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Refactor main script to utilize DiscreteMaterialPlanExtractor for data extraction and streamline order processing

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This commit is contained in:
Misaka_Company
2026-01-16 13:51:20 +08:00
parent c8a9c33ecc
commit 51cba4caee
3 changed files with 290 additions and 184 deletions
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186
main.py
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@@ -1,196 +1,28 @@
"""
主程序 - 批量下载离散备料计划维护数据
主程序 - 使用离散备料计划维护数据提取工具
"""
from playwright.sync_api import sync_playwright
from login import login
import re
import os
import pandas as pd
from time import sleep
from utils.excel_converter import ExcelConverter
def read_order_ids(file_path):
"""读取订单号文件"""
with open(file_path, 'r', encoding='utf-8') as f:
# 去除空白行和空格
order_ids = [line.strip() for line in f if line.strip()]
return order_ids
def group_order_ids(order_ids, group_size=100):
"""将订单号分组"""
for i in range(0, len(order_ids), group_size):
yield order_ids[i:i + group_size]
def download_batch(inner_frame, order_ids, batch_index, page1, debug_mode=False, debug_batch=None):
"""下载一批订单号的数据"""
# 清空文本框
textbox = inner_frame.get_by_role("textbox", name="来源生产订单号")
textbox.fill("")
# 填充订单号
textbox.fill(",".join(order_ids))
# 点击查询
inner_frame.locator(".search-component-searchBtn").click()
print(f"第 {batch_index + 1} 批查询完成，等待加载结果...")
# 等待加载完成
loading_locator = inner_frame.locator("div").filter(has_text="加载中").nth(1)
try:
loading_locator.wait_for(state="visible", timeout=3000)
loading_locator.wait_for(state="hidden", timeout=0) # 无限等待，直到消失
except TimeoutError:
# 加载很快完成，或者没有出现加载提示
pass
print(f"第 {batch_index + 1} 批加载完成，开始选择数据...")
# 调试模式：只在指定批次暂停
if debug_mode and (debug_batch is None or batch_index == debug_batch):
print(f"=== 调试暂停：第 {batch_index + 1} 批 ===")
page1.pause()
# 选择所有数据
inner_frame.get_by_role("row", name="序号").get_by_label("").click()
# 点击输出
inner_frame.get_by_role("button", name="更多").hover()
inner_frame.get_by_text("输出", exact=True).click()
# 设置行数阈值
input_box = inner_frame.locator("div").filter(has_text=re.compile(r"^行数阈值$")).locator("input[type='text']")
input_box.fill("300000")
# 下载文件
download_path = f"D:/python/playwrite/data/temp_batch_{batch_index + 1}.xlsx"
with page1.expect_download() as download_info:
inner_frame.get_by_role("button", name="确定(Y)").click()
download = download_info.value
download.save_as(download_path)
print(f"第 {batch_index + 1} 批下载完成: {download_path}")
# 关闭输出对话框（如果有的话）
try:
inner_frame.get_by_role("button", name="取消").click()
except:
pass
# 等待页面恢复，准备下一次查询
import time
time.sleep(1)
return download_path
def convert_and_merge_files(file_paths, output_path):
"""使用 ExcelConverter 转换并合并所有文件"""
converter = ExcelConverter(verbose=False) # 不打印详细日志
all_dataframes = []
for i, file_path in enumerate(file_paths, 1):
print(f"转换第 {i} 个文件: {file_path}")
df = converter.convert(file_path, output_file=None) # 只转换，不保存
all_dataframes.append(df)
print(f" 提取到 {len(df)} 条记录")
if all_dataframes:
print(f"\n合并 {len(all_dataframes)} 个文件的数据...")
merged_df = pd.concat(all_dataframes, ignore_index=True)
merged_df.to_excel(output_path, index=False)
print(f"合并完成: {output_path}, 总共 {len(merged_df)} 条记录")
# 删除临时文件
for file_path in file_paths:
os.remove(file_path)
print(f"已删除临时文件: {file_path}")
return output_path
return None
from utils.离散备料计划维护数据提取 import DiscreteMaterialPlanExtractor
def main():
with sync_playwright() as playwright:
# 调用登录模块
browser, context, page, main_frame = login(
playwright=playwright,
# 创建提取器
extractor = DiscreteMaterialPlanExtractor(
username="BLDpengqiangqiang",
password="Cqbld123456.",
headless=False,
ignore_https_errors=True
verbose=True
)
# 登录成功后可以进行后续操作
# 点击打开"菜单"
main_frame.locator("i").first.click()
# 点击打开"离散备料计划维护"
with page.expect_popup() as page1_info:
main_frame.get_by_title("离散备料计划维护", exact=True).first.click()
page1 = page1_info.value
# 获取 nested iframe
main_frame = page1.locator("#forwardFrame").content_frame
inner_frame_locator = main_frame.locator("#mainiframe")
inner_frame_locator.wait_for(state="visible", timeout=15000)
inner_frame = inner_frame_locator.content_frame
# 点击图标按钮打开查询界面
inner_frame.locator(".search-name-wrapper > .iconfont").click()
inner_frame.get_by_text("订单号查询").click()
inner_frame.get_by_role("tab", name="全部").click()
# 填充并验证，如果失败则重试
max_retries = 3
expected_value = "5000"
for attempt in range(max_retries):
inner_frame.locator("#rc_select_0").fill(expected_value)
inner_frame.locator("#rc_select_0").press("Enter")
# 检查填充是否成功
actual_value = inner_frame.locator("#rc_select_0").input_value()
if actual_value == expected_value:
print(f"文本框填充成功: {expected_value}")
break
else:
print(f"第 {attempt + 1} 次填充失败，实际值: {actual_value}，重试...")
if attempt == max_retries - 1:
print(f"警告: {max_retries} 次尝试后仍未成功填充，继续执行...")
# 读取订单号文件
# 设置文件路径
order_id_file = os.path.join(os.path.dirname(__file__), "orderID.txt")
order_ids = read_order_ids(order_id_file)
print(f"共读取到 {len(order_ids)} 个订单号")
output_file = r"D:/python/playwrite/data/离散备料计划维护_合并.xlsx"
# 确保 data 目录存在
data_dir = "D:/python/playwrite/data"
os.makedirs(data_dir, exist_ok=True)
# 按批次下载
downloaded_files = []
for batch_index, order_ids_batch in enumerate(group_order_ids(order_ids, 100)):
print(f"\n=== 开始处理第 {batch_index + 1} 批，共 {len(order_ids_batch)} 个订单号 ===")
downloaded_file = download_batch(inner_frame, order_ids_batch, batch_index, page1, debug_mode=False, debug_batch=None)
downloaded_files.append(downloaded_file)
# 转换并合并文件
if downloaded_files:
print(f"\n=== 开始转换并合并 {len(downloaded_files)} 个文件 ===")
final_output = "D:/python/playwrite/data/离散备料计划维护_合并.xlsx"
convert_and_merge_files(downloaded_files, final_output)
else:
print("\n没有下载到任何文件")
print(f"\n=== 全部完成 ===")
print(f"最终文件: {final_output}")
# 执行提取
extractor.extract(order_id_file, output_file)
input("按回车退出...")
# 关闭浏览器
context.close()
browser.close()
if __name__ == "__main__":
main()

3
utils/__init__.py
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工具组件包
"""
from .excel_converter import ExcelConverter
from .离散备料计划维护数据提取 import DiscreteMaterialPlanExtractor
__all__ = ['ExcelConverter']
__all__ = ['ExcelConverter', 'DiscreteMaterialPlanExtractor']

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utils/离散备料计划维护数据提取.py Normal file
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@@ -0,0 +1,273 @@
"""
离散备料计划维护数据提取工具
负责登录、批量下载、转换数据
"""
import os
import pandas as pd
from playwright.sync_api import sync_playwright
from utils.excel_converter import ExcelConverter
class DiscreteMaterialPlanExtractor:
"""离散备料计划维护数据提取器"""
def __init__(self, username, password, headless=False, verbose=True):
"""
初始化提取器
Args:
username: 登录用户名
password: 登录密码
headless: 是否无头模式运行
verbose: 是否打印详细日志
"""
self.username = username
self.password = password
self.headless = headless
self.verbose = verbose
self.converter = ExcelConverter(verbose=verbose)
def _print(self, *args, **kwargs):
"""打印日志（如果 verbose=True）"""
if self.verbose:
print(*args, **kwargs)
def read_order_ids(self, file_path):
"""读取订单号文件"""
with open(file_path, 'r', encoding='utf-8') as f:
# 去除空白行和空格
order_ids = [line.strip() for line in f if line.strip()]
return order_ids
def group_order_ids(self, order_ids, group_size=100):
"""将订单号分组"""
for i in range(0, len(order_ids), group_size):
yield order_ids[i:i + group_size]
def download_batch(self, inner_frame, order_ids, batch_index, page1, debug_mode=False, debug_batch=None):
"""下载一批订单号的数据"""
from playwright.sync_api import TimeoutError
import re
import time
# 清空文本框
textbox = inner_frame.get_by_role("textbox", name="来源生产订单号")
textbox.fill("")
# 填充订单号
textbox.fill(",".join(order_ids))
# 点击查询
inner_frame.locator(".search-component-searchBtn").click()
self._print(f"第 {batch_index + 1} 批查询完成，等待加载结果...")
# 等待加载完成
loading_locator = inner_frame.locator("div").filter(has_text="加载中").nth(1)
try:
loading_locator.wait_for(state="visible", timeout=3000)
loading_locator.wait_for(state="hidden", timeout=0) # 无限等待，直到消失
except TimeoutError:
# 加载很快完成，或者没有出现加载提示
pass
self._print(f"第 {batch_index + 1} 批加载完成，开始选择数据...")
# 调试模式：只在指定批次暂停
if debug_mode and (debug_batch is None or batch_index == debug_batch):
self._print(f"=== 调试暂停：第 {batch_index + 1} 批 ===")
page1.pause()
# 选择所有数据
inner_frame.get_by_role("row", name="序号").get_by_label("").click()
# 点击输出
inner_frame.get_by_role("button", name="更多").hover()
inner_frame.get_by_text("输出", exact=True).click()
# 设置行数阈值
input_box = inner_frame.locator("div").filter(has_text=re.compile(r"^行数阈值$")).locator("input[type='text']")
input_box.fill("300000")
# 下载文件
download_path = f"D:/python/playwrite/data/temp_batch_{batch_index + 1}.xlsx"
with page1.expect_download() as download_info:
inner_frame.get_by_role("button", name="确定(Y)").click()
download = download_info.value
download.save_as(download_path)
self._print(f"第 {batch_index + 1} 批下载完成: {download_path}")
# 关闭输出对话框（如果有的话）
# try:
# inner_frame.get_by_role("button", name="取消").click()
# except:
# pass
# 等待页面恢复，准备下一次查询
time.sleep(1)
return download_path
def convert_and_merge_files(self, file_paths, output_path):
"""使用 ExcelConverter 转换并合并所有文件"""
# 确保输出文件路径是正确的格式
output_path = os.path.normpath(output_path)
output_dir = os.path.dirname(output_path)
output_filename = os.path.basename(output_path)
self._print(f"输出文件路径: {output_path}")
self._print(f"输出目录: {output_dir}")
self._print(f"输出文件名: {output_filename}")
# 确保输出文件的父目录存在
if output_dir and not os.path.exists(output_dir):
self._print(f"创建输出目录: {output_dir}")
os.makedirs(output_dir)
all_dataframes = []
for i, file_path in enumerate(file_paths, 1):
self._print(f"转换第 {i} 个文件: {file_path}")
df = self.converter.convert(file_path, output_file=None) # 只转换，不保存
all_dataframes.append(df)
self._print(f" 提取到 {len(df)} 条记录")
if all_dataframes:
self._print(f"\n合并 {len(all_dataframes)} 个文件的数据...")
merged_df = pd.concat(all_dataframes, ignore_index=True)
merged_df.to_excel(output_path, index=False)
self._print(f"合并完成: {output_path}, 总共 {len(merged_df)} 条记录")
# 删除临时文件
for file_path in file_paths:
os.remove(file_path)
self._print(f"已删除临时文件: {file_path}")
return output_path
return None
def setup_query_interface(self, inner_frame):
"""设置查询界面"""
import re
# 点击图标按钮打开查询界面
inner_frame.locator(".search-name-wrapper > .iconfont").click()
inner_frame.get_by_text("订单号查询").click()
inner_frame.get_by_role("tab", name="全部").click()
# 填充并验证，如果失败则重试
max_retries = 3
expected_value = "5000"
for attempt in range(max_retries):
inner_frame.locator("#rc_select_0").fill(expected_value)
inner_frame.locator("#rc_select_0").press("Enter")
# 检查填充是否成功
actual_value = inner_frame.locator("#rc_select_0").input_value()
if actual_value == expected_value:
self._print(f"文本框填充成功: {expected_value}")
break
else:
self._print(f"第 {attempt + 1} 次填充失败，实际值: {actual_value}，重试...")
if attempt == max_retries - 1:
self._print(f"警告: {max_retries} 次尝试后仍未成功填充，继续执行...")
def extract(self, order_id_file, data_dir="D:/python/playwrite/data",
output_file="D:/python/playwrite/data/离散备料计划维护_合并.xlsx",
debug_mode=False, debug_batch=None):
"""
执行完整的数据提取流程
Args:
order_id_file: 订单号文件路径
data_dir: 数据保存目录
output_file: 最终输出文件路径
debug_mode: 是否启用调试模式
debug_batch: 调试批次号
Returns:
输出文件路径
"""
from login import login
with sync_playwright() as playwright:
# 调用登录模块
browser, context, page, main_frame = login(
playwright=playwright,
username=self.username,
password=self.password,
headless=self.headless,
ignore_https_errors=True
)
self._print("=" * 80)
self._print("开始执行离散备料计划维护数据提取")
self._print("=" * 80)
# 登录成功后可以进行后续操作
# 点击打开"菜单"
main_frame.locator("i").first.click()
# 点击打开"离散备料计划维护"
with page.expect_popup() as page1_info:
main_frame.get_by_title("离散备料计划维护", exact=True).first.click()
page1 = page1_info.value
# 获取 nested iframe
main_frame = page1.locator("#forwardFrame").content_frame
inner_frame_locator = main_frame.locator("#mainiframe")
inner_frame_locator.wait_for(state="visible", timeout=15000)
inner_frame = inner_frame_locator.content_frame
# 设置查询界面
self.setup_query_interface(inner_frame)
# 读取订单号文件
order_ids = self.read_order_ids(order_id_file)
self._print(f"共读取到 {len(order_ids)} 个订单号")
# 按批次下载
downloaded_files = []
for batch_index, order_ids_batch in enumerate(self.group_order_ids(order_ids, 100)):
self._print(f"\n=== 开始处理第 {batch_index + 1} 批，共 {len(order_ids_batch)} 个订单号 ===")
downloaded_file = self.download_batch(
inner_frame, order_ids_batch, batch_index, page1,
debug_mode=debug_mode, debug_batch=debug_batch
)
downloaded_files.append(downloaded_file)
# 转换并合并文件
if downloaded_files:
self._print(f"\n=== 开始转换并合并 {len(downloaded_files)} 个文件 ===")
self.convert_and_merge_files(downloaded_files, output_file)
else:
self._print("\n没有下载到任何文件")
self._print(f"\n=== 全部完成 ===")
self._print(f"最终文件: {output_file}")
# 关闭浏览器
context.close()
browser.close()
return output_file
def main():
"""测试函数"""
extractor = DiscreteMaterialPlanExtractor(
username="BLDpengqiangqiang",
password="Cqbld123456.",
headless=False,
verbose=True
)
order_id_file = os.path.join(os.path.dirname(__file__), "orderID.txt")
output_file = "D:/python/playwrite/data/离散备料计划维护_合并.xlsx"
extractor.extract(order_id_file, output_file)
input("按回车退出...")
if __name__ == "__main__":
main()