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import logging |
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import sys |
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from io import BytesIO |
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import pandas as pd |
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from openpyxl import Workbook, load_workbook |
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from rag.nlp import find_codec |
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class RAGFlowExcelParser: |
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@staticmethod |
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def _load_excel_to_workbook(file_like_object): |
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if isinstance(file_like_object, bytes): |
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file_like_object = BytesIO(file_like_object) |
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file_like_object.seek(0) |
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file_head = file_like_object.read(4) |
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file_like_object.seek(0) |
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if not (file_head.startswith(b'PK\x03\x04') or file_head.startswith(b'\xD0\xCF\x11\xE0')): |
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logging.info("****wxy: Not an Excel file, converting CSV to Excel Workbook") |
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try: |
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file_like_object.seek(0) |
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df = pd.read_csv(file_like_object) |
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return RAGFlowExcelParser._dataframe_to_workbook(df) |
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except Exception as e_csv: |
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raise Exception(f"****wxy: Failed to parse CSV and convert to Excel Workbook: {e_csv}") |
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try: |
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return load_workbook(file_like_object) |
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except Exception as e: |
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logging.info(f"****wxy: openpyxl load error: {e}, try pandas instead") |
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try: |
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file_like_object.seek(0) |
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df = pd.read_excel(file_like_object) |
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return RAGFlowExcelParser._dataframe_to_workbook(df) |
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except Exception as e_pandas: |
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raise Exception(f"****wxy: pandas.read_excel error: {e_pandas}, original openpyxl error: {e}") |
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@staticmethod |
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def _dataframe_to_workbook(df): |
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wb = Workbook() |
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ws = wb.active |
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ws.title = "Data" |
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for col_num, column_name in enumerate(df.columns, 1): |
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ws.cell(row=1, column=col_num, value=column_name) |
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for row_num, row in enumerate(df.values, 2): |
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for col_num, value in enumerate(row, 1): |
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ws.cell(row=row_num, column=col_num, value=value) |
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return wb |
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def html(self, fnm, chunk_rows=256): |
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file_like_object = BytesIO(fnm) if not isinstance(fnm, str) else fnm |
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wb = RAGFlowExcelParser._load_excel_to_workbook(file_like_object) |
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tb_chunks = [] |
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for sheetname in wb.sheetnames: |
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ws = wb[sheetname] |
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rows = list(ws.rows) |
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if not rows: |
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continue |
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tb_rows_0 = "<tr>" |
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for t in list(rows[0]): |
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tb_rows_0 += f"<th>{t.value}</th>" |
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tb_rows_0 += "</tr>" |
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for chunk_i in range((len(rows) - 1) // chunk_rows + 1): |
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tb = "" |
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tb += f"<table><caption>{sheetname}</caption>" |
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tb += tb_rows_0 |
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for r in list( |
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rows[1 + chunk_i * chunk_rows: 1 + (chunk_i + 1) * chunk_rows] |
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): |
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tb += "<tr>" |
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for i, c in enumerate(r): |
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if c.value is None: |
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tb += "<td></td>" |
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else: |
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tb += f"<td>{c.value}</td>" |
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tb += "</tr>" |
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tb += "</table>\n" |
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tb_chunks.append(tb) |
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return tb_chunks |
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def __call__(self, fnm): |
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file_like_object = BytesIO(fnm) if not isinstance(fnm, str) else fnm |
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wb = RAGFlowExcelParser._load_excel_to_workbook(file_like_object) |
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res = [] |
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for sheetname in wb.sheetnames: |
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ws = wb[sheetname] |
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rows = list(ws.rows) |
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if not rows: |
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continue |
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ti = list(rows[0]) |
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for r in list(rows[1:]): |
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fields = [] |
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for i, c in enumerate(r): |
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if not c.value: |
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continue |
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t = str(ti[i].value) if i < len(ti) else "" |
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t += (":" if t else "") + str(c.value) |
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fields.append(t) |
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line = "; ".join(fields) |
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if sheetname.lower().find("sheet") < 0: |
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line += " ——" + sheetname |
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res.append(line) |
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return res |
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@staticmethod |
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def row_number(fnm, binary): |
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if fnm.split(".")[-1].lower().find("xls") >= 0: |
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wb = RAGFlowExcelParser._load_excel_to_workbook(BytesIO(binary)) |
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total = 0 |
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for sheetname in wb.sheetnames: |
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ws = wb[sheetname] |
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total += len(list(ws.rows)) |
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return total |
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if fnm.split(".")[-1].lower() in ["csv", "txt"]: |
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encoding = find_codec(binary) |
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txt = binary.decode(encoding, errors="ignore") |
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return len(txt.split("\n")) |
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if __name__ == "__main__": |
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psr = RAGFlowExcelParser() |
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psr(sys.argv[1]) |
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