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Note this assumes dablooms has added support for 'in' in their Python wrapper - see bitly/dablooms#50 - you could test without it but it would require special case code to use their check method instead.
I'm not sure how representative your test set is but pydablooms is significantly faster (which I also observed on the real data sample I was trying this on). Note on my machine both libraries are doing far better than the requested 10% error rate, although pybloomfiltermmap has the lower error rate.
The text was updated successfully, but these errors were encountered:
Suggested patch to also profile the bitly Dablooms Python wrapper available from https://github.com/bitly/dablooms
Note this assumes dablooms has added support for 'in' in their Python wrapper - see bitly/dablooms#50 - you could test without it but it would require special case code to use their check method instead.
I'm not sure how representative your test set is but pydablooms is significantly faster (which I also observed on the real data sample I was trying this on). Note on my machine both libraries are doing far better than the requested 10% error rate, although pybloomfiltermmap has the lower error rate.
The text was updated successfully, but these errors were encountered: