A pure python bloom filter (low storage requirement, probabilistic set datastructure) is provided.
Includes mmap, in-memory and disk-seek backends.
The user specifies the desired maximum number of elements and the desired maximum false positive probability, and the module calculates the rest.
- Example use:
>>> bf = bloom_filter_mod.Bloom_filter(ideal_num_elements_n=100, error_rate_p=0.01) >>> for i in range(0, 200, 2): ... bf.add(i) ... >>> for i in range(0, 200, 3): ... print(i in bf) ...
1 maintainer
Metadata
1 maintainer
Release files for drs-bloom-filter 2.4
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| drs-bloom-filter-2.4.tar.gz | 6.7 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| drs_bloom_filter-2.4-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 13.3 kB
Release files / drs-bloom-filter-2.4.tar.gz
| Download URL | drs-bloom-filter-2.4.tar.gz |
|---|---|
| Size | 6.7 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
a77c9d75bbd14ddcd0b86bd16b0606b9495c238b9c659350345ab28b3a86c27a
|
|
BLAKE2b-256 checksum How to use checksums |
4e0b35dc29c29af58b77a8a61cf596eccebc6989e9f124e031ca642e5f1d0bbe
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.0 CPython/3.9.2
|
Release files / drs_bloom_filter-2.4-py3-none-any.whl
| Download URL | drs_bloom_filter-2.4-py3-none-any.whl |
|---|---|
| Size | 6.5 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
060637b6f1eb840a9a96c4563982fc3e4498de091ac1bad8246848f65755da7a
|
|
BLAKE2b-256 checksum How to use checksums |
654d039e12c31af7a54f5083529f2bd6b925942fd6367b5ae0f02109a1bf66a9
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.0 CPython/3.9.2
|
