bincio-activity/bincio/extract/writer.py

"""Write a processed activity to BAS JSON files."""

import json
import re
import unicodedata
from pathlib import Path

from bincio.extract.metrics import ComputedMetrics
from bincio.extract.models import LapData, ParsedActivity
from bincio.extract.simplify import build_geojson, preview_coords
from bincio.extract.timeseries import build_timeseries


def make_activity_id(activity: ParsedActivity) -> str:
    """Generate a BAS activity ID from started_at + optional title slug.

    Always uses UTC with Z suffix so IDs are URL-safe (no + chars).
    """
    from datetime import timezone
    ts = activity.started_at.astimezone(timezone.utc)
    ts_part = ts.strftime("%Y-%m-%dT%H%M%SZ")

    if activity.title:
        slug = _slugify(activity.title)
        return f"{ts_part}-{slug}" if slug else ts_part
    return ts_part


def write_activity(
    activity: ParsedActivity,
    metrics: ComputedMetrics,
    output_dir: Path,
    privacy: str = "public",
    duplicate_of: str | None = None,
    rdp_epsilon: float = 0.0001,
) -> str:
    """Write {id}.json and (if GPS available) {id}.geojson. Returns the ID."""
    activity_id = make_activity_id(activity)
    acts_dir = output_dir / "activities"
    acts_dir.mkdir(parents=True, exist_ok=True)

    source = _infer_source(activity)
    has_gps = metrics.bbox is not None and privacy not in ("no_gps", "private")

    # ── detail JSON ──────────────────────────────────────────────────────────
    detail: dict = {
        "bas_version": "1.0",
        "id": activity_id,
        "title": activity.title or _auto_title(activity),
        "description": activity.description,
        "sport": activity.sport,
        "sub_sport": activity.sub_sport,
        "started_at": activity.started_at.isoformat(),
        "distance_m": metrics.distance_m,
        "duration_s": metrics.duration_s,
        "moving_time_s": metrics.moving_time_s,
        "elevation_gain_m": metrics.elevation_gain_m,
        "elevation_loss_m": metrics.elevation_loss_m,
        "avg_speed_kmh": metrics.avg_speed_kmh,
        "max_speed_kmh": metrics.max_speed_kmh,
        "avg_hr_bpm": metrics.avg_hr_bpm,
        "max_hr_bpm": metrics.max_hr_bpm,
        "avg_cadence_rpm": metrics.avg_cadence_rpm,
        "avg_power_w": metrics.avg_power_w,
        "max_power_w": metrics.max_power_w,
        "gear": activity.gear,
        "device": activity.device,
        "bbox": list(metrics.bbox) if metrics.bbox else None,
        "start_latlng": list(metrics.start_latlng) if metrics.start_latlng else None,
        "end_latlng": list(metrics.end_latlng) if metrics.end_latlng else None,
        "mmp": metrics.mmp,
        "best_efforts": metrics.best_efforts,
        "best_climb_m": metrics.best_climb_m,
        "laps": [_serialise_lap(lap) for lap in activity.laps],
        "timeseries": build_timeseries(activity.points, activity.started_at, privacy),
        "source": source,
        "source_file": activity.source_file,
        "source_hash": activity.source_hash,
        "strava_id": activity.strava_id,
        "duplicate_of": duplicate_of,
        "privacy": privacy,
        "custom": {},
    }

    json_path = acts_dir / f"{activity_id}.json"
    json_path.write_text(json.dumps(detail, indent=2, ensure_ascii=False))

    # ── GeoJSON track ────────────────────────────────────────────────────────
    if has_gps:
        geojson = build_geojson(activity.points, activity_id, epsilon=rdp_epsilon)
        geojson_path = acts_dir / f"{activity_id}.geojson"
        geojson_path.write_text(json.dumps(geojson, indent=2, ensure_ascii=False))

    return activity_id


def build_summary(
    activity: ParsedActivity,
    metrics: ComputedMetrics,
    activity_id: str,
    privacy: str = "public",
) -> dict:
    """Build the Activity Summary object for index.json."""
    has_gps = metrics.bbox is not None and privacy not in ("no_gps", "private")
    return {
        "id": activity_id,
        "title": activity.title or _auto_title(activity),
        "sport": activity.sport,
        "sub_sport": activity.sub_sport,
        "started_at": activity.started_at.isoformat(),
        "distance_m": metrics.distance_m,
        "duration_s": metrics.duration_s,
        "moving_time_s": metrics.moving_time_s,
        "elevation_gain_m": metrics.elevation_gain_m,
        "avg_speed_kmh": metrics.avg_speed_kmh,
        "max_speed_kmh": metrics.max_speed_kmh,
        "avg_hr_bpm": metrics.avg_hr_bpm,
        "max_hr_bpm": metrics.max_hr_bpm,
        "avg_cadence_rpm": metrics.avg_cadence_rpm,
        "avg_power_w": metrics.avg_power_w,
        "mmp": metrics.mmp,
        "best_efforts": metrics.best_efforts,
        "best_climb_m": metrics.best_climb_m,
        "source": _infer_source(activity),
        "privacy": privacy,
        "detail_url": f"activities/{activity_id}.json",
        "track_url": f"activities/{activity_id}.geojson" if has_gps else None,
        # Small track preview for card thumbnails — no separate fetch needed
        "preview_coords": preview_coords(activity.points) if has_gps else None,
    }


def write_athlete_json(summaries: list[dict], output_dir: Path, athlete_config: dict) -> None:
    """Aggregate per-activity MMP curves and personal records into athlete.json."""
    from datetime import datetime, timezone

    now = datetime.now(timezone.utc)

    def _cutoff_iso(days: int) -> str:
        from datetime import timedelta
        return (now - timedelta(days=days)).isoformat()

    cutoff_365 = _cutoff_iso(365)
    cutoff_90  = _cutoff_iso(90)

    # ── MMP aggregation ───────────────────────────────────────────────────────

    def _merge_mmps(activity_mmps: list[list[list[int]]]) -> list[list[int]]:
        best: dict[int, int] = {}
        for mmp in activity_mmps:
            for d, w in mmp:
                if d not in best or w > best[d]:
                    best[d] = w
        return [[d, w] for d, w in sorted(best.items())]

    all_mmps = [s["mmp"] for s in summaries if s.get("mmp")]
    mmps_365 = [s["mmp"] for s in summaries if s.get("mmp") and s["started_at"] >= cutoff_365]
    mmps_90  = [s["mmp"] for s in summaries if s.get("mmp") and s["started_at"] >= cutoff_90]

    # ── Personal records aggregation ──────────────────────────────────────────
    # records[sport][distance_km] = {time_s, activity_id, started_at, title}
    # best_climb[activity_id] = {climb_m, started_at, title}

    SPORTS = ["running", "cycling", "swimming", "hiking", "walking", "skiing", "other"]
    records: dict[str, dict[float, dict]] = {s: {} for s in SPORTS}
    best_climb: list[dict] = []   # top 10 best climbs for cycling

    for s in summaries:
        sport = s.get("sport", "other")
        act_id = s.get("id", "")
        started = s.get("started_at", "")
        title = s.get("title", "")

        # Distance-based best efforts
        for d_km, t_s in (s.get("best_efforts") or []):
            bucket = records.get(sport, {})
            existing = bucket.get(d_km)
            if existing is None or t_s < existing["time_s"]:
                bucket[d_km] = {
                    "time_s": t_s,
                    "activity_id": act_id,
                    "started_at": started,
                    "title": title,
                }
            records[sport] = bucket

        # Best climb (cycling only) — collect all, trim to top 10 after loop
        climb = s.get("best_climb_m")
        if climb and sport == "cycling":
            best_climb.append({
                "climb_m": climb,
                "activity_id": act_id,
                "started_at": started,
                "title": title,
            })

        # Hiking / walking: track longest distance and most elevation from summaries
        if sport in ("hiking", "walking"):
            dist = s.get("distance_m") or 0
            elev = s.get("elevation_gain_m") or 0
            for metric, key, val in [("longest_m", "distance_m", dist),
                                      ("most_elevation_m", "elevation_gain_m", elev)]:
                bucket = records[sport]
                existing = bucket.get(metric)
                if val and (existing is None or val > existing.get("value", 0)):
                    bucket[metric] = {
                        "value": val,
                        "activity_id": act_id,
                        "started_at": started,
                        "title": title,
                    }
                records[sport] = bucket

    # Serialise records: convert float keys to strings for JSON
    def _serialise_sport_records(bucket: dict) -> dict:
        return {str(k): v for k, v in bucket.items()}

    athlete = {
        "bas_version": "1.0",
        "generated_at": now.isoformat(),
        "power_curve": {
            "all_time":  _merge_mmps(all_mmps) if all_mmps else None,
            "last_365d": _merge_mmps(mmps_365) if mmps_365 else None,
            "last_90d":  _merge_mmps(mmps_90)  if mmps_90  else None,
        },
        "records": {
            sport: _serialise_sport_records(records[sport])
            for sport in SPORTS
            if records[sport]
        },
        "best_climbs": sorted(best_climb, key=lambda x: x["climb_m"], reverse=True)[:10],
        **athlete_config,
    }
    (output_dir / "athlete.json").write_text(
        json.dumps(athlete, indent=2, ensure_ascii=False)
    )


def write_index(summaries: list[dict], output_dir: Path, owner: dict) -> None:
    """Write index.json (sorted newest first)."""
    sorted_summaries = sorted(
        summaries,
        key=lambda s: s["started_at"],
        reverse=True,
    )
    index = {
        "bas_version": "1.0",
        "owner": owner,
        "generated_at": _now_iso(),
        "shards": [],
        "activities": sorted_summaries,
    }
    (output_dir / "index.json").write_text(
        json.dumps(index, indent=2, ensure_ascii=False)
    )


# ── helpers ──────────────────────────────────────────────────────────────────

def _now_iso() -> str:
    from datetime import datetime, timezone
    return datetime.now(timezone.utc).isoformat()


def _auto_title(activity: ParsedActivity) -> str:
    ts = activity.started_at
    hour = ts.hour
    if 5 <= hour < 12:
        time_of_day = "Morning"
    elif 12 <= hour < 17:
        time_of_day = "Afternoon"
    elif 17 <= hour < 21:
        time_of_day = "Evening"
    else:
        time_of_day = "Night"
    sport = activity.sport.capitalize()
    return f"{time_of_day} {sport}"


def _infer_source(activity: ParsedActivity) -> str | None:
    if activity.strava_id:
        return "strava_export"
    name = activity.source_file.lower()
    # Karoo uses UUID-style names
    if "activity" in name and len(name.split(".")) >= 3:
        return "karoo"
    if name.endswith(".fit") or name.endswith(".fit.gz"):
        return "fit_file"
    if name.endswith(".gpx") or name.endswith(".gpx.gz"):
        return "gpx_file"
    if name.endswith(".tcx") or name.endswith(".tcx.gz"):
        return "tcx_file"
    return None


def _slugify(text: str) -> str:
    text = unicodedata.normalize("NFKD", text)
    text = text.encode("ascii", "ignore").decode("ascii")
    text = text.lower()
    text = re.sub(r"[^a-z0-9]+", "-", text)
    return text.strip("-")[:60]


def _serialise_lap(lap: LapData) -> dict:
    return {
        "index": lap.index,
        "started_at": lap.started_at.isoformat(),
        "duration_s": lap.duration_s,
        "distance_m": lap.distance_m,
        "elevation_gain_m": lap.elevation_gain_m,
        "avg_speed_kmh": lap.avg_speed_kmh,
        "avg_hr_bpm": lap.avg_hr_bpm,
        "avg_power_w": lap.avg_power_w,
    }