import streamlit as st
import re
import lark_oapi as lark
from lark_oapi.api.bitable.v1 import *
import time
import openpyxl
import os
from dotenv import load_dotenv
import logging
from tenacity import retry, stop_after_attempt, wait_exponential

# Configure logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

# Load environment variables
load_dotenv()

def parse_bitable_url(url):
    """
    Extracts app_token and table_id from a Bitable URL.
    Expected format: .../base/<app_token>?table=<table_id>...
    """
    try:
        # Extract app_token
        app_token_match = re.search(r'/base/([^/?]+)', url)
        if not app_token_match:
            return None, None
        app_token = app_token_match.group(1)

        # Extract table_id
        table_id_match = re.search(r'table=([^&]+)', url)
        if not table_id_match:
            return None, None
        table_id = table_id_match.group(1)
        
        return app_token, table_id
    except Exception:
        return None, None

def get_bitable_client(app_id, app_secret):
    return lark.Client.builder().app_id(app_id).app_secret(app_secret).build()

def get_table_fields(client, app_token, table_id):
    logger.info(f"Fetching fields for app_token={app_token}, table_id={table_id}")
    fields = []
    page_token = None
    has_more = True
    
    while has_more:
        req = ListAppTableFieldRequest.builder() \
            .app_token(app_token) \
            .table_id(table_id) \
            .page_size(100)
        
        if page_token:
            req.page_token(page_token)
            
        req = req.build()
            
        try:
            resp = client.bitable.v1.app_table_field.list(req)
        except Exception as e:
            logger.error(f"API call failed: {e}", exc_info=True)
            raise

        if not resp.success():
            logger.error(f"Failed to list fields: code={resp.code}, msg={resp.msg}, log_id={resp.get_log_id()}")
            raise Exception(f"Failed to list fields: {resp.msg}, log_id: {resp.get_log_id()}")
            
        if resp.data and resp.data.items:
            fields.extend(resp.data.items)
            logger.info(f"Fetched {len(resp.data.items)} fields. Current total: {len(fields)}")
            logger.info(f"Page token: {page_token} -> {resp.data.page_token}, Has more: {resp.data.has_more}")
        
        # Determine if we should continue based on result count
        # Some APIs return has_more=True even if they return fewer items than page_size on the last page.
        # But generally, if len(items) < page_size, it's the last page.
        # Or if len(items) == 0, we are done.
        
        items_count = len(resp.data.items) if (resp.data and resp.data.items) else 0
        
        if items_count < 100:
             has_more = False
        else:
             has_more = resp.data.has_more
             
        # Still keep the infinite loop safeguard just in case
        new_page_token = resp.data.page_token
        
        if has_more and new_page_token == page_token:
             logger.warning("Infinite loop detected: page_token did not update. Breaking.")
             has_more = False
             
        page_token = new_page_token
        
    logger.info(f"Total fields fetched: {len(fields)}")
    return fields

def validate_primary_keys(excel_columns, target_fields):
    # For Excel, we assume the first column is the primary key (or at least the one to check against)
    # But usually Excel doesn't have strict schema.
    # However, the user asked to check "Primary Key Name Type".
    # We can check if the Target PK name exists in Excel columns.
    
    target_pk = next((f for f in target_fields if f.is_primary), None)
    
    if not target_pk:
        return False, "Target table has no primary key."
        
    if target_pk.field_name not in excel_columns:
        return False, f"Target Primary Key '{target_pk.field_name}' not found in Excel columns."
    
    # We can't strictly validate TYPE from Excel as Excel types are loose, 
    # but we validated the existence of the PK column.
    return True, f"Primary key '{target_pk.field_name}' found in Excel."

@retry(stop=stop_after_attempt(3), wait=wait_exponential(multiplier=1, min=4, max=10))
def _send_batch(client, app_token, table_id, records):
    req = BatchCreateAppTableRecordRequest.builder() \
        .app_token(app_token) \
        .table_id(table_id) \
        .request_body(BatchCreateAppTableRecordRequestBody.builder().records(records).build()) \
        .build()
        
    resp = client.bitable.v1.app_table_record.batch_create(req)
    if not resp.success():
        logger.error(f"Batch create failed: code={resp.code}, msg={resp.msg}, log_id={resp.get_log_id()}")
        if resp.error:
             logger.error(f"Error details: {resp.error}")
        raise Exception(f"Batch create failed: {resp.msg}, log_id: {resp.get_log_id()}")

def sync_data(client, excel_rows, excel_columns, special_col_name, manual_source_value, excel_file_name, target_app_token, target_table_id, target_fields):
    target_field_names = {f.field_name: f for f in target_fields}
    
    batch_records = []
    total_records = len(excel_rows)
    
    if total_records == 0:
        st.warning("No records to sync.")
        return

    progress_bar = st.progress(0)
    status_text = st.empty()
    processed_count = 0
    
    for row in excel_rows:
        new_fields = {}
        # row is a tuple/list matching excel_columns order
        
        row_dict = dict(zip(excel_columns, row))
        
        # 1. Copy common fields
        for col_name, val in row_dict.items():
            if col_name in target_field_names and val is not None:
                # Basic type conversion for API
                # Excel reads everything as is (int, float, datetime, string)
                # API expects specific formats sometimes.
                # For simplicity, we send as is, assuming Lark SDK or API handles basic types.
                # DateTime might need conversion to timestamp if API requires it. 
                # Lark API expects Unix timestamp (ms) for Date fields usually.
                target_type = target_field_names[col_name].type
                
                if target_type == 5: # Date
                    if hasattr(val, 'timestamp'): # datetime object
                        new_fields[col_name] = int(val.timestamp() * 1000)
                    else:
                        new_fields[col_name] = val
                elif target_type == 4: # MultiSelect
                     # Excel might have comma separated string?
                     if isinstance(val, str):
                         new_fields[col_name] = [v.strip() for v in val.split(',')]
                     else:
                         new_fields[col_name] = val
                elif target_type == 11: # User
                    # User field is complex (list of objects). Excel might just have names.
                    # We might skip or try to pass simple text? 
                    # Writing text to User field usually fails or requires specific format.
                    # Let's skip complex fields for now or assume user knows what they are doing.
                    pass 
                else:
                    new_fields[col_name] = val
        
        # 2. Handle Special "Source Record" Column
        if special_col_name and special_col_name in target_field_names:
            target_col_def = target_field_names[special_col_name]
            
            # Use manual value provided by user if available, otherwise fallback to filename
            final_val = manual_source_value if manual_source_value else f"Imported from {excel_file_name}"
            
            if target_col_def.type == 15: # Hyperlink
                 # If final_val is a string that looks like a URL, use it
                 # If it's just text, treat as text
                 link_url = str(final_val) if final_val else ""
                 if not link_url.startswith("http"):
                      link_url = "" # Can't link if no URL
                 
                 new_fields[special_col_name] = {
                     "link": link_url,
                     "text": str(final_val)
                 }
            else: 
                 new_fields[special_col_name] = final_val

        batch_records.append(AppTableRecord.builder().fields(new_fields).build())
        
        if len(batch_records) >= 100:
            _send_batch(client, target_app_token, target_table_id, batch_records)
            processed_count += len(batch_records)
            progress_bar.progress(processed_count / total_records)
            status_text.text(f"Synced {processed_count}/{total_records} records")
            batch_records = []
            
    if batch_records:
        _send_batch(client, target_app_token, target_table_id, batch_records)
        processed_count += len(batch_records)
        progress_bar.progress(1.0)
        status_text.text(f"Synced {processed_count}/{total_records} records")

def main():
    st.set_page_config(page_title="Bitbcpy - 多维表格合并工具", layout="wide")
    st.title("Bitbcpy - 多维表格合并脚本")
    st.markdown("将本地 Excel 的行抄到目标表，同名列合并，忽略目标表不存在的列。")

    if 'target_fields' not in st.session_state:
        st.session_state.target_fields = []
    if 'target_fields_loaded' not in st.session_state:
        st.session_state.target_fields_loaded = False

    with st.sidebar:
        st.header("配置")
        
        default_app_id = os.getenv("LARK_OAPI_APPID", "")
        default_app_secret = os.getenv("LARK_OAPI_SECRET", "")
        
        app_id = st.text_input("App ID", value=default_app_id)
        app_secret = st.text_input("App Secret", type="password", value=default_app_secret)
        
    target_url = st.text_input("目标文档链接")
    
    if st.button("读取目标表字段"):
        if not app_id or not app_secret:
            st.error("请填写 App ID 和 App Secret")
        elif not target_url:
            st.error("请填写目标文档链接")
        else:
            t_token, t_table = parse_bitable_url(target_url)
            if not (t_token and t_table):
                st.error("目标链接解析失败")
            else:
                client = get_bitable_client(app_id, app_secret)
                try:
                    with st.spinner("Fetching schema..."):
                         fields = get_table_fields(client, t_token, t_table)
                         st.session_state.target_fields = fields
                         st.session_state.target_fields_loaded = True
                         st.success("字段加载成功")
                except Exception as e:
                     st.error(f"Error: {str(e)}")
    
    source_col = None
    manual_source_val = None
    
    if st.session_state.target_fields_loaded:
        field_names = [f.field_name for f in st.session_state.target_fields]
        source_col = st.selectbox("哪一列记录来源", options=field_names)
        manual_source_val = st.text_input("该列统一填写的来源信息", help="例如：2023年Q1销售数据")

    uploaded_file = st.file_uploader("上传来源 Excel (xlsx)", type=['xlsx'])

    if st.button("开始合并"):
        if not app_id or not app_secret:
            st.error("请在左侧侧边栏填写 App ID 和 App Secret")
            return
        
        if not uploaded_file:
            st.error("请上传来源 Excel 文件")
            return
            
        t_token, t_table = parse_bitable_url(target_url)
        
        if not (t_token and t_table):
            st.error("目标链接解析失败，请检查链接格式")
            return
            
        client = get_bitable_client(app_id, app_secret)
        
        try:
            # Read Excel
            wb = openpyxl.load_workbook(uploaded_file, data_only=True)
            sheet = wb.active
            
            # Assuming first row is header
            rows = list(sheet.iter_rows(values_only=True))
            if not rows:
                st.error("Excel 文件为空")
                return
                
            header = rows[0]
            data_rows = rows[1:]
            
            # Filter None headers
            excel_columns = [str(h) for h in header if h is not None]
            
            # Use cached fields if available, else fetch
            t_fields = st.session_state.target_fields
            if not t_fields:
                 with st.spinner("Fetching target table schema..."):
                    t_fields = get_table_fields(client, t_token, t_table)
                
            valid, msg = validate_primary_keys(excel_columns, t_fields)
            if not valid:
                st.error(f"主键校验失败: {msg}")
                return
            else:
                st.success("主键校验通过")
                
            st.info(f"Found {len(data_rows)} records in Excel.")
            
            sync_data(client, data_rows, excel_columns, source_col, manual_source_val, uploaded_file.name, t_token, t_table, t_fields)
            st.success("合并完成！")
            
        except Exception as e:
            logger.error(f"Error in main loop: {e}", exc_info=True)
            st.error(f"Error: {str(e)}")

if __name__ == "__main__":
    main()