"""Turns a checkout of free-exercise-db into ZenXercise's bundled Exercise Library.

Writes `exercises.json` (slimmed, with each Exercise's Mode) and one WebP per
image into the output folder, flattened to `images/<id>_<n>.webp` because
Flutter assets are declared per folder.
"""

from __future__ import annotations

import json
from pathlib import Path

from PIL import Image

STRETCHING_CATEGORY = "stretching"
MAX_EDGE = 480
WEBP_QUALITY = 72


def mode_of(category: str) -> str:
    """Category `stretching` belongs to Stretching Mode, everything else to Workout Mode."""
    return "stretching" if category == STRETCHING_CATEGORY else "workout"


def slim(exercise: dict) -> dict:
    """The fields the app needs, with images reduced to a count."""
    return {
        "id": exercise["id"],
        "name": exercise["name"],
        "mode": mode_of(exercise["category"]),
        "category": exercise["category"],
        "level": exercise["level"],
        "equipment": exercise.get("equipment"),
        "force": exercise.get("force"),
        "mechanic": exercise.get("mechanic"),
        "primaryMuscles": exercise["primaryMuscles"],
        "secondaryMuscles": exercise["secondaryMuscles"],
        "instructions": [line.strip() for line in exercise["instructions"] if line.strip()],
        "imageCount": len(exercise["images"]),
    }


def image_name(exercise_id: str, index: int) -> str:
    return f"{exercise_id}_{index}.webp"


def convert_image(source: Path, target: Path) -> None:
    with Image.open(source) as image:
        image = image.convert("RGB")
        image.thumbnail((MAX_EDGE, MAX_EDGE))
        image.save(target, "WEBP", quality=WEBP_QUALITY, method=6)


def run(source_root: Path, output_root: Path) -> list[dict]:
    exercises = json.loads((source_root / "dist" / "exercises.json").read_text(encoding="utf-8"))
    images = output_root / "images"
    images.mkdir(parents=True, exist_ok=True)
    for stale in images.glob("*.webp"):
        stale.unlink()

    slimmed = sorted((slim(e) for e in exercises), key=lambda e: e["name"].lower())
    for exercise in exercises:
        for index, relative in enumerate(exercise["images"]):
            convert_image(source_root / "exercises" / relative, images / image_name(exercise["id"], index))

    (output_root / "exercises.json").write_text(
        json.dumps(slimmed, ensure_ascii=False, separators=(",", ":")), encoding="utf-8"
    )
    return slimmed