Refactor main script to utilize DiscreteMaterialPlanExtractor for data extraction and streamline order processing
This commit is contained in:
198
main.py
198
main.py
@@ -1,195 +1,27 @@
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"""
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主程序 - 批量下载离散备料计划维护数据
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主程序 - 使用离散备料计划维护数据提取工具
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"""
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from playwright.sync_api import sync_playwright
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from login import login
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import re
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import os
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import pandas as pd
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from time import sleep
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from utils.excel_converter import ExcelConverter
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def read_order_ids(file_path):
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"""读取订单号文件"""
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with open(file_path, 'r', encoding='utf-8') as f:
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# 去除空白行和空格
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order_ids = [line.strip() for line in f if line.strip()]
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return order_ids
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def group_order_ids(order_ids, group_size=100):
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"""将订单号分组"""
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for i in range(0, len(order_ids), group_size):
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yield order_ids[i:i + group_size]
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def download_batch(inner_frame, order_ids, batch_index, page1, debug_mode=False, debug_batch=None):
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"""下载一批订单号的数据"""
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# 清空文本框
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textbox = inner_frame.get_by_role("textbox", name="来源生产订单号")
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textbox.fill("")
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# 填充订单号
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textbox.fill(",".join(order_ids))
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# 点击查询
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inner_frame.locator(".search-component-searchBtn").click()
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print(f"第 {batch_index + 1} 批查询完成,等待加载结果...")
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# 等待加载完成
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loading_locator = inner_frame.locator("div").filter(has_text="加载中").nth(1)
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try:
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loading_locator.wait_for(state="visible", timeout=3000)
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loading_locator.wait_for(state="hidden", timeout=0) # 无限等待,直到消失
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except TimeoutError:
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# 加载很快完成,或者没有出现加载提示
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pass
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print(f"第 {batch_index + 1} 批加载完成,开始选择数据...")
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# 调试模式:只在指定批次暂停
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if debug_mode and (debug_batch is None or batch_index == debug_batch):
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print(f"=== 调试暂停:第 {batch_index + 1} 批 ===")
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page1.pause()
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# 选择所有数据
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inner_frame.get_by_role("row", name="序号").get_by_label("").click()
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# 点击输出
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inner_frame.get_by_role("button", name="更多").hover()
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inner_frame.get_by_text("输出", exact=True).click()
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# 设置行数阈值
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input_box = inner_frame.locator("div").filter(has_text=re.compile(r"^行数阈值$")).locator("input[type='text']")
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input_box.fill("300000")
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# 下载文件
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download_path = f"D:/python/playwrite/data/temp_batch_{batch_index + 1}.xlsx"
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with page1.expect_download() as download_info:
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inner_frame.get_by_role("button", name="确定(Y)").click()
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download = download_info.value
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download.save_as(download_path)
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print(f"第 {batch_index + 1} 批下载完成: {download_path}")
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# 关闭输出对话框(如果有的话)
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try:
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inner_frame.get_by_role("button", name="取消").click()
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except:
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pass
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# 等待页面恢复,准备下一次查询
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import time
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time.sleep(1)
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return download_path
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def convert_and_merge_files(file_paths, output_path):
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"""使用 ExcelConverter 转换并合并所有文件"""
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converter = ExcelConverter(verbose=False) # 不打印详细日志
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all_dataframes = []
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for i, file_path in enumerate(file_paths, 1):
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print(f"转换第 {i} 个文件: {file_path}")
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df = converter.convert(file_path, output_file=None) # 只转换,不保存
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all_dataframes.append(df)
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print(f" 提取到 {len(df)} 条记录")
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if all_dataframes:
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print(f"\n合并 {len(all_dataframes)} 个文件的数据...")
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merged_df = pd.concat(all_dataframes, ignore_index=True)
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merged_df.to_excel(output_path, index=False)
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print(f"合并完成: {output_path}, 总共 {len(merged_df)} 条记录")
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# 删除临时文件
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for file_path in file_paths:
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os.remove(file_path)
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print(f"已删除临时文件: {file_path}")
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return output_path
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return None
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from utils.离散备料计划维护数据提取 import DiscreteMaterialPlanExtractor
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def main():
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with sync_playwright() as playwright:
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# 调用登录模块
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browser, context, page, main_frame = login(
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playwright=playwright,
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username="BLDpengqiangqiang",
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password="Cqbld123456.",
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headless=False,
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ignore_https_errors=True
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)
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# 创建提取器
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extractor = DiscreteMaterialPlanExtractor(
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username="BLDpengqiangqiang",
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password="Cqbld123456.",
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headless=False,
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verbose=True
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)
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# 登录成功后可以进行后续操作
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# 点击打开"菜单"
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main_frame.locator("i").first.click()
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# 设置文件路径
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order_id_file = os.path.join(os.path.dirname(__file__), "orderID.txt")
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output_file = r"D:/python/playwrite/data/离散备料计划维护_合并.xlsx"
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# 点击打开"离散备料计划维护"
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with page.expect_popup() as page1_info:
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main_frame.get_by_title("离散备料计划维护", exact=True).first.click()
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page1 = page1_info.value
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# 执行提取
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extractor.extract(order_id_file, output_file)
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# 获取 nested iframe
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main_frame = page1.locator("#forwardFrame").content_frame
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inner_frame_locator = main_frame.locator("#mainiframe")
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inner_frame_locator.wait_for(state="visible", timeout=15000)
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inner_frame = inner_frame_locator.content_frame
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# 点击图标按钮打开查询界面
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inner_frame.locator(".search-name-wrapper > .iconfont").click()
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inner_frame.get_by_text("订单号查询").click()
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inner_frame.get_by_role("tab", name="全部").click()
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# 填充并验证,如果失败则重试
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max_retries = 3
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expected_value = "5000"
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for attempt in range(max_retries):
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inner_frame.locator("#rc_select_0").fill(expected_value)
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inner_frame.locator("#rc_select_0").press("Enter")
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# 检查填充是否成功
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actual_value = inner_frame.locator("#rc_select_0").input_value()
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if actual_value == expected_value:
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print(f"文本框填充成功: {expected_value}")
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break
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else:
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print(f"第 {attempt + 1} 次填充失败,实际值: {actual_value},重试...")
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if attempt == max_retries - 1:
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print(f"警告: {max_retries} 次尝试后仍未成功填充,继续执行...")
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# 读取订单号文件
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order_id_file = os.path.join(os.path.dirname(__file__), "orderID.txt")
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order_ids = read_order_ids(order_id_file)
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print(f"共读取到 {len(order_ids)} 个订单号")
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# 确保 data 目录存在
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data_dir = "D:/python/playwrite/data"
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os.makedirs(data_dir, exist_ok=True)
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# 按批次下载
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downloaded_files = []
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for batch_index, order_ids_batch in enumerate(group_order_ids(order_ids, 100)):
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print(f"\n=== 开始处理第 {batch_index + 1} 批,共 {len(order_ids_batch)} 个订单号 ===")
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downloaded_file = download_batch(inner_frame, order_ids_batch, batch_index, page1, debug_mode=False, debug_batch=None)
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downloaded_files.append(downloaded_file)
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# 转换并合并文件
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if downloaded_files:
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print(f"\n=== 开始转换并合并 {len(downloaded_files)} 个文件 ===")
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final_output = "D:/python/playwrite/data/离散备料计划维护_合并.xlsx"
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convert_and_merge_files(downloaded_files, final_output)
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else:
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print("\n没有下载到任何文件")
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print(f"\n=== 全部完成 ===")
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print(f"最终文件: {final_output}")
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input("按回车退出...")
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# 关闭浏览器
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context.close()
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browser.close()
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input("按回车退出...")
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if __name__ == "__main__":
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