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.

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

0.2.0.14

0.2.0.13

0.2.0.12

This version

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-0.2.0.11.tar.gz (104.3 kB view details)

Uploaded Source

Built Distributions

PyLBFGS-0.2.0.11-cp37-cp37m-win_amd64.whl (53.4 kB view details)

Uploaded CPython 3.7m Windows x86-64

PyLBFGS-0.2.0.11-cp37-cp37m-win32.whl (44.9 kB view details)

Uploaded CPython 3.7m Windows x86

PyLBFGS-0.2.0.11-cp37-cp37m-manylinux1_x86_64.whl (207.8 kB view details)

Uploaded CPython 3.7m

PyLBFGS-0.2.0.11-cp37-cp37m-manylinux1_i686.whl (191.2 kB view details)

Uploaded CPython 3.7m

PyLBFGS-0.2.0.11-cp37-cp37m-macosx_10_13_x86_64.whl (57.4 kB view details)

Uploaded CPython 3.7m macOS 10.13+ x86-64

PyLBFGS-0.2.0.11-cp36-cp36m-win_amd64.whl (53.4 kB view details)

Uploaded CPython 3.6m Windows x86-64

PyLBFGS-0.2.0.11-cp36-cp36m-win32.whl (45.0 kB view details)

Uploaded CPython 3.6m Windows x86

PyLBFGS-0.2.0.11-cp36-cp36m-manylinux1_x86_64.whl (210.5 kB view details)

Uploaded CPython 3.6m

PyLBFGS-0.2.0.11-cp36-cp36m-manylinux1_i686.whl (190.7 kB view details)

Uploaded CPython 3.6m

PyLBFGS-0.2.0.11-cp36-cp36m-macosx_10_12_x86_64.whl (56.5 kB view details)

Uploaded CPython 3.6m macOS 10.12+ x86-64

PyLBFGS-0.2.0.11-cp35-cp35m-win_amd64.whl (52.8 kB view details)

Uploaded CPython 3.5m Windows x86-64

PyLBFGS-0.2.0.11-cp35-cp35m-win32.whl (44.4 kB view details)

Uploaded CPython 3.5m Windows x86

PyLBFGS-0.2.0.11-cp35-cp35m-manylinux1_x86_64.whl (202.8 kB view details)

Uploaded CPython 3.5m

PyLBFGS-0.2.0.11-cp35-cp35m-manylinux1_i686.whl (184.6 kB view details)

Uploaded CPython 3.5m

PyLBFGS-0.2.0.11-cp34-cp34m-win_amd64.whl (51.0 kB view details)

Uploaded CPython 3.4m Windows x86-64

PyLBFGS-0.2.0.11-cp34-cp34m-win32.whl (43.5 kB view details)

Uploaded CPython 3.4m Windows x86

PyLBFGS-0.2.0.11-cp34-cp34m-manylinux1_x86_64.whl (208.4 kB view details)

Uploaded CPython 3.4m

PyLBFGS-0.2.0.11-cp34-cp34m-manylinux1_i686.whl (187.7 kB view details)

Uploaded CPython 3.4m

PyLBFGS-0.2.0.11-cp27-cp27mu-manylinux1_x86_64.whl (186.6 kB view details)

Uploaded CPython 2.7mu

PyLBFGS-0.2.0.11-cp27-cp27mu-manylinux1_i686.whl (167.8 kB view details)

Uploaded CPython 2.7mu

PyLBFGS-0.2.0.11-cp27-cp27m-win_amd64.whl (51.8 kB view details)

Uploaded CPython 2.7m Windows x86-64

PyLBFGS-0.2.0.11-cp27-cp27m-win32.whl (42.7 kB view details)

Uploaded CPython 2.7m Windows x86

PyLBFGS-0.2.0.11-cp27-cp27m-manylinux1_x86_64.whl (186.6 kB view details)

Uploaded CPython 2.7m

PyLBFGS-0.2.0.11-cp27-cp27m-manylinux1_i686.whl (167.7 kB view details)

Uploaded CPython 2.7m

PyLBFGS-0.2.0.11-cp27-cp27m-macosx_10_12_x86_64.whl (57.0 kB view details)

Uploaded CPython 2.7m macOS 10.12+ x86-64

File details

Details for the file PyLBFGS-0.2.0.11.tar.gz.

File metadata

  • Download URL: PyLBFGS-0.2.0.11.tar.gz
  • Upload date:
  • Size: 104.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for PyLBFGS-0.2.0.11.tar.gz
Algorithm Hash digest
SHA256 67ad145e966ebcfe77162cd581be433233c7a0e122983ae12f430e230119a35e
MD5 0674a6f0b17573db95ac7ed98134a898
BLAKE2b-256 c9b5afbdb7342c973e808dbf570d2db8a5d0962ea9bd3bff73de2fb0f5344bd4

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.11-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: PyLBFGS-0.2.0.11-cp37-cp37m-win_amd64.whl
  • Upload date:
  • Size: 53.4 kB
  • Tags: CPython 3.7m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.11.0 pkginfo/1.4.2 requests/2.19.1 setuptools/39.0.1 requests-toolbelt/0.8.0 tqdm/4.24.0 CPython/3.7.0

File hashes

Hashes for PyLBFGS-0.2.0.11-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 9f994e93588531d9ae40d35abf958430044883bd339a612fadfe8f2a3dd85208
MD5 4e132a53901c34451916274f5881617a
BLAKE2b-256 01554bb3e6a7b084daad32d6e212049c75db106ee30942b7f442654bd15ebd65

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.11-cp37-cp37m-win32.whl.

File metadata

  • Download URL: PyLBFGS-0.2.0.11-cp37-cp37m-win32.whl
  • Upload date:
  • Size: 44.9 kB
  • Tags: CPython 3.7m, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.11.0 pkginfo/1.4.2 requests/2.19.1 setuptools/39.0.1 requests-toolbelt/0.8.0 tqdm/4.24.0 CPython/3.7.0

File hashes

Hashes for PyLBFGS-0.2.0.11-cp37-cp37m-win32.whl
Algorithm Hash digest
SHA256 2c56aa7844f9f8818a84925c457d1e4114bcb2eb9aae0b432cfc047e20f1e36d
MD5 e90937b7f512330e857997068806aa1e
BLAKE2b-256 12c3f10b6076170117022585a7822f1dcad9a3a18948112212eb3003acca6fd7

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.11-cp37-cp37m-manylinux1_x86_64.whl.

File metadata

  • Download URL: PyLBFGS-0.2.0.11-cp37-cp37m-manylinux1_x86_64.whl
  • Upload date:
  • Size: 207.8 kB
  • Tags: CPython 3.7m
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.11.0 pkginfo/1.4.2 requests/2.19.1 setuptools/38.2.4 requests-toolbelt/0.8.0 tqdm/4.24.0 CPython/2.7.14

File hashes

Hashes for PyLBFGS-0.2.0.11-cp37-cp37m-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 f5e4b6b67f1395c886536be095e14436646461e02a50a2abc61bd231d6122062
MD5 6fdbf8e55b5965ea0987f5856be07707
BLAKE2b-256 b79014bb8a05a836e1a61973ed6576ab9c871c4ee72d015e7a745d14f22daab8

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.11-cp37-cp37m-manylinux1_i686.whl.

File metadata

  • Download URL: PyLBFGS-0.2.0.11-cp37-cp37m-manylinux1_i686.whl
  • Upload date:
  • Size: 191.2 kB
  • Tags: CPython 3.7m
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.11.0 pkginfo/1.4.2 requests/2.19.1 setuptools/38.2.4 requests-toolbelt/0.8.0 tqdm/4.24.0 CPython/2.7.14

File hashes

Hashes for PyLBFGS-0.2.0.11-cp37-cp37m-manylinux1_i686.whl
Algorithm Hash digest
SHA256 2fa54bb99ab87c33047cc06ddae2564736fe3641c8bec76d7213a61d33c662ae
MD5 32dff504b7e0485b862ffa067f3a83d9
BLAKE2b-256 a4fe96d063b67ad7c753015f72fc63421a4ea879957435e6c66877c7d52c7325

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.11-cp37-cp37m-macosx_10_13_x86_64.whl.

File metadata

  • Download URL: PyLBFGS-0.2.0.11-cp37-cp37m-macosx_10_13_x86_64.whl
  • Upload date:
  • Size: 57.4 kB
  • Tags: CPython 3.7m, macOS 10.13+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.11.0 pkginfo/1.4.2 requests/2.19.1 setuptools/40.0.0 requests-toolbelt/0.8.0 tqdm/4.24.0 CPython/3.7.0

File hashes

Hashes for PyLBFGS-0.2.0.11-cp37-cp37m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 b290478e81606cd13918a54028a666bea76b41b1a88680f631f8ef4101144e5c
MD5 dca7d9c0b20ed63fa6d26f1f89a2ce9a
BLAKE2b-256 c501d57a762652221490c0831f6f51f1009672d2a165648c9d84223efcd1bd45

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.11-cp36-cp36m-win_amd64.whl.

File metadata

  • Download URL: PyLBFGS-0.2.0.11-cp36-cp36m-win_amd64.whl
  • Upload date:
  • Size: 53.4 kB
  • Tags: CPython 3.6m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.11.0 pkginfo/1.4.2 requests/2.19.1 setuptools/39.0.1 requests-toolbelt/0.8.0 tqdm/4.24.0 CPython/3.6.6

File hashes

Hashes for PyLBFGS-0.2.0.11-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 9d509375ff56a78de229c0090626bb3a2f48f544328777a7663baca1e1e66a11
MD5 7911fcbb2966d1f3ef36b5709f056981
BLAKE2b-256 254d18864ce0e3fd5e13e98092bfad69b24c2282de2366dbc0edae6c55224b7a

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.11-cp36-cp36m-win32.whl.

File metadata

  • Download URL: PyLBFGS-0.2.0.11-cp36-cp36m-win32.whl
  • Upload date:
  • Size: 45.0 kB
  • Tags: CPython 3.6m, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.11.0 pkginfo/1.4.2 requests/2.19.1 setuptools/39.0.1 requests-toolbelt/0.8.0 tqdm/4.24.0 CPython/3.6.6

File hashes

Hashes for PyLBFGS-0.2.0.11-cp36-cp36m-win32.whl
Algorithm Hash digest
SHA256 b67c68843b10c7af21fc92a28e05c027270cc7ab1df38a38baf5ee5440c45d0b
MD5 100b23058e6bff28a6c4518a3c1257be
BLAKE2b-256 8f88ab40d93f7e7bfb27de79b6ea0498b8e6f67388142ca6a9be793f1d7c0300

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.11-cp36-cp36m-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for PyLBFGS-0.2.0.11-cp36-cp36m-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 77e5b5b80a4f80c5cde8ed35163c94e62a7d31afb46b354b78e5a7488417b1ee
MD5 feb22ea57eea5e2ba1382f823facd48a
BLAKE2b-256 b64fc74562e66a2b1b973e31b5fbcf0de8e11952c69eb3fceff5605dca1d1d63

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.11-cp36-cp36m-manylinux1_i686.whl.

File metadata

File hashes

Hashes for PyLBFGS-0.2.0.11-cp36-cp36m-manylinux1_i686.whl
Algorithm Hash digest
SHA256 a9d4b0dbd0fc8426bc9f05cff80d0008e10806ef02c4787d41fb15fc251dbdc9
MD5 a0a22858a4ab0d71827e323d958378d8
BLAKE2b-256 49876ede8be3ab0c8f16a26b8bde56ef2e46cf97e9a113a18c40ab16c3a189e9

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.11-cp36-cp36m-macosx_10_12_x86_64.whl.

File metadata

File hashes

Hashes for PyLBFGS-0.2.0.11-cp36-cp36m-macosx_10_12_x86_64.whl
Algorithm Hash digest
SHA256 42d7c4adc90ffc5c5d3ca47379875b4da34573be63dc6a96fe1edf3ba496e83f
MD5 21866a58de0c377972474b2e4833b1c2
BLAKE2b-256 db28f82c229c66fb8c454df64df9903eba5ea20dc807481065a3f88219658e75

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.11-cp35-cp35m-win_amd64.whl.

File metadata

  • Download URL: PyLBFGS-0.2.0.11-cp35-cp35m-win_amd64.whl
  • Upload date:
  • Size: 52.8 kB
  • Tags: CPython 3.5m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.11.0 pkginfo/1.4.2 requests/2.19.1 setuptools/28.8.0 requests-toolbelt/0.8.0 tqdm/4.24.0 CPython/3.5.3

File hashes

Hashes for PyLBFGS-0.2.0.11-cp35-cp35m-win_amd64.whl
Algorithm Hash digest
SHA256 eac03d8b52865d932d596951cbc87c47aa2d497474dd7852c296cd594cff5386
MD5 9f2d31cc557f871bd4c280c4d617b010
BLAKE2b-256 922f873cf456d13e486a8592c1c0aed34c2f817488bcaf85cef62ef0dfd52345

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.11-cp35-cp35m-win32.whl.

File metadata

  • Download URL: PyLBFGS-0.2.0.11-cp35-cp35m-win32.whl
  • Upload date:
  • Size: 44.4 kB
  • Tags: CPython 3.5m, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.11.0 pkginfo/1.4.2 requests/2.19.1 setuptools/28.8.0 requests-toolbelt/0.8.0 tqdm/4.24.0 CPython/3.5.3

File hashes

Hashes for PyLBFGS-0.2.0.11-cp35-cp35m-win32.whl
Algorithm Hash digest
SHA256 a2c3353de0dd5a77d169f1f6e06e721a9851ff848d84e3e334661e58f3ae01f6
MD5 c3b3d25fb743720d7acc0dfbc2936707
BLAKE2b-256 d495700ae7770b33af25e3c8bd3ceee6208ab7608f550a8f0a209cbf44555876

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.11-cp35-cp35m-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for PyLBFGS-0.2.0.11-cp35-cp35m-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 aa31d967a78d0606bd1c92d05b7f0ba05467a54e94ce8d2067269a81d82ba358
MD5 73f43f546f8de35ff488d7847dc6b4e4
BLAKE2b-256 af02f930647c41c0d5ffdafbff3f29bdf5e9cf8f3e39becbcce975d714bb15dd

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.11-cp35-cp35m-manylinux1_i686.whl.

File metadata

File hashes

Hashes for PyLBFGS-0.2.0.11-cp35-cp35m-manylinux1_i686.whl
Algorithm Hash digest
SHA256 cebd3c3a96da1ec281b0cdc6b6b93a68cf1ae73bc5b8ae54c66cc6c3b7767243
MD5 ce2ccca2a0e90ba3c01c6afc2f9aa205
BLAKE2b-256 577ceaf62881a51ecb09b818dd35447d3673ae3ab0d75b7e0236a74bd8457f23

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.11-cp34-cp34m-win_amd64.whl.

File metadata

File hashes

Hashes for PyLBFGS-0.2.0.11-cp34-cp34m-win_amd64.whl
Algorithm Hash digest
SHA256 56cbc6930f5a6f5db447236a2f4fe4b4acf77d883ad8a3b3d16cfc400c90e356
MD5 f114f8a22c495398197e0f88a6ecde92
BLAKE2b-256 40a17aa816f427791731f4a639cca7c35178e9ab374eef0bc31388ae1ad57f93

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.11-cp34-cp34m-win32.whl.

File metadata

File hashes

Hashes for PyLBFGS-0.2.0.11-cp34-cp34m-win32.whl
Algorithm Hash digest
SHA256 aef57c418985498ba1811ab6b18067c0fe092ca25dcbf8f2365981f844f7e1ed
MD5 1c61892a23d195d6bbfafc07c2c4bd88
BLAKE2b-256 933dcba12edbb1bf169fca53cff9c8ba57c7bda419125d1d2f10d9909aad4e7a

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.11-cp34-cp34m-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for PyLBFGS-0.2.0.11-cp34-cp34m-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 74a7f0603e6fe32ec429ac6044359b3d18f8f229006916effa47604f80751777
MD5 7fe31bcf3d009eb423c2736d63ba9226
BLAKE2b-256 43953cfcde937502773a22b9f8069270c686db480c989b54ecc089c3cde6cb49

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.11-cp34-cp34m-manylinux1_i686.whl.

File metadata

File hashes

Hashes for PyLBFGS-0.2.0.11-cp34-cp34m-manylinux1_i686.whl
Algorithm Hash digest
SHA256 c0be5107c992fe80a2e916f006c4953ddc1295e59eabc12496884c695944e59f
MD5 fe033f7a8e6e39551fd3127119e4beb5
BLAKE2b-256 6e0e3995a6524f3b192fa844c6e23536577759d5abf6350e6cea14d2e1b8c413

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.11-cp27-cp27mu-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for PyLBFGS-0.2.0.11-cp27-cp27mu-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 e992ec6f8d43de1913eadbc1289b3e27407ade19e7c8194bbce8c3315d625354
MD5 ee9c1f285f7fe9338695dcfd62a456b1
BLAKE2b-256 244075efa70c92671f2b2f04d41d3b02dae570516c44e1c4e3c8cdc41c470a76

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.11-cp27-cp27mu-manylinux1_i686.whl.

File metadata

File hashes

Hashes for PyLBFGS-0.2.0.11-cp27-cp27mu-manylinux1_i686.whl
Algorithm Hash digest
SHA256 50d40fe0d9a1768ec07f9f7f0a3336587470a1b34f4e8900477a55441d4c3aae
MD5 b6b52b91a6df70c2da39694897a6589a
BLAKE2b-256 c10ce137f508ba2605f720da134638b5a24608d7e96a0a50869885b802a6904d

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.11-cp27-cp27m-win_amd64.whl.

File metadata

File hashes

Hashes for PyLBFGS-0.2.0.11-cp27-cp27m-win_amd64.whl
Algorithm Hash digest
SHA256 10dc879bf2a7d664932935ca34737a4c896213c6fda1b9ae600583ea2758a119
MD5 14f1dceccca153dca6f63650202d163a
BLAKE2b-256 720358d9b922415734f567312250ac90f48a6a6119be6af8074cc5836f762da3

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.11-cp27-cp27m-win32.whl.

File metadata

File hashes

Hashes for PyLBFGS-0.2.0.11-cp27-cp27m-win32.whl
Algorithm Hash digest
SHA256 3bee9aedbb19082cbca5d8e8bacfe6c853627b81eb38c66431e68ba418527c7a
MD5 6ae92e0a3698e3bd7ab2ed899c3c92b6
BLAKE2b-256 a26f6bfec3b5d2549f6f65f6bac7198a1073f5828767d43434e37a4fd7589b02

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.11-cp27-cp27m-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for PyLBFGS-0.2.0.11-cp27-cp27m-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 0ceaaffa2ef5bf1ec26d037911661005622331067408f329005dc98107f9af5a
MD5 f705b1a8ce7eb8c7f06b9315d31346e4
BLAKE2b-256 ef6f6f76442ff847a19ea69ce353dfc9b4dedcc8d5804f123783585989b2d9f5

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.11-cp27-cp27m-manylinux1_i686.whl.

File metadata

File hashes

Hashes for PyLBFGS-0.2.0.11-cp27-cp27m-manylinux1_i686.whl
Algorithm Hash digest
SHA256 4f35e770df48ef4340f85c0e58311471340c6f07ddc188be05bb7413917a66c3
MD5 def9426d5c52b89074244db755e63267
BLAKE2b-256 46f869d57d8f1aa98e8c2fd88fe71dfe159df73a165bc9047ffb35e68369a2a0

See more details on using hashes here.

File details

Details for the file PyLBFGS-0.2.0.11-cp27-cp27m-macosx_10_12_x86_64.whl.

File metadata

File hashes

Hashes for PyLBFGS-0.2.0.11-cp27-cp27m-macosx_10_12_x86_64.whl
Algorithm Hash digest
SHA256 dbe659ed666b895cb2ddbc1cd692329c2e6e28c96e21c5f2e0bee4e9fc8b1c17
MD5 deae10f251a6fab20535bc6a05ad7fb2
BLAKE2b-256 b2cbfc50ceb26fc3c5596e732c3a7f794074cb3bb62d134774f5d29dff78f6e5

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