semvec/pypi-packages huggingface dataset:
amanita 0.0.1
Create python customizable projects
License: MIT

===============================
amanita
===============================

.. image:: https://img.shields.io/pypi/v/amanita.svg
    :target: https://pypi.python.org/pypi/amanita
    :alt: Latest PyPI version

Create python customizable projects.

Usage
=====

Ingredients
===========

  .. image:: resources/img/python.png
     :target: https://www.python.org

  .. image:: resources/img/reestructuredtext.png
     :target: http://docutils.sourceforge.net/rst.html

  .. image:: resources/img/debian.png
     :target: https://www.debian.org

  .. image:: resources/img/cookiecutter.png
     :target: https://github.com/audreyr/cookiecutter

  .. image:: resources/img/amanita.png
     :target: https://es.wikipedia.org/wiki/Amanita_muscaria

Installation
============

.. code-block:: sh

   pip install amanita

------------
Requirements
------------

Compatibility
=============

License
=======

MIT. See the `LICENSE <LICENSE>`_ file for more details.

Authors
=======

`amanita` was written by `constrict0r <constrict0r@protonmail.com>`_.

Enjoy!!

  .. image:: resources/img/enjoy.png
gym-chrome-dino 0.0.3
Chrome Dino in OpenAI Gym
License: MIT

# gym-chrome-dino

An OpenAI Gym environment for Chrome Dino / T-Rex Runner Game

This environment utilizes 
[a forked version](https://github.com/elvisyjlin/t-rex-runner) 
of _Chrome Dino_, also called _T-Rex Runner_, 
extracted from chromium offline error page. 
See [here](https://github.com/wayou/t-rex-runner).


## Installation

You can install `gym-chrome-dino` from PyPI by either 

```bash
pip install gym-chrome-dino
```

or

```bash
git clone https://github.com/elvisyjlin/gym-chrome-dino.git
cd gym-chrome-dino
pip install -e .
```


## Usage

You can get started as follows:

```python
import gym
import gym_chrome_dino
env = gym.make('ChromeDino-v0')
```

To create a headless (without opening browser) environment

```python
env = gym.make('ChromeDinoNoBrowser-v0')
```

### Observations, Actions and Rewards

* The observation is a RGB numpy array with shape of (150, 600, 3).  
* The available actions are 0: _do nothing_, 1: _jump_, and 2: _duck_.  
* A positive reward 0.01 is given when the dinosaur is alive; a negative penalty -1.0 is given when the dinosaur hits an obstable, which might be a cactus or a bird.

For the DeepMind DQN recipe, where we give 4-stacked resized grayscaled frames (80, 160, 4) to the agent, we provide a wrapping method `make_dino()`. It also comes with a timer wrapper, which reports the interval between `env.step()`.

```python
from gym_chrome_dino.wrappers import make_dino
env = make_dino(env, timer=True, frame_stack=True)
```

### DinoGame

An instance of `DinoGame` is created when the environment is made. There are some useful methods for fine control of the training environment. The `DineGame` can be accessed as follows:

```python
env.unwrapped.game
```

`DinoGame` provides a `get_score()` method to get the score of current game.

```python
score = env.unwrapped.game.get_score()
```

By default, the acceleration of the game is set to zero. If you want to restore the original acceleration value, please do `set_acceleration(True)`. On the other hand, `set_acceleration(False)` sets the value to zero.

```python
env.unwrapped.game.set_acceleration(True)
```


## Example

Here is a simple example to use `gym-chrome-dino`.

```python
import gym
import gym_chrome_dino
from gym_chrome_dino.utils.wrappers import make_dino
env = gym.make('ChromeDino-v0')
env = make_dino(env, timer=True, frame_stack=True)
done = True
while True:
    if done:
        env.reset()
    action = env.action_space.sample()
    observation, reward, done, info = env.step(action)
```


## WebDriver

`gym-chrome-dino` runs the game on [chromedriver](http://chromedriver.chromium.org) via `selenium` because it is a proper way to monitor and to play _Chrome Dino_. As a result, the latest chromedriver executable file will be downloaded to the current working directory where your program is.
hb 1.4.2
A simple command-line utility for calculating checksums.
License: MIT
Requires Python: >=3.6,<4.0
Keywords: checksum,digest,hash,md5,sha1

# Hash Brown

[![CircleCI](https://circleci.com/gh/chingc/Hash-Brown.svg?style=shield)](https://circleci.com/gh/chingc/workflows/Hash-Brown) [![codecov](https://codecov.io/gh/chingc/Hash-Brown/branch/master/graph/badge.svg)](https://codecov.io/gh/chingc/Hash-Brown) [![License](https://img.shields.io/badge/license-MIT-blue.svg)](./LICENSE) [![PyPI](https://img.shields.io/pypi/v/hb.svg)](https://pypi.org/project/hb/)

A simple command-line utility for calculating checksums.

## Install

```
pip install hb
```

## Usage

Calculate the sha1 of a file:

```
$ hb -a sha1 hello.txt
sha1 (hello.txt) = 493a253abf93d705d67edeb463134a5c8752fc9d
```

Check to see if file matches a given checksum:

```
$ hb -a md5 hello.txt -g 77060c267470021a97392b815138733e
md5 (hello.txt) = 77060c267470021a97392b815138733e OK

$ hb -a md5 hello.txt -g 0123456789abcdef
md5 (hello.txt) = 0123456789abcdef BAD
```

Checksums can be read from a file:

```
$ hb -c checksums.txt
sha512 (hello.txt) = 493a253abf93d705d67edeb463134a5c8752fc9d OK
sha512 (world.txt) = 683e4ee04e75e71a6dca42807001f00be1fcb2a3 OK
sha512 (image.jpg) = f3a53e6c2743645f08faedadd7a2c57cbc38632f OK
sha512 (video.mp4) = 03ba9191fc4cd74f218df58542643fbc07dca532 OK
```

Hash Brown outputs its results in BSD style.  The checksum files are also BSD style.

All files are read in binary mode.

Globbing and recursive globbing are supported via `*` and `**` respectively.

Dotfiles are not included when globbing and need to be specified explicitly.

## Options

```
-a, --algorithm [blake2b|blake2s|md5|sha1|sha224|sha256|sha384|sha512|adler32|crc32]
-c, --check                     Read checksums from a file.
-g, --given TEXT                See if the given checksum `TEXT` matches the
                                computed checksum. (use with -a)
-p, --parallel                  Process files in parallel.
-q, --quiet                     Hide results that are OK. (use with -c)
-t, --timer                     Display elapsed time in seconds.
--version                       Show the version and exit.
-h, --help                      Show this message and exit.
```