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# 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.
#
from openpyxl import load_workbook, Workbook
import sys
from io import BytesIO
from rag.nlp import find_codec
import pandas as pd
class RAGFlowExcelParser:
def html(self, fnm, chunk_rows=256):
# if isinstance(fnm, str):
# wb = load_workbook(fnm)
# else:
# wb = load_workbook(BytesIO(fnm))++
s_fnm = fnm
if not isinstance(fnm, str):
s_fnm = BytesIO(fnm)
else:
pass
try:
wb = load_workbook(s_fnm)
except Exception as e:
print(f'****wxy: file parser error: {e}, s_fnm={s_fnm}, trying convert files')
df = pd.read_excel(s_fnm)
wb = Workbook()
# if len(wb.worksheets) > 0:
# del wb.worksheets[0]
# else: pass
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)
else:
pass
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)
else:
pass
else:
pass
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):
# if isinstance(fnm, str):
# wb = load_workbook(fnm)
# else:
# wb = load_workbook(BytesIO(fnm))
s_fnm = fnm
if not isinstance(fnm, str):
s_fnm = BytesIO(fnm)
else:
pass
try:
wb = load_workbook(s_fnm)
except Exception as e:
print(f'****wxy: file parser error: {e}, s_fnm={s_fnm}, trying convert files')
df = pd.read_excel(s_fnm)
wb = Workbook()
if len(wb.worksheets) > 0:
del wb.worksheets[0]
else:
pass
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)
else:
pass
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)
else:
pass
else:
pass
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 = load_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])
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