ragflow / deepdoc /parser /excel_parser.py
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# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
import logging
import sys
from io import BytesIO
import pandas as pd
from openpyxl import Workbook, load_workbook
from rag.nlp import find_codec
class RAGFlowExcelParser:
@staticmethod
def _load_excel_to_workbook(file_like_object):
if isinstance(file_like_object, bytes):
file_like_object = BytesIO(file_like_object)
# Read first 4 bytes to determine file type
file_like_object.seek(0)
file_head = file_like_object.read(4)
file_like_object.seek(0)
if not (file_head.startswith(b'PK\x03\x04') or file_head.startswith(b'\xD0\xCF\x11\xE0')):
logging.info("****wxy: Not an Excel file, converting CSV to Excel Workbook")
try:
file_like_object.seek(0)
df = pd.read_csv(file_like_object)
return RAGFlowExcelParser._dataframe_to_workbook(df)
except Exception as e_csv:
raise Exception(f"****wxy: Failed to parse CSV and convert to Excel Workbook: {e_csv}")
try:
return load_workbook(file_like_object)
except Exception as e:
logging.info(f"****wxy: openpyxl load error: {e}, try pandas instead")
try:
file_like_object.seek(0)
df = pd.read_excel(file_like_object)
return RAGFlowExcelParser._dataframe_to_workbook(df)
except Exception as e_pandas:
raise Exception(f"****wxy: pandas.read_excel error: {e_pandas}, original openpyxl error: {e}")
@staticmethod
def _dataframe_to_workbook(df):
wb = Workbook()
ws = wb.active
ws.title = "Data"
for col_num, column_name in enumerate(df.columns, 1):
ws.cell(row=1, column=col_num, value=column_name)
for row_num, row in enumerate(df.values, 2):
for col_num, value in enumerate(row, 1):
ws.cell(row=row_num, column=col_num, value=value)
return wb
def html(self, fnm, chunk_rows=256):
file_like_object = BytesIO(fnm) if not isinstance(fnm, str) else fnm
wb = RAGFlowExcelParser._load_excel_to_workbook(file_like_object)
tb_chunks = []
for sheetname in wb.sheetnames:
ws = wb[sheetname]
rows = list(ws.rows)
if not rows:
continue
tb_rows_0 = "<tr>"
for t in list(rows[0]):
tb_rows_0 += f"<th>{t.value}</th>"
tb_rows_0 += "</tr>"
for chunk_i in range((len(rows) - 1) // chunk_rows + 1):
tb = ""
tb += f"<table><caption>{sheetname}</caption>"
tb += tb_rows_0
for r in list(
rows[1 + chunk_i * chunk_rows: 1 + (chunk_i + 1) * chunk_rows]
):
tb += "<tr>"
for i, c in enumerate(r):
if c.value is None:
tb += "<td></td>"
else:
tb += f"<td>{c.value}</td>"
tb += "</tr>"
tb += "</table>\n"
tb_chunks.append(tb)
return tb_chunks
def __call__(self, fnm):
file_like_object = BytesIO(fnm) if not isinstance(fnm, str) else fnm
wb = RAGFlowExcelParser._load_excel_to_workbook(file_like_object)
res = []
for sheetname in wb.sheetnames:
ws = wb[sheetname]
rows = list(ws.rows)
if not rows:
continue
ti = list(rows[0])
for r in list(rows[1:]):
fields = []
for i, c in enumerate(r):
if not c.value:
continue
t = str(ti[i].value) if i < len(ti) else ""
t += (":" if t else "") + str(c.value)
fields.append(t)
line = "; ".join(fields)
if sheetname.lower().find("sheet") < 0:
line += " ——" + sheetname
res.append(line)
return res
@staticmethod
def row_number(fnm, binary):
if fnm.split(".")[-1].lower().find("xls") >= 0:
wb = RAGFlowExcelParser._load_excel_to_workbook(BytesIO(binary))
total = 0
for sheetname in wb.sheetnames:
ws = wb[sheetname]
total += len(list(ws.rows))
return total
if fnm.split(".")[-1].lower() in ["csv", "txt"]:
encoding = find_codec(binary)
txt = binary.decode(encoding, errors="ignore")
return len(txt.split("\n"))
if __name__ == "__main__":
psr = RAGFlowExcelParser()
psr(sys.argv[1])