# 导出文件权限
if file_privileges:
file_df = pd.DataFrame(file_privileges)
file_explanations = {col: "文件权限相关字段" for col in file_df.columns}
export_field_explanations(writer, "文件权限", file_df, file_explanations)

# 导出 UDF 信息
if udf_info:
udf_df = pd.DataFrame(udf_info)
udf_explanations = {col: "UDF 信息字段" for col in udf_df.columns}
export_field_explanations(writer, "UDF信息", udf_df, udf_explanations)

# 导出各数据表分析结果
for db, tables in db_structure.items():
for table, content in tables.items():
data = content["samples"]
columns = content["columns"]
df = pd.DataFrame(data, columns=columns)
# 如果有敏感字段信息，第一行标记
table_result = table_analysis.get(db, {}).get(table, {})
sensitive_fields = table_result.get("sensitive_fields", [])
sensitive_marks = ["敏感字段" if col in sensitive_fields else "" for col in columns]
mark_row = pd.DataFrame([sensitive_marks], columns=columns)
df = pd.concat([mark_row, df], ignore_index=True)
field_explanations = {col: f"{col} 的中文解释" for col in columns}
sheet_name = f"{db}_{table}"[:31]
export_field_explanations(writer, sheet_name, df, field_explanations)
logging.info(f"数据导出完成：{OUTPUT_FILE}")


# ====== 主流程 ======
def main():
conn = connect_db()
if not conn:
return

# 采集 MySQL 服务器数据
db_structure, server_info, access_logs, log_configs, file_privileges, udf_info = collect_db_info(conn)
conn.close()

# 第一步：对每个数据表进行单独分析
table_analysis = analyze_tables(db_structure, server_info)

# 第二步：对每个数据库的所有数据表分析结果进行汇总
db_summary = summarize_all_databases(db_structure, table_analysis)

# 第三步：结合服务器整体信息和各数据库汇总，再进行整体分析
server_overall = analyze_server_overall(server_info, db_summary, access_logs, log_configs, file_privileges, udf_info)

# 导出所有分析结果到 Excel
export_to_excel(db_structure, db_summary, table_analysis, server_info, access_logs, log_configs, file_privileges, udf_info, server_overall)
logging.info("整体流程完成！")


if name == "main":
main()