{"library":"pyprobables","type":"library","category":null,"description":"pyprobables is a pure-Python library offering implementations of common probabilistic data structures like Bloom filters, Count-Min sketches, Cuckoo filters, and Quotient filters. It provides memory-efficient ways to perform operations such as set membership testing and approximate frequency counting. The library is actively maintained, with its current version being 0.7.0, and receives regular updates including new features, bug fixes, and Python version support changes.","language":"python","status":"active","version":"0.7.0","tags":["probabilistic data structures","bloom filter","count-min sketch","quotient filter","cuckoo filter","data structures"],"install":[{"cmd":"pip install pyprobables","imports":["from probables import BloomFilter","from probables import CountMinSketch","from probables import CuckooFilter","from probables import QuotientFilter"]}],"homepage":null,"github":"https://github.com/barrust/pyprobables","docs":"https://pyprobables.readthedocs.io/","changelog":null,"pypi":"https://pypi.org/project/pyprobables/","npm":null,"openapi_spec":null,"status_page":null,"smithery":null,"compatibility":{"summary":{"python_range":"3.10–3.9","success_rate":100,"avg_install_s":1.6,"avg_import_s":0.05,"wheel_type":"wheel"},"url":"https://checklist.day/v1/registry/pyprobables/compatibility"},"provenance":{"verified_status":"passing","verified_at":"Sun Jun 28","last_verified":"Sun Jun 28","next_check":"Tue Jul 28","install_tag":null}}