semvec/pypi-packages huggingface dataset:
pynavi 0.1.2
pynavi framework based on django

# navi framework
navi 框架，基于django封装，将常用逻辑抽象封装，简化rest服务开发流程

enjoy it ~

问题反馈：sunguangran@daixiaomi.com



<br />

## 安装方式
* 使用内部pypi源安装

```
pip install pynavi -i http://pypi.intra.yongqianbao.com —trusted-host pypi.intra.yongqianbao.com
```
awsLogger 0.0.9
log into a file and push it to aws s3

# awsLogger

AwsLogger is a simple logging utility.
It allow you to log all type of data ( string, numbers, list, dictionaries or even custom objects ) into a file and push it to amazon s3.

## Installation

```
pip install awsLogger
```

## How to use

First import awsLogger:

```
import awsLogger
```

To log on your local machine:

```
awsLogger.log("this will be added to your log file", config)
```

To push current file to amazon s3:

```
awsLogger.push(config)
```

To log on your local machine and push to amazon s3:

```
awsLogger.logAndPush("this will be added to your log file and pushed to aws", config)
```

## How to configure

```
config = {
    "awsId":<Your aws api id>,
    "awsSecret":<Your aws api secret key>,
    "projectId":<Identifier, if bucket name is not specifed, it will be used as bucket name, it will be used to generate a log file name if no log file name is specified>,
    "bucketName":<The s3 bucket where to put the log file>,
    "bucketPathFromRoot":<path on s3 bucket>
    "fileName":"logfile name"
    "filePath":"local file path"
}
```

All configuration entries are optional. if no awsId and no awsSecret are given, it will use your system default.
gym_ple 0.3
This package allows to use PLE as a gym environment.
Keywords: AI

gym-ple
******

PyGame Learning Environment (PLE) is a learning environment, mimicking the Arcade Learning Environment interface, allowing a quick start to Reinforcement Learning in Python. 
The goal of PLE is allow practitioners to focus design of models and experiments instead of environment design.
This package allows to use PLE as a gym environment.

Installing everything
---------------------
gym_ple requires PLE, to install PLE clone the repo and install with pip.

.. code:: shell

    git clone https://github.com/ntasfi/PyGame-Learning-Environment.git
    cd PyGame-Learning-Environment/
    pip install -e .


PLE requires PyGame installed:

On OSX:

.. code:: shell

    brew install sdl sdl_ttf sdl_image sdl_mixer portmidi  # brew or use equivalent means
    conda install -c tlatorre pygame=1.9.2 # using Anaconda

On Ubuntu 14.04:

.. code:: shell

    apt-get install -y python-pygame

More configurations and installation details on: http://www.pygame.org/wiki/GettingStarted#Pygame%20Installation

And finally clone and install this package

.. code:: shell

    git clone https://github.com/lusob/gym-ple.git 
    cd gym-ple/
    pip install -e .

You also can install it from PyPi:

.. code:: shell

    pip install gym_ple 


Example
=======

Run ``python example.py`` file to play a PLE game (flappybird) with a random_agent (you need to have installed openai gym).