so this is not really a question but rather a bug report for the pandarallel package:
this is the end of my code:
...
print('Calculate costs NEG...')
for i, group in tqdm(df_mol_neg.groupby('DELIVERY_DATE')):
srl_slice = df_srl.loc[df_srl['DATE'] == i]
srl_slice['srl_soll'] = srl_slice['srl_soll'].copy() * -1
df_aep_neg.loc[df_aep_neg['DATE'] == i, 'SRL_cost'] = srl_slice['srl_soll'].parallel_apply(lambda x: get_cost_of_nearest_mol(group, x)).sum()
what happens here is that instead of doing the parallel_apply function, it loops back to the start of my code and repeats it all again. the exact same code works fine on my remote linux mashine so I have 2 possible error sources:
- since pandarallel itself already has some difficulties with the windows os it might just be a windows problem
- the other thing is that I currently use the early access version of pycharm (223.7401.13) and use the debugger which might also be a problem source
other than this bug I can highly recommend the pandarallel package (at least for linux users). it's super easy to use and if you got some cores it can really shave off some time, in my case it shaved off a cool 90% of time.
(also if there is a better way to report bugs, please let me know)
