Skip to main content

Data Removal-Enabled Random Forests

Project description

DaRE RF: Data Removal-Enabled Random Forests

PyPi version Python version Github License Build

dare-rf is a python library that implements machine unlearning for random forests, enabling the efficient removal of training data without having to retrain from scratch. It is built using Cython and is designed to be scalable to large datasets.

thumbnail

Installation

pip install dare-rf

Usage

Simple example of removing a single training instance:

import dare
import numpy as np

# training data
X_train = np.array([[0, 1], [0, 1], [0, 1], [1, 0], [1, 0]])
y_train = np.array([1, 1, 1, 0, 1])

X_test = np.array([[1, 0]])  # test instance

# train a DaRE RF model
rf = dare.Forest(n_estimators=100,
                 max_depth=3,
                 k=5,  # no. thresholds to consider per attribute
                 topd=0,  # no. random node layers
                 random_state=1)
rf.fit(X_train, y_train)

rf.predict_proba(X_test)  # prediction before deletion => [0.5, 0.5]
rf.delete(3)  # delete training example at index 3 ([1, 0], 0)
rf.predict_proba(X_test)  # prediction after deletion => [0.0, 1.0]

License

Apache License 2.0.

Reference

Brophy and Lowd. Machine Unlearning for Random Forests. ICML 2021.

@inproceedings{brophy2021machine,
  title={Machine Unlearning for Random Forests},
  author={Brophy, Jonathan and Lowd, Daniel},
  booktitle={International Conference on Machine Learning},
  pages={1092--1104},
  year={2021},
  organization={PMLR}
}

Project details


Download files

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

Source Distribution

dare_rf-1.1.4.tar.gz (1.2 MB view details)

Uploaded Source

Built Distributions

dare_rf-1.1.4-cp310-cp310-win_amd64.whl (1.8 MB view details)

Uploaded CPython 3.10 Windows x86-64

dare_rf-1.1.4-cp310-cp310-win32.whl (1.7 MB view details)

Uploaded CPython 3.10 Windows x86

dare_rf-1.1.4-cp310-cp310-musllinux_1_1_x86_64.whl (4.8 MB view details)

Uploaded CPython 3.10 musllinux: musl 1.1+ x86-64

dare_rf-1.1.4-cp310-cp310-musllinux_1_1_i686.whl (4.6 MB view details)

Uploaded CPython 3.10 musllinux: musl 1.1+ i686

dare_rf-1.1.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (4.7 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ x86-64

dare_rf-1.1.4-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl (4.6 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ i686 manylinux: glibc 2.5+ i686

dare_rf-1.1.4-cp310-cp310-macosx_10_9_x86_64.whl (1.9 MB view details)

Uploaded CPython 3.10 macOS 10.9+ x86-64

dare_rf-1.1.4-cp39-cp39-win_amd64.whl (1.8 MB view details)

Uploaded CPython 3.9 Windows x86-64

dare_rf-1.1.4-cp39-cp39-win32.whl (1.7 MB view details)

Uploaded CPython 3.9 Windows x86

dare_rf-1.1.4-cp39-cp39-musllinux_1_1_x86_64.whl (4.8 MB view details)

Uploaded CPython 3.9 musllinux: musl 1.1+ x86-64

dare_rf-1.1.4-cp39-cp39-musllinux_1_1_i686.whl (4.6 MB view details)

Uploaded CPython 3.9 musllinux: musl 1.1+ i686

dare_rf-1.1.4-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (4.7 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ x86-64

dare_rf-1.1.4-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl (4.6 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ i686 manylinux: glibc 2.5+ i686

dare_rf-1.1.4-cp39-cp39-macosx_10_9_x86_64.whl (1.9 MB view details)

Uploaded CPython 3.9 macOS 10.9+ x86-64

dare_rf-1.1.4-cp38-cp38-win_amd64.whl (1.8 MB view details)

Uploaded CPython 3.8 Windows x86-64

dare_rf-1.1.4-cp38-cp38-win32.whl (1.7 MB view details)

Uploaded CPython 3.8 Windows x86

dare_rf-1.1.4-cp38-cp38-musllinux_1_1_x86_64.whl (4.9 MB view details)

Uploaded CPython 3.8 musllinux: musl 1.1+ x86-64

dare_rf-1.1.4-cp38-cp38-musllinux_1_1_i686.whl (4.7 MB view details)

Uploaded CPython 3.8 musllinux: musl 1.1+ i686

dare_rf-1.1.4-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (4.8 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ x86-64

dare_rf-1.1.4-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl (4.6 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ i686 manylinux: glibc 2.5+ i686

dare_rf-1.1.4-cp38-cp38-macosx_10_9_x86_64.whl (1.9 MB view details)

Uploaded CPython 3.8 macOS 10.9+ x86-64

dare_rf-1.1.4-cp37-cp37m-win_amd64.whl (1.8 MB view details)

Uploaded CPython 3.7m Windows x86-64

dare_rf-1.1.4-cp37-cp37m-win32.whl (1.7 MB view details)

Uploaded CPython 3.7m Windows x86

dare_rf-1.1.4-cp37-cp37m-musllinux_1_1_x86_64.whl (4.5 MB view details)

Uploaded CPython 3.7m musllinux: musl 1.1+ x86-64

dare_rf-1.1.4-cp37-cp37m-musllinux_1_1_i686.whl (4.4 MB view details)

Uploaded CPython 3.7m musllinux: musl 1.1+ i686

dare_rf-1.1.4-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (4.5 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ x86-64

dare_rf-1.1.4-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl (4.4 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ i686 manylinux: glibc 2.5+ i686

dare_rf-1.1.4-cp37-cp37m-macosx_10_9_x86_64.whl (1.9 MB view details)

Uploaded CPython 3.7m macOS 10.9+ x86-64

File details

Details for the file dare_rf-1.1.4.tar.gz.

File metadata

  • Download URL: dare_rf-1.1.4.tar.gz
  • Upload date:
  • Size: 1.2 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.0 CPython/3.9.19

File hashes

Hashes for dare_rf-1.1.4.tar.gz
Algorithm Hash digest
SHA256 5deeab6129cb4f6bc0989b6fff7d53eb329dd4055607df28c4f29f6f65e01764
MD5 e3fc52e3e08a575e323192b3f8528397
BLAKE2b-256 ca1561f6af29f5f70920bf42d6aa7f6bcb4abeb174b68fbaa53c39a167f6c8fb

See more details on using hashes here.

File details

Details for the file dare_rf-1.1.4-cp310-cp310-win_amd64.whl.

File metadata

  • Download URL: dare_rf-1.1.4-cp310-cp310-win_amd64.whl
  • Upload date:
  • Size: 1.8 MB
  • Tags: CPython 3.10, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.0 CPython/3.9.19

File hashes

Hashes for dare_rf-1.1.4-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 4c4ef9c9e3f94281edbe6d0def20d0a8fc1300853ec932f23ae649b7c9d8a57d
MD5 6ad4ea9f733026e64e9e6248ede2f33d
BLAKE2b-256 ed1af86525c3dd7536a3443b899d0a7293b0f4c030e5329aec67429a590e44e5

See more details on using hashes here.

File details

Details for the file dare_rf-1.1.4-cp310-cp310-win32.whl.

File metadata

  • Download URL: dare_rf-1.1.4-cp310-cp310-win32.whl
  • Upload date:
  • Size: 1.7 MB
  • Tags: CPython 3.10, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.0 CPython/3.9.19

File hashes

Hashes for dare_rf-1.1.4-cp310-cp310-win32.whl
Algorithm Hash digest
SHA256 ee94733936e33ffb74841883e6f6a111dfa5645800e19535847c3ad46666df7a
MD5 81e7dff34c7d5b74ae8cc1e2b7fe1cfa
BLAKE2b-256 da12921ea3b1a1087fadd873162a60a28f485aa7299ad4e38b27d643e826cccc

See more details on using hashes here.

File details

Details for the file dare_rf-1.1.4-cp310-cp310-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for dare_rf-1.1.4-cp310-cp310-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 e85803317ec7f7042ad8b030b343c95a8352924f198febcc2413f0f1e0e3df23
MD5 9434e20ee2a710a5e1e91be87f2f5963
BLAKE2b-256 6edece7714108623faa8d1ac6dd60604d8a3223e7e27a85c01a7a1dcd9e3a90c

See more details on using hashes here.

File details

Details for the file dare_rf-1.1.4-cp310-cp310-musllinux_1_1_i686.whl.

File metadata

File hashes

Hashes for dare_rf-1.1.4-cp310-cp310-musllinux_1_1_i686.whl
Algorithm Hash digest
SHA256 7d9042cff6731e4ec7d04f74990e5355b9b20a09801102b56a18b459c953bc82
MD5 2479f9fa3c6568a24308d2f412e2ca7d
BLAKE2b-256 a0a0493f32f6219e30a43a47f9856e75f3619dea5f79896f8a39248006e45bff

See more details on using hashes here.

File details

Details for the file dare_rf-1.1.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for dare_rf-1.1.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 6423f3998ca16a63634460cb8141794db9119e962ddfe07f3e85d88ccbf7665c
MD5 df2f308472f84014301c402a5ac702d1
BLAKE2b-256 1b7981d2591a6332e43991ccaae90b732d27c6fa03349a06c085e32f03f05ac9

See more details on using hashes here.

File details

Details for the file dare_rf-1.1.4-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for dare_rf-1.1.4-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 78b54907c2e221b350cbc32267277bdaf5a43d72a8a921ac8b4d4407b10e7f31
MD5 a219e36ae2c2f4bed0770210169dfcc0
BLAKE2b-256 0f4699a68be012e7f57ac79f856683c6c771a4f076ef5080cf78c164362048b7

See more details on using hashes here.

File details

Details for the file dare_rf-1.1.4-cp310-cp310-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for dare_rf-1.1.4-cp310-cp310-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 4fc19ab18b3895118208a070b2b3195160179f5bc9cecc750aac20203d2cd17b
MD5 ebbf3d901019c5667a2036c905ff678b
BLAKE2b-256 001612265c922d395f899935cdd3ae956b7feb8fc91264b295e2cfc5d056063a

See more details on using hashes here.

File details

Details for the file dare_rf-1.1.4-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: dare_rf-1.1.4-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 1.8 MB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.0 CPython/3.9.19

File hashes

Hashes for dare_rf-1.1.4-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 2b9b59cb27fa16161419c2ff14757422dee4f6029ac5bc5bb2fc7d91f1c3a4e9
MD5 40b3c902edcbbe9a846db2b07e611774
BLAKE2b-256 26ad884b957b861453375cfb5a3bf5de6fbf7ac1b9428bb5e39990941a71920d

See more details on using hashes here.

File details

Details for the file dare_rf-1.1.4-cp39-cp39-win32.whl.

File metadata

  • Download URL: dare_rf-1.1.4-cp39-cp39-win32.whl
  • Upload date:
  • Size: 1.7 MB
  • Tags: CPython 3.9, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.0 CPython/3.9.19

File hashes

Hashes for dare_rf-1.1.4-cp39-cp39-win32.whl
Algorithm Hash digest
SHA256 627eb96ba995f932b79a8edc2ea815ba17e2bb21deccac32f235d31fc1cf6f05
MD5 efd7d7642283a6eccce94564ec396510
BLAKE2b-256 8454bfe26be4ff9f40cc64eaee6ce78e7c2e55ded057533304fbbadb7128ffdf

See more details on using hashes here.

File details

Details for the file dare_rf-1.1.4-cp39-cp39-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for dare_rf-1.1.4-cp39-cp39-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 538b446e7492a6a0bffd74a52ed7f18d8712a36c90187441a6dabdbcad6f0992
MD5 7758743aa62dcb62eb2b4c577093aee1
BLAKE2b-256 624bf422dd6f931d46c082a2f83e2f0b7feb01dd938ab0869e200be9fbefe1fa

See more details on using hashes here.

File details

Details for the file dare_rf-1.1.4-cp39-cp39-musllinux_1_1_i686.whl.

File metadata

File hashes

Hashes for dare_rf-1.1.4-cp39-cp39-musllinux_1_1_i686.whl
Algorithm Hash digest
SHA256 e44c69f360870acdec240f2c0f1bcded5f90617c2ebabc494668f659be1b92a8
MD5 70050dc1e53f8110e3e683b7016166d1
BLAKE2b-256 d65225cde26949824c5ffd7b5e22c03a8f67e63cc7cd511585343555a9dc3e44

See more details on using hashes here.

File details

Details for the file dare_rf-1.1.4-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for dare_rf-1.1.4-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 3cda6949053962a3b10861a9f1fbe593de8b517786ec01d7a36214658d6cf8f6
MD5 1aebe8d48bd98daba383a6f633d558b7
BLAKE2b-256 3e3723993984a6cccba1fbc6b2eba8331f77be4130397001b948e68c4ff911dc

See more details on using hashes here.

File details

Details for the file dare_rf-1.1.4-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for dare_rf-1.1.4-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 c2c7dfffaf3139e61d7308a6f0f564b2361d47b16b0c2854c4d8aa21afaeb8e2
MD5 2e26470851cd9b953add1c2be9acb28f
BLAKE2b-256 b209620ae85b3647a31c29962ec8f613544cedee303715e9ab7cc08ae98755d1

See more details on using hashes here.

File details

Details for the file dare_rf-1.1.4-cp39-cp39-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for dare_rf-1.1.4-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 518b9bcdda1c61615a120128b8cd5bd2b57cc226f53a122d300c650ccf57f73e
MD5 8b99494ea3412762570f975dc0b3d7d4
BLAKE2b-256 cccdd4b33e803700008f3fda4db9a5ce83dc490a937cdeb2e1e671eaf2129396

See more details on using hashes here.

File details

Details for the file dare_rf-1.1.4-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: dare_rf-1.1.4-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 1.8 MB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.0 CPython/3.9.19

File hashes

Hashes for dare_rf-1.1.4-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 b50f44588464436f0df617d6d15ce1af152a00bcd595c29f5f1d35665491b0ce
MD5 82dabbaabe292faac6f701545790d7ca
BLAKE2b-256 3047834ad6299a7cb4a7da43400d67639d8027d1c9ee3ce448d622575f48bc10

See more details on using hashes here.

File details

Details for the file dare_rf-1.1.4-cp38-cp38-win32.whl.

File metadata

  • Download URL: dare_rf-1.1.4-cp38-cp38-win32.whl
  • Upload date:
  • Size: 1.7 MB
  • Tags: CPython 3.8, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.0 CPython/3.9.19

File hashes

Hashes for dare_rf-1.1.4-cp38-cp38-win32.whl
Algorithm Hash digest
SHA256 af3e9dcffab4fc6c8410a2f249277ea8d88b8a40b5509e9ad168eda5f9d9356d
MD5 53fdf6aadb7e03eb78a51ff1847e2f3f
BLAKE2b-256 8070db109fac3ab330d95e8c7cb9d5d7dc82fcbac2f99e29ed7849a8bc424025

See more details on using hashes here.

File details

Details for the file dare_rf-1.1.4-cp38-cp38-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for dare_rf-1.1.4-cp38-cp38-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 41f87a272457ed65f3d79a8b708a22ffd3b96a59f7b94bbf61399bd2dac0d07e
MD5 1f2a361a3f7e67547b233c127681231c
BLAKE2b-256 b3da7b3a65f35de2f1dc949398a61a25a0b8cb87023fa31f5e646f190c08d712

See more details on using hashes here.

File details

Details for the file dare_rf-1.1.4-cp38-cp38-musllinux_1_1_i686.whl.

File metadata

File hashes

Hashes for dare_rf-1.1.4-cp38-cp38-musllinux_1_1_i686.whl
Algorithm Hash digest
SHA256 71a3c39e05ea549560193245783004c5e709b110953c47b4f2916672032e946a
MD5 f8899bcab18b08aaed032d9d8a0dc3d0
BLAKE2b-256 e20b4c147296f9529c3423a4f69759c4f512c9f38757de6d8b1e007dabc88ebf

See more details on using hashes here.

File details

Details for the file dare_rf-1.1.4-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for dare_rf-1.1.4-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 4880e375e946de2123b5d98d6f931fd82b5321d91f44438cd9a04f3bb5fded0e
MD5 b8b35b252a5ce3da1eea1dcbe6f4ffee
BLAKE2b-256 458c3fb00e5e0a20ff761cf7b5a5221ad2d194f05afcbce33e2b5d381c38b6d1

See more details on using hashes here.

File details

Details for the file dare_rf-1.1.4-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for dare_rf-1.1.4-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 33792e41b660970d2557eccbae4cda4a6ceafca501e15eab9711dd791c124d8b
MD5 9acb8334f0997943cc5164829d2e6a2a
BLAKE2b-256 75927629017153bf24b6716b23583088ec747a18b62ad8b6f34d615d43ce125a

See more details on using hashes here.

File details

Details for the file dare_rf-1.1.4-cp38-cp38-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for dare_rf-1.1.4-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 90d92f61173f7c75054e56673a7efdfd52dae4aae282c9d2167ddaafe94462ed
MD5 3fb6bc3add7623a5bdc85c6f147fcf7c
BLAKE2b-256 ce1c8516fd366e89a986171fa42502bee0cef3b4292c6a6dfb71592a29ee6a5c

See more details on using hashes here.

File details

Details for the file dare_rf-1.1.4-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: dare_rf-1.1.4-cp37-cp37m-win_amd64.whl
  • Upload date:
  • Size: 1.8 MB
  • Tags: CPython 3.7m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.0 CPython/3.9.19

File hashes

Hashes for dare_rf-1.1.4-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 45ca2ab2363e14c8f0be401c26ffd8e94baf744b6917a450d62244d4f87a92ed
MD5 4f8c2cdb799aa09e417d05333180d9fd
BLAKE2b-256 40ac4bc16ac813ecd14583db0f41d2ec21dbd155206f4c0ed56345f0f289e50a

See more details on using hashes here.

File details

Details for the file dare_rf-1.1.4-cp37-cp37m-win32.whl.

File metadata

  • Download URL: dare_rf-1.1.4-cp37-cp37m-win32.whl
  • Upload date:
  • Size: 1.7 MB
  • Tags: CPython 3.7m, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.0 CPython/3.9.19

File hashes

Hashes for dare_rf-1.1.4-cp37-cp37m-win32.whl
Algorithm Hash digest
SHA256 8609ca2418c92f318fc3082561e4eaff81aa4cc545e03e26a7bc6a640457386c
MD5 7c97263361721aa5186a57d2d315e2e7
BLAKE2b-256 b7530b63fdfa9dc9be5fd84de828efda2c0524e402240eb4119d58df6d82c38a

See more details on using hashes here.

File details

Details for the file dare_rf-1.1.4-cp37-cp37m-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for dare_rf-1.1.4-cp37-cp37m-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 98909b4cce2c97622f2a98d488e8f22ad10faafbc7f7226321ca583f5a3d6642
MD5 ac1316648c76ff82ce8b9a2a4bbdab9d
BLAKE2b-256 cc75674a815703dff85cd1a3d7656e50e4a43c011071378888ce4fbb14ef8338

See more details on using hashes here.

File details

Details for the file dare_rf-1.1.4-cp37-cp37m-musllinux_1_1_i686.whl.

File metadata

File hashes

Hashes for dare_rf-1.1.4-cp37-cp37m-musllinux_1_1_i686.whl
Algorithm Hash digest
SHA256 892536f373661025c567db17518dbb54e1f562cf4ebe466db769dac6f391df4f
MD5 a1f5773d836117a65842faa9ae1bf80a
BLAKE2b-256 ba27b6b07c96fc4164b28fbd9281bf456126be341e3b1b77bf0de1ca07d1c700

See more details on using hashes here.

File details

Details for the file dare_rf-1.1.4-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for dare_rf-1.1.4-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 91d214d6d0787abf030e8ea55cfc7a81034ad1d8242cf34fff375b6f0ca73a7b
MD5 b39b91e191ee0707e6fcb6424e681207
BLAKE2b-256 cd52747aea17cb9bf07598a5f6098c96f4d83d26d7db2541ae60e073865725fa

See more details on using hashes here.

File details

Details for the file dare_rf-1.1.4-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for dare_rf-1.1.4-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 3348a84092d0a3399584a60408b2b5348b45db6f5ced3fa0ac77a8c1244256c6
MD5 551c23b3b4b7b42f86d1a5791c00bb4e
BLAKE2b-256 f53e9ae85d00ae7a624cf43652edd57452e227ee04adba1c55324e6eab177ec0

See more details on using hashes here.

File details

Details for the file dare_rf-1.1.4-cp37-cp37m-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for dare_rf-1.1.4-cp37-cp37m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 ce0b6075cea15ba425d8928ac7501ab92214529919884c1e59a812ace2667ae7
MD5 dd272b45d24ad1e510426337324c2f30
BLAKE2b-256 3e8a4134383ed84830a02863b11d306fa33fba7c01676a75f00e5f1fc397047e

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