Gymnasium
flake8
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Gymnasium
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NASA JPL Open Source Rover That Runs ROS 2
"Show HN: Ghidra Plays Mario" (2023) https://news.ycombinator.com/item?id=37475761 :
[RL, MuZero reduxxxx ]
> Farama-Foundation/Gymnasium is a fork of OpenAI/gym and it has support for additional Environments like MuJoCo: https://github.com/Farama-Foundation/Gymnasium#environments
> Farama-Foundatiom/MO-Gymnasiun: "Multi-objective Gymnasium environments for reinforcement learning": https://github.com/Farama-Foundation/MO-Gymnasium
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Show HN: Ghidra Plays Mario
https://github.com/Farama-Foundation/Gymnasium#environments
Farama-Foundatiom/MO-Gymnasiun:
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Are there any AI projects that plays a game for you and learns?
https://github.com/Farama-Foundation/Gymnasium - A framework Python library to build and train your own AI to play games
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Unstable SAC training of sparse-reward task
The only change in the environment from the one here is the reward function which is given its return value using the following code snippet (replacing lines 648-672 in the above url):
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Any resources on experiments simulated environments?
This may be useful: https://github.com/Farama-Foundation/Gymnasium
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What's the most challenging Gym environment?
Here are all the environments. So for example, if instead of Hopper-v2 you want the acrobat environment from classic control you can write: env = gym.make('Acrobot-v1')
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Gymnasium 0.28 is now released
This release also includes a large number of documentation updates, minor bug fixes, and other minor improvements; the full release notes are available here if you’d like to learn more: https://github.com/Farama-Foundation/Gymnasium/releases/tag/v0.28.0.
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TransformerXL + PPO Baseline + MemoryGym
Thanks! It really depends on the task that you want to implement. But in general, sticking to the standard gymnasium API is important. If you want to implement a 2D environment then PyGame is promising. If it's more like a game, check out Unity ML-Agents or Godot RL Agents. Anything simpler can also be just pure python code. You also need to carefully design your observation space, action space and reward function. My advice is to explore design choices of related environments.
- Gymnasium 0.27 - the first new version since Gymnasium was announced - is now released. It has almost no breaking changes.
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[N] Gymnasium 0.27 - the first new version since Gymnasium was announced - is now released. It has almost no breaking changes.
You can read the release notes here: https://github.com/Farama-Foundation/Gymnasium/releases/tag/v0.27.0. You can upgrade from 0.26 without any changes unless you're doing something very uncommon; this is how releases will generally be going forward.
flake8
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How I start every new Python backend API project
repos: - repo: https://github.com/pre-commit/pre-commit-hooks rev: v4.3.0 hooks: - id: trailing-whitespace - id: check-merge-conflict - id: check-yaml args: [--unsafe] - id: check-json - id: detect-private-key - id: end-of-file-fixer - repo: https://github.com/timothycrosley/isort rev: 5.10.1 hooks: - id: isort - repo: https://github.com/psf/black rev: 22.8.0 hooks: - id: black - repo: https://gitlab.com/pycqa/flake8 rev: 3.9.2 hooks: - id: flake8 - repo: https://github.com/pre-commit/mirrors-mypy rev: v0.971 hooks: - id: mypy args: [ --warn-unused-configs, --ignore-missing-imports, --disallow-untyped-defs, --follow-imports=silent, --install-types, --non-interactive ]
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Flake8 took down the gitlab repository in favor of github
I just ran `pre-commit autoupdate`. It's asking for a username for https://gitlab.com/pycqa/flake8. :-(
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flake8-length: Flake8 plugin for a smart line length validation.
Flake8 plugin for a smart line length validation.
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Should I follow the warnings in Pycharm? Does anyone do this?
repo: https://gitlab.com/pycqa/flake8 rev: 3.9.2 hooks:
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flake8-pylint: Flake8 plugin that runs PyLint
Flake8 plugin that runs PyLint.
- Ask HN: Did somebody have success with the migration of Python 2.7 to Java/C#?
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Make your Django project newbie contributor friendly with pre-commit
$ pre-commit install pre-commit installed at .git/hooks/pre-commit $ git add .pre-commit-config.yaml $ git commit -m "Add pre-commit config" [INFO] Initializing environment for https://github.com/pre-commit/pre-commit-hooks. [INFO] Initializing environment for https://gitlab.com/pycqa/flake8. [INFO] Initializing environment for https://github.com/pycqa/isort. [INFO] Initializing environment for https://github.com/python/black. [INFO] Installing environment for https://github.com/pre-commit/pre-commit-hooks. [INFO] Once installed this environment will be reused. [INFO] This may take a few minutes... [INFO] Installing environment for https://gitlab.com/pycqa/flake8. [INFO] Once installed this environment will be reused. [INFO] This may take a few minutes... [INFO] Installing environment for https://github.com/pycqa/isort. [INFO] Once installed this environment will be reused. [INFO] This may take a few minutes... [INFO] Installing environment for https://github.com/python/black. [INFO] Once installed this environment will be reused. [INFO] This may take a few minutes... Trim Trailing Whitespace.................................................Passed Check Yaml...............................................................Passed Check for merge conflicts................................................Passed Debug Statements (Python)............................(no files to check)Skipped Check for added large files..............................................Passed Fix requirements.txt.................................(no files to check)Skipped Check django project for potential problems..........(no files to check)Skipped Check django project for missing migrations..........(no files to check)Skipped flake8...............................................(no files to check)Skipped isort................................................(no files to check)Skipped black................................................(no files to check)Skipped
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On unit testing
If you're looking for just good automated error checking, I personally use a bunch of flake8 plugins via pre-commit hooks: flake8-bugbear, flake8-builtins, flake8-bandit, etc. You can find a bunch of sites that give recommended plugins and you just need to pick which ones you care about :)
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Python: Setting Up Project Environment
flake8 is Python style checker based on PEP8(Python Enhance Proposal 8). black is a good code formatter. But some items such as Documentation String, black is not provided the check option. flake8 not only helps for lack of black but also can be easily applied with black.
What are some alternatives?
flake8 - The official GitHub mirror of https://gitlab.com/pycqa/flake8
pyright - Static Type Checker for Python
Flake8-pyproject - Flake8 plug-in loading the configuration from pyproject.toml
black - The uncompromising Python code formatter [Moved to: https://github.com/psf/black]
ruff - An extremely fast Python linter and code formatter, written in Rust.
yapf - A formatter for Python files
agents - TF-Agents: A reliable, scalable and easy to use TensorFlow library for Contextual Bandits and Reinforcement Learning.
pyre-check - Performant type-checking for python.
Visual Studio Code - Visual Studio Code
mypy - Optional static typing for Python
episodic-transformer-memory-ppo - Clean baseline implementation of PPO using an episodic TransformerXL memory
pre-commit - A framework for managing and maintaining multi-language pre-commit hooks.