Writing data to Excel give me 'ZIP does not support timestamps before 1980' - pandas

Question

I hope to don't create any duplicate but I looked around (stack overflow and other forum) and I found some similar question but none of them solved my problem.
I have a python code that the only thing that does is query the DB, create a DataFrame in Pandas and write it to an Excel file.
The code worked without problem locally but when I introduced it in my server it start to give this error:
File "Test.py", line 34, in <module>
test()
File "Test.py", line 31, in test
ex.generate_file()
File "/home/carlo/Test/Utility/ExportExcell.py", line 96, in generate_file
writer.save()
File "/usr/local/lib/python2.7/dist-packages/pandas/io/excel.py", line 1952, in save
return self.book.close()
File "/usr/local/lib/python2.7/dist-packages/xlsxwriter/workbook.py", line 306, in close
self._store_workbook()
File "/usr/local/lib/python2.7/dist-packages/xlsxwriter/workbook.py", line 677, in _store_workbook
xlsx_file.write(os_filename, xml_filename)
File "/usr/lib/python2.7/zipfile.py", line 1135, in write
zinfo = ZipInfo(arcname, date_time)
File "/usr/lib/python2.7/zipfile.py", line 305, in __init__
raise ValueError('ZIP does not support timestamps before 1980')
ValueError: ZIP does not support timestamps before 1980
To ensure that is everything ok I printed my DataFrame and for me it looks good even because when I run it locally it geenrate an excell file without problem:
Computer_System_Memory_Size Count_of_HostName Disk_Total_Size Number_of_CPU OS_Family
0 5736053088256 70 6072238035456 282660 Windows
1 96159653888 607 96630589440 2451066 vCenter
2 0 9 0 36342 Virtualization
3 2469361287143424 37 2389533519619072 149406 Unix
4 3691651514368 90 5817485303808 363420 Linux
I don't see any timestamp here and this is part of my code:
pivot = pd.DataFrame.from_dict(pivot) #pivot= information extracted from DB
pd.to_numeric(pivot['Count_of_HostName'], downcast='signed')#try to enforce to be a numeric value in case it get confused with a datetime
pd.to_numeric(pivot['Disk_Total_Size'], downcast='signed')#try to enforce to be a numeric value in case it get confused with a datetime
pd.to_numeric(pivot['Computer_System_Memory_Size'], downcast='signed')#try to enforce to be a numeric value in case it get confused with a datetime
pd.to_numeric(pivot['Number_of_CPU'], downcast='signed')#try to enforce to be a numeric value in case it get confused with a datetime
print pivot
name = 'TempReport/Report.xlsx'#set-up file name
writer = pd.ExcelWriter(name, engine='xlsxwriter')#create excel with file name
pivot.to_excel(writer, 'Pivot', index=False)#introduce my data to excel
writer.save()#write to file, it's where it fail
Does someone know why it doesn't work in an Ubuntu 16.04 server without give me 'ZIP does not support timestamps before 1980' error?
I checked many things, library version, ensure that there are no data

Answer 1

XlsxWriter set the individual XML files that make up an XLSX file with a creation date of 1/1/1980 which is (I think) the ZIP epoch and the date used by Excel. This allows binary reproducibility of files created by XlsxWriter once the same input data and metadata is used.
It sets the date as follows (for the non-in-memory zipfile.py) case:
timestamp = time.mktime((1980, 1, 1, 0, 0, 0, 0, 0, 0))
os.utime(os_filename, (timestamp, timestamp))
The error that you are seeing occurs when this fails in some way and the date is set before 1/1/1980.
I've only seen this happen once before in a situation where the user was using a container and the container had a different time to the host system.
Do you have a situation like this or where the timestamp may be set incorrectly for some reason?
Update: Try run this in the same environment as the example that fails:
import os
import time
filename = 'file.txt'
file = open(filename, 'w')
file.close()
timestamp = time.mktime((1980, 1, 1, 0, 0, 0, 0, 0, 0))
os.utime(filename, (timestamp, timestamp))
print(time.ctime(os.path.getmtime(filename)))
# Should give:
# Tue Jan 1 00:00:00 1980
Update: This issue is fixed in XlsxWriter >= 1.1.9.

Answer 2

Try using this engine:
pd.to_excel('file_name.xlsx', engine = 'openpyxl')

Answer 3

This issue is fixed in XlsxWriter 1.2.1!