嘗試對load_workbook()類使用read_only = True屬性,這會導致您獲得的工作表為IterableWroksheet,這意味著您只能迭代它們,您不能直接使用列/行號來訪問其中的單元格值.根據

documentation,這將提供接近恒定的存儲器消耗.

此外,您不需要關閉文件,語句將為您處理.

示例 –

import openpyxl

import csv

import time

print(time.ctime())

importedfile = openpyxl.load_workbook(filename = "C:/Users/User/Desktop/Giant Workbook.xlsm", read_only = True, keep_vba = False)

tabnames = importedfile.get_sheet_names()

substring = "Keyword"

for num in tabnames:

if num.find(substring) > -1:

sheet=importedfile.get_sheet_by_name(num)

name = "C:/Users/User/Desktop/Test/" + num + ".csv"

with open(name, 'w', newline='') as file:

savefile = csv.writer(file)

for i in sheet.rows:

savefile.writerow([cell.value for cell in i])

print(time.ctime())

Sometimes, you will need to open or write extremely large XLSX files, and the common routines in openpyxl won’t be able to handle that load. Fortunately, there are two modes that enable you to read and write unlimited amounts of data with (near) constant memory consumption.

總結

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