[Python] performance using python3/pandas to read .ods (opendocument spreadsheet)file

Environment:


inside docker container in WSL2/Ubuntu22.04
python 3.12
pandas 2.2.2
odfpy 1.4.1
openpyxl 3.1.3


The .ods file I have on disk is 6.8MB (two sheets, one sheet has 16,000 rows, the other has 74,000 rows). I can open this file in MS excel in no time.

I have the following code to read this file (first read it into a bytes variable):

t1 = time.perf_counter()
excel = ExcelFile(BytesIO(file_content), engine="odf")
t2 = time.perf_counter()
data = pd.read_excel(BytesIO(file_content), engine="odf")
t3 = time.perf_counter()


the following is the value of t1, t2 and t3 after the file content is read into excel and data:


t1: 366108.7721855
t2: 366606.7265884
t3: 367100.7166519


It takes about 10 minutes to read the data as Excel or pandas dataframe. Anywhere I can tune to improve the reading performance?

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