{"id":6988,"date":"2025-07-02T09:02:55","date_gmt":"2025-07-02T01:02:55","guid":{"rendered":"https:\/\/www.xinyixx.com\/?p=6988"},"modified":"2025-07-02T09:02:55","modified_gmt":"2025-07-02T01:02:55","slug":"coding","status":"publish","type":"post","link":"https:\/\/www.xinyixx.com\/index.php\/2025\/07\/02\/coding\/","title":{"rendered":"\u7a7a\u8c03\u98ce\u673a\u542f\u505c\u65f6\u957f\u7edf\u8ba1\u7684\u7cfb\u7edf\u5f00\u53d1"},"content":{"rendered":"

\u65b9\u68481\uff1a\u56fe\u5f62\u8bc6\u522b<\/h2>\n\n\n\n

\u7528 Python \u56fe\u50cf\u8bc6\u522b + \u81ea\u52a8\u5316\u64cd\u4f5c \u6765\u5b9e\u73b0\u98ce\u673a\u65f6\u957f\u7684\u76d1\u63a7\u4e0e\u7edf\u8ba1\uff1a<\/p>\n\n\n\n

1.1\u7528python \u7f16\u7a0b\u601d\u60f3\u5b9e\u73b0\u601d\u8def<\/h3>\n\n\n\n

\u2e3b<\/p>\n\n\n\n

\u2705 \u603b\u4f53\u5b9e\u73b0\u76ee\u6807\u62c6\u89e3<\/p>\n\n\n\n

\ud83c\udfaf \u4f60\u7684\u76ee\u6807\uff1a 1. \u8bc6\u522b\u6240\u6709\u98ce\u673a\u5f53\u524d\u72b6\u6001\uff08\u7eff\u8272 = \u5f00\uff0c\u7070\u8272 = \u5173\uff09\uff1b 2. \u5b9a\u65f6\u68c0\u6d4b\u72b6\u6001\u53d8\u66f4\u5e76\u8bb0\u5f55\u8d77\u6b62\u65f6\u95f4\uff1b 3. \u81ea\u52a8\u7ffb\u9875\u5207\u6362\u4e0d\u540c\u697c\u5c42\uff08\u53f3\u4e0a\u89d2\u70b9\u51fb\uff09\uff1b 4. \u5468\u671f\u6027\u6c47\u603b\u7edf\u8ba1\u5f00\u673a\u65f6\u95f4\u5e76\u5bfc\u51fa Excel\u3002<\/p>\n\n\n\n

\u2e3b<\/p>\n\n\n\n

\u2705 \u5efa\u8bae\u65b9\u6848\uff1a\u4f7f\u7528 Python \u81ea\u52a8\u5316\u6846\u67b6<\/p>\n\n\n\n

\u6280\u672f\u6a21\u5757<\/th>\u5de5\u5177\/\u5e93<\/th><\/tr><\/thead>
\u56fe\u50cf\u8bc6\u522b\uff08\u989c\u8272\u8bc6\u522b\uff09<\/td>PIL \u6216 OpenCV<\/td><\/tr>
\u5c4f\u5e55\u622a\u56fe<\/td>pyautogui \u6216 mss<\/td><\/tr>
\u81ea\u52a8\u70b9\u51fb\u697c\u5c42\u5207\u6362\u6309\u94ae<\/td>pyautogui<\/td><\/tr>
\u6570\u636e\u5b58\u50a8\/\u5bfc\u51fa<\/td>pandas + openpyxl<\/td><\/tr>
\u540e\u53f0\u5b9a\u65f6\u8fd0\u884c<\/td>threading + schedule\uff08\u53ef\u9009\uff09<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

\u2e3b<\/p>\n\n\n\n

\ud83e\udde0 \u57fa\u7840\u539f\u7406\u8bf4\u660e 1. \u6bcf\u4e2a\u98ce\u673a\u662f\u4e00\u4e2a\u201c\u5361\u7247\u201d\uff0c\u4e2d\u95f4\u662f\u4e00\u4e2a \u98ce\u6247\u56fe\u6807\uff0c\u989c\u8272\u4e3a\u7eff\u6216\u7070\uff1b 2. \u6bcf\u9875\u56fe\u6807\u6570\u91cf\u56fa\u5b9a\u3001\u6392\u5e03\u6574\u9f50\uff0c\u56e0\u6b64\u53ef\u4ee5\u7528\u7f51\u683c\u65b9\u5f0f\u8ba1\u7b97\u6bcf\u4e2a\u56fe\u6807\u7684\u5750\u6807\u4e2d\u5fc3\u70b9\uff1b 3. \u6bcf\u9694 1 \u5206\u949f\u622a\u56fe\uff0c\u68c0\u6d4b\u6bcf\u4e2a\u70b9\u7684\u989c\u8272\u53d8\u5316\uff0c\u5e76\u66f4\u65b0\u8fd0\u884c\u65f6\u95f4\u8bb0\u5f55\uff1b 4. \u6bcf\u9875\u76d1\u6d4b\u5b8c\u540e\uff0c\u70b9\u51fb\u53f3\u4e0a\u89d2\u7bad\u5934\uff08\u4f60\u63d0\u4f9b\u56fe\u4e2d\u90a3\u4e2a \u84dd\u8272\u5706\u5f62\u56fe\u6807\uff09\uff0c\u8fdb\u5165\u4e0b\u4e00\u9875\u7ee7\u7eed\u8bc6\u522b\uff1b 5. \u6240\u6709\u9875\u5b8c\u6210\u540e\uff0c\u7b49\u5f85\u4e00\u5206\u949f\u7ee7\u7eed\u4e0b\u4e00\u8f6e\u3002<\/p>\n\n\n\n

\u2e3b<\/p>\n\n\n\n

\u2705 \u6838\u5fc3\u6d41\u7a0b\u4e0e\u4ee3\u7801\u6846\u67b6<\/p>\n\n\n\n

\ud83d\uddbc\ufe0f 1. \u83b7\u53d6\u98ce\u673a\u4f4d\u7f6e\u5750\u6807\uff08\u624b\u52a8\u6807\u4e00\u6b21\uff09<\/p>\n\n\n\n

\u4f60\u53ea\u9700\u5728\u5c4f\u5e55\u5206\u8fa8\u7387\u4e00\u81f4\u7684\u524d\u63d0\u4e0b\uff0c\u7528\u622a\u56fe\u5de5\u5177\u6807\u51fa\u7b2c\u4e00\u6392\u7b2c\u4e00\u4e2a\u98ce\u673a\u56fe\u6807\u4e2d\u5fc3\u5750\u6807\uff0c\u6bd4\u5982\uff1a(120, 240)\uff0c\u6bcf\u4e2a\u98ce\u673a\u5bbd\u7ea6 120px\uff0c\u9ad8\u7ea6 100px\uff0c\u5219\uff1a<\/p>\n\n\n\n

\u5047\u8bbe\u754c\u9762\u67096\u884c \u00d7 8\u5217\u98ce\u673a\u5361\u7247<\/p>\n\n\n\n

 fan_positions = []
 start_x, start_y = 120, 240
 x_spacing, y_spacing = 120, 100
 rows, cols = 6, 8
 \u200b
 for r in range(rows):
     for c in range(cols):
         fan_positions.append((
             start_x + c * x_spacing,
             start_y + r * y_spacing
         ))<\/pre>\n\n\n\n
\u2e3b<\/p>\n\n\n\n
\ud83c\udfa8 2. \u5224\u65ad\u56fe\u6807\u989c\u8272\u662f\u5426\u4e3a\u7eff\u8272<\/p>\n\n\n\n
 from PIL import ImageGrab
 \u200b
 def is_fan_on(pixel):
     r, g, b = pixel
     return g > 180 and r < 100 and b < 100  # \u7eff\u8272
 \u200b
 def check_fan_status(x, y):
     screenshot = ImageGrab.grab()
     pixel = screenshot.getpixel((x, y))
     return \"ON\" if is_fan_on(pixel) else \"OFF\"<\/pre>\n\n\n\n
\u2e3b<\/p>\n\n\n\n
\ud83d\uddb1\ufe0f 3. \u81ea\u52a8\u70b9\u51fb\u53f3\u4e0a\u89d2\u7ffb\u9875\u6309\u94ae<\/p>\n\n\n\n
 import pyautogui
 \u200b
 def click_next_floor():
     pyautogui.moveTo(990, 140)  # \u6b64\u4e3a\u53f3\u4e0a\u89d2\u6309\u94ae\u7684\u5927\u81f4\u4f4d\u7f6e\uff0c\u8bf7\u7528 pyautogui.position() \u7cbe\u8c03
     pyautogui.click()
 \u200b<\/pre>\n\n\n\n
\u4f60\u53ef\u4ee5\u5148\u8fd0\u884c\uff1a<\/p>\n\n\n\n
pyautogui.position()<\/code><\/p>\n\n\n\n
\u5c06\u9f20\u6807\u79fb\u52a8\u5230\u4f60\u622a\u56fe\u4e2d\u90a3\u4e2a \u201c\u53f3\u4e0a\u89d2\u7ffb\u9875\u7bad\u5934\u6309\u94ae\u201d \u4e0a\uff0c\u8bb0\u5f55\u5176\u5750\u6807\u503c\u3002<\/p>\n\n\n\n
\u2e3b<\/p>\n\n\n\n
\ud83d\udcca 4. \u8bb0\u5f55\u72b6\u6001\u5207\u6362\u4e0e\u6301\u7eed\u65f6\u95f4<\/p>\n\n\n\n
 from datetime import datetime
 \u200b
 status_log = {}
 run_records = []
 \u200b
 def update_fan_status(fan_id, new_status):
     now = datetime.now()
     last_status, start_time = status_log.get(fan_id, (None, None))
 \u200b
 if new_status != last_status:
     if new_status == \"ON\":
         status_log[fan_id] = (\"ON\", now)
     elif new_status == \"OFF\" and start_time:
         duration = (now - start_time).total_seconds() \/ 60
         run_records.append({
             \"FanID\": fan_id,
             \"StartTime\": start_time,
             \"EndTime\": now,
             \"Duration(min)\": duration
         })
         status_log[fan_id] = (\"OFF\", None)<\/pre>\n\n\n\n
\u2e3b<\/p>\n\n\n\n
\ud83d\udce6 5. \u5bfc\u51fa\u4e3a Excel<\/p>\n\n\n\n
 import pandas as pd
 def export_to_excel():
     df = pd.DataFrame(run_records)
     df.to_excel(\"fan_log.xlsx\", index=False)<\/pre>\n\n\n\n
\u2e3b<\/p>\n\n\n\n
\ud83d\udd01 6. \u603b\u5faa\u73af\uff08\u591a\u9875\u8f6e\u8be2\uff09<\/p>\n\n\n\n
 def monitor_all_pages(total_pages=8):
     for page in range(total_pages):
         for idx, (x, y) in enumerate(fan_positions):
             fan_id = f\"P{page+1}-F{idx+1}\"
             status = check_fan_status(x, y)
             update_fan_status(fan_id, status)
         click_next_floor()
         time.sleep(3)  # \u7b49\u9875\u9762\u5237\u65b0<\/pre>\n\n\n\n
\u2e3b<\/p>\n\n\n\n
1.2\u5b8c\u6574\u5b9e\u73b0\u65b9\u6848\u4e0e\u4e0b\u4e00\u6b65\u8ba1\u5212<\/h3>\n\n\n\n
\u2e3b<\/p>\n\n\n\n
\u2705 \u9879\u76ee\u76ee\u6807\u6982\u8ff0<\/p>\n\n\n\n
\u529f\u80fd\u6a21\u5757<\/th>\u5185\u5bb9<\/th><\/tr><\/thead>
\u2460 \u56fe\u50cf\u8bc6\u522b<\/td>\u81ea\u52a8\u8bc6\u522b\u5c4f\u5e55\u4e0a\u98ce\u673a\u7684\u72b6\u6001\uff08\u7eff=\u5f00\uff0c\u7070=\u5173\uff09<\/td><\/tr>
\u2461 \u72b6\u6001\u76d1\u63a7<\/td>\u5b9a\u65f6\u8bc6\u522b\u5404\u98ce\u673a\u72b6\u6001\u53d8\u5316\uff0c\u8bb0\u5f55\u5f00\u5173\u65f6\u95f4<\/td><\/tr>
\u2462 \u697c\u5c42\u5207\u6362<\/td>\u81ea\u52a8\u70b9\u51fb\u53f3\u4e0a\u89d2\u6309\u94ae\uff0c\u8f6e\u8be28\u4e2a\u697c\u5c42<\/td><\/tr>
\u2463 \u6570\u636e\u5b58\u50a8<\/td>\u8bb0\u5f55\u6bcf\u6b21\u98ce\u673a\u5f00\u5173\u7684\u6301\u7eed\u65f6\u95f4<\/td><\/tr>
\u2464 \u7edf\u8ba1\u5206\u6790<\/td>\u6309\u6708\/\u5b63\u5ea6\/\u5e74\u7edf\u8ba1\u5f00\u673a\u65f6\u957f<\/td><\/tr>
\u2465 \u5bfc\u51fa Excel<\/td>\u5c06\u8bb0\u5f55\u5bfc\u51fa\u4e3a .xlsx \u62a5\u8868<\/td><\/tr>
\u2466 GUI \u9762\u677f<\/td>\u63d0\u4f9b\u53ef\u89c6\u5316\u6309\u94ae\u4e0e\u542f\u52a8\u3001\u67e5\u770b\u72b6\u6001\u7b49\u529f\u80fd\uff08\u53ef\u9009\uff09<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n
\u2e3b<\/p>\n\n\n\n
\ud83d\udee0\ufe0f \u63a5\u4e0b\u6765\u7684\u6b65\u9aa4\u5b89\u6392<\/p>\n\n\n\n
\u2705 Step 1\uff1a\u56fe\u50cf\u8bc6\u522b\u5750\u6807 & \u521d\u59cb\u6d4b\u8bd5\u811a\u672c<\/p>\n\n\n\n
\u6211\u4eec\u5148\u751f\u6210\uff1a \u2022 \u57fa\u4e8e\u4f60\u56fe\u4e2d\u9875\u9762\u8bc6\u522b\u7684 48 \u4e2a\u98ce\u673a\u4f4d\u7f6e\u5750\u6807\uff1b \u2022 \u63d0\u4f9b\u4e00\u4e2a\u53ef\u8fd0\u884c\u7684 .py \u811a\u672c\uff0c\u5b9a\u65f6\u622a\u56fe\u8bc6\u522b\u98ce\u673a\u72b6\u6001\uff0c\u5e76\u8f93\u51fa\u5f53\u524d\u9875\u98ce\u673a\u72b6\u6001\u5217\u8868\u3002<\/p>\n\n\n\n
\u2e3b<\/p>\n\n\n\n
\u2705 Step 2\uff1a\u72b6\u6001\u53d8\u5316\u8bb0\u5f55\u903b\u8f91<\/p>\n\n\n\n
\u63a5\u4e0b\u6765\u6211\u5c06\u5b9e\u73b0\u4ee5\u4e0b\u529f\u80fd\uff1a \u2022 \u6bcf\u4e2a\u98ce\u673a\u72b6\u6001\u4ece\u201c\u7070\u2192\u7eff\u2192\u7070\u201d\u7b97\u4e00\u6b21\u8fd0\u884c\uff1b \u2022 \u8bb0\u5f55\u5f00\u59cb\u65f6\u95f4\u3001\u7ed3\u675f\u65f6\u95f4\u3001\u6301\u7eed\u5206\u949f\uff1b \u2022 \u4fdd\u5b58\u5728 CSV\/Excel \u4e2d\uff0c\u5e76\u53ef\u5b9a\u671f\u6c47\u603b\u3002<\/p>\n\n\n\n
\u2e3b<\/p>\n\n\n\n
\u2705 Step 3\uff1a\u697c\u5c42\u8f6e\u8be2 & \u81ea\u52a8\u70b9\u51fb<\/p>\n\n\n\n
\u7cfb\u7edf\u4f1a\uff1a \u2022 \u8bc6\u522b\u5f53\u524d\u9875\u98ce\u673a\uff1b \u2022 \u81ea\u52a8\u70b9\u51fb\u53f3\u4e0a\u89d2\u6309\u94ae\uff1b \u2022 \u7ee7\u7eed\u8bc6\u522b\u4e0b\u4e00\u9875\uff0c\u76f4\u5230\u5168\u90e8\u9875\u5b8c\u6210\u3002<\/p>\n\n\n\n
\u2e3b<\/p>\n\n\n\n
\u2705 Step 4\uff1a\u7edf\u8ba1\u6c47\u603b\u4e0e\u5bfc\u51fa<\/p>\n\n\n\n
\u5c06\u63d0\u4f9b\uff1a \u2022 \u6708\u5ea6\u3001\u5b63\u5ea6\u3001\u5e74\u5ea6\u7edf\u8ba1\u6c47\u603b\u51fd\u6570\uff1b \u2022 \u6bcf\u53f0\u98ce\u673a\u7684\u5f00\u673a\u65f6\u957f\u3001\u9891\u6b21\u3001\u56fe\u8868\uff08\u53ef\u9009\uff09\uff1b \u2022 \u5bfc\u51fa\u4e3a Excel \u62a5\u8868\u683c\u5f0f\uff08EPPlus or pandas\uff09\u3002<\/p>\n\n\n\n
\u2e3b<\/p>\n\n\n\n
\u2705 Step 5\uff08\u53ef\u9009\uff09\uff1a\u5e26 GUI \u7684\u76d1\u63a7\u5de5\u5177<\/p>\n\n\n\n
\u4f60\u53ef\u4ee5\u62e5\u6709\uff1a \u2022 \u56fe\u5f62\u754c\u9762\u5e26\u6309\u94ae\u542f\u52a8\u76d1\u63a7\uff1b \u2022 \u53ef\u89c6\u5316\u72b6\u6001\u663e\u793a\uff08\u4f8b\u5982\u7eff\u7ea2\u706f\u6807\u5fd7\uff09\uff1b \u2022 \u5bfc\u51fa\u4e00\u952e\u70b9\u51fb\u3002<\/p>\n\n\n\n
\u2e3b<\/p>\n\n\n\n
1.3\u751f\u6210\u4e00\u4e2a\u5b8c\u6574\u53ef\u8fd0\u884c\u7684 Python \u811a\u672c<\/h3>\n\n\n\n
\u5b9e\u73b0\uff1a<\/p>\n\n\n\n
\u2705 \u56fe\u50cf\u8bc6\u522b\u98ce\u673a\u72b6\u6001 \u2705 \u6bcf5\u5206\u949f\u81ea\u52a8\u8f6e\u8be2\u8bc6\u522b\u6240\u6709\u9875\u9762\uff088\u9875\uff09 \u2705 \u81ea\u52a8\u70b9\u51fb\u53f3\u4e0a\u89d2\u5207\u9875\u6309\u94ae \u2705 \u8bb0\u5f55\u6bcf\u53f0\u98ce\u673a\u5f00\u542f\uff08\u7eff\u8272\uff09\u6301\u7eed\u65f6\u95f4 \u2705 \u5bfc\u51fa\u8fd0\u884c\u8bb0\u5f55\u4e3a Excel \u8868\u683c<\/p>\n\n\n\n
\u2e3b<\/p>\n\n\n\n
\ud83e\udde0 \u5b9e\u73b0\u524d\u63d0 \u2022 \u754c\u9762\u6392\u5e03\u4e3a 6 \u884c \u00d7 8 \u5217\uff08\u5171 48 \u53f0\u98ce\u673a\uff09\uff1b \u2022 \u6bcf\u9875\u98ce\u673a\u4f4d\u7f6e\u4e00\u81f4\uff1b \u2022 \u9f20\u6807\u81ea\u52a8\u70b9\u51fb\u53f3\u4e0a\u89d2\u7bad\u5934\u7ffb\u9875\uff08\u6211\u9ed8\u8ba4\u5176\u5750\u6807\u4e3a (1840, 140)\uff0c\u4f60\u53ef\u5fae\u8c03\uff09\uff1b \u2022 \u72b6\u6001\u5224\u65ad\u57fa\u4e8e\u4e2d\u5fc3\u50cf\u7d20\u662f\u5426\u4e3a\u7eff\u8272\u3002<\/p>\n\n\n\n
\u2e3b<\/p>\n\n\n\n
\ud83d\udce6 \u6587\u4ef6\u7ed3\u6784<\/p>\n\n\n\n
 fan_monitor\/
 \u251c\u2500\u2500 fan_monitor.py           # \u4e3b\u7a0b\u5e8f\uff08\u8f6e\u8be2+\u8bc6\u522b+\u8bb0\u5f55+\u5bfc\u51fa\uff09
 \u251c\u2500\u2500 fan_log.xlsx             # \u5bfc\u51fa\u7684\u8fd0\u884c\u65e5\u5fd7<\/pre>\n\n\n\n
\u2e3b<\/p>\n\n\n\n
\u2705 \u5b8c\u6574\u811a\u672c\uff08fan_monitor.py\uff09<\/p>\n\n\n\n
 import pyautogui
 import time
 from datetime import datetime
 from PIL import ImageGrab
 import pandas as pd
 import os
 \u200b
 ========== \u914d\u7f6e\u90e8\u5206 ==========
 \u200b
 ROWS = 6
 COLS = 8
 PAGES = 8
 X0, Y0 = 190, 270  # \u7b2c\u4e00\u4e2a\u98ce\u673a\u56fe\u6807\u4e2d\u5fc3\u5750\u6807\uff08\u53c2\u8003\u622a\u56fe\uff09
 X_GAP = 172        # \u6a2a\u5411\u95f4\u8ddd
 Y_GAP = 120        # \u7eb5\u5411\u95f4\u8ddd
 NEXT_BUTTON_POS = (1840, 140)  # \u7ffb\u9875\u6309\u94ae\u5750\u6807\uff08\u53f3\u4e0a\u89d2\uff09
 SCREEN_REGION = (0, 0, 1920, 1080)
 CHECK_INTERVAL = 300  # \u8f6e\u8be2\u95f4\u9694\uff08\u79d2\uff09
 \u200b
 ========== \u6570\u636e\u7ed3\u6784 ==========
 \u200b
 status_log = {}  # {fan_id: (\"ON\"\/\"OFF\", start_time)}
 run_records = []  # \u8fd0\u884c\u65f6\u95f4\u6bb5\u8bb0\u5f55\u5217\u8868
 \u200b
 def get_fan_positions():
     positions = []
     for row in range(ROWS):
         for col in range(COLS):
             x = X0 + col * X_GAP
             y = Y0 + row * Y_GAP
             positions.append((x, y))
     return positions
 \u200b
 def is_green(pixel):
     r, g, b = pixel
     return g > 180 and r < 100 and b < 100
 \u200b
 def check_status(screenshot, pos):
     pixel = screenshot.getpixel(pos)
     return \"ON\" if is_green(pixel) else \"OFF\"
 \u200b
 def update_status(fan_id, new_status):
     now = datetime.now()
     last_status, start_time = status_log.get(fan_id, (None, None))
     if new_status != last_status:
         if new_status == \"ON\":
             status_log[fan_id] = (\"ON\", now)
         elif new_status == \"OFF\" and start_time:
             duration = (now - start_time).total_seconds() \/ 60
             run_records.append({
                 \"FanID\": fan_id,
                 \"StartTime\": start_time,
                 \"EndTime\": now,
                 \"Duration(min)\": duration
             })
             status_log[fan_id] = (\"OFF\", None)
 \u200b
 def click_next_page():
     pyautogui.moveTo(*NEXT_BUTTON_POS)
     pyautogui.click()
     time.sleep(2)  # \u7b49\u5f85\u9875\u9762\u5237\u65b0
 \u200b
 def monitor_once():
     fan_positions = get_fan_positions()
     for page in range(PAGES):
         screenshot = ImageGrab.grab(SCREEN_REGION)
         for idx, pos in enumerate(fan_positions):
             fan_id = f\"P{page+1}-F{idx+1}\"
             status = check_status(screenshot, pos)
             update_status(fan_id, status)
         if page < PAGES - 1:
             click_next_page()
 \u200b
 def export_log():
     if not run_records:
         return
     df = pd.DataFrame(run_records)
     os.makedirs(\"export\", exist_ok=True)
     df.to_excel(f\"export\/fan_log_{datetime.now().strftime('%Y%m%d_%H%M%S')}.xlsx\", index=False)
 \u200b
 def run_monitor():
     print(\"\u542f\u52a8\u98ce\u673a\u76d1\u63a7...\")
     try:
         while True:
             print(f\"[{datetime.now().strftime('%Y-%m-%d %H:%M:%S')}] \u8f6e\u8be2\u4e2d...\")
             monitor_once()
             export_log()
             time.sleep(CHECK_INTERVAL)
     except KeyboardInterrupt:
         print(\"\u76d1\u63a7\u4e2d\u65ad\uff0c\u5bfc\u51fa\u8bb0\u5f55...\")
         export_log()
 \u200b
 if __name__ == \"__main__\":
     run_monitor()<\/pre>\n\n\n\n
\u2e3b<\/p>\n\n\n\n
\u2705 \u4f7f\u7528\u8bf4\u660e 1. \u5b89\u88c5\u4f9d\u8d56\uff08\u786e\u4fdd\u7528 Python 3.9+\uff09\uff1a<\/p>\n\n\n\n
pip install pyautogui pillow pandas openpyxl<\/pre>\n\n\n\n
    \n
  1. \u8fd0\u884c\u811a\u672c\uff08\u8bb0\u5f97\u5148\u6253\u5f00\u98ce\u673a\u76d1\u63a7\u754c\u9762\uff09\uff1a<\/li>\n<\/ol>\n\n\n\n
    python fan_monitor.py<\/pre>\n\n\n\n
      \n
    1. \u7ed3\u679c\u5bfc\u51fa\uff1a<\/li>\n<\/ol>\n\n\n\n
      \u2022 \u6bcf\u8f6e\u8fd0\u884c\u540e\uff0c\u4f1a\u5728 export\/ \u6587\u4ef6\u5939\u4e2d\u751f\u6210 fan_log_*.xlsx \u6587\u4ef6\uff1b \u2022 \u6587\u4ef6\u5305\u542b\u6bcf\u4e2a\u98ce\u673a\u7684\u8fd0\u884c\u65f6\u95f4\u6bb5\u53ca\u6301\u7eed\u65f6\u95f4\u3002<\/p>\n\n\n\n
      \u2e3b<\/p>\n\n\n\n
      \u2705 \u540e\u7eed\u53ef\u52a0\u529f\u80fd\uff08\u53ef\u6309\u9700\u6dfb\u52a0\uff09<\/p>\n\n\n\n
      \u529f\u80fd<\/th>\u5b9e\u73b0\u65b9\u5f0f<\/th><\/tr><\/thead>
      GUI \u53ef\u89c6\u5316\u76d1\u63a7\u754c\u9762<\/td>\u4f7f\u7528 Tkinter or PyQt<\/td><\/tr>
      \u5f02\u5e38\u62a5\u8b66\uff08\u8fde\u7eed\u8fd0\u884c\u8d85\u65f6\uff09<\/td>\u52a0\u9608\u503c\u5224\u65ad<\/td><\/tr>
      \u5206\u6790\u56fe\u8868\uff08\u8fd0\u884c\u8d8b\u52bf\uff09<\/td>\u7528 matplotlib \u7ed8\u56fe<\/td><\/tr>
      \u6309\u6708\/\u5b63\u5ea6\/\u5e74\u7edf\u8ba1<\/td>\u7528 groupby \u7edf\u8ba1\u6c47\u603b<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n
      \u2e3b<\/p>\n\n\n\n
      1.4\u4e3a\u73b0\u6709\u7684\u811a\u672c\u6dfb\u52a0\u529f\u80fd<\/h3>\n\n\n\n
      \u2705 \u7edf\u8ba1\u6bcf\u53f0\u98ce\u673a\u7684\u603b\u8fd0\u884c\u65f6\u957f\uff08\u6309\u6708\u3001\u5b63\u5ea6\u3001\u5e74\uff09 \u2705 \u81ea\u52a8\u5728\u5bfc\u51fa Excel \u4e2d\u52a0\u5165\u7edf\u8ba1\u6c47\u603b\u9875<\/p>\n\n\n\n
      \u2e3b<\/p>\n\n\n\n
      \u2705 \u4fee\u6539\u6b65\u9aa4\u6982\u89c8<\/p>\n\n\n\n
      \ud83e\udde9 \u76ee\u6807\u6548\u679c\uff1a \u2022 \u6bcf\u8f6e\u5bfc\u51fa\u65e5\u5fd7\u65f6\uff0c\u81ea\u52a8\u65b0\u589e\u4e00\u4e2a \u6c47\u603b \u5de5\u4f5c\u8868\uff1b \u2022 \u6c47\u603b\u5305\u542b\u6bcf\u53f0\u98ce\u673a\u5728\u8be5\u65f6\u95f4\u6bb5\u5185\u7684\uff1a \u2022 \u6708\u8fd0\u884c\u65f6\u957f \u2022 \u5b63\u5ea6\u8fd0\u884c\u65f6\u957f \u2022 \u5e74\u8fd0\u884c\u65f6\u957f\uff08\u5f53\u524d\u5e74\u5ea6\uff09<\/p>\n\n\n\n
      \u2e3b<\/p>\n\n\n\n
      \u2705 \u4ee3\u7801\u4fee\u6539\u90e8\u5206<\/p>\n\n\n\n
      \u66ff\u6362\u539f\u811a\u672c\u4e2d\u7684 export_log() \u51fd\u6570\u4e3a\u4ee5\u4e0b\u5185\u5bb9\uff1a<\/p>\n\n\n\n
      def export_log():
          if not run_records:
              return
          df = pd.DataFrame(run_records)
          df['StartTime'] = pd.to_datetime(df['StartTime'])
          df['Year'] = df['StartTime'].dt.year
          df['Month'] = df['StartTime'].dt.to_period('M')
          df['Quarter'] = df['StartTime'].dt.to_period('Q')
      # \u5206\u7ec4\u7edf\u8ba1\u603b\u8fd0\u884c\u65f6\u957f\uff08\u5206\u949f\uff09
      df_month = df.groupby(['FanID', 'Month'])['Duration(min)'].sum().reset_index()
      df_quarter = df.groupby(['FanID', 'Quarter'])['Duration(min)'].sum().reset_index()
      df_year = df.groupby(['FanID', 'Year'])['Duration(min)'].sum().reset_index()

      # \u521b\u5efa\u5de5\u4f5c\u7c3f
      now = datetime.now().strftime('%Y%m%d_%H%M%S')
      out_path = f\"export\/fan_log_{now}.xlsx\"
      with pd.ExcelWriter(out_path, engine='openpyxl') as writer:
          df.to_excel(writer, sheet_name='\u8fd0\u884c\u8bb0\u5f55', index=False)
          df_month.to_excel(writer, sheet_name='\u6708\u7edf\u8ba1', index=False)
          df_quarter.to_excel(writer, sheet_name='\u5b63\u5ea6\u7edf\u8ba1', index=False)
          df_year.to_excel(writer, sheet_name='\u5e74\u5ea6\u7edf\u8ba1', index=False)<\/pre>\n\n\n\n
      \u2e3b<\/p>\n\n\n\n
      1.5\u6700\u7ec8\u751f\u6210 Excel \u5185\u5bb9\u7ed3\u6784\u793a\u4f8b<\/h3>\n\n\n\n
      \ud83d\udcc4 Sheet 1\uff1a\u8fd0\u884c\u8bb0\u5f55<\/p>\n\n\n\n
      FanID<\/th>StartTime<\/th>EndTime<\/th>Duration(min)<\/th><\/tr><\/thead>
      P1-F01<\/td>2025-07-01 10:00<\/td>2025-07-01 11:30<\/td>90<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n
      \ud83d\udcc4 Sheet 2\uff1a\u6708\u7edf\u8ba1<\/p>\n\n\n\n
      FanID<\/th>Month<\/th>Duration(min)<\/th><\/tr><\/thead>
      P1-F01<\/td>2025-07<\/td>300<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n
      \ud83d\udcc4 Sheet 3\uff1a\u5b63\u5ea6\u7edf\u8ba1<\/p>\n\n\n\n
      FanID<\/th>Quarter<\/th>Duration(min)<\/th><\/tr><\/thead>
      P1-F01<\/td>2025Q3<\/td>300<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n
      \ud83d\udcc4 Sheet 4\uff1a\u5e74\u5ea6\u7edf\u8ba1<\/p>\n\n\n\n
      FanID<\/th>Year<\/th>Duration(min)<\/th><\/tr><\/thead>
      P1-F01<\/td>2025<\/td>300<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n
      \u2e3b<\/p>\n\n\n\n
      \u2705 \u4e0b\u4e00\u6b65\u5efa\u8bae\uff08\u53ef\u9009\u6269\u5c55\uff09<\/p>\n\n\n\n
      \u529f\u80fd<\/th>\u63cf\u8ff0<\/th><\/tr><\/thead>
      \u56fe\u8868\u53ef\u89c6\u5316\uff08\u67f1\u72b6\/\u6298\u7ebf\uff09<\/td>\u7528 matplotlib \u6216 openpyxl \u7ed8\u56fe<\/td><\/tr>
      GUI \u4ea4\u4e92\u754c\u9762<\/td>\u542f\u52a8\/\u505c\u6b62\/\u67e5\u770b\u8fd0\u884c\u72b6\u6001\u6309\u94ae<\/td><\/tr>
      \u5f00\u5173\u65e5\u5fd7\u5206\u79bb\u6309\u9875\u4fdd\u5b58<\/td>\u6bcf\u9875\u4e00\u4e2a\u65e5\u5fd7\u6587\u4ef6\u66f4\u6613\u5ba1\u8ba1<\/td><\/tr>
      \u81ea\u52a8\u5b9a\u65f6\u542f\u52a8<\/td>\u52a0\u5165 Windows \u4efb\u52a1\u8ba1\u5212\u6216\u7528 PyInstaller \u6253\u5305\u670d\u52a1<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n
      \u2e3b<\/p>\n\n\n\n
      \n\n\n\n
      \u65b9\u68482\uff1a\u53cd\u7f16\u8bd1<\/h2>\n\n\n\n
      \u7528dnspy\u53cd\u7f16\u8bd1\u8f6f\u4ef6\u5c1d\u8bd5\u5bf9\u3010touchvew\u3011\u5b9e\u73b0\u5728\u539f\u6709\u7cfb\u7edf\u4e0a\u8fdb\u884c\u529f\u80fd\u589e\u6dfb\uff0c\u770b\u6e90\u7a0b\u5e8f\u754c\u9762\u662f\u57fa\u4e8ewinform\u6846\u67b6\u5f00\u53d1\u7684\uff1a<\/p>\n\n\n\n