| Port details |
- py-pyprobables Probabilistic data structures in python
- 0.7.0 math
=0 0.6.2Version of this port present on the latest quarterly branch. - Maintainer: sunpoet@FreeBSD.org
 - Port Added: 2024-02-21 15:19:06
- Last Update: 2026-03-09 18:19:08
- Commit Hash: 187e76c
- Also Listed In: python
- License: MIT
- WWW:
- https://pyprobables.readthedocs.io/en/latest/
- https://github.com/barrust/pyprobables
- Description:
- pyprobables is a pure-python library for probabilistic data structures. The goal
is to provide the developer with a pure-python implementation of common
probabilistic data-structures to use in their work.
To achieve better raw performance, it is recommended supplying an alternative
hashing algorithm that has been compiled in C. This could include using the MD5
and SHA512 algorithms provided or installing a third party package and writing
your own hashing strategy. Some options include the murmur hash mmh3 or those
from the pyhash library. Each data object in pyprobables makes it easy to pass
in a custom hashing function.
 ¦ ¦ ¦ ¦ 
- Manual pages:
- FreshPorts has no man page information for this port.
- pkg-plist: as obtained via:
make generate-plist - There is no configure plist information for this port.
- USE_RC_SUBR (Service Scripts)
- no SUBR information found for this port
- Dependency lines:
-
- ${PYTHON_PKGNAMEPREFIX}pyprobables>0:math/py-pyprobables@${PY_FLAVOR}
- To install the port:
- cd /usr/ports/math/py-pyprobables/ && make install clean
- To add the package, run one of these commands:
- pkg install math/py-pyprobables
- pkg install py311-pyprobables
NOTE: If this package has multiple flavors (see below), then use one of them instead of the name specified above. NOTE: This is a Python port. Instead of py311-pyprobables listed in the above command, you can pick from the names under the Packages section.- PKGNAME: py311-pyprobables
- Package flavors (<flavor>: <package>)
- distinfo:
- TIMESTAMP = 1771421708
SHA256 (pyprobables-0.7.0.tar.gz) = 77fef358cb70bffc2756639c30d182e7713041b99f788dfb2c5a0c5b146631ff
SIZE (pyprobables-0.7.0.tar.gz) = 37403
Packages (timestamps in pop-ups are UTC):
- Dependencies
- NOTE: FreshPorts displays only information on required and default dependencies. Optional dependencies are not covered.
- Build dependencies:
-
- py311-setuptools>=61.2.0 : devel/py-setuptools@py311
- py311-wheel>=0 : devel/py-wheel@py311
- python3.11 : lang/python311
- py311-build>=0 : devel/py-build@py311
- py311-installer>=0 : devel/py-installer@py311
- Test dependencies:
-
- python3.11 : lang/python311
- Runtime dependencies:
-
- python3.11 : lang/python311
- There are no ports dependent upon this port
Configuration Options:
- No options to configure
- Options name:
- math_py-pyprobables
- USES:
- python
- FreshPorts was unable to extract/find any pkg message
- Master Sites:
|
Number of commits found: 4
| Commit History - (may be incomplete: for full details, see links to repositories near top of page) |
| Commit | Credits | Log message |
0.7.0 09 Mar 2026 18:19:08
    |
Po-Chuan Hsieh (sunpoet)  |
math/py-pyprobables: Update to 0.7.0
Changes: https://github.com/barrust/pyprobables/releases |
0.6.2 02 Dec 2025 12:08:24
    |
Po-Chuan Hsieh (sunpoet)  |
math/py-pyprobables: Update to 0.6.2
Changes: https://github.com/barrust/pyprobables/releases |
0.6.1 31 Dec 2024 15:50:00
    |
Po-Chuan Hsieh (sunpoet)  |
math/py-pyprobables: Update to 0.6.1
Changes: https://github.com/barrust/pyprobables/releases |
0.6.0 21 Feb 2024 15:06:07
    |
Po-Chuan Hsieh (sunpoet)  |
math/py-pyprobables: Add py-pyprobables 0.6.0
pyprobables is a pure-python library for probabilistic data structures. The goal
is to provide the developer with a pure-python implementation of common
probabilistic data-structures to use in their work.
To achieve better raw performance, it is recommended supplying an alternative
hashing algorithm that has been compiled in C. This could include using the MD5
and SHA512 algorithms provided or installing a third party package and writing
your own hashing strategy. Some options include the murmur hash mmh3 or those
from the pyhash library. Each data object in pyprobables makes it easy to pass
in a custom hashing function. |
Number of commits found: 4
|