#!/usr/bin/env python3
"""
基于Streamlit的OCR可视化校验工具（重构版）
提供丰富的交互组件和更好的用户体验
"""

import streamlit as st
from pathlib import Path
from PIL import Image
from typing import Dict, List, Optional
import plotly.graph_objects as go
from io import BytesIO
import pandas as pd
import numpy as np
import plotly.express as px

# 导入工具模块
from ocr_validator_utils import (
    load_config, load_css_styles, load_ocr_data_file, process_ocr_data,
    draw_bbox_on_image, get_ocr_statistics, convert_html_table_to_markdown,
    parse_html_tables, find_available_ocr_files, create_dynamic_css,
    export_tables_to_excel, get_table_statistics, group_texts_by_category
)
from ocr_validator_layout import OCRLayoutManager


class StreamlitOCRValidator:
    def __init__(self):
        self.config = load_config()
        self.ocr_data = []
        self.md_content = ""
        self.image_path = ""
        self.text_bbox_mapping = {}
        self.selected_text = None
        self.marked_errors = set()
        self.show_all_boxes = False
        self.fit_to_container = True
        self.zoom_level = 1.0
        self.current_angle = 0

        # 初始化布局管理器
        self.layout_manager = OCRLayoutManager(self)
        
    def setup_page_config(self):
        """设置页面配置"""
        ui_config = self.config['ui']
        st.set_page_config(
            page_title=ui_config['page_title'],
            page_icon=ui_config['page_icon'],
            layout=ui_config['layout'],
            initial_sidebar_state=ui_config['sidebar_state']
        )
        
        # 加载CSS样式
        css_content = load_css_styles()
        st.markdown(f"<style>{css_content}</style>", unsafe_allow_html=True)
    
    def load_ocr_data(self, json_path: str, md_path: Optional[str] = None, image_path: Optional[str] = None):
        """加载OCR相关数据"""
        try:
            self.ocr_data, self.md_content, self.image_path = load_ocr_data_file(json_path, self.config)
            self.process_data()
        except Exception as e:
            st.error(f"❌ 加载失败: {e}")
    
    def process_data(self):
        """处理OCR数据"""
        self.text_bbox_mapping = process_ocr_data(self.ocr_data, self.config)
    
    def get_statistics(self) -> Dict:
        """获取统计信息"""
        return get_ocr_statistics(self.ocr_data, self.text_bbox_mapping, self.marked_errors)
    
    def display_html_table_as_dataframe(self, html_content: str, enable_editing: bool = False):
        """将HTML表格解析为DataFrame显示 - 增强版本支持横向滚动"""
        tables = parse_html_tables(html_content)
        
        if not tables:
            st.warning("未找到可解析的表格")
            # 对于无法解析的HTML表格，使用自定义CSS显示
            st.markdown("""
            <style>
            .scrollable-table {
                overflow-x: auto;
                white-space: nowrap;
                border: 1px solid #ddd;
                border-radius: 5px;
                margin: 10px 0;
            }
            .scrollable-table table {
                width: 100%;
                border-collapse: collapse;
            }
            .scrollable-table th, .scrollable-table td {
                border: 1px solid #ddd;
                padding: 8px;
                text-align: left;
                min-width: 100px;
            }
            .scrollable-table th {
                background-color: #f5f5f5;
                font-weight: bold;
            }
            </style>
            """, unsafe_allow_html=True)
            
            st.markdown(f'<div class="scrollable-table">{html_content}</div>', unsafe_allow_html=True)
            return
            
        for i, table in enumerate(tables):
            st.subheader(f"📊 表格 {i+1}")
            
            # 表格信息显示
            col_info1, col_info2, col_info3, col_info4 = st.columns(4)
            with col_info1:
                st.metric("行数", len(table))
            with col_info2:
                st.metric("列数", len(table.columns))
            with col_info3:
                # 检查是否有超宽表格
                is_wide_table = len(table.columns) > 8
                st.metric("表格类型", "超宽表格" if is_wide_table else "普通表格")
            with col_info4:
                # 表格操作模式选择
                display_mode = st.selectbox(
                    f"显示模式 (表格{i+1})",
                    ["完整显示", "分页显示", "筛选列显示"],
                    key=f"display_mode_{i}"
                )
            
            # 创建表格操作按钮
            col1, col2, col3, col4 = st.columns(4)
            with col1:
                show_info = st.checkbox(f"显示详细信息", key=f"info_{i}")
            with col2:
                show_stats = st.checkbox(f"显示统计信息", key=f"stats_{i}")
            with col3:
                enable_filter = st.checkbox(f"启用过滤", key=f"filter_{i}")
            with col4:
                enable_sort = st.checkbox(f"启用排序", key=f"sort_{i}")
            
            # 根据显示模式处理表格
            display_table = self._process_table_display_mode(table, i, display_mode)
            
            # 数据过滤和排序逻辑
            filtered_table = self._apply_table_filters_and_sorts(display_table, i, enable_filter, enable_sort)
            
            # 显示表格 - 使用自定义CSS支持横向滚动
            st.markdown("""
            <style>
            .dataframe-container {
                overflow-x: auto;
                border: 1px solid #ddd;
                border-radius: 5px;
                margin: 10px 0;
            }
            
            /* 为超宽表格特殊样式 */
            .wide-table-container {
                overflow-x: auto;
                max-height: 500px;
                overflow-y: auto;
                border: 2px solid #0288d1;
                border-radius: 8px;
                background: linear-gradient(90deg, #f8f9fa 0%, #ffffff 100%);
            }
            
            .dataframe thead th {
                position: sticky;
                top: 0;
                background-color: #f5f5f5 !important;
                z-index: 10;
                border-bottom: 2px solid #0288d1;
            }
            
            .dataframe tbody td {
                white-space: nowrap;
                min-width: 100px;
                max-width: 300px;
                overflow: hidden;
                text-overflow: ellipsis;
            }
            </style>
            """, unsafe_allow_html=True)
            
            # 根据表格宽度选择显示容器
            container_class = "wide-table-container" if len(table.columns) > 8 else "dataframe-container"
            
            if enable_editing:
                st.markdown(f'<div class="{container_class}">', unsafe_allow_html=True)
                edited_table = st.data_editor(
                    filtered_table, 
                    use_container_width=True, 
                    key=f"editor_{i}",
                    height=400 if len(table.columns) > 8 else None
                )
                st.markdown('</div>', unsafe_allow_html=True)
                
                if not edited_table.equals(filtered_table):
                    st.success("✏️ 表格已编辑，可以导出修改后的数据")
            else:
                st.markdown(f'<div class="{container_class}">', unsafe_allow_html=True)
                st.dataframe(
                    filtered_table, 
                    # use_container_width=True,
                    width =400 if len(table.columns) > 8 else "stretch"
                )
                st.markdown('</div>', unsafe_allow_html=True)
            
            # 显示表格信息和统计
            self._display_table_info_and_stats(table, filtered_table, show_info, show_stats, i)
            
            st.markdown("---")
    
    def _apply_table_filters_and_sorts(self, table: pd.DataFrame, table_index: int, enable_filter: bool, enable_sort: bool) -> pd.DataFrame:
        """应用表格过滤和排序"""
        filtered_table = table.copy()
        
        # 数据过滤
        if enable_filter and not table.empty:
            filter_col = st.selectbox(
                f"选择过滤列 (表格 {table_index+1})", 
                options=['无'] + list(table.columns),
                key=f"filter_col_{table_index}"
            )
            
            if filter_col != '无':
                filter_value = st.text_input(f"过滤值 (表格 {table_index+1})", key=f"filter_value_{table_index}")
                if filter_value:
                    filtered_table = table[table[filter_col].astype(str).str.contains(filter_value, na=False)]
        
        # 数据排序
        if enable_sort and not filtered_table.empty:
            sort_col = st.selectbox(
                f"选择排序列 (表格 {table_index+1})", 
                options=['无'] + list(filtered_table.columns),
                key=f"sort_col_{table_index}"
            )
            
            if sort_col != '无':
                sort_order = st.radio(
                    f"排序方式 (表格 {table_index+1})",
                    options=['升序', '降序'],
                    horizontal=True,
                    key=f"sort_order_{table_index}"
                )
                ascending = (sort_order == '升序')
                filtered_table = filtered_table.sort_values(sort_col, ascending=ascending)
        
        return filtered_table
    
    def _display_table_info_and_stats(self, original_table: pd.DataFrame, filtered_table: pd.DataFrame, 
                                     show_info: bool, show_stats: bool, table_index: int):
        """显示表格信息和统计数据"""
        if show_info:
            st.write("**表格信息:**")
            st.write(f"- 原始行数: {len(original_table)}")
            st.write(f"- 过滤后行数: {len(filtered_table)}")
            st.write(f"- 列数: {len(original_table.columns)}")
            st.write(f"- 列名: {', '.join(original_table.columns)}")
        
        if show_stats:
            st.write("**统计信息:**")
            numeric_cols = filtered_table.select_dtypes(include=[np.number]).columns
            if len(numeric_cols) > 0:
                st.dataframe(filtered_table[numeric_cols].describe())
            else:
                st.info("表格中没有数值列")
        
        # 导出功能
        if st.button(f"📥 导出表格 {table_index+1}", key=f"export_{table_index}"):
            self._create_export_buttons(filtered_table, table_index)
    
    def _create_export_buttons(self, table: pd.DataFrame, table_index: int):
        """创建导出按钮"""
        # CSV导出
        csv_data = table.to_csv(index=False)
        st.download_button(
            label=f"下载CSV (表格 {table_index+1})",
            data=csv_data,
            file_name=f"table_{table_index+1}.csv",
            mime="text/csv",
            key=f"download_csv_{table_index}"
        )
        
        # Excel导出
        excel_buffer = BytesIO()
        table.to_excel(excel_buffer, index=False)
        st.download_button(
            label=f"下载Excel (表格 {table_index+1})",
            data=excel_buffer.getvalue(),
            file_name=f"table_{table_index+1}.xlsx",
            mime="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
            key=f"download_excel_{table_index}"
        )
    
    def _process_table_display_mode(self, table: pd.DataFrame, table_index: int, display_mode: str) -> pd.DataFrame:
        """根据显示模式处理表格"""
        if display_mode == "分页显示":
            # 分页显示
            page_size = st.selectbox(
                f"每页显示行数 (表格 {table_index+1})",
                [10, 20, 50, 100],
                key=f"page_size_{table_index}"
            )
            
            total_pages = (len(table) - 1) // page_size + 1
            
            if total_pages > 1:
                page_number = st.selectbox(
                    f"页码 (表格 {table_index+1})",
                    range(1, total_pages + 1),
                    key=f"page_number_{table_index}"
                )
                
                start_idx = (page_number - 1) * page_size
                end_idx = start_idx + page_size
                return table.iloc[start_idx:end_idx]
            
            return table
            
        elif display_mode == "筛选列显示":
            # 列筛选显示
            if len(table.columns) > 5:
                selected_columns = st.multiselect(
                    f"选择要显示的列 (表格 {table_index+1})",
                    table.columns.tolist(),
                    default=table.columns.tolist()[:5],  # 默认显示前5列
                    key=f"selected_columns_{table_index}"
                )
                
                if selected_columns:
                    return table[selected_columns]
            
            return table
            
        else:  # 完整显示
            return table
    
    # 布局方法现在委托给布局管理器
    def create_compact_layout(self, config):
        """创建滚动凑布局"""
        return self.layout_manager.create_compact_layout(config)


def main():
    """主应用"""
    # 初始化应用
    if 'validator' not in st.session_state:
        st.session_state.validator = StreamlitOCRValidator()
        st.session_state.validator.setup_page_config()
    
    if 'selected_text' not in st.session_state:
        st.session_state.selected_text = None
    
    if 'marked_errors' not in st.session_state:
        st.session_state.marked_errors = set()
    
    # 同步标记的错误到validator
    st.session_state.validator.marked_errors = st.session_state.marked_errors
    
    # 页面标题
    config = st.session_state.validator.config
    st.title(config['ui']['page_title'])
    st.markdown("---")
    
    # 侧边栏 - 文件选择和控制
    with st.sidebar:
        st.header("📁 文件选择")
        
        # 查找可用的OCR文件
        available_files = find_available_ocr_files(config['paths']['ocr_out_dir'])
        
        if available_files:
            selected_file = st.selectbox("选择OCR结果文件", available_files, index=0)
            
            if st.button("🔄 加载文件", type="primary") and selected_file:
                st.session_state.validator.load_ocr_data(selected_file)
                st.success("✅ 文件加载成功！")
                st.rerun()
        else:
            st.warning("未找到OCR结果文件")
            st.info("请确保output目录下有OCR结果文件")
        
        st.markdown("---")
        
        # 控制面板
        st.header("🎛️ 控制面板")
        
        if st.button("🧹 清除选择"):
            st.session_state.selected_text = None
            st.rerun()
        
        if st.button("❌ 清除错误标记"):
            st.session_state.marked_errors = set()
            st.rerun()
    
    # 主内容区域
    validator = st.session_state.validator
    
    if not validator.ocr_data:
        st.info("👈 请在左侧选择并加载OCR结果文件")
        return
    
    # 显示统计信息
    stats = validator.get_statistics()
    
    col1, col2, col3, col4, col5 = st.columns(5)  # 增加一列
    with col1:
        st.metric("📊 总文本块", stats['total_texts'])
    with col2:
        st.metric("🔗 可点击文本", stats['clickable_texts'])
    with col3:
        st.metric("❌ 标记错误", stats['marked_errors'])
    with col4:
        st.metric("✅ 准确率", f"{stats['accuracy_rate']:.1f}%")
    with col5:
        # 显示OCR工具信息
        if stats['tool_info']:
            tool_names = list(stats['tool_info'].keys())
            main_tool = tool_names[0] if tool_names else "未知"
            st.metric("🔧 OCR工具", main_tool)
    
    # 详细工具信息
    if stats['tool_info']:
        st.expander("🔧 OCR工具详情", expanded=False).write(stats['tool_info'])
    
    st.markdown("---")
    
    # 创建标签页
    tab1, tab2, tab3, tab4 = st.tabs(["📄 内容校验", "📊 表格分析", "📈 数据统计", "🚀 快速导航"])
    
    with tab1:
        validator.create_compact_layout(config)

    with tab2:
        # 表格分析页面
        st.header("📊 表格数据分析")
        
        if validator.md_content and '<table' in validator.md_content.lower():
            col1, col2 = st.columns([2, 1])
            
            with col1:
                st.subheader("🔍 表格数据预览")
                validator.display_html_table_as_dataframe(validator.md_content)
            
            with col2:
                st.subheader("⚙️ 表格操作")
                
                if st.button("📥 导出表格数据", type="primary"):
                    tables = parse_html_tables(validator.md_content)
                    if tables:
                        output = export_tables_to_excel(tables)
                        st.download_button(
                            label="📥 下载Excel文件",
                            data=output.getvalue(),
                            file_name="ocr_tables.xlsx",
                            mime="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                        )
        else:
            st.info("当前OCR结果中没有检测到表格数据")
    
    with tab3:
        # 数据统计页面
        st.header("📈 OCR数据统计")
        
        if stats['categories']:
            st.subheader("📊 类别分布")
            fig_pie = px.pie(
                values=list(stats['categories'].values()),
                names=list(stats['categories'].keys()),
                title="文本类别分布"
            )
            st.plotly_chart(fig_pie, use_container_width=True)
        
        # 错误率分析
        st.subheader("📈 质量分析")
        accuracy_data = {
            '状态': ['正确', '错误'],
            '数量': [stats['clickable_texts'] - stats['marked_errors'], stats['marked_errors']]
        }
        
        fig_bar = px.bar(
            accuracy_data, x='状态', y='数量', title="识别质量分布",
            color='状态', color_discrete_map={'正确': 'green', '错误': 'red'}
        )
        st.plotly_chart(fig_bar, use_container_width=True)
    
    with tab4:
        # 快速导航功能
        st.header("🚀 快速导航")
        
        if not validator.text_bbox_mapping:
            st.info("没有可用的文本项进行导航")
        else:
            # 按类别分组
            categories = group_texts_by_category(validator.text_bbox_mapping)
            
            # 创建导航按钮
            for category, texts in categories.items():
                with st.expander(f"{category} ({len(texts)}项)", expanded=False):
                    cols = st.columns(3)  # 每行3个按钮
                    for i, text in enumerate(texts):
                        col_idx = i % 3
                        with cols[col_idx]:
                            display_text = text[:15] + "..." if len(text) > 15 else text
                            if st.button(display_text, key=f"nav_{category}_{i}"):
                                st.session_state.selected_text = text
                                st.rerun()


if __name__ == "__main__":
    main()