dl-organizer/src/vlm/commands/analyze.py

"""Analyze command implementation."""

import json
from pathlib import Path
from typing import Optional

import click

from vlm.analysis import analyze_series_completeness, detect_duplicates
from vlm.context import CLIContext
from vlm.io import identities_to_analysis_input, load_identities_json, load_inventory_csv
from vlm.models import MovieIdentity, SeriesIdentity
from vlm.utils import utc_now


def analyze_cmd(
    ctx: CLIContext,
    input: Path,
    output: Path,
    inventory: Optional[Path],
) -> None:
    """Run analysis: completeness and duplicate detection."""
    config = ctx.config
    logger = ctx.logger

    click.echo(f"Analyzing identities from: {input}")
    if inventory:
        click.echo(f"Merging metadata from inventory: {inventory}")
    click.echo()

    identities_data = load_identities_json(input)
    movies_data = identities_data.get("movies", [])
    series_data = identities_data.get("series", [])

    click.echo(f"Loaded {len(movies_data)} movies and {len(series_data)} series")
    click.echo()

    inventory_files = load_inventory_csv(inventory) if inventory else None
    movie_identities, series_identities, video_files = identities_to_analysis_input(
        identities_data, inventory_files=inventory_files
    )

    click.echo("Analyzing series completeness...")
    completeness_results = analyze_series_completeness(series_identities)

    click.echo("Detecting duplicates...")
    n_movies = len(movie_identities)
    identity_file_pairs = (
        list(zip(movie_identities, video_files[:n_movies]))
        + list(zip(series_identities, video_files[n_movies:]))
    )
    duplicate_groups = detect_duplicates(identity_file_pairs)

    click.echo()
    click.echo("Analysis complete!")
    click.echo()
    click.echo("Results:")
    click.echo(f"  Series with episode gaps: {len(completeness_results)}")
    if completeness_results:
        total_missing = sum(len(c.episodes_missing) for c in completeness_results)
        click.echo(f"    - Total missing episodes: {total_missing}")
    click.echo(f"  Duplicate groups found: {len(duplicate_groups)}")
    if duplicate_groups:
        total_duplicates = sum(len(g.files) for g in duplicate_groups)
        click.echo(f"    - Total duplicate files: {total_duplicates}")

    click.echo()
    click.echo(f"Saving analysis results to: {output}")
    output.parent.mkdir(parents=True, exist_ok=True)

    generation_timestamp = utc_now().strftime("%Y-%m-%dT%H:%M:%S")
    completeness_list = [
        {
            "series_title": c.series_title,
            "season": c.season,
            "episodes_found": c.episodes_found,
            "episodes_missing": c.episodes_missing,
        }
        for c in completeness_results
    ]
    duplicates_list = []
    for d in duplicate_groups:
        if isinstance(d.identity, MovieIdentity):
            identity_info = {"type": "movie", "title": d.identity.title, "year": d.identity.year}
        else:
            identity_info = {
                "type": "series",
                "title": d.identity.title,
                "season": d.identity.season,
                "episodes": d.identity.episodes,
            }
        duplicates_list.append(
            {
                "identity": identity_info,
                "files": [str(f.path) for f in d.files],
                "quality_comparison": d.quality_comparison,
            }
        )
    analysis_data = {
        "metadata": {
            "generated": generation_timestamp,
            "source_identities": str(input),
            "total_movies": len(movies_data),
            "total_series": len(series_data),
        },
        "completeness": completeness_list,
        "duplicates": duplicates_list,
    }
    with open(output, "w", encoding="utf-8") as jsonfile:
        json.dump(analysis_data, jsonfile, indent=2, ensure_ascii=False)

    click.echo("Analysis results saved successfully!")
    logger.info(
        f"Analysis completed: {len(completeness_results)} incomplete series, "
        f"{len(duplicate_groups)} duplicate groups, saved to {output}"
    )