import os
import pandas as pd
def parse_excel_file(file_path):
"""
通用表格解析函数，支持 Excel (.xlsx/.xls) 和 CSV 文件
返回统一格式的数据块列表
"""
blocks = []
# 根据文件扩展名选择读取方式
file_ext = os.path.splitext(file_path)[1].lower()
try:
if file_ext in (".xlsx", ".xls"):
# 处理Excel文件（多sheet）
all_sheets = pd.read_excel(file_path, sheet_name=None)
for sheet_name, df in all_sheets.items():
blocks.extend(_process_dataframe(df, sheet_name))
elif file_ext == ".csv":
# 处理CSV文件（单sheet）
df = pd.read_csv(file_path)
blocks.extend(_process_dataframe(df, "CSV"))
else:
raise ValueError(f"Unsupported file format: {file_ext}")
except Exception as e:
raise ValueError(f"Failed to parse file {file_path}: {str(e)}")
return blocks
def _process_dataframe(df, sheet_name):
"""处理单个DataFrame，生成统一格式的数据块"""
df = df.ffill()
headers = df.columns.tolist()
blocks = []
for _, row in df.iterrows():
html_table = "".format("".join(f"| {col} | " for col in headers), "".join(f"{row[col]} | " for col in headers))
block = {"type": "table", "img_path": "", "table_caption": "", "table_footnote": [], "table_body": html_table, "page_idx": 0}
blocks.append(block)
return blocks
if __name__ == "__main__":
# 测试示例
excel_path = "test.xlsx"
csv_path = "test.csv"
try:
# 测试Excel解析
excel_blocks = parse_excel_file(excel_path)
print(f"Excel解析结果（共{len(excel_blocks)}条）:")
print(excel_blocks[:1]) # 打印第一条示例
# 测试CSV解析
csv_blocks = parse_excel_file(csv_path)
print(f"\nCSV解析结果（共{len(csv_blocks)}条）:")
print(csv_blocks[:1])
except Exception as e:
print(f"错误: {str(e)}")