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Hi,
It's not a real issue, we use your Framework to make validation of entries before exporting an ldif. With a code that looks like this
ldif_connection=Connection(server=None,client_strategy='LDIF')
user_entry_type=EntryType('...') #Put whatever data here, dn is a template using uid attributeforuser_datainusers_data: # users_data is a list of dict containing more than 10 attributesuser=user_entry_type(user_data) # It takes about 0.001 for each userldif_connection.add( # This too takes about 0.001 for each useruser.entry_dn,
user.object_classes,
user.entry_attributes_as_dict
)
We found that each of the two operations in the loop cost 0.001 s.
Are there some parameters we could use to speed up one of those operations?
Is it possible to make it much faster with more CPU or RAM?
Can multprocessing help here?
Thanks.
The text was updated successfully, but these errors were encountered:
Thanks for reaching out @TcaManager. Indeed there is some overhead on instantiation of dynamic classes. I'll have a look at this but it will need some time to profile the code myself to pin point the problem. If you are using SMP multiprocessing can increase performance by chunking your entries to several processes. Nevertheless this just mitigates the real issue.
Hi,
It's not a real issue, we use your Framework to make validation of entries before exporting an ldif. With a code that looks like this
We found that each of the two operations in the loop cost 0.001 s.
Are there some parameters we could use to speed up one of those operations?
Is it possible to make it much faster with more CPU or RAM?
Can multprocessing help here?
Thanks.
The text was updated successfully, but these errors were encountered: