LBFGS and OWL-QN optimization algorithms

Navigation

Verified details

These details have been verified by PyPI
Maintainers
Avatar for Derek.Eder from gravatar.com Derek.Eder Avatar for fgregg from gravatar.com fgregg

Unverified details

These details have not been verified by PyPI
Project links
Meta
Classifiers

Project description

PyLBFGS

https://travis-ci.org/dedupeio/pylbfgs.svg?branch=master

This is a Python wrapper around Naoaki Okazaki (chokkan)’s liblbfgs library of quasi-Newton optimization routines (limited memory BFGS and OWL-QN).

This package aims to provide a cleaner interface to the LBFGS algorithm than is currently available in SciPy, and to provide the OWL-QN algorithm to Python users.

Part of the Dedupe.io cloud service and open source toolset for de-duplicating and finding fuzzy matches in your data.

Installing

Type:

pip install pylbfgs

Hacking

Type:

pip install "pip>=10"
pip install -r requirements.txt
pip install -e .

To run the test suite:

pytest tests

Authors

PyLBFGS was written by Lars Buitinck.

Alexis Mignon submitted a patch for error handling.

Project details

Verified details

These details have been verified by PyPI
Maintainers
Avatar for Derek.Eder from gravatar.com Derek.Eder Avatar for fgregg from gravatar.com fgregg

Unverified details

These details have not been verified by PyPI
Project links
Meta
Classifiers

Release history Release notifications | RSS feed

0.2.0.16

0.2.0.15

This version

0.2.0.14

0.2.0.13

0.2.0.12

0.2.0.11

0.2.0.10

0.2.0.9

0.2.0.8

0.2.0.7

0.2.0.6

0.2.0.5

0.2.0.4

0.2.0.3

0.2.0.2

0.2.0.1

0.1.13

0.1.12

0.1.11

0.1.10

0.1.9

0.1.8

0.1.7

0.1.6

0.1.5

0.1.4

0.1.3

0.1.2

0.1.1

0.1

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

PyLBFGS-0.2.0.14.tar.gz (98.7 kB view details)

Uploaded Source

Built Distributions

PyLBFGS-0.2.0.14-pp37-pypy37_pp73-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (53.6 kB view details)

Uploaded PyPy manylinux: glibc 2.12+ x86-64 manylinux: glibc 2.5+ x86-64

PyLBFGS-0.2.0.14-cp310-cp310-win_amd64.whl (54.6 kB view details)

Uploaded CPython 3.10 Windows x86-64

PyLBFGS-0.2.0.14-cp310-cp310-win32.whl (45.8 kB view details)

Uploaded CPython 3.10 Windows x86

PyLBFGS-0.2.0.14-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (279.2 kB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ ARM64

PyLBFGS-0.2.0.14-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (274.7 kB view details)

Uploaded CPython 3.10 manylinux: glibc 2.12+ x86-64 manylinux: glibc 2.5+ x86-64

PyLBFGS-0.2.0.14-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_12_i686.manylinux2010_i686.whl (258.4 kB view details)

Uploaded CPython 3.10 manylinux: glibc 2.12+ i686 manylinux: glibc 2.5+ i686

PyLBFGS-0.2.0.14-cp310-cp310-macosx_11_0_arm64.whl (49.3 kB view details)

Uploaded CPython 3.10 macOS 11.0+ ARM64

PyLBFGS-0.2.0.14-cp310-cp310-macosx_10_9_x86_64.whl (56.3 kB view details)

Uploaded CPython 3.10 macOS 10.9+ x86-64

PyLBFGS-0.2.0.14-cp310-cp310-macosx_10_9_universal2.whl (100.2 kB view details)

Uploaded CPython 3.10 macOS 10.9+ universal2 (ARM64, x86-64)

PyLBFGS-0.2.0.14-cp39-cp39-win_amd64.whl (54.4 kB view details)

Uploaded CPython 3.9 Windows x86-64

PyLBFGS-0.2.0.14-cp39-cp39-win32.whl (45.6 kB view details)

Uploaded CPython 3.9 Windows x86

PyLBFGS-0.2.0.14-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (278.5 kB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ ARM64

PyLBFGS-0.2.0.14-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (273.9 kB view details)

Uploaded CPython 3.9 manylinux: glibc 2.12+ x86-64 manylinux: glibc 2.5+ x86-64

PyLBFGS-0.2.0.14-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_12_i686.manylinux2010_i686.whl (256.9 kB view details)

Uploaded CPython 3.9 manylinux: glibc 2.12+ i686 manylinux: glibc 2.5+ i686

PyLBFGS-0.2.0.14-cp39-cp39-macosx_11_0_arm64.whl (48.9 kB view details)

Uploaded CPython 3.9 macOS 11.0+ ARM64

PyLBFGS-0.2.0.14-cp39-cp39-macosx_10_9_x86_64.whl (55.9 kB view details)

Uploaded CPython 3.9 macOS 10.9+ x86-64

PyLBFGS-0.2.0.14-cp39-cp39-macosx_10_9_universal2.whl (99.2 kB view details)

Uploaded CPython 3.9 macOS 10.9+ universal2 (ARM64, x86-64)

PyLBFGS-0.2.0.14-cp38-cp38-win_amd64.whl (54.7 kB view details)

Uploaded CPython 3.8 Windows x86-64

PyLBFGS-0.2.0.14-cp38-cp38-win32.whl (46.1 kB view details)

Uploaded CPython 3.8 Windows x86

PyLBFGS-0.2.0.14-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (282.1 kB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ ARM64

PyLBFGS-0.2.0.14-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (284.7 kB view details)

Uploaded CPython 3.8 manylinux: glibc 2.12+ x86-64 manylinux: glibc 2.5+ x86-64

PyLBFGS-0.2.0.14-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_12_i686.manylinux2010_i686.whl (266.2 kB view details)

Uploaded CPython 3.8 manylinux: glibc 2.12+ i686 manylinux: glibc 2.5+ i686

PyLBFGS-0.2.0.14-cp38-cp38-macosx_11_0_arm64.whl (49.3 kB view details)

Uploaded CPython 3.8 macOS 11.0+ ARM64

PyLBFGS-0.2.0.14-cp38-cp38-macosx_10_9_x86_64.whl (56.3 kB view details)

Uploaded CPython 3.8 macOS 10.9+ x86-64

PyLBFGS-0.2.0.14-cp38-cp38-macosx_10_9_universal2.whl (100.1 kB view details)

Uploaded CPython 3.8 macOS 10.9+ universal2 (ARM64, x86-64)

PyLBFGS-0.2.0.14-cp37-cp37m-win_amd64.whl (54.1 kB view details)

Uploaded CPython 3.7m Windows x86-64

PyLBFGS-0.2.0.14-cp37-cp37m-win32.whl (45.5 kB view details)

Uploaded CPython 3.7m Windows x86

PyLBFGS-0.2.0.14-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (252.7 kB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ ARM64

PyLBFGS-0.2.0.14-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (239.7 kB view details)

Uploaded CPython 3.7m manylinux: glibc 2.12+ x86-64 manylinux: glibc 2.5+ x86-64

PyLBFGS-0.2.0.14-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_12_i686.manylinux2010_i686.whl (222.7 kB view details)

Uploaded CPython 3.7m manylinux: glibc 2.12+ i686 manylinux: glibc 2.5+ i686

PyLBFGS-0.2.0.14-cp37-cp37m-macosx_10_9_x86_64.whl (55.6 kB view details)

Uploaded CPython 3.7m macOS 10.9+ x86-64

PyLBFGS-0.2.0.14-cp36-cp36m-win_amd64.whl (54.2 kB view details)

Uploaded CPython 3.6m Windows x86-64

PyLBFGS-0.2.0.14-cp36-cp36m-win32.whl (45.5 kB view details)

Uploaded CPython 3.6m Windows x86

PyLBFGS-0.2.0.14-cp36-cp36m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (251.6 kB view details)

Uploaded CPython 3.6m manylinux: glibc 2.17+ ARM64

PyLBFGS-0.2.0.14-cp36-cp36m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (239.4 kB view details)

Uploaded CPython 3.6m manylinux: glibc 2.12+ x86-64 manylinux: glibc 2.5+ x86-64

PyLBFGS-0.2.0.14-cp36-cp36m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_12_i686.manylinux2010_i686.whl (222.5 kB view details)

Uploaded CPython 3.6m manylinux: glibc 2.12+ i686 manylinux: glibc 2.5+ i686

PyLBFGS-0.2.0.14-cp36-cp36m-macosx_10_9_x86_64.whl (57.3 kB view details)

Uploaded CPython 3.6m macOS 10.9+ x86-64

File details

Details for the file PyLBFGS-0.2.0.14.tar.gz.

File metadata

  • Download URL: PyLBFGS-0.2.0.14.tar.gz
  • Upload date:
  • Size: 98.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.9.0 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.10.0

File hashes

Hashes for PyLBFGS-0.2.0.14.tar.gz
Algorithm Hash digest
SHA256 0394ac3de598b818a01fb225a6b853abbd0e09620e35c072c6c96b0bbe558b99
MD5 b8d3eb0ecc8fe2fc3762924b28ae32b1
BLAKE2b-256 e27ee014b3394a547148618764d25fd173835de1de80e3b11356d052ac80ef4f

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.14-pp37-pypy37_pp73-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for PyLBFGS-0.2.0.14-pp37-pypy37_pp73-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 7c52630f02182cbba0fdf5f60ffb4226c3d21d16ddaee8aa162191792c71884e
MD5 4d039e590d0e8ffbe3a8d8c244877c8c
BLAKE2b-256 ddcbb7195fd0c1f36004a15487ec89384c0b82895181669b5e55fea3d3f69a31

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.14-cp310-cp310-win_amd64.whl.

File metadata

  • Download URL: PyLBFGS-0.2.0.14-cp310-cp310-win_amd64.whl
  • Upload date:
  • Size: 54.6 kB
  • Tags: CPython 3.10, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.9.0 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.10.0

File hashes

Hashes for PyLBFGS-0.2.0.14-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 fb60b7c1862a114286a6f889b704c32a8980f7e1147b315b67d2aaf0ccad5b5a
MD5 4d546d39d479f5156fd258332b20dc3d
BLAKE2b-256 91f727d1d7658c38f1387cd5bd3a45e84a56105977e43d82fc9cb262de40b90c

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.14-cp310-cp310-win32.whl.

File metadata

  • Download URL: PyLBFGS-0.2.0.14-cp310-cp310-win32.whl
  • Upload date:
  • Size: 45.8 kB
  • Tags: CPython 3.10, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.9.0 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.10.0

File hashes

Hashes for PyLBFGS-0.2.0.14-cp310-cp310-win32.whl
Algorithm Hash digest
SHA256 2b3ec45d9bd500f31affa85e7a5355a2b59878d420913a1464f88e3459371a16
MD5 357f7801ad9dbdfc99c0ed3a2512c1f5
BLAKE2b-256 1074925813fe1f473e9f812bf88e3a8281d681962c74d556c1b868aa3324b6a8

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.14-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for PyLBFGS-0.2.0.14-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 0113798a124f22f715cb6871dbad266c51db5e47caf7d1f527c4e97c17edcae9
MD5 dc49c336c5fda0af380b9c25fc0a904d
BLAKE2b-256 99c9d5d4daf77b4b0aa315357a8ffa9ada8f94c74236bdf262ab247891b73eab

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.14-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for PyLBFGS-0.2.0.14-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 9084301156f4d9da67940c3266403ccaf5401a541782e6d12e41c5f504eb322b
MD5 fb178873e9566f09cec4a9baf3aded62
BLAKE2b-256 25aaadeb52569585e5e8e491f6ae14db298f23e15fa34abb09c6fa0634a6dc25

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.14-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_12_i686.manylinux2010_i686.whl.

File metadata

File hashes

Hashes for PyLBFGS-0.2.0.14-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_12_i686.manylinux2010_i686.whl
Algorithm Hash digest
SHA256 c55dacad1118e0d53cbd14912400373a0c0dc55fa70607cde26254ab9f5f2096
MD5 633a74555e67406816b60d763e9ea5a9
BLAKE2b-256 20d4c8a4c396487dfe401b618b3287aee8a85b51128ca18d3328b7e7479d4161

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.14-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

  • Download URL: PyLBFGS-0.2.0.14-cp310-cp310-macosx_11_0_arm64.whl
  • Upload date:
  • Size: 49.3 kB
  • Tags: CPython 3.10, macOS 11.0+ ARM64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.9.0 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.10.0

File hashes

Hashes for PyLBFGS-0.2.0.14-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 8a1f62a1589e8aaa18dbace61907e2251c079d8943418bb514f8de914dfcb7dc
MD5 eba3371832023f8239d3569697564f8b
BLAKE2b-256 c01b495a982ec0f6379c9a3055f3d38fefa736c892a6c2299680777776536f88

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.14-cp310-cp310-macosx_10_9_x86_64.whl.

File metadata

  • Download URL: PyLBFGS-0.2.0.14-cp310-cp310-macosx_10_9_x86_64.whl
  • Upload date:
  • Size: 56.3 kB
  • Tags: CPython 3.10, macOS 10.9+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.9.0 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.10.0

File hashes

Hashes for PyLBFGS-0.2.0.14-cp310-cp310-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 61c4ea861608a43a1b4b48bcec34e30365d33d97f6598f4ccf22ea7cdef78b4f
MD5 f9d580494877f094b2c2703686e812fd
BLAKE2b-256 d8a0a924f00bb205fbc1152056643c1181ab0685ec62edce6a9200e5569592cb

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.14-cp310-cp310-macosx_10_9_universal2.whl.

File metadata

  • Download URL: PyLBFGS-0.2.0.14-cp310-cp310-macosx_10_9_universal2.whl
  • Upload date:
  • Size: 100.2 kB
  • Tags: CPython 3.10, macOS 10.9+ universal2 (ARM64, x86-64)
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.9.0 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.10.0

File hashes

Hashes for PyLBFGS-0.2.0.14-cp310-cp310-macosx_10_9_universal2.whl
Algorithm Hash digest
SHA256 b548636e9e3c4f34d5fbd4592e196d8cb3795919d4e9d18f39bcb4c7816ece52
MD5 f2e5c83c79406bb0ed2d1c72e93aae83
BLAKE2b-256 8f7caf257ff125247f57f38654a81e1f042ba750577cbc3c9c89fc6e36cd0547

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.14-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: PyLBFGS-0.2.0.14-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 54.4 kB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.9.0 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.10.0

File hashes

Hashes for PyLBFGS-0.2.0.14-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 9300eb47e759258231375a01a1f974fc648b946d5c1ccb6d595969c2caf95d2b
MD5 b64616c5f6cf0c0be51004a596dd8f3c
BLAKE2b-256 f4f7005f8d37c303695f1067ccbf794126216fc48afda73471de1ee66d30988e

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.14-cp39-cp39-win32.whl.

File metadata

  • Download URL: PyLBFGS-0.2.0.14-cp39-cp39-win32.whl
  • Upload date:
  • Size: 45.6 kB
  • Tags: CPython 3.9, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.9.0 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.10.0

File hashes

Hashes for PyLBFGS-0.2.0.14-cp39-cp39-win32.whl
Algorithm Hash digest
SHA256 dd945767da347b60a0c92117e4760803dc389227f7f784fad70b487209245385
MD5 c0d44a3294a2932f7da2e04d7b9080d6
BLAKE2b-256 d7bc6cd7669c54b2b4a2691f8e0e0e1f9f4275a1710ea2e6af3b73e295d3b109

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.14-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for PyLBFGS-0.2.0.14-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 b50cb4a013ac1103e196f646be73362bcdff094465ed911bd8147f28918fe789
MD5 84840f077f089f4a680e33200001fab6
BLAKE2b-256 34e2f5f05bbafd70a519901db66d62e79dee0a553c68d7f161b53a2552b63f61

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.14-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for PyLBFGS-0.2.0.14-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 e8d0abbe6bdfe2ed27e0d9a7d35cf852570264978585e1b5801fe731aa7f7e29
MD5 17287ea4fad6de5407018d3007f828be
BLAKE2b-256 1a13c831fe9f17d2c17e9b9dd16a59de022a8cd064b6a95a8070a0c2028c1639

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.14-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_12_i686.manylinux2010_i686.whl.

File metadata

File hashes

Hashes for PyLBFGS-0.2.0.14-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_12_i686.manylinux2010_i686.whl
Algorithm Hash digest
SHA256 dc14f9ca15d57e35f6ff9675d8e2b0870b30395ae6876d69c91fe8b644f287cf
MD5 cad0246707f3028c3f560175edea476a
BLAKE2b-256 31ff06c698711d1864381d7444aeb9fc06c2b8ccb408c59d1c2306f47785a3db

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.14-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

  • Download URL: PyLBFGS-0.2.0.14-cp39-cp39-macosx_11_0_arm64.whl
  • Upload date:
  • Size: 48.9 kB
  • Tags: CPython 3.9, macOS 11.0+ ARM64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.9.0 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.10.0

File hashes

Hashes for PyLBFGS-0.2.0.14-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 56f5daf41e6717f7317f39194e2a11e68d5ddb4d67491cf93665a76fbe2bdb5b
MD5 359ea056ae22ac013cecec1f680cb8b9
BLAKE2b-256 2a80c30458fe2a7712e81a771ec1f7443174ad85a513bf4fde331e8dbc170550

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.14-cp39-cp39-macosx_10_9_x86_64.whl.

File metadata

  • Download URL: PyLBFGS-0.2.0.14-cp39-cp39-macosx_10_9_x86_64.whl
  • Upload date:
  • Size: 55.9 kB
  • Tags: CPython 3.9, macOS 10.9+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.9.0 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.10.0

File hashes

Hashes for PyLBFGS-0.2.0.14-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 d2560c519245f0e69105946f692b24e005921f1b0eb75117e84e8b9b57a79368
MD5 badb166e24fddba33db5b499de53c4d1
BLAKE2b-256 af2476dbbeb78a39ee0379af6a231008e853fa330a6cf5e5c9df1e692928fdd0

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.14-cp39-cp39-macosx_10_9_universal2.whl.

File metadata

  • Download URL: PyLBFGS-0.2.0.14-cp39-cp39-macosx_10_9_universal2.whl
  • Upload date:
  • Size: 99.2 kB
  • Tags: CPython 3.9, macOS 10.9+ universal2 (ARM64, x86-64)
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.9.0 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.10.0

File hashes

Hashes for PyLBFGS-0.2.0.14-cp39-cp39-macosx_10_9_universal2.whl
Algorithm Hash digest
SHA256 5b1959d47acc72ecfa92db145581ca7c0a8722b9e2c0c9f82e489b6e78d91b6d
MD5 7ca55f068e064f0fa4211df9ade4b1b1
BLAKE2b-256 f44e3676febf7393e703a1d5b6f20db6d2778ac0a6e06b83eb3ba81a4496034e

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.14-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: PyLBFGS-0.2.0.14-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 54.7 kB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.9.0 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.10.0

File hashes

Hashes for PyLBFGS-0.2.0.14-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 8bde2d229b431237849d8ad6b43e115e57c8530a1bdc29fb5974c5c8599f2711
MD5 d2f51b3e8ad494e0278a307091108e44
BLAKE2b-256 2dae452bf338ce8c5b99ea39beefbf190f1abd4b582239fc511277d391c24353

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.14-cp38-cp38-win32.whl.

File metadata

  • Download URL: PyLBFGS-0.2.0.14-cp38-cp38-win32.whl
  • Upload date:
  • Size: 46.1 kB
  • Tags: CPython 3.8, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.9.0 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.10.0

File hashes

Hashes for PyLBFGS-0.2.0.14-cp38-cp38-win32.whl
Algorithm Hash digest
SHA256 a1603198330cfc2628e4c5eb925928b90870c7f27f0b7f263ed03cb38580fc6c
MD5 0949cae845eea233a24d718d193d44de
BLAKE2b-256 ad4c75d19f0962eb38e0268ef463e6029005f476b2cdad3ebffb9e5183e87055

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.14-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for PyLBFGS-0.2.0.14-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 b697972eed2a79f3d1c5e5e7f5f9066c16dce0c737cfcd8734aa22a9a6c7d05e
MD5 84ec15bd9ac4a7a05f6893a2613d4594
BLAKE2b-256 b786853458ce2c54002fe0181a87c6775590121338cd57e509250de8ea1db3c2

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.14-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for PyLBFGS-0.2.0.14-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 b0198f3019d78193a215d742830c88135c8a2c7ceec5d5e41b1bbd096fe2213a
MD5 8b40166eb4da744d469e2158fefa5421
BLAKE2b-256 c09d854fa8bf1bfef5afb0f565b7d23b6df8f2820f9307398e4c013f92cdc872

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.14-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_12_i686.manylinux2010_i686.whl.

File metadata

File hashes

Hashes for PyLBFGS-0.2.0.14-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_12_i686.manylinux2010_i686.whl
Algorithm Hash digest
SHA256 3efb2a830e31f3772c2a0d5ca3100cfe65298a647c71681e0560bbee53a2ef90
MD5 bcbe43aeb4cf620e44b5e3ed3ce454f7
BLAKE2b-256 4cc08f3e1a1b943ad198a5b5d8aaceac9a3c17fff36fddfd143cffd4ba752a07

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.14-cp38-cp38-macosx_11_0_arm64.whl.

File metadata

  • Download URL: PyLBFGS-0.2.0.14-cp38-cp38-macosx_11_0_arm64.whl
  • Upload date:
  • Size: 49.3 kB
  • Tags: CPython 3.8, macOS 11.0+ ARM64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.9.0 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.10.0

File hashes

Hashes for PyLBFGS-0.2.0.14-cp38-cp38-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 1dd1f01c392a0f99665df33eb492030ad9f4fb96bc9fe63292bf4c8c1e7f341d
MD5 39613bc7ecfc58c813ceea1a10126767
BLAKE2b-256 c5086aaf56bc4322a44cb799d6d14cc716e5e3bfaee3484935cd9734fa65a79b

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.14-cp38-cp38-macosx_10_9_x86_64.whl.

File metadata

  • Download URL: PyLBFGS-0.2.0.14-cp38-cp38-macosx_10_9_x86_64.whl
  • Upload date:
  • Size: 56.3 kB
  • Tags: CPython 3.8, macOS 10.9+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.9.0 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.10.0

File hashes

Hashes for PyLBFGS-0.2.0.14-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 977d24a2f5cd34ba3d4d4fbe9e55eac9ef226aff4ffc53490fe7fb9f05c4b010
MD5 7f2b851a3b9c745b66420c8ec46614d2
BLAKE2b-256 0ace99abed2349fba3ad2cfe19eabb64a4f960bc2a6568d9d623719f8099fd58

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.14-cp38-cp38-macosx_10_9_universal2.whl.

File metadata

  • Download URL: PyLBFGS-0.2.0.14-cp38-cp38-macosx_10_9_universal2.whl
  • Upload date:
  • Size: 100.1 kB
  • Tags: CPython 3.8, macOS 10.9+ universal2 (ARM64, x86-64)
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.9.0 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.10.0

File hashes

Hashes for PyLBFGS-0.2.0.14-cp38-cp38-macosx_10_9_universal2.whl
Algorithm Hash digest
SHA256 50c9638db3f5e28a85dd0329e3b769a59acf9c2eb73dc6a668a0604ecf29b32a
MD5 ec9787121da52c4ae2baa12268d863d8
BLAKE2b-256 9c25106284ce87e00c48e3a33514da0ac4da6b85824fe82a5442726a5824b502

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.14-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: PyLBFGS-0.2.0.14-cp37-cp37m-win_amd64.whl
  • Upload date:
  • Size: 54.1 kB
  • Tags: CPython 3.7m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.9.0 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.10.0

File hashes

Hashes for PyLBFGS-0.2.0.14-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 f850fbee9339f51b881fcbd6b0ff924396cc828e335e4cf189ede4c0d47e0083
MD5 be9af2886a135581509291024237a7f4
BLAKE2b-256 5808542ca4aed339cdb225cd2d3dbe3f0a22cbd6fe34096ca789402ab82e9403

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.14-cp37-cp37m-win32.whl.

File metadata

  • Download URL: PyLBFGS-0.2.0.14-cp37-cp37m-win32.whl
  • Upload date:
  • Size: 45.5 kB
  • Tags: CPython 3.7m, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.9.0 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.10.0

File hashes

Hashes for PyLBFGS-0.2.0.14-cp37-cp37m-win32.whl
Algorithm Hash digest
SHA256 7ccc7922ffe6463838d91b59973dfe63a46f2eca73a2b45cb9f57770b5d5aff6
MD5 5923d51d10ffe697aafa3ed51a6f986f
BLAKE2b-256 f418dd06e9ec6610c3b2486b5a769872f433b6754a51554aaf236ed730134df6

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.14-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for PyLBFGS-0.2.0.14-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 c9313a7ed808bfee8a7ff6f8545f21afa8dcd557c9b582ea865b4c28971d2bde
MD5 a4d89972a9be5e72ef87a943b8955106
BLAKE2b-256 073e1bb04b5e42ef674af47263e90932a8e32258a99261646d26de227e1e1973

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.14-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for PyLBFGS-0.2.0.14-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 b0e265c74f200d18c35763721156bcede5f1b76aa3d188bb79dda6ed48b5231d
MD5 0ff3dfe88044d148796bf85f5b153462
BLAKE2b-256 4f341ac0f6f9f1b490b6cb738b153e7097ed676afeb52e4e59067df7e0a78a2e

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.14-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_12_i686.manylinux2010_i686.whl.

File metadata

File hashes

Hashes for PyLBFGS-0.2.0.14-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_12_i686.manylinux2010_i686.whl
Algorithm Hash digest
SHA256 d0937d4e0ce03f79260f7ac711e50ceecbd6736f762327f0f8e0e08c30952354
MD5 3d64a802f276ba2991f03af45d73eac5
BLAKE2b-256 de9ccfb37dde1439bf9856db3b0ae4bb20e8d80e086b7b6d77f35cdcd8be5ce6

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.14-cp37-cp37m-macosx_10_9_x86_64.whl.

File metadata

  • Download URL: PyLBFGS-0.2.0.14-cp37-cp37m-macosx_10_9_x86_64.whl
  • Upload date:
  • Size: 55.6 kB
  • Tags: CPython 3.7m, macOS 10.9+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.9.0 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.10.0

File hashes

Hashes for PyLBFGS-0.2.0.14-cp37-cp37m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 dbd6366d1229662e8cd121153468f7224e5e1939c15285f77cb6c87b84da987a
MD5 3dadd9de997aabe8647a71f28d2640a3
BLAKE2b-256 b86cb5cfd3f1145b5e98ceaec7347608b580f7d84cefa3c61f1181eb649bdef7

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.14-cp36-cp36m-win_amd64.whl.

File metadata

  • Download URL: PyLBFGS-0.2.0.14-cp36-cp36m-win_amd64.whl
  • Upload date:
  • Size: 54.2 kB
  • Tags: CPython 3.6m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.9.0 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.10.0

File hashes

Hashes for PyLBFGS-0.2.0.14-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 86fac1c53dc0c6da5fccb0b05d3a0f34cb2a576fa57909cb0a4ef92bda2928c1
MD5 37344ef3fe3ab01c636bb8863f31197b
BLAKE2b-256 ae11390cf14035caa2d857e648902aa020ee06cd47d1a3a4d8c31488155a4f55

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.14-cp36-cp36m-win32.whl.

File metadata

  • Download URL: PyLBFGS-0.2.0.14-cp36-cp36m-win32.whl
  • Upload date:
  • Size: 45.5 kB
  • Tags: CPython 3.6m, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.9.0 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.10.0

File hashes

Hashes for PyLBFGS-0.2.0.14-cp36-cp36m-win32.whl
Algorithm Hash digest
SHA256 454f2a126b8592b38e6deaaf9f7b03f2a7890e1200f1c3698c85fab1abadf0e2
MD5 01579e92f62f4a0c862158b35a7764c7
BLAKE2b-256 c7b84490398b9daf2b26f58ce7b365100e8b969dffbe38661d61a2f23f8c8afa

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.14-cp36-cp36m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for PyLBFGS-0.2.0.14-cp36-cp36m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 7b05e9ba5f229ff84f2dd8e5e1deabeee2df9b7ab887c5a2f8ecf14658e7fb90
MD5 b6080debcc68ba9379f4b1e2f904eb02
BLAKE2b-256 77e9c22977df290d264331eda4fe0eb780c04c4a5f6e6da719b99465f0e3a2e6

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.14-cp36-cp36m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for PyLBFGS-0.2.0.14-cp36-cp36m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 4069ef8babe788b5ecae22c9fd59491abb82359f56db48d86061ab577e2002e9
MD5 4f6efa464de42deadcac0564f96253cd
BLAKE2b-256 f5694771701791150f3732a1b69b1eee930b0056f43adb278bac1336e2850ca7

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.14-cp36-cp36m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_12_i686.manylinux2010_i686.whl.

File metadata

File hashes

Hashes for PyLBFGS-0.2.0.14-cp36-cp36m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_12_i686.manylinux2010_i686.whl
Algorithm Hash digest
SHA256 7db6dac1e0671b9c806753260b581a772b8ff764ab34e1d70115f82cbeb6d8ee
MD5 e90f0706ac4af4d8b24d47613000e9eb
BLAKE2b-256 62a85d10a3a2a41f03aaf384ebe1ddbdb68b6ab4f87ddd2293ea03c0ce39a31e

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.14-cp36-cp36m-macosx_10_9_x86_64.whl.

File metadata

  • Download URL: PyLBFGS-0.2.0.14-cp36-cp36m-macosx_10_9_x86_64.whl
  • Upload date:
  • Size: 57.3 kB
  • Tags: CPython 3.6m, macOS 10.9+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.9.0 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.10.0

File hashes

Hashes for PyLBFGS-0.2.0.14-cp36-cp36m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 5140598839f34890f4fa44e2fc1f212f03f1e5d4c8bd1bd7b995bcf91af3a163
MD5 6dea61bc8470125e218e5df9d2c5bf87
BLAKE2b-256 98ddeaf7d9c8dfa3a5bdbc655bd990c3b192fefcc440e16f838fa9caae73baff

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page