mjx

Features

Mjx is a Japanese Mahjong (riichi Mahjong) simulator. Mjx works as a game server as Mjai, a popular Mahjong simulator, to evaluate Mahjong AIs but have additional features:

Fast (100x faster than Mjai)
Exact Tenhou compatibility (Mjx is validated with numerous Tenhou game logs)
Gym-like API
Easy distributed computing (available for large-scale RL and evaluation thanks to gRPC)
Mjai compatible (mjx_mjai_translater)
Beautiful visualization

mjx

Quick start

Google colab

Install

$ pip install mjx

Requirements. Mjx supports Python3.7 or later in Linux and macOS Intel (10.15 or later). Currently Windows and macOS Apple Silicon are NOT supported. Contributions for supporting Windows and macOS Apple Silicon are more than welcome!

Example

import mjx

agent = mjx.RandomAgent()
env = mjx.MjxEnv()
obs_dict = env.reset()
while not env.done():
  actions = {player_id: agent.act(obs)
    for player_id, obs in obs_dict.items()}
  obs_dict = env.step(actions)
returns = env.rewards()

Sever Usage

Server	Client
import random import mjx class RandomAgent(mjx.Agent): def __init__(self): super().__init__() # When you use neural network models # you may want to infer actions by batch def act_batch(self, observations): return [random.choice(obs.legal_actions()) for obs in observations] agent = RandomAgent() # act_batch is called instead of act agent.serve("127.0.0.1:8080", batch_size=8)	import mjx host="127.0.0.1:8080" mjx.run( {f"player_{i}": host for i in range(4)}, num_games=1000, num_parallels=16 )

Server

Client

import random
import mjx

class RandomAgent(mjx.Agent):
  def __init__(self):
    super().__init__()

  # When you use neural network models
  # you may want to infer actions by batch
  def act_batch(self, observations):
    return [random.choice(obs.legal_actions()) 
            for obs in observations]


agent = RandomAgent()
# act_batch is called instead of act
agent.serve("127.0.0.1:8080", batch_size=8)

import mjx

host="127.0.0.1:8080"

mjx.run(
  {f"player_{i}": host for i in range(4)},
  num_games=1000,
  num_parallels=16
)

How to develop

We recommend you to develop Mjx inside a container. Easiest way is open this repository from VsCode. Feel free to mention to @sotetsuk if you have any questions.

License

MIT

Metadata

Release files for mjx 0.1.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for mjx 0.1.0
File	Size	Uploaded
mjx-0.1.0.tar.gz	355.0 kB	Aug 23, 2022	Details

Built distributions (wheels)

Table of built distributions (wheels) for mjx 0.1.0
File	Interpreter	ABI	Platform	Reset
mjx-0.1.0-cp39-cp39-manylinux2014_x86_64.whl 16.0 MB Aug 23, 2022	CPython 3.9	CPython 3.9	Linux glibc 2.17+ x86-64	Details
mjx-0.1.0-cp39-cp39-manylinux2014_i686.whl 16.3 MB Aug 23, 2022	CPython 3.9	CPython 3.9	Linux glibc 2.17+ x86-32	Details
mjx-0.1.0-cp39-cp39-macosx_10_15_x86_64.whl 13.0 MB Aug 23, 2022	CPython 3.9	CPython 3.9	macOS 10.15+ x86-64	Details
mjx-0.1.0-cp38-cp38-manylinux2014_x86_64.whl 16.0 MB Aug 23, 2022	CPython 3.8	CPython 3.8	Linux glibc 2.17+ x86-64	Details
mjx-0.1.0-cp38-cp38-manylinux2014_i686.whl 16.3 MB Aug 23, 2022	CPython 3.8	CPython 3.8	Linux glibc 2.17+ x86-32	Details
mjx-0.1.0-cp38-cp38-macosx_10_15_x86_64.whl 13.0 MB Aug 23, 2022	CPython 3.8	CPython 3.8	macOS 10.15+ x86-64	Details
mjx-0.1.0-cp37-cp37m-manylinux2014_x86_64.whl 16.0 MB Aug 23, 2022	CPython 3.7	CPython 3.7 pymalloc	Linux glibc 2.17+ x86-64	Details
mjx-0.1.0-cp37-cp37m-manylinux2014_i686.whl 16.3 MB Aug 23, 2022	CPython 3.7	CPython 3.7 pymalloc	Linux glibc 2.17+ x86-32	Details
mjx-0.1.0-cp37-cp37m-macosx_10_15_x86_64.whl 13.0 MB Aug 23, 2022	CPython 3.7	CPython 3.7 pymalloc	macOS 10.15+ x86-64	Details

Total release size: 136.3 MB

Release files / mjx-0.1.0.tar.gz

Download URL	mjx-0.1.0.tar.gz
Size	355.0 kB
Tags	Source
SHA-256 checksum How to use checksums	`d20f66f8245ce093edb72dd23ec31f7a07c54ecb97040327db895692bffaae1d`
BLAKE2b-256 checksum How to use checksums	`824602410a5c43853f526bf41f5ee5bf8244d9dca88f9925ffdb8dab9ce86bbb`
Upload date	Aug 23, 2022
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/4.0.1 CPython/3.9.13`

Release files / mjx-0.1.0-cp39-cp39-manylinux2014_x86_64.whl

Download URL	mjx-0.1.0-cp39-cp39-manylinux2014_x86_64.whl
Size	16.0 MB
Tags	CPython 3.9 Linux glibc 2.17+ x86-64
SHA-256 checksum How to use checksums	`7202fac52ac176c2921d9c6fd5706efda43e4c85dbc6322bbb5dc9b68efb73cd`
BLAKE2b-256 checksum How to use checksums	`298a57e3d0f8e3aea7c024171409990ebb495f2fda8f419d9b9ac8bcb2644cf5`
Upload date	Aug 23, 2022
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/4.0.1 CPython/3.9.13`

Release files / mjx-0.1.0-cp39-cp39-manylinux2014_i686.whl

Download URL	mjx-0.1.0-cp39-cp39-manylinux2014_i686.whl
Size	16.3 MB
Tags	CPython 3.9 Linux glibc 2.17+ x86-32
SHA-256 checksum How to use checksums	`1bbb58794571e556f947595ed9744eabf9bbe65c71cc474db5fed84b08c1dd9a`
BLAKE2b-256 checksum How to use checksums	`5f7356db1be6f9d8ce99392365ac94133b83a1b200d5ab68bc0641da677588a7`
Upload date	Aug 23, 2022
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/4.0.1 CPython/3.9.13`

Release files / mjx-0.1.0-cp39-cp39-macosx_10_15_x86_64.whl

Download URL	mjx-0.1.0-cp39-cp39-macosx_10_15_x86_64.whl
Size	13.0 MB
Tags	CPython 3.9 macOS 10.15+ x86-64
SHA-256 checksum How to use checksums	`fd402a1ce4ddf4c339537280f4afe73f3ab4ca968bdb5d094b4794194c0d8529`
BLAKE2b-256 checksum How to use checksums	`d01b58bc9fb9d99bda7c33cc3888f3985848929717dc140b1f47795ed73872fb`
Upload date	Aug 23, 2022
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/4.0.1 CPython/3.9.13`

Release files / mjx-0.1.0-cp38-cp38-manylinux2014_x86_64.whl

Download URL	mjx-0.1.0-cp38-cp38-manylinux2014_x86_64.whl
Size	16.0 MB
Tags	CPython 3.8 Linux glibc 2.17+ x86-64
SHA-256 checksum How to use checksums	`49d6212615a967c75a7708e57870108b9e100fa9ece40f2c3d25e4885e731721`
BLAKE2b-256 checksum How to use checksums	`3d8ea37e4df1810bd81473dac78cf0ff5f6bbb7cc444a4e758b9b12e2df66c62`
Upload date	Aug 23, 2022
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/4.0.1 CPython/3.9.13`

Release files / mjx-0.1.0-cp38-cp38-manylinux2014_i686.whl

Download URL	mjx-0.1.0-cp38-cp38-manylinux2014_i686.whl
Size	16.3 MB
Tags	CPython 3.8 Linux glibc 2.17+ x86-32
SHA-256 checksum How to use checksums	`e032f7c4a6d9c43ae9b3fbb4ffd7a1f9949914543b705b140455adfc7bc1dbdf`
BLAKE2b-256 checksum How to use checksums	`fb47108a3fb8478d05024c691381d7f4313475e8b499a61e6792c5f063e99a7d`
Upload date	Aug 23, 2022
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/4.0.1 CPython/3.9.13`

Release files / mjx-0.1.0-cp38-cp38-macosx_10_15_x86_64.whl

Download URL	mjx-0.1.0-cp38-cp38-macosx_10_15_x86_64.whl
Size	13.0 MB
Tags	CPython 3.8 macOS 10.15+ x86-64
SHA-256 checksum How to use checksums	`a526158cd4b0a90e7712b6cc1c650d055dddb99c6d55c6a53b325a067bfc4b0d`
BLAKE2b-256 checksum How to use checksums	`70ba9a1b785e243221c267fce98858df86da720158fc099cbd847e761544ed03`
Upload date	Aug 23, 2022
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Uploaded via	`twine/4.0.1 CPython/3.9.13`

Release files / mjx-0.1.0-cp37-cp37m-manylinux2014_x86_64.whl

Download URL	mjx-0.1.0-cp37-cp37m-manylinux2014_x86_64.whl
Size	16.0 MB
Tags	CPython 3.7 CPython 3.7 pymalloc Linux glibc 2.17+ x86-64
SHA-256 checksum How to use checksums	`3080ff0b3f852fbfca9be7b8c9ca73a7878bfba500e9fb5757db8d357aa17d8d`
BLAKE2b-256 checksum How to use checksums	`edd74ab923eaccc9605c316646092f084bd6ccfac409dfd3f5f2a50aed8c2591`
Upload date	Aug 23, 2022
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Uploaded via	`twine/4.0.1 CPython/3.9.13`

Release files / mjx-0.1.0-cp37-cp37m-manylinux2014_i686.whl

Download URL	mjx-0.1.0-cp37-cp37m-manylinux2014_i686.whl
Size	16.3 MB
Tags	CPython 3.7 CPython 3.7 pymalloc Linux glibc 2.17+ x86-32
SHA-256 checksum How to use checksums	`d5a2a5a192dcef297dc2f5374a43b7f589fc20c777e869407034c1c6223d47ff`
BLAKE2b-256 checksum How to use checksums	`54603295d04cd5cede1b830f568d926f852c29f7ee9bb53f6fe95e0dd991f781`
Upload date	Aug 23, 2022
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Uploaded via	`twine/4.0.1 CPython/3.9.13`

Release files / mjx-0.1.0-cp37-cp37m-macosx_10_15_x86_64.whl

Download URL	mjx-0.1.0-cp37-cp37m-macosx_10_15_x86_64.whl
Size	13.0 MB
Tags	CPython 3.7 CPython 3.7 pymalloc macOS 10.15+ x86-64
SHA-256 checksum How to use checksums	`7a79bd8b2d9750bf56f56dc2c068b8a2a93ca129fd9cd5dbe1d72c316c369965`
BLAKE2b-256 checksum How to use checksums	`7a80563744362708103ca4ba0a8ef22789adbe99eb85a14707bc22285e134eab`
Upload date	Aug 23, 2022
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Uploaded via	`twine/4.0.1 CPython/3.9.13`