chore: move scripts to tools directory
Move analyze_excel.py, excel_to_markdown.py, and locator_helper.py into the tools/ subdirectory to improve project organization.
This commit is contained in:
Misaka_Company
63
tools/analyze_excel.py
Normal file
63
tools/analyze_excel.py
Normal file
@@ -0,0 +1,63 @@
|
||||
"""
|
||||
分析 Excel 文件的数据结构
|
||||
"""
|
||||
import pandas as pd
|
||||
import openpyxl
|
||||
import sys
|
||||
|
||||
# 设置输出编码
|
||||
if sys.platform == 'win32':
|
||||
import io
|
||||
sys.stdout = io.TextIOWrapper(sys.stdout.buffer, encoding='utf-8')
|
||||
|
||||
# 读取 Excel 文件
|
||||
file_path = "data/导出文件.xlsx"
|
||||
|
||||
print("=" * 80)
|
||||
print("1. 读取所有工作表名称")
|
||||
print("=" * 80)
|
||||
|
||||
wb = openpyxl.load_workbook(file_path)
|
||||
sheet_names = wb.sheetnames
|
||||
print(f"工作表数量: {len(sheet_names)}")
|
||||
print(f"工作表名称: {sheet_names}")
|
||||
|
||||
print("\n" + "=" * 80)
|
||||
print("2. 逐行读取原始数据（使用 openpyxl）")
|
||||
print("=" * 80)
|
||||
|
||||
for sheet_name in sheet_names:
|
||||
print(f"\n--- 工作表: {sheet_name} ---")
|
||||
ws = wb[sheet_name]
|
||||
|
||||
for idx, row in enumerate(ws.iter_rows(values_only=True), 1):
|
||||
# 检查是否为空行
|
||||
is_empty = all(cell is None or str(cell).strip() == "" for cell in row)
|
||||
if is_empty:
|
||||
print(f"行 {idx}: [空行]")
|
||||
else:
|
||||
# 过滤掉 None 和空字符串，只显示有效数据
|
||||
valid_data = [str(cell) if cell is not None else "" for cell in row]
|
||||
print(f"行 {idx}: {valid_data}")
|
||||
|
||||
print("\n" + "=" * 80)
|
||||
print("3. 使用 pandas 读取数据（观察列结构）")
|
||||
print("=" * 80)
|
||||
|
||||
for sheet_name in sheet_names:
|
||||
print(f"\n--- 工作表: {sheet_name} ---")
|
||||
df = pd.read_excel(file_path, sheet_name=sheet_name)
|
||||
print(f"DataFrame 形状: {df.shape}")
|
||||
print(f"\n列名:")
|
||||
for i, col in enumerate(df.columns):
|
||||
print(f" 列 {i}: {col}")
|
||||
print(f"\n数据预览:")
|
||||
pd.set_option('display.max_rows', 25)
|
||||
pd.set_option('display.max_columns', 20)
|
||||
pd.set_option('display.width', 200)
|
||||
pd.set_option('display.max_colwidth', 30)
|
||||
print(df)
|
||||
pd.reset_option('display.max_rows')
|
||||
pd.reset_option('display.max_columns')
|
||||
pd.reset_option('display.width')
|
||||
pd.reset_option('display.max_colwidth')
|
||||
350
tools/excel_to_markdown.py
Normal file
350
tools/excel_to_markdown.py
Normal file
@@ -0,0 +1,350 @@
|
||||
"""
|
||||
Excel to Markdown Converter
|
||||
|
||||
将Excel文件转换为Markdown格式的表格，包含行号和列号（英文字母）。
|
||||
"""
|
||||
|
||||
import pandas as pd
|
||||
import argparse
|
||||
import sys
|
||||
from pathlib import Path
|
||||
|
||||
|
||||
def number_to_excel_col(n):
|
||||
"""将数字转换为Excel列号（A, B, ..., Z, AA, AB, ...）"""
|
||||
result = ""
|
||||
while n > 0:
|
||||
n -= 1
|
||||
result = chr(n % 26 + ord('A')) + result
|
||||
n //= 26
|
||||
return result
|
||||
|
||||
|
||||
def excel_to_markdown(input_file, output_file=None, sheet_name=0, include_row_numbers=True, include_col_numbers=True):
|
||||
"""
|
||||
将Excel文件转换为Markdown表格
|
||||
|
||||
Args:
|
||||
input_file: 输入的Excel文件路径
|
||||
output_file: 输出的Markdown文件路径（可选，默认为同名.md文件）
|
||||
sheet_name: 工作表名称或索引，或列表（默认为第一个工作表）
|
||||
include_row_numbers: 是否包含行号
|
||||
include_col_numbers: 是否包含列号
|
||||
"""
|
||||
input_path = Path(input_file)
|
||||
|
||||
if not input_path.exists():
|
||||
print(f"错误: 文件 '{input_file}' 不存在")
|
||||
return False
|
||||
|
||||
# 设置默认输出文件名
|
||||
if output_file is None:
|
||||
output_file = input_path.with_suffix('.md')
|
||||
else:
|
||||
output_file = Path(output_file)
|
||||
|
||||
try:
|
||||
# 读取Excel文件
|
||||
print(f"正在读取文件: {input_file}")
|
||||
|
||||
# 获取所有工作表名称（用于索引转换）
|
||||
xls = pd.ExcelFile(input_file)
|
||||
all_sheet_names = xls.sheet_names
|
||||
|
||||
# 将索引转换为实际的工作表名称
|
||||
def resolve_sheet_name(name):
|
||||
if isinstance(name, int):
|
||||
if 0 <= name < len(all_sheet_names):
|
||||
return all_sheet_names[name]
|
||||
else:
|
||||
raise ValueError(f"工作表索引 {name} 超出范围")
|
||||
return name
|
||||
|
||||
# 处理多个工作表的情况
|
||||
if isinstance(sheet_name, (list, tuple)):
|
||||
# 转换索引为名称
|
||||
resolved_names = [resolve_sheet_name(s) for s in sheet_name]
|
||||
dfs = pd.read_excel(input_file, sheet_name=resolved_names, header=None)
|
||||
# 如果只有一个工作表，转换为单个DataFrame
|
||||
if len(resolved_names) == 1:
|
||||
dfs = {resolved_names[0]: dfs}
|
||||
sheet_name = resolved_names
|
||||
else:
|
||||
resolved_name = resolve_sheet_name(sheet_name)
|
||||
df = pd.read_excel(input_file, sheet_name=resolved_name, header=None)
|
||||
dfs = {resolved_name: df}
|
||||
sheet_name = resolved_name
|
||||
|
||||
# 生成所有工作表的Markdown内容
|
||||
all_sheets_content = {}
|
||||
|
||||
for sheet_key, df in dfs.items():
|
||||
# 转换数据为字符串，处理NaN值
|
||||
df = df.fillna('')
|
||||
df = df.astype(str)
|
||||
|
||||
# 生成Markdown表格
|
||||
markdown_lines = []
|
||||
|
||||
# 添加工作表标题
|
||||
sheet_title = f"工作表: {sheet_key}"
|
||||
markdown_lines.append(f"## {sheet_title}\n")
|
||||
|
||||
# 添加列号行
|
||||
if include_col_numbers:
|
||||
col_headers = [''] if include_row_numbers else []
|
||||
col_headers.extend(number_to_excel_col(i + 1) for i in range(len(df.columns)))
|
||||
markdown_lines.append('| ' + ' | '.join(col_headers) + ' |')
|
||||
markdown_lines.append('| ' + ' | '.join(['---' for _ in col_headers]) + ' |')
|
||||
|
||||
# 添加数据行
|
||||
for idx, row in df.iterrows():
|
||||
row_data = []
|
||||
if include_row_numbers:
|
||||
row_data.append(str(idx + 1))
|
||||
row_data.extend(row)
|
||||
markdown_lines.append('| ' + ' | '.join(row_data) + ' |')
|
||||
|
||||
# 添加统计信息
|
||||
markdown_lines.append(f"\n**统计信息:**")
|
||||
markdown_lines.append(f"- 总行数: {len(df)}")
|
||||
markdown_lines.append(f"- 总列数: {len(df.columns)}")
|
||||
markdown_lines.append(f"- 数据范围: A1:{number_to_excel_col(len(df.columns))}{len(df)}")
|
||||
|
||||
all_sheets_content[sheet_key] = '\n'.join(markdown_lines)
|
||||
|
||||
# 写入文件
|
||||
if len(dfs) == 1:
|
||||
# 单个工作表：直接写入
|
||||
sheet_key = list(dfs.keys())[0]
|
||||
output_content = f"# {input_path.stem}\n\n"
|
||||
output_content += f"从 `{input_file}` (工作表: {sheet_key}) 转换\n\n"
|
||||
output_content += all_sheets_content[sheet_key]
|
||||
output_file.write_text(output_content, encoding='utf-8')
|
||||
|
||||
print(f"✓ 转换成功!")
|
||||
print(f" 输入文件: {input_file}")
|
||||
print(f" 输出文件: {output_file}")
|
||||
print(f" 工作表: {sheet_key}")
|
||||
print(f" 行数: {len(dfs[sheet_key])}, 列数: {len(dfs[sheet_key].columns)}")
|
||||
else:
|
||||
return all_sheets_content, dfs, input_path, input_file
|
||||
|
||||
except Exception as e:
|
||||
print(f"错误: {str(e)}")
|
||||
import traceback
|
||||
traceback.print_exc()
|
||||
return False
|
||||
|
||||
|
||||
def convert_multiple_sheets(input_file, output_file=None, sheet_names=None, include_row_numbers=True, include_col_numbers=True, merge_to_one_file=True):
|
||||
"""
|
||||
转换多个工作表
|
||||
|
||||
Args:
|
||||
input_file: 输入的Excel文件路径
|
||||
output_file: 输出的Markdown文件路径
|
||||
sheet_names: 工作表名称或索引列表
|
||||
include_row_numbers: 是否包含行号
|
||||
include_col_numbers: 是否包含列号
|
||||
merge_to_one_file: 是否合并到一个文件（True）或分别输出（False）
|
||||
"""
|
||||
input_path = Path(input_file)
|
||||
|
||||
if not input_path.exists():
|
||||
print(f"错误: 文件 '{input_file}' 不存在")
|
||||
return False
|
||||
|
||||
# 设置默认输出文件名
|
||||
if output_file is None:
|
||||
output_file = input_path.with_suffix('.md')
|
||||
else:
|
||||
output_file = Path(output_file)
|
||||
|
||||
try:
|
||||
# 读取Excel文件
|
||||
print(f"正在读取文件: {input_file}")
|
||||
|
||||
# 获取所有工作表名称
|
||||
xls = pd.ExcelFile(input_file)
|
||||
all_sheet_names = xls.sheet_names
|
||||
|
||||
if sheet_names is None or len(sheet_names) == 0:
|
||||
# 读取所有工作表
|
||||
sheet_names = all_sheet_names
|
||||
print(f"找到 {len(sheet_names)} 个工作表")
|
||||
else:
|
||||
# 将索引转换为实际的工作表名称
|
||||
resolved_names = []
|
||||
for name in sheet_names:
|
||||
if isinstance(name, int):
|
||||
# 索引转换为名称
|
||||
if 0 <= name < len(all_sheet_names):
|
||||
resolved_names.append(all_sheet_names[name])
|
||||
else:
|
||||
print(f"警告: 工作表索引 {name} 超出范围，已跳过")
|
||||
else:
|
||||
# 直接使用名称
|
||||
resolved_names.append(name)
|
||||
sheet_names = resolved_names
|
||||
|
||||
# 使用实际的工作表名称读取数据
|
||||
dfs = pd.read_excel(input_file, sheet_name=sheet_names, header=None)
|
||||
|
||||
# 确保返回的是字典格式
|
||||
if not isinstance(dfs, dict):
|
||||
dfs = {sheet_names[0]: dfs}
|
||||
|
||||
# 生成所有工作表的Markdown内容
|
||||
all_sheets_content = {}
|
||||
|
||||
for sheet_key, df in dfs.items():
|
||||
# 转换数据为字符串，处理NaN值
|
||||
df = df.fillna('')
|
||||
df = df.astype(str)
|
||||
|
||||
# 生成Markdown表格
|
||||
markdown_lines = []
|
||||
|
||||
# 添加工作表标题
|
||||
sheet_title = f"工作表: {sheet_key}"
|
||||
markdown_lines.append(f"## {sheet_title}\n")
|
||||
|
||||
# 添加列号行
|
||||
if include_col_numbers:
|
||||
col_headers = [''] if include_row_numbers else []
|
||||
col_headers.extend(number_to_excel_col(i + 1) for i in range(len(df.columns)))
|
||||
markdown_lines.append('| ' + ' | '.join(col_headers) + ' |')
|
||||
markdown_lines.append('| ' + ' | '.join(['---' for _ in col_headers]) + ' |')
|
||||
|
||||
# 添加数据行
|
||||
for idx, row in df.iterrows():
|
||||
row_data = []
|
||||
if include_row_numbers:
|
||||
row_data.append(str(idx + 1))
|
||||
row_data.extend(row)
|
||||
markdown_lines.append('| ' + ' | '.join(row_data) + ' |')
|
||||
|
||||
# 添加统计信息
|
||||
markdown_lines.append(f"\n**统计信息:**")
|
||||
markdown_lines.append(f"- 总行数: {len(df)}")
|
||||
markdown_lines.append(f"- 总列数: {len(df.columns)}")
|
||||
markdown_lines.append(f"- 数据范围: A1:{number_to_excel_col(len(df.columns))}{len(df)}")
|
||||
|
||||
all_sheets_content[sheet_key] = '\n'.join(markdown_lines)
|
||||
|
||||
# 写入文件
|
||||
if merge_to_one_file:
|
||||
# 合并到一个文件
|
||||
output_content = f"# {input_path.stem}\n\n"
|
||||
output_content += f"从 `{input_file}` 转换，共 {len(dfs)} 个工作表\n\n"
|
||||
output_content += "---\n\n"
|
||||
|
||||
for sheet_key in sheet_names:
|
||||
if sheet_key in all_sheets_content:
|
||||
output_content += all_sheets_content[sheet_key] + "\n\n---\n\n"
|
||||
|
||||
output_file.write_text(output_content, encoding='utf-8')
|
||||
|
||||
print(f"✓ 转换成功!")
|
||||
print(f" 输入文件: {input_file}")
|
||||
print(f" 输出文件: {output_file}")
|
||||
print(f" 工作表数量: {len(dfs)}")
|
||||
for sheet_key in sheet_names:
|
||||
if sheet_key in dfs:
|
||||
print(f" - {sheet_key}: {len(dfs[sheet_key])}行 x {len(dfs[sheet_key].columns)}列")
|
||||
else:
|
||||
# 分别输出到多个文件
|
||||
output_stem = output_file.stem
|
||||
output_suffix = output_file.suffix
|
||||
output_dir = output_file.parent
|
||||
|
||||
for sheet_key in sheet_names:
|
||||
if sheet_key not in all_sheets_content:
|
||||
continue
|
||||
|
||||
# 为每个工作表创建单独的文件
|
||||
sheet_filename = f"{output_stem}_{sheet_key}{output_suffix}"
|
||||
sheet_output_file = output_dir / sheet_filename
|
||||
|
||||
output_content = f"# {input_path.stem} - {sheet_key}\n\n"
|
||||
output_content += f"从 `{input_file}` (工作表: {sheet_key}) 转换\n\n"
|
||||
output_content += all_sheets_content[sheet_key]
|
||||
|
||||
sheet_output_file.write_text(output_content, encoding='utf-8')
|
||||
|
||||
print(f"✓ 转换成功!")
|
||||
print(f" 输入文件: {input_file}")
|
||||
print(f" 输出目录: {output_dir}")
|
||||
print(f" 工作表数量: {len(dfs)}")
|
||||
for sheet_key in sheet_names:
|
||||
if sheet_key in dfs:
|
||||
sheet_filename = f"{output_stem}_{sheet_key}{output_suffix}"
|
||||
print(f" - {sheet_key} -> {sheet_filename} ({len(dfs[sheet_key])}行 x {len(dfs[sheet_key].columns)}列)")
|
||||
|
||||
return True
|
||||
|
||||
except Exception as e:
|
||||
print(f"错误: {str(e)}")
|
||||
import traceback
|
||||
traceback.print_exc()
|
||||
return False
|
||||
|
||||
|
||||
# ============================================================
|
||||
# 配置区域 - 直接修改下面的参数
|
||||
# ============================================================
|
||||
|
||||
# 输入文件路径（必填）
|
||||
INPUT_FILE = r"D:\python\playwrite\data\YTHN-100.A0.532-BOM-1.2版.xlsx"
|
||||
|
||||
# 输出文件路径（可选，默认为输入文件同名.md文件）
|
||||
OUTPUT_FILE = None # 或指定 r"D:\path\to\output.md"
|
||||
|
||||
# 工作表名称或索引（可选，默认为0即第一个工作表）
|
||||
# 可以是单个值: 0 或 "Sheet1"
|
||||
# 可以是列表: [0, 1, 2] 或 ["Sheet1", "Sheet2", "Sheet3"]
|
||||
# 可以是 None 表示读取所有工作表
|
||||
SHEET_NAMES = [0, 1,2,3] # 指定多个工作表索引
|
||||
|
||||
# 是否包含行号（可选，默认为True）
|
||||
INCLUDE_ROW_NUMBERS = True
|
||||
|
||||
# 是否包含列号（可选，默认为True）
|
||||
INCLUDE_COL_NUMBERS = True
|
||||
|
||||
# 如果指定了多个工作表，是否合并到一个文件（可选，默认为True）
|
||||
# True: 所有工作表合并到一个文件
|
||||
# False: 每个工作表生成单独的文件（文件名格式: 原文件名_工作表名.md）
|
||||
MULTI_SHEETS_TO_ONE_FILE = True
|
||||
|
||||
# ============================================================
|
||||
|
||||
|
||||
def main():
|
||||
"""主函数 - 使用上方配置区域定义的参数"""
|
||||
# 判断是否为多个工作表
|
||||
if isinstance(SHEET_NAMES, list) and len(SHEET_NAMES) > 1:
|
||||
# 多个工作表
|
||||
convert_multiple_sheets(
|
||||
input_file=INPUT_FILE,
|
||||
output_file=OUTPUT_FILE,
|
||||
sheet_names=SHEET_NAMES,
|
||||
include_row_numbers=INCLUDE_ROW_NUMBERS,
|
||||
include_col_numbers=INCLUDE_COL_NUMBERS,
|
||||
merge_to_one_file=MULTI_SHEETS_TO_ONE_FILE
|
||||
)
|
||||
else:
|
||||
# 单个工作表
|
||||
sheet_name = SHEET_NAMES if isinstance(SHEET_NAMES, list) and len(SHEET_NAMES) == 1 else SHEET_NAMES
|
||||
excel_to_markdown(
|
||||
input_file=INPUT_FILE,
|
||||
output_file=OUTPUT_FILE,
|
||||
sheet_name=sheet_name,
|
||||
include_row_numbers=INCLUDE_ROW_NUMBERS,
|
||||
include_col_numbers=INCLUDE_COL_NUMBERS
|
||||
)
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
main()
|
||||
171
tools/locator_helper.py
Normal file
171
tools/locator_helper.py
Normal file
@@ -0,0 +1,171 @@
|
||||
"""
|
||||
元素定位辅助工具 - 用于快速验证定位是否有效
|
||||
"""
|
||||
from playwright.sync_api import Page, Frame, Locator
|
||||
|
||||
|
||||
def debug_locator(frame: Frame, locator: Locator, timeout: int = 5000):
|
||||
"""
|
||||
调试定位器 - 检查定位是否有效并显示详细信息
|
||||
|
||||
参数:
|
||||
frame: 页面或iframe对象
|
||||
locator: 定位器对象
|
||||
timeout: 超时时间（毫秒）
|
||||
|
||||
返回:
|
||||
bool: 定位是否成功
|
||||
"""
|
||||
print(f"\n验证定位: {locator}")
|
||||
print("=" * 50)
|
||||
|
||||
try:
|
||||
# 检查数量
|
||||
count = locator.count()
|
||||
print(f"元素数量: {count}")
|
||||
|
||||
if count == 0:
|
||||
print("✗ 未找到任何匹配元素")
|
||||
return False
|
||||
|
||||
# 检查第一个元素是否可见
|
||||
first_visible = locator.first.is_visible(timeout=timeout)
|
||||
print(f"第一个元素可见: {first_visible}")
|
||||
|
||||
# 获取文本内容
|
||||
for i in range(min(3, count)): # 最多显示3个
|
||||
element = locator.nth(i)
|
||||
try:
|
||||
if element.is_visible(timeout=1000):
|
||||
text = element.inner_text(timeout=1000)
|
||||
print(f" 元素{i + 1}文本: {text[:100] if len(text) > 100 else text}")
|
||||
else:
|
||||
print(f" 元素{i + 1}: 存在但不可见")
|
||||
except:
|
||||
print(f" 元素{i + 1}: 无法获取信息")
|
||||
|
||||
print("=" * 50)
|
||||
return True
|
||||
|
||||
except Exception as e:
|
||||
print(f"✗ 验证失败: {e}")
|
||||
print("=" * 50)
|
||||
return False
|
||||
|
||||
|
||||
def try_multiple_locators(frame: Frame, selectors: list[str], timeout: int = 5000) -> Locator:
|
||||
"""
|
||||
尝试多个选择器，返回第一个有效的定位器
|
||||
|
||||
参数:
|
||||
frame: 页面或iframe对象
|
||||
selectors: 选择器列表
|
||||
timeout: 超时时间（毫秒）
|
||||
|
||||
返回:
|
||||
第一个有效的 Locator，如果没有则返回 None
|
||||
"""
|
||||
print(f"\n尝试 {len(selectors)} 个定位方式...")
|
||||
print("-" * 50)
|
||||
|
||||
for i, selector in enumerate(selectors):
|
||||
print(f"[{i + 1}] 尝试: {selector}")
|
||||
try:
|
||||
locator = frame.locator(selector)
|
||||
count = locator.count()
|
||||
visible_count = sum(1 for j in range(count) if locator.nth(j).is_visible(timeout=1000))
|
||||
|
||||
print(f" 找到 {count} 个元素，其中 {visible_count} 个可见")
|
||||
|
||||
if visible_count > 0:
|
||||
print(f" ✓ 使用此定位器")
|
||||
print("-" * 50)
|
||||
return locator
|
||||
except Exception as e:
|
||||
print(f" ✗ 失败: {e}")
|
||||
|
||||
print("-" * 50)
|
||||
return None
|
||||
|
||||
|
||||
def interactive_locate(frame: Frame):
|
||||
"""
|
||||
交互式定位调试 - 进入交互模式测试定位表达式
|
||||
"""
|
||||
print("\n进入交互式定位调试模式")
|
||||
print("输入定位表达式，输入 'q' 或 'quit' 退出")
|
||||
print("-" * 50)
|
||||
|
||||
while True:
|
||||
try:
|
||||
selector = input("\n>>> ")
|
||||
selector = selector.strip()
|
||||
|
||||
if selector.lower() in ('q', 'quit'):
|
||||
break
|
||||
|
||||
if not selector:
|
||||
continue
|
||||
|
||||
debug_locator(frame, frame.locator(selector))
|
||||
|
||||
except KeyboardInterrupt:
|
||||
break
|
||||
except Exception as e:
|
||||
print(f"错误: {e}")
|
||||
|
||||
print("退出调试模式")
|
||||
|
||||
|
||||
# 示例使用代码（单独运行此文件时的演示）
|
||||
if __name__ == "__main__":
|
||||
from playwright.sync_api import sync_playwright
|
||||
import re
|
||||
|
||||
with sync_playwright() as pw:
|
||||
browser = pw.chromium.launch(headless=False)
|
||||
context = browser.new_context(ignore_https_errors=True)
|
||||
page = context.new_page()
|
||||
|
||||
# 登录
|
||||
page.goto("https://68.11.34.30:8082/yonbip/resources/uap/rbac/login/main/index.html")
|
||||
main_frame = page.locator("#forwardFrame").content_frame
|
||||
main_frame.get_by_role("textbox", name="用户名").fill("BLDpengqiangqiang")
|
||||
main_frame.get_by_role("textbox", name="密码").fill("Cqbld123456.")
|
||||
main_frame.get_by_role("button", name="登录").click()
|
||||
confirm_btn = main_frame.get_by_role("button", name="确定")
|
||||
if confirm_btn.count() > 0:
|
||||
confirm_btn.click()
|
||||
|
||||
# 循环切换 Inspector 和交互式调试
|
||||
print("\n" + "=" * 60)
|
||||
print("元素定位调试工具")
|
||||
print("=" * 60)
|
||||
print("循环模式：")
|
||||
print(" 1. Inspector 窗口 - 使用浏览器录制/选择元素")
|
||||
print(" 2. 交互式调试 - 验证定位表达式")
|
||||
print(" 输入 'q' 或 'quit' 退出程序\n")
|
||||
|
||||
while True:
|
||||
# 1. 打开 Inspector 窗口
|
||||
print("\n【打开 Inspector 窗口】")
|
||||
print("请在 Inspector 中获取元素定位器，然后关闭 Inspector 继续...")
|
||||
page.pause()
|
||||
|
||||
# 2. 进入交互式定位调试
|
||||
print("\n【进入交互式定位调试】")
|
||||
interactive_locate(main_frame)
|
||||
|
||||
# 询问是否继续
|
||||
choice = input("\n是否继续下一轮调试？(y/n/q): ").strip().lower()
|
||||
if choice in ('n', 'q', 'quit'):
|
||||
print("退出程序")
|
||||
break
|
||||
elif choice in ('y', ''): # 默认继续
|
||||
continue
|
||||
else:
|
||||
print("未知选项，退出程序")
|
||||
break
|
||||
|
||||
context.close()
|
||||
browser.close()
|
||||
Reference in New Issue
Block a user