|
|
|
@@ -1,6 +1,3 @@ |
|
|
|
# |
|
|
|
# Copyright 2025 The InfiniFlow Authors. All Rights Reserved. |
|
|
|
# |
|
|
|
# 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 |
|
|
|
@@ -14,19 +11,51 @@ |
|
|
|
# limitations under the License. |
|
|
|
# |
|
|
|
|
|
|
|
from openpyxl import load_workbook |
|
|
|
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) |
|
|
|
|
|
|
|
# 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: |
|
|
|
wb = load_workbook(BytesIO(fnm)) |
|
|
|
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: |
|
|
|
@@ -45,7 +74,7 @@ class RAGFlowExcelParser: |
|
|
|
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] |
|
|
|
rows[1 + chunk_i * chunk_rows: 1 + (chunk_i + 1) * chunk_rows] |
|
|
|
): |
|
|
|
tb += "<tr>" |
|
|
|
for i, c in enumerate(r): |
|
|
|
@@ -60,10 +89,41 @@ class RAGFlowExcelParser: |
|
|
|
return tb_chunks |
|
|
|
|
|
|
|
def __call__(self, fnm): |
|
|
|
if isinstance(fnm, str): |
|
|
|
wb = load_workbook(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: |
|
|
|
wb = load_workbook(BytesIO(fnm)) |
|
|
|
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] |
|
|
|
@@ -104,3 +164,4 @@ class RAGFlowExcelParser: |
|
|
|
if __name__ == "__main__": |
|
|
|
psr = RAGFlowExcelParser() |
|
|
|
psr(sys.argv[1]) |
|
|
|
|