A python module desgined for RL logging, monitoring and experiments managing.

Navigation

Verified details

These details have been verified by PyPI
Maintainers
Avatar for typoverflow from gravatar.com typoverflow

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: MIT
  • Author: typoverflow
  • Requires: Python >=3.7

Project description

UtilsRL

UtilsRL is a reinforcement learning utility python package, which is designed for fast integration into other RL projects. Despite its lightweightness, it still provides a full set of functions needed for RL algorithms development.

Currently UtilsRL is maintained by researchers from LAMDA-RL group. Any bug report / feature request / improvement is appreciated.

Installation

You can install this package directly from pypi:

pip install UtilsRL

After installation, you may still need to configure some other dependencies based on your platform, such as PyTorch.

Features & Usage

See the documentation for details.

Acknowledgements

We took inspiration for module design from tianshou and Polixir OfflineRL.

We also thank @YuRuiii, @cmj2020, @paperplane03 and @momanto for their participation in code testing and performance benchmarking.

Project details

Verified details

These details have been verified by PyPI
Maintainers
Avatar for typoverflow from gravatar.com typoverflow

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: MIT
  • Author: typoverflow
  • Requires: Python >=3.7

Release history Release notifications | RSS feed

0.6.11

0.6.10

0.6.9

0.6.8

0.6.7

0.6.6

0.6.5

0.6.4

0.6.3

0.6.2

0.6.1

0.6.0

0.5.9

0.5.8

0.5.7

0.5.6

0.5.5

0.5.4

0.5.3

0.5.2

0.5.1

0.5.0

0.5.0b3 pre-release

0.5.0b2 pre-release

0.5.0b1 pre-release

0.5.0b0 pre-release

This version

0.5.0a0 pre-release

0.4.8

0.4.7

0.4.6

0.4.5

0.4.4

0.4.3

0.4.2

0.4.1

0.4.0

0.3.13

0.3.12

0.3.11

0.3.10

0.3.8

0.3.7

0.3.6

0.3.5

0.3.4

0.3.3

0.3.2

0.3.1

0.3.0

0.2.4

0.2.3

0.2.2

0.2.1

0.2.0

0.1.1

0.1.0

0.0.2

0.0.1

Download files

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

Source Distribution

UtilsRL-0.5.0a0.tar.gz (37.7 kB view details)

Uploaded Source

Built Distributions

UtilsRL-0.5.0a0-pp39-pypy39_pp73-win_amd64.whl (123.5 kB view details)

Uploaded PyPy Windows x86-64

UtilsRL-0.5.0a0-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (160.6 kB view details)

Uploaded PyPy manylinux: glibc 2.17+ x86-64

UtilsRL-0.5.0a0-pp39-pypy39_pp73-manylinux_2_17_i686.manylinux2014_i686.whl (168.6 kB view details)

Uploaded PyPy manylinux: glibc 2.17+ i686

UtilsRL-0.5.0a0-pp38-pypy38_pp73-win_amd64.whl (123.4 kB view details)

Uploaded PyPy Windows x86-64

UtilsRL-0.5.0a0-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (162.3 kB view details)

Uploaded PyPy manylinux: glibc 2.17+ x86-64

UtilsRL-0.5.0a0-pp38-pypy38_pp73-manylinux_2_17_i686.manylinux2014_i686.whl (168.5 kB view details)

Uploaded PyPy manylinux: glibc 2.17+ i686

UtilsRL-0.5.0a0-pp37-pypy37_pp73-win_amd64.whl (123.4 kB view details)

Uploaded PyPy Windows x86-64

UtilsRL-0.5.0a0-pp37-pypy37_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (163.1 kB view details)

Uploaded PyPy manylinux: glibc 2.17+ x86-64

UtilsRL-0.5.0a0-pp37-pypy37_pp73-manylinux_2_17_i686.manylinux2014_i686.whl (169.2 kB view details)

Uploaded PyPy manylinux: glibc 2.17+ i686

UtilsRL-0.5.0a0-cp310-cp310-win_amd64.whl (124.3 kB view details)

Uploaded CPython 3.10 Windows x86-64

UtilsRL-0.5.0a0-cp310-cp310-win32.whl (112.6 kB view details)

Uploaded CPython 3.10 Windows x86

UtilsRL-0.5.0a0-cp310-cp310-musllinux_1_1_x86_64.whl (682.6 kB view details)

Uploaded CPython 3.10 musllinux: musl 1.1+ x86-64

UtilsRL-0.5.0a0-cp310-cp310-musllinux_1_1_i686.whl (743.7 kB view details)

Uploaded CPython 3.10 musllinux: musl 1.1+ i686

UtilsRL-0.5.0a0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (167.7 kB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ x86-64

UtilsRL-0.5.0a0-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl (175.0 kB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ i686

UtilsRL-0.5.0a0-cp39-cp39-win_amd64.whl (123.7 kB view details)

Uploaded CPython 3.9 Windows x86-64

UtilsRL-0.5.0a0-cp39-cp39-win32.whl (112.8 kB view details)

Uploaded CPython 3.9 Windows x86

UtilsRL-0.5.0a0-cp39-cp39-musllinux_1_1_x86_64.whl (683.0 kB view details)

Uploaded CPython 3.9 musllinux: musl 1.1+ x86-64

UtilsRL-0.5.0a0-cp39-cp39-musllinux_1_1_i686.whl (743.9 kB view details)

Uploaded CPython 3.9 musllinux: musl 1.1+ i686

UtilsRL-0.5.0a0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (167.4 kB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ x86-64

UtilsRL-0.5.0a0-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl (175.2 kB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ i686

UtilsRL-0.5.0a0-cp38-cp38-win_amd64.whl (124.3 kB view details)

Uploaded CPython 3.8 Windows x86-64

UtilsRL-0.5.0a0-cp38-cp38-win32.whl (112.7 kB view details)

Uploaded CPython 3.8 Windows x86

UtilsRL-0.5.0a0-cp38-cp38-musllinux_1_1_x86_64.whl (682.5 kB view details)

Uploaded CPython 3.8 musllinux: musl 1.1+ x86-64

UtilsRL-0.5.0a0-cp38-cp38-musllinux_1_1_i686.whl (743.0 kB view details)

Uploaded CPython 3.8 musllinux: musl 1.1+ i686

UtilsRL-0.5.0a0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (167.7 kB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ x86-64

UtilsRL-0.5.0a0-cp38-cp38-manylinux_2_17_i686.manylinux2014_i686.whl (174.9 kB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ i686

UtilsRL-0.5.0a0-cp37-cp37m-win_amd64.whl (124.2 kB view details)

Uploaded CPython 3.7m Windows x86-64

UtilsRL-0.5.0a0-cp37-cp37m-win32.whl (113.5 kB view details)

Uploaded CPython 3.7m Windows x86

UtilsRL-0.5.0a0-cp37-cp37m-musllinux_1_1_x86_64.whl (685.8 kB view details)

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

UtilsRL-0.5.0a0-cp37-cp37m-musllinux_1_1_i686.whl (747.1 kB view details)

Uploaded CPython 3.7m musllinux: musl 1.1+ i686

UtilsRL-0.5.0a0-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (168.8 kB view details)

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

UtilsRL-0.5.0a0-cp37-cp37m-manylinux_2_17_i686.manylinux2014_i686.whl (177.0 kB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ i686

File details

Details for the file UtilsRL-0.5.0a0.tar.gz.

File metadata

  • Download URL: UtilsRL-0.5.0a0.tar.gz
  • Upload date:
  • Size: 37.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.11.1

File hashes

Hashes for UtilsRL-0.5.0a0.tar.gz
Algorithm Hash digest
SHA256 250c4dfa0c6d8deb67de0585849edc78490fd6d3f69eeff6fba339eb9883cc08
MD5 a77ae94dae2027943e952f87ad1746b1
BLAKE2b-256 9051b88140ec5436f4e9f46a45c88b3657eabdf85ee89431528fb938ae154ac5

See more details on using hashes here.

File details

Details for the file UtilsRL-0.5.0a0-pp39-pypy39_pp73-win_amd64.whl.

File metadata

File hashes

Hashes for UtilsRL-0.5.0a0-pp39-pypy39_pp73-win_amd64.whl
Algorithm Hash digest
SHA256 5611995fc4333e97cbf6834e9a2f0aa1468f3b8ca63fba17dfa103be6161f969
MD5 e3cae4adb28b0f8b0cb4d323cd69e1c9
BLAKE2b-256 095033e1b3236c09f12a4425b501028f8411733b8c554dd1cc0a667289e8e4bc

See more details on using hashes here.

File details

Details for the file UtilsRL-0.5.0a0-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for UtilsRL-0.5.0a0-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 1e212d704d9ee01d6c6d8b3201170b98597fe8b5dc8b632756c8c31aa31aa4e0
MD5 59b63b90a9a0de15fa1f255921bc8ea5
BLAKE2b-256 1b70dade3ff442c63152befd8fad39f661dddf5ba42456869d5de4719c5158b3

See more details on using hashes here.

File details

Details for the file UtilsRL-0.5.0a0-pp39-pypy39_pp73-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for UtilsRL-0.5.0a0-pp39-pypy39_pp73-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 e1999375df5c6e7daca9c724a047ab004b0be414f2adf314373d2a2a31977f18
MD5 0a3b140d68c1b2f7f912696567e46f9b
BLAKE2b-256 843391c453fb21fefd1e5cf98e007cf7fb223a4a6acbfd181ceca85bd78bb7f6

See more details on using hashes here.

File details

Details for the file UtilsRL-0.5.0a0-pp38-pypy38_pp73-win_amd64.whl.

File metadata

File hashes

Hashes for UtilsRL-0.5.0a0-pp38-pypy38_pp73-win_amd64.whl
Algorithm Hash digest
SHA256 6c8c943b2d30968a355f133d04bd51972444bc9f77525ee987a21d6f7e57e50d
MD5 62dbc85970b985b1ac0c9f932da286ad
BLAKE2b-256 0bab942a66be62ab3932b3ddc2b3c7a1216821463421aa7f3cf40fd87ff6d09e

See more details on using hashes here.

File details

Details for the file UtilsRL-0.5.0a0-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for UtilsRL-0.5.0a0-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 5b4cfe42b6457c758eef4c0668d6ffb5b5c407ea99462957d6eaeed7dd50a9c5
MD5 1d509fac10a104c00e1c57c1883ee903
BLAKE2b-256 95796bd41984ecd7ba533cfb583bc6ba6d7988c065760a74522e12c6bb5427fc

See more details on using hashes here.

File details

Details for the file UtilsRL-0.5.0a0-pp38-pypy38_pp73-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for UtilsRL-0.5.0a0-pp38-pypy38_pp73-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 a21320b14732dce36d95ab13f050d2e023d0a46bbfaef6fc32102d2e33d2b5c9
MD5 5dd95671f0336800f5fdd73d2ee88c32
BLAKE2b-256 cf544541175e42cab8696a985a1a4da87217112f84c99c7e3c8f27cdf4ee8385

See more details on using hashes here.

File details

Details for the file UtilsRL-0.5.0a0-pp37-pypy37_pp73-win_amd64.whl.

File metadata

File hashes

Hashes for UtilsRL-0.5.0a0-pp37-pypy37_pp73-win_amd64.whl
Algorithm Hash digest
SHA256 4e41247c4557d4a0a35091dffa02e5315d5a8e7199720a30186bde6ec5e78f5c
MD5 0be908f780a89567387e4716dcebde87
BLAKE2b-256 63526cdb5b2b37f545c389aaf443072353cf8ab2abd63057cfa2257cfa6da0ac

See more details on using hashes here.

File details

Details for the file UtilsRL-0.5.0a0-pp37-pypy37_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for UtilsRL-0.5.0a0-pp37-pypy37_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 4f2a936c18c05e10e4e1e43bacbe359bf8102935256d2d9d98c2a7f6cc4883e2
MD5 8267c5206eea1d3a004b85a1fa2f7724
BLAKE2b-256 03b00b1f669752a771261f2f537d173e2276367930ccac37ddce961b63e4d917

See more details on using hashes here.

File details

Details for the file UtilsRL-0.5.0a0-pp37-pypy37_pp73-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for UtilsRL-0.5.0a0-pp37-pypy37_pp73-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 10fe12a7ea4bbea61ef60b3fe9409be6d1a473f588e969bd547f73657a2382ab
MD5 aca692c6b146fa3a036741e8e2be339a
BLAKE2b-256 8bcd0645b565f533b80e647069914139c55508012e0ca32a94874087ba159e5a

See more details on using hashes here.

File details

Details for the file UtilsRL-0.5.0a0-cp310-cp310-win_amd64.whl.

File metadata

File hashes

Hashes for UtilsRL-0.5.0a0-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 04d5dff77e4f770f0ce2f68afccce79ee243f0d960b9ec6643ea525040246ac2
MD5 19cf2546839ae650f6f2254128e4f593
BLAKE2b-256 1b2e407727cd1884e353d38264833c66b59a4af2a8b0bccb07847ddde5e84d9e

See more details on using hashes here.

File details

Details for the file UtilsRL-0.5.0a0-cp310-cp310-win32.whl.

File metadata

  • Download URL: UtilsRL-0.5.0a0-cp310-cp310-win32.whl
  • Upload date:
  • Size: 112.6 kB
  • Tags: CPython 3.10, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.11.1

File hashes

Hashes for UtilsRL-0.5.0a0-cp310-cp310-win32.whl
Algorithm Hash digest
SHA256 3dd3e525f8928f6a0151700a4b5b54930d1a0e78098339c1f9f014e7f7824139
MD5 38964e9a45822aa80168516f28fa084a
BLAKE2b-256 2c39725cd4e553c740bb1a4614495632ab18dc67cf10421d697e86427bfbe223

See more details on using hashes here.

File details

Details for the file UtilsRL-0.5.0a0-cp310-cp310-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for UtilsRL-0.5.0a0-cp310-cp310-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 ada7bbd9845e7604d4673637f78f1a7d0c0a8071ccaca5b3dc1dada4dfc003fa
MD5 353d593df7c8e86787c9662e2279ad69
BLAKE2b-256 27136c749674ca101cc0569eda1d2adcc9ad6b4f8712fd2a6ec3cd88bcc80dc0

See more details on using hashes here.

File details

Details for the file UtilsRL-0.5.0a0-cp310-cp310-musllinux_1_1_i686.whl.

File metadata

File hashes

Hashes for UtilsRL-0.5.0a0-cp310-cp310-musllinux_1_1_i686.whl
Algorithm Hash digest
SHA256 d3a900594de6eef78da183d618a37b020de052257469771b51e7e759a2f17fcd
MD5 5eb19b2db012c2d77ad0582631b890e0
BLAKE2b-256 9dbf12e33f8ea892aff2969c47bfe1c2dc83ec501bd75063f54e985ea4618574

See more details on using hashes here.

File details

Details for the file UtilsRL-0.5.0a0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for UtilsRL-0.5.0a0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 3c4573f360224af07b76ec3b4bf2a61532fb81d83afeaf7f83ec9177ce88ce13
MD5 41b51acc747baec3d681c54b87522170
BLAKE2b-256 c1d08b5409f7b6d409941e733271affc22904b9cf04bb3e48fa562ebae6d3571

See more details on using hashes here.

File details

Details for the file UtilsRL-0.5.0a0-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for UtilsRL-0.5.0a0-cp310-cp310-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 11c183cd2ba30f0ec57309a4cac2728c02bf73ee81b4dc592f8cc0cfdd04f063
MD5 f30f08a7f161f31ee3381199d6c4d3c9
BLAKE2b-256 a7c5a5949250436acff93b2d8e7795d7e1ba57435e2e23124e94b0c711878bed

See more details on using hashes here.

File details

Details for the file UtilsRL-0.5.0a0-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: UtilsRL-0.5.0a0-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 123.7 kB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.11.1

File hashes

Hashes for UtilsRL-0.5.0a0-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 0dc95de8db864452d2ee46397eb95da29771e38b550878be58eeaea858857f2b
MD5 b14af3482ef68c72b35891ab1e6cdf34
BLAKE2b-256 7e4354852196d45fe6c4079d2ab5100c7e521fe15d8e4c57b970806bb88d587b

See more details on using hashes here.

File details

Details for the file UtilsRL-0.5.0a0-cp39-cp39-win32.whl.

File metadata

  • Download URL: UtilsRL-0.5.0a0-cp39-cp39-win32.whl
  • Upload date:
  • Size: 112.8 kB
  • Tags: CPython 3.9, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.11.1

File hashes

Hashes for UtilsRL-0.5.0a0-cp39-cp39-win32.whl
Algorithm Hash digest
SHA256 6ee2c80d35f23152663b121009ce1aa9e8a3cf7575c5f4a27bc436a2d4399fa1
MD5 68b3c1f60ee6726a7d478f3114be49f3
BLAKE2b-256 9c09db229c8d6fc3ed1442987a0a5e166003cb23987911dc0399bf0c73447c96

See more details on using hashes here.

File details

Details for the file UtilsRL-0.5.0a0-cp39-cp39-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for UtilsRL-0.5.0a0-cp39-cp39-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 43c3a15054fa7dcc267323e19281ea548f5e47eba8ef70adb471076916ea2465
MD5 4e8c7d648d1a528aebd6b54a3d18e68b
BLAKE2b-256 388c7e4a38ab2541b607dc077fe1484c4bbe41d2112e2238077477f10bb24087

See more details on using hashes here.

File details

Details for the file UtilsRL-0.5.0a0-cp39-cp39-musllinux_1_1_i686.whl.

File metadata

File hashes

Hashes for UtilsRL-0.5.0a0-cp39-cp39-musllinux_1_1_i686.whl
Algorithm Hash digest
SHA256 56717299352a655f18b2d1b3d292cfebee589c69338bc01131e88d44cf92366f
MD5 fae413be298ded77c332677bf67d2c11
BLAKE2b-256 483017ae672ec27df217e7a98789e46cc50266eb16d9c11d84544184cd46ed46

See more details on using hashes here.

File details

Details for the file UtilsRL-0.5.0a0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for UtilsRL-0.5.0a0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 286291e2f9f4fc647fb93db021e8b966f3cf1256e853497f037ede70c09e9c0a
MD5 767522dc9014009e7cce1e0bc565bd98
BLAKE2b-256 c73d4a0ed364ea26e85f1ccb8851e3d76f9877b86529e713b09f6d1a74554938

See more details on using hashes here.

File details

Details for the file UtilsRL-0.5.0a0-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for UtilsRL-0.5.0a0-cp39-cp39-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 9cea0201657e1a7d03323229036ec25d509fde87bc4eb296686bf598db756626
MD5 82bef5949ccc8e31e3fb24ca2d5d96ac
BLAKE2b-256 028dc26de11ffde7555b264386ae04170f6324db7baa501979e581d9b3b9f7a6

See more details on using hashes here.

File details

Details for the file UtilsRL-0.5.0a0-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: UtilsRL-0.5.0a0-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 124.3 kB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.11.1

File hashes

Hashes for UtilsRL-0.5.0a0-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 80d3feb43a3eafed8fee32322907ff483468194ab8e391d3937a0a48a739ac98
MD5 2a9387a5008994485954bab1fedf7d42
BLAKE2b-256 dfab1de1eda2b2a77c1da8f8ef72a6dadb1cd98604c2b971c8d68afc932b2d4f

See more details on using hashes here.

File details

Details for the file UtilsRL-0.5.0a0-cp38-cp38-win32.whl.

File metadata

  • Download URL: UtilsRL-0.5.0a0-cp38-cp38-win32.whl
  • Upload date:
  • Size: 112.7 kB
  • Tags: CPython 3.8, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.11.1

File hashes

Hashes for UtilsRL-0.5.0a0-cp38-cp38-win32.whl
Algorithm Hash digest
SHA256 350c19454b477480a28d680ed5a665dc47e04e4bb37a9fe1113cf3206fbcc6a0
MD5 7e8eb7166ca934dedb8a444499e86423
BLAKE2b-256 cdefd3cae999d224591c039edf55aa109fa7c654c909d0b40d5c2a21559662df

See more details on using hashes here.

File details

Details for the file UtilsRL-0.5.0a0-cp38-cp38-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for UtilsRL-0.5.0a0-cp38-cp38-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 9da0aa6a1842b130fe8db4a7fbab390f3ed81f89da18529e547a1e15a85f2b96
MD5 75b0b3aee5c25dbfbda7b71cbb1672e0
BLAKE2b-256 135b1578a68400120a7c7a41559c0ed7826f101fd7d053f77d0c5601911a9cc0

See more details on using hashes here.

File details

Details for the file UtilsRL-0.5.0a0-cp38-cp38-musllinux_1_1_i686.whl.

File metadata

File hashes

Hashes for UtilsRL-0.5.0a0-cp38-cp38-musllinux_1_1_i686.whl
Algorithm Hash digest
SHA256 747bb4b5632f14fa2ba4f682eeb0cd4c3e0e7812a21aacf1688c6db29ae00f00
MD5 2c60493ecbce3c5e43c3109991ede7d2
BLAKE2b-256 3a48311919001c66271420b0f41479358cd61acce058b878a4f159797a5dbd66

See more details on using hashes here.

File details

Details for the file UtilsRL-0.5.0a0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for UtilsRL-0.5.0a0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 408203b39bc5f29e84e61d551a30238bb67aac7c0858d630e0cb3a1a6877c269
MD5 c2ae6f0168cb65edc64c6f712ed2ba4e
BLAKE2b-256 9f5c9bac57c73277367b25f17c1ad32217de2897f6a5d372cf3ef1d3643f3edc

See more details on using hashes here.

File details

Details for the file UtilsRL-0.5.0a0-cp38-cp38-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for UtilsRL-0.5.0a0-cp38-cp38-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 d35cecf5d5c154c079e9e97b5550f5d877696c1417665d8f334cc750c6cbda1e
MD5 37e2dc1157fbbc9131f530d64abbfc85
BLAKE2b-256 91fe527a9d71926ddccc59b84bfa30fc3f9da312adbcfc94f39bb2ba6ddb0c3f

See more details on using hashes here.

File details

Details for the file UtilsRL-0.5.0a0-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: UtilsRL-0.5.0a0-cp37-cp37m-win_amd64.whl
  • Upload date:
  • Size: 124.2 kB
  • Tags: CPython 3.7m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.11.1

File hashes

Hashes for UtilsRL-0.5.0a0-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 b02b8ef3d4c0e087e7b926fdfb837c6de44cd9e52705cbe281c79c8e2657cd9d
MD5 c2ad34c5b69720e9cff206493ca593d5
BLAKE2b-256 e915d21b3f6d3bae737368fc704b518d89182316c82a497186596f96c56b38d4

See more details on using hashes here.

File details

Details for the file UtilsRL-0.5.0a0-cp37-cp37m-win32.whl.

File metadata

  • Download URL: UtilsRL-0.5.0a0-cp37-cp37m-win32.whl
  • Upload date:
  • Size: 113.5 kB
  • Tags: CPython 3.7m, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.11.1

File hashes

Hashes for UtilsRL-0.5.0a0-cp37-cp37m-win32.whl
Algorithm Hash digest
SHA256 d6a7c497049222214d5c69b8f1372101dedb96349f61f40d45c20093e98aa5cc
MD5 5ce26330edf75b8a62a9fd4864634df3
BLAKE2b-256 56c4368c126250e23615b45ac87fcc8151943ffec32829c06e1a63eca0b36219

See more details on using hashes here.

File details

Details for the file UtilsRL-0.5.0a0-cp37-cp37m-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for UtilsRL-0.5.0a0-cp37-cp37m-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 ca13b6782cc8b1132b26902cb0c4773b938477000afdce29103becd341a21fcc
MD5 92e82584c18e434ef43072166768826c
BLAKE2b-256 2979d8525da2cfc70066d0d26530c7a8f811a5e646db1f31f1004be5ab18a2cd

See more details on using hashes here.

File details

Details for the file UtilsRL-0.5.0a0-cp37-cp37m-musllinux_1_1_i686.whl.

File metadata

File hashes

Hashes for UtilsRL-0.5.0a0-cp37-cp37m-musllinux_1_1_i686.whl
Algorithm Hash digest
SHA256 a92e99d15fd42fd91a0e2d613ec841641532fcc50facc1cc74b181663e8da9e9
MD5 d87a0ac3afdc58f398bc7ab1355a4524
BLAKE2b-256 90d2928fbea588ef83915c4457a1f2f6e589d8ff1748f9b1dc419a639a97aad7

See more details on using hashes here.

File details

Details for the file UtilsRL-0.5.0a0-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for UtilsRL-0.5.0a0-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 0d1328cae119497b6f1580b4b7a7310f42400e283eb6853efbf244b264e6682b
MD5 d195990448f0c0e99c6da7c14eb11e01
BLAKE2b-256 8353421a946a76fb9533f062f026481390797c3fb63bc903095d15c03654f5e9

See more details on using hashes here.

File details

Details for the file UtilsRL-0.5.0a0-cp37-cp37m-manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for UtilsRL-0.5.0a0-cp37-cp37m-manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 ce9b3858aaa6cef477312a63e634e6190fd4739e1bd338672070c289f0de8fa7
MD5 382acf38c15bca4c7bb4febd387ad3d1
BLAKE2b-256 6dc8ac65d74c46c6b47502c5a9298dec86585f28f057c368d689704c458bc037

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