Skip to main content

Griddly Python Libraries

Project description

Griddly Python

This module contains all you need to run the Griddly AI research environment using python.

Installation

Currently the library supports any python > 3.6. It is recommended to use a conda environment:

conda create --name griddly_env python=3.7
conda activate griddly_env
pip install griddly

Usage

Full documentation can be found here: https://griddly.readthedocs.org

Project details


Release history Release notifications | RSS feed

Download files

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

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

griddly-1.6.1-cp310-cp310-win_amd64.whl (7.0 MB view details)

Uploaded CPython 3.10Windows x86-64

griddly-1.6.1-cp310-cp310-manylinux_2_28_x86_64.whl (7.3 MB view details)

Uploaded CPython 3.10manylinux: glibc 2.28+ x86-64

griddly-1.6.1-cp310-cp310-macosx_10_15_x86_64.whl (7.2 MB view details)

Uploaded CPython 3.10macOS 10.15+ x86-64

griddly-1.6.1-cp39-cp39-win_amd64.whl (7.0 MB view details)

Uploaded CPython 3.9Windows x86-64

griddly-1.6.1-cp39-cp39-manylinux_2_28_x86_64.whl (7.3 MB view details)

Uploaded CPython 3.9manylinux: glibc 2.28+ x86-64

griddly-1.6.1-cp39-cp39-macosx_10_15_x86_64.whl (7.2 MB view details)

Uploaded CPython 3.9macOS 10.15+ x86-64

griddly-1.6.1-cp38-cp38-win_amd64.whl (7.0 MB view details)

Uploaded CPython 3.8Windows x86-64

griddly-1.6.1-cp38-cp38-manylinux_2_28_x86_64.whl (7.3 MB view details)

Uploaded CPython 3.8manylinux: glibc 2.28+ x86-64

griddly-1.6.1-cp38-cp38-macosx_10_15_x86_64.whl (7.2 MB view details)

Uploaded CPython 3.8macOS 10.15+ x86-64

griddly-1.6.1-cp37-cp37m-win_amd64.whl (7.0 MB view details)

Uploaded CPython 3.7mWindows x86-64

griddly-1.6.1-cp37-cp37m-manylinux_2_28_x86_64.whl (7.3 MB view details)

Uploaded CPython 3.7mmanylinux: glibc 2.28+ x86-64

griddly-1.6.1-cp37-cp37m-macosx_10_15_x86_64.whl (7.2 MB view details)

Uploaded CPython 3.7mmacOS 10.15+ x86-64

File details

Details for the file griddly-1.6.1-cp310-cp310-win_amd64.whl.

File metadata

  • Download URL: griddly-1.6.1-cp310-cp310-win_amd64.whl
  • Upload date:
  • Size: 7.0 MB
  • Tags: CPython 3.10, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.10.8

File hashes

Hashes for griddly-1.6.1-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 d5df474b4a8c3f4ef4d74901088b52178b50a807a5499e5ec3fde10b6402d5d2
MD5 a37bd9b9e7b54fd0708ab142ae9be883
BLAKE2b-256 79b1b2fa6b77e835a9ce7dfce568aa3726d427d6746e21f18d7e966ea317fc3d

See more details on using hashes here.

File details

Details for the file griddly-1.6.1-cp310-cp310-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for griddly-1.6.1-cp310-cp310-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 d1983eada86040e48246a71ff2da265dc8eff50ab72a1a1574984fe77aeaf2ee
MD5 2cfff1f0b8cdd2deb7b6a5303db57fd4
BLAKE2b-256 35707b67bcf3d198b749e65d8665c934ca19c77e4c0cc88ba0851a4195d807c1

See more details on using hashes here.

File details

Details for the file griddly-1.6.1-cp310-cp310-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for griddly-1.6.1-cp310-cp310-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 b0817ac3ceb528d49c8c18c9f0a3bbf34b26287c55daadc98c0ea5fcc5f297f9
MD5 997af82f7d4387d5ab50ab3da4710f4d
BLAKE2b-256 09c0a70f1ddada153fa43b1f9a9bc87086fb4397b7fec248a98bd09c5b41f5db

See more details on using hashes here.

File details

Details for the file griddly-1.6.1-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: griddly-1.6.1-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 7.0 MB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.13

File hashes

Hashes for griddly-1.6.1-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 2f05523b78865cb8461501fa7dfcf40f2e5069d2cda805206750fb416b08ef95
MD5 ac13481556916be1e6478d9fa854343f
BLAKE2b-256 5813903a9db3c8b8c151f7ff37e13b08a498da84d11a64e87df5a921e9e671d2

See more details on using hashes here.

File details

Details for the file griddly-1.6.1-cp39-cp39-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for griddly-1.6.1-cp39-cp39-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 ebe87fddc65f4a20cfe73030611dc414cdb5089c4c42726e01a5e8e215ac53ee
MD5 907dfb1edc0f4541b6783f79c1ca7d77
BLAKE2b-256 8b0f04c8380e9543844c6807f492130a08a65de6460d42a4d2f3ef9b150b0845

See more details on using hashes here.

File details

Details for the file griddly-1.6.1-cp39-cp39-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for griddly-1.6.1-cp39-cp39-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 2a1dface635c115f1132784fe7d5fabda880999a500de04a408d883730542638
MD5 f02356f907f96e85c70d8936b48163a2
BLAKE2b-256 da45ec1523ca7690d9c0fbba28d8573c694b7ea5180fb60e4d1601ff4febafc5

See more details on using hashes here.

File details

Details for the file griddly-1.6.1-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: griddly-1.6.1-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 7.0 MB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.8.10

File hashes

Hashes for griddly-1.6.1-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 9bbf982305733440357335a685901a13859276ae3efac58858e5a5d7ce1f7866
MD5 c5f9d67c98b19c5ad7120a7956a2737d
BLAKE2b-256 080e0efc5b89fad9a56158bed9b4125bb96cddc7e99b5bd0e6f18fcb74b94847

See more details on using hashes here.

File details

Details for the file griddly-1.6.1-cp38-cp38-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for griddly-1.6.1-cp38-cp38-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 c360d1386333f1b1c9754087807ad99a4b788c810579d56cd935b1136002aa60
MD5 1ae71741d456d80a3ee8ca4464494dad
BLAKE2b-256 beae0ff6970aa69ca528133868efd21abd1727757b2923d6a87f7451bd1098ba

See more details on using hashes here.

File details

Details for the file griddly-1.6.1-cp38-cp38-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for griddly-1.6.1-cp38-cp38-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 94c0a31ddb0cf611d8ebc45d51a6c336561f62b3b7317c1f62d19f5ad9ad6d20
MD5 886657e277c23bcb9bd2ca35f961dc55
BLAKE2b-256 32ff00c41ffbce55a68fb091ccf087b780ee58e1d20b478690643e3606ee9dd9

See more details on using hashes here.

File details

Details for the file griddly-1.6.1-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: griddly-1.6.1-cp37-cp37m-win_amd64.whl
  • Upload date:
  • Size: 7.0 MB
  • Tags: CPython 3.7m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.7.9

File hashes

Hashes for griddly-1.6.1-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 62b3434a091f0d19749c04d9c27b8ed77d9773bd9fde020cfbf1ee72eaee9497
MD5 8595d3732948469aa1372d986a69aa8e
BLAKE2b-256 eab8fa09321947e63639e1513ed88dd2633d7cf09158ec41ace86240d0929307

See more details on using hashes here.

File details

Details for the file griddly-1.6.1-cp37-cp37m-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for griddly-1.6.1-cp37-cp37m-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 2c5d83bc1e15bc1a73db1749954d5b07fdb22b50cc2b51fef591af8bb0b1389e
MD5 c313703ba6c10ee865e22ef67dcb522d
BLAKE2b-256 90702adb31fadb7c41180ba6f9983ad1f74d57329c7533cbb064f97748a9617b

See more details on using hashes here.

File details

Details for the file griddly-1.6.1-cp37-cp37m-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for griddly-1.6.1-cp37-cp37m-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 1e30145f106743e43267f9a75ff1b3e30999ec560d5451bac46a79f4f2ca9af2
MD5 ae9437d1415413eae6a598ecab30a282
BLAKE2b-256 c823d3ca50f174aa60a5311303d1cc429fef6086277e6308ee71068348412971

See more details on using hashes here.

Supported by

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