"""Expand persisted compact laps or moving segments without reading raw recordings."""

from copy import copy

from .stats_analysis import evaluate, expression_tree, valid
from .stats_dsl import QueryError


def expand(history, q, catalog):
    rows = []
    trees = [
        (spec["name"], expression_tree(spec["expression"], catalog)[0]) for spec in q["derived"]
    ]
    for activity in history:
        for index, unit in enumerate((activity.analysis_summary or {}).get(q["source"], [])):
            if (
                not isinstance(unit, dict)
                or not valid(unit.get("distance"))
                or not valid(unit.get("duration"))
                or unit["duration"] <= 0
                or unit["distance"] <= 0
            ):
                continue
            row = copy(activity)
            row.activity_id = activity.id
            row.id = activity.id * 1000000 + index
            row.title = (
                f"{activity.title} · {'lap' if q['source'] == 'laps' else 'segment'} {index + 1}"
            )
            row.distance_m, row.duration_s = unit["distance"], unit["duration"]
            row.elevation_m = unit.get("elevation")
            row.avg_hr = (
                unit.get("heart_rate")
                if valid(unit.get("heart_rate")) and unit["heart_rate"] > 0
                else None
            )
            row.values = {key: None for key in catalog}
            row.values.update(
                count=1,
                distance=row.distance_m / 1000,
                duration=row.duration_s / 3600,
                pace=row.duration_s * 1000 / row.distance_m,
                speed=row.distance_m / row.duration_s * 3.6,
                heart_rate=row.avg_hr,
                elevation=row.elevation_m,
                elevation_per_km=row.elevation_m / (row.distance_m / 1000)
                if valid(row.elevation_m)
                else None,
            )
            for key in ("gap", "pace_variability", "heart_rate_drift", "sensor_coverage"):
                row.values[key] = unit.get(key)
            row.analysis_summary = row.values
            row.previous = None
            for name, tree in trees:
                row.values[name] = evaluate(tree, row.values)
            rows.append(row)
            if len(rows) > 100000:
                raise QueryError(
                    "This expands over 100,000 recording units. Use a shorter date range."
                )
    return rows