import re
import os
from collections import Counter

# ================= 配置区域 =================
# 1. 你的错误日志文件路径
LOG_FILE = 'copy_errors.log'

# 2. 图片路径中 category 和 sequence 的位置模式
# 假设路径是: data/raw_images/{category}/{sequence}/images/filename.jpg
# 我们使用正则来提取。
# 解释: 
#   data/raw_images/  -> 匹配前缀 (根据你的实际路径调整，或者用通用的)
#   ([^/]+)           -> 第一个捕获组: category (不包含/的任意字符)
#   /                 -> 分隔符
#   ([^/]+)           -> 第二个捕获组: sequence
#   /images/          -> 后面紧跟着 images 目录
PATH_PATTERN = re.compile(r'data/raw_images/([^/]+)/([^/]+)/images/')
# ===========================================

def analyze_log(log_file):
    if not os.path.exists(log_file):
        print(f"[Error] 找不到日志文件: {log_file}")
        return

    print(f"[*] 正在分析日志文件: {log_file} ...")

    failed_categories = set()
    failed_sequences = set()
    
    # 用于统计每个 category 和 sequence 缺失了多少张图
    category_counter = Counter()
    sequence_counter = Counter()

    # 用于存储 {category: [sequence1, sequence2, ...]} 的层级关系
    cat_seq_map = {}

    with open(log_file, 'r', encoding='utf-8') as f:
        current_path = ""
        
        for line in f:
            line = line.strip()
            
            # 提取日志中的图片路径行
            # 日志格式: [FAIL] 图片路径: data/raw_images/bowl/...
            if line.startswith("[FAIL] 图片路径:"):
                # 提取路径部分
                path_str = line.split(": ", 1)[1]
                
                # 使用正则提取 category 和 sequence
                match = PATH_PATTERN.search(path_str)
                if match:
                    category = match.group(1)
                    sequence = match.group(2)

                    # 存入集合 (去重)
                    failed_categories.add(category)
                    failed_sequences.add(sequence)

                    # 计数
                    category_counter[category] += 1
                    sequence_counter[sequence] += 1

                    # 构建层级关系
                    if category not in cat_seq_map:
                        cat_seq_map[category] = set()
                    cat_seq_map[category].add(sequence)
                else:
                    # 如果正则匹配失败，可能路径格式不一样，打印出来看看
                    # print(f"[Warning] 无法解析路径结构: {path_str}")
                    pass

    # ================= 输出结果 =================
    print("\n" + "="*50)
    print("分析报告 (Analysis Report)")
    print("="*50)

    print(f"\n1. 缺失图片涉及的 Category 总数: {len(failed_categories)}")
    print("-" * 30)
    # 按缺失数量从多到少排序
    for cat, count in category_counter.most_common():
        print(f"   - {cat}: 缺失 {count} 张图")

    print(f"\n2. 缺失图片涉及的 Sequence 总数: {len(failed_sequences)}")
    print("-" * 30)
    # 如果 sequence 太多，只打印前 20 个
    top_n = 20
    for seq, count in sequence_counter.most_common(top_n):
        print(f"   - {seq}: 缺失 {count} 张图")
    if len(sequence_counter) > top_n:
        print(f"   ... (还有 {len(sequence_counter) - top_n} 个 sequence)")

    print(f"\n3. 详细层级结构 (Category -> Sequence)")
    print("-" * 30)
    for cat in sorted(cat_seq_map.keys()):
        seqs = cat_seq_map[cat]
        print(f"[{cat}] 下有 {len(seqs)} 个有问题的 sequence:")
        # 将 set 转为 list 并排序，方便查看
        sorted_seqs = sorted(list(seqs))
        
        # 打印方式：如果很多，就一行打印多个
        # 这里简单处理，每行打印一个，或者你可以改成逗号分隔
        print(f"   {', '.join(sorted_seqs)}")
        print("")

    # 保存结果到文件
    output_file = "missing_stats.txt"
    with open(output_file, 'w', encoding='utf-8') as f_out:
        f_out.write("=== 缺失数据统计 ===\n")
        f_out.write(f"Category 总数: {len(failed_categories)}\n")
        f_out.write(f"Sequence 总数: {len(failed_sequences)}\n\n")
        
        f_out.write("=== Category 列表 (格式: 名称 [缺失数量]) ===\n")
        for cat, count in category_counter.most_common():
            f_out.write(f"{cat} [{count}]\n")
            
        f_out.write("\n=== Sequence 列表 (按 Category 分组) ===\n")
        for cat in sorted(cat_seq_map.keys()):
            f_out.write(f"\n[{cat}]\n")
            for seq in sorted(list(cat_seq_map[cat])):
                f_out.write(f"  - {seq} (缺失 {sequence_counter[seq]} 张)\n")
    
    print(f"\n[*] 详细统计已保存至: {output_file}")

if __name__ == "__main__":
    analyze_log(LOG_FILE)