mirror of
https://git.mirrors.martin98.com/https://github.com/infiniflow/ragflow.git
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124 lines
4.3 KiB
Python
124 lines
4.3 KiB
Python
# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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import logging
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from openpyxl import load_workbook, Workbook
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import sys
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from io import BytesIO
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from rag.nlp import find_codec
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import pandas as pd
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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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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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df = pd.read_excel(file_like_object)
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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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except Exception as e_pandas:
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raise Exception(f"****wxy: pandas read error: {e_pandas}, original openpyxl error: {e}")
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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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