[Python] Read CSV or Excel

I'm allowing users to upload a CSV or Excel file. I'm using pandas to read the file and create a dataframe. Since I can't predict which filetype the user will upload, I wrapped pd.read_csv() and pd.read_excel() in a try/except block.

if form.validate_on_submit():
input_filename = secure_filename(form.file.data.filename)
try:
df = pd.read_csv(form.file.data, header=0, skip_blank_lines=True, skipinitialspace=True, encoding='latin-1')
except:
df = pd.read_excel(form.file.data, header=0, skip_blank_lines=True, skipinitialspace=True, encoding='latin-1')


If pd.read_csv() is first in the try/except block and I upload a .csv file it works. If I attempt to upload a .xlsx file, I get this error:

TypeError: expected str, bytes or os.PathLike object, not NoneType


If pd.read_excel() is first in the try/except block and I upload an .xlsx file it works. If I attempt to upload a .csv file, I get this error:

pandas.io.common.EmptyDataError: No columns to parse from file


Previously, I used mimetype to route the file to the correct pandas function, but I was hoping for a cleaner (and all encompassing) solution that didn't involve several if/elif statements. This is what I had:

if form.file.data.mimetype == 'text/csv':
df = pd.read_csv(form.file.data, header=0, skip_blank_lines=True, skipinitialspace=True, encoding='latin-1')
elif form.file.data.mimetype == 'application/octet-stream':
df = pd.read_excel(form.file.data, header=0, skip_blank_lines=True, skipinitialspace=True, encoding='latin-1')
elif form.file.data.mimetype == 'application/vnd.openxmlformats-officedocument.spreadsheetml.sheet':
df = pd.read_excel(form.file.data, header=0, skip_blank_lines=True, skipinitialspace=True, encoding='latin-1')
else:
flash('Error Uploading File. Invalid file type. Please use xls, xlsx or csv.', 'danger')
return render_template('upload.html', current_user=current_user, form=form)


I'm using Flask, WTForms and Python 3. Thank you.

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