From 615278958c7bb79bfa27fc1126af49980f042449 Mon Sep 17 00:00:00 2001
From: alexad <643757595@qq.com>
Date: Fri, 18 Oct 2024 08:43:39 +0000
Subject: [PATCH] python post_processing.py --input_csv
 /home/xieyukai/ceshi/evaluation_results_20241018_105411.csv --output_path
 /home/xieyukai/ceshi/

Signed-off-by: alexad <643757595@qq.com>
---
 .../post_processing.py                        | 88 +++++++++++++++++++
 1 file changed, 88 insertions(+)
 create mode 100644 app/customer_service_evaluation_system/post_processing.py

diff --git a/app/customer_service_evaluation_system/post_processing.py b/app/customer_service_evaluation_system/post_processing.py
new file mode 100644
index 0000000..d9f20bb
--- /dev/null
+++ b/app/customer_service_evaluation_system/post_processing.py
@@ -0,0 +1,88 @@
+import glob
+import pymysql
+import pandas as pd
+import argparse
+from rich.console import Console
+from rich.table import Table
+import cfg
+parser = argparse.ArgumentParser(description="Process Excel files and update with database information.")
+parser.add_argument('--input_csv', required=True, help='Path to input .xlsx file or directory containing .xlsx files.')
+parser.add_argument('--output_path', required=True, help='Path to save the updated .xlsx files.')
+args = parser.parse_args()
+
+db = pymysql.connect(
+    host=cfg.db["host"],
+    port=cfg.db["port"],
+    user=cfg.db["user"],
+    password=cfg.db["password"],
+    database=cfg.db["database"]
+)
+cursor = db.cursor()
+
+file_paths = glob.glob(f"{args.input_csv}/*.xlsx") if args.input_csv.endswith('/') else [args.input_csv]
+console = Console()
+
+for file_path in file_paths:
+    df = pd.read_csv(file_path)
+    print("Excel 文件加载完成，共有行数:", len(df))
+    df['ID'] = df['ID'].astype(str)
+    df[['caller_num', 'callee_num', 'url']] = None
+
+    begintimes = df['ID'].str[:14].unique()
+    begintime_str = ','.join([f"'{bt[:4]}-{bt[4:6]}-{bt[6:8]} {bt[8:10]}:{bt[10:12]}:{bt[12:]}'" for bt in begintimes])
+    query1 = f"SELECT begintime, customer_uuid, record_file_name FROM cti_record WHERE begintime IN ({begintime_str});"
+    cursor.execute(query1)
+    results1 = cursor.fetchall()
+    begintime_map = {str(row[0]): (row[1], row[2]) for row in results1}
+    customer_uuids = [row[1] for row in results1 if row[1] is not None]
+    customer_uuid_str = ','.join([f"'{uuid}'" for uuid in customer_uuids])
+
+    if customer_uuid_str:
+        query2 = f"SELECT call_uuid, caller_num, callee_num FROM cti_cdr_call WHERE call_uuid IN ({customer_uuid_str});"
+        cursor.execute(query2)
+        results2 = cursor.fetchall()
+        customer_uuid_map = {row[0]: (row[1], row[2]) for row in results2}
+    else:
+        customer_uuid_map = {}
+        print("未找到任何有效的 customer_uuid，跳过相关查询。")
+
+    for index, row in df.iterrows():
+        begintime = row['ID'][:14]
+        formatted_begintime = f"{begintime[:4]}-{begintime[4:6]}-{begintime[6:8]} {begintime[8:10]}:{begintime[10:12]}:{begintime[12:]}"
+        if formatted_begintime in begintime_map:
+            customer_uuid, record_file_name = begintime_map[formatted_begintime]
+            if customer_uuid in customer_uuid_map:
+                caller_num, callee_num = customer_uuid_map[customer_uuid]
+                df.at[index, 'caller_num'] = caller_num
+                df.at[index, 'callee_num'] = callee_num
+                df.at[index, 'url'] = f"http://116.62.120.233{record_file_name}"
+            else:
+                print(f"未找到 customer_uuid {customer_uuid} 对应的 caller_num 和 callee_num。")
+        else:
+            print(f"未找到 begintime {formatted_begintime} 对应的 customer_uuid 和 record_file_name。")
+
+    output_file_path = f"{args.output_path}/{file_path.split('/')[-1].replace('.csv', '.xlsx')}"
+    df.to_excel(output_file_path, index=False)
+
+    filtered_columns = [col for col in df.columns if 'ID' not in col and '原因' not in col and '关键' in col]
+    main_table = Table(title="Evaluation Results", show_header=True)
+    main_table.add_column("Category", justify="left", style="cyan", width=20)
+    main_table.add_column("Value", justify="left", style="cyan", width=45)
+    main_table.add_column("Count", justify="right", style="magenta", width=10)
+    main_table.add_column("Percentage", justify="right", style="green", width=15)
+
+    for col in filtered_columns:
+        value_counts = df[col].value_counts()
+        percentages = value_counts / value_counts.sum() * 100
+        for i, (value, count) in enumerate(value_counts.items()):
+            percentage = '{:.2f}%'.format(percentages[value])
+            if i == 0:
+                main_table.add_row(col, str(value), str(count), percentage)
+            else:
+                main_table.add_row("", str(value), str(count), percentage)
+
+    console.print(main_table)
+
+cursor.close()
+db.close()
+print("数据库连接已关闭")
-- 
Gitee