from pathlib import Path
from typing import Dict

import cv2
import numpy as np


class ProjectView:
    """Project view that displays videos in current directory with progress bars"""
    
    THUMBNAIL_SIZE = (200, 150)
    THUMBNAIL_MARGIN = 20
    PROGRESS_BAR_HEIGHT = 8
    TEXT_HEIGHT = 30
    
    BG_COLOR = (40, 40, 40)
    THUMBNAIL_BG_COLOR = (60, 60, 60)
    PROGRESS_BG_COLOR = (80, 80, 80)
    PROGRESS_FILL_COLOR = (0, 120, 255)
    TEXT_COLOR = (255, 255, 255)
    SELECTED_COLOR = (255, 165, 0)
    
    def __init__(self, directory: Path, video_editor):
        self.directory = directory
        self.video_editor = video_editor
        self.video_files = []
        self.thumbnails: Dict[Path, np.ndarray] = {}
        self.progress_data = {}
        self.selected_index = 0
        self.scroll_offset = 0
        self.items_per_row = 2
        self.window_width = 1200
        self.window_height = 800
        
        self._load_video_files()
        self._load_progress_data()
    
    def _calculate_thumbnail_size(self, window_width: int) -> tuple:
        available_width = window_width - self.THUMBNAIL_MARGIN
        item_width = (available_width - (self.items_per_row - 1) * self.THUMBNAIL_MARGIN) // self.items_per_row
        thumbnail_width = max(50, item_width)
        thumbnail_height = int(thumbnail_width * self.THUMBNAIL_SIZE[1] / self.THUMBNAIL_SIZE[0])
        return (thumbnail_width, thumbnail_height)
    
    def _load_video_files(self):
        self.video_files = []
        for file_path in self.directory.iterdir():
            if (file_path.is_file() and 
                file_path.suffix.lower() in self.video_editor.VIDEO_EXTENSIONS):
                self.video_files.append(file_path)
        self.video_files.sort(key=lambda x: x.name)
    
    def _load_progress_data(self):
        self.progress_data = {}
        for video_path in self.video_files:
            state_file = video_path.with_suffix('.json')
            if state_file.exists():
                try:
                    with open(state_file, 'r') as f:
                        import json
                        state = json.load(f)
                    current_frame = state.get('current_frame', 0)
                    cap = cv2.VideoCapture(str(video_path))
                    if cap.isOpened():
                        total_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
                        cap.release()
                        if total_frames > 0:
                            progress = current_frame / (total_frames - 1)
                            self.progress_data[video_path] = {
                                'current_frame': current_frame,
                                'total_frames': total_frames,
                                'progress': progress
                            }
                except Exception as e:  # noqa: BLE001 - preserve original behavior
                    print(f"Error loading progress for {video_path.name}: {e}")
    
    def refresh_progress_data(self):
        self._load_progress_data()
    
    def get_progress_for_video(self, video_path: Path) -> float:
        if video_path in self.progress_data:
            return self.progress_data[video_path]['progress']
        return 0.0
    
    def get_thumbnail_for_video(self, video_path: Path, size: tuple = None) -> np.ndarray:
        if size is None:
            size = self.THUMBNAIL_SIZE
        if video_path in self.thumbnails:
            original_thumbnail = self.thumbnails[video_path]
            return cv2.resize(original_thumbnail, size)
        try:
            cap = cv2.VideoCapture(str(video_path))
            if cap.isOpened():
                total_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
                if total_frames > 0:
                    middle_frame = total_frames // 2
                    cap.set(cv2.CAP_PROP_POS_FRAMES, middle_frame)
                    ret, frame = cap.read()
                    if ret:
                        original_thumbnail = cv2.resize(frame, self.THUMBNAIL_SIZE)
                        self.thumbnails[video_path] = original_thumbnail
                        cap.release()
                        return cv2.resize(original_thumbnail, size)
            cap.release()
        except Exception as e:  # noqa: BLE001 - preserve original behavior
            print(f"Error generating thumbnail for {video_path.name}: {e}")
        placeholder = np.full((size[1], size[0], 3), self.THUMBNAIL_BG_COLOR, dtype=np.uint8)
        return placeholder
    
    # draw() and input handling remain in main editor for now to minimize churn