纯Python Bloom Filter模块
项目描述
提供了一个纯Python Bloom Filter（低存储需求，概率集合数据结构）。已知它在CPython 3.x、Pypy和Jython上工作。
包括mmap、内存和磁盘查找后端。
本项目基于drs-bloom-filter和bloom_filter_mod构建。详情和链接可以在AUTHORS.md中找到。
使用方法
用户指定所需的元素最大数量和期望的最大误报概率，模块将计算其余部分。
from bloom_filter2 import BloomFilter
# instantiate BloomFilter with custom settings,
# max_elements is how many elements you expect the filter to hold.
# error_rate defines accuracy; You can use defaults with
# `BloomFilter()` without any arguments. Following example
# is same as defaults:
bloom = BloomFilter(max_elements=10000, error_rate=0.1)
# Test whether the bloom-filter has seen a key:
assert "test-key" not in bloom
# Mark the key as seen
bloom.add("test-key")
# Now check again
assert "test-key" in bloom
关闭
bloom-filter2-2.0.0-1.tar.gz 的哈希值
| 算法 | 哈希摘要 | |
|---|---|---|
| SHA256 | 310e5d3aa15be6e3d2285a7111f60cc44a1f500159412f2c72d155f43037cefd |
|
| MD5 | 5c9dd90c629e42d51bebf7fbafdc7930 |
|
| BLAKE2b-256 | 2b5d8de4a849ebe212217e6d8f4798a6918d4035e741c44730da81272f170b47 |
关闭
bloom_filter2-2.0.0-py3-none-any.whl 的哈希值
| 算法 | 哈希摘要 | |
|---|---|---|
| SHA256 | f9d3a3a44ae917ab9c13f71b542ac88b863f0cf4e64afbca48777cf0d5310c93 |
|
| MD5 | 295ef3562662feedf0245deca6ab5356 |
|
| BLAKE2b-256 | 52d7871408c1c1230af64eb00e2064f6e8a065ae652f17f010b3f4f102e5fbac |