||
|
||||
<form method="post" action="/timeline">
|
||||
<div class="grid">
|
||||
<label>Data urodzenia
|
||||
<input type="date" name="date" value="{{ form.date or '' }}" required>
|
||||
</label>
|
||||
<label>Godzina (lokalna)
|
||||
<input type="time" name="time" value="{{ form.time or '' }}" required>
|
||||
</label>
|
||||
<label>Strefa (offset h)
|
||||
<input type="number" name="tz_offset" step="0.25" value="{{ form.tz_offset if form.tz_offset is not none else 0 }}">
|
||||
</label>
|
||||
<label>Szerokość (lat)
|
||||
<input type="number" name="lat" step="0.0001" value="{{ form.lat if form.lat is not none else 0 }}">
|
||||
</label>
|
||||
<label>Długość (lon)
|
||||
<input type="number" name="lon" step="0.0001" value="{{ form.lon if form.lon is not none else 0 }}">
|
||||
</label>
|
||||
</div>
|
||||
<div class="grid">
|
||||
<label>Zakres od
|
||||
<input type="date" name="from_date" value="{{ form.from_date or '' }}" required>
|
||||
</label>
|
||||
<label>Zakres do
|
||||
<input type="date" name="to_date" value="{{ form.to_date or '' }}" required>
|
||||
</label>
|
||||
</div>
|
||||
<div class="actions">
|
||||
<button type="button" id="nowBtn" class="ghost">Tu i teraz</button>
|
||||
<button type="submit">Pokaż kalendarz</button>
|
||||
<span id="geoNote" class="muted small"></span>
|
||||
</div>
|
||||
</form>
|
||||
|
||||
{% if error %}<div class="error">{{ error }}</div>{% endif %}
|
||||
|
||||
{% if result %}
|
||||
{% if result.data_error %}<div class="error">{{ result.data_error }}</div>{% endif %}
|
||||
<div class="meta">
|
||||
Silnik: <strong>{{ result.engine }}</strong> ·
|
||||
zdarzeń: {{ result.count }} · zakres {{ result.from }} → {{ result.to }}
|
||||
</div>
|
||||
|
||||
{% for e in result.events %}
|
||||
<div class="sig-item">
|
||||
<div class="sig-head">
|
||||
<span class="badge">{{ e.exact }}</span>
|
||||
<span class="badge">{{ e.technique }}</span>
|
||||
<strong>{{ e.significator }}</strong>
|
||||
<span class="muted small">(okno {{ e.start }} → {{ e.end }})</span>
|
||||
</div>
|
||||
{% if e.interpretations %}
|
||||
<table class="samples">
|
||||
<tbody>
|
||||
{% for s in e.interpretations %}
|
||||
<tr><td class="sig nowrap" title="{{ s.significator }}">{{ s.expanded }}</td><td>{{ s.effect }}</td></tr>
|
||||
{% endfor %}
|
||||
</tbody>
|
||||
</table>
|
||||
{% if e.interpretations_count > e.interpretations | length %}
|
||||
<div class="muted small">…i {{ e.interpretations_count - (e.interpretations | length) }} więcej</div>
|
||||
{% endif %}
|
||||
{% elif e.technique != 'solar_return' %}
|
||||
<div class="muted small">brak dopasowań w bazie</div>
|
||||
{% endif %}
|
||||
</div>
|
||||
{% endfor %}
|
||||
{% endif %}
|
||||
|
||||
<script src="/static/now.js"></script>
|
||||
{% endblock %}
|
||||
Reference in New Issue
Block a user