#!/usr/bin/env python

import opensim as osim

from osim.redis.client import Client

from osim.env import *

import numpy as np

import argparse

import os

"""

NOTE: For testing your submission scripts, you first need to ensure that redis-server is running in the background

and you can locally run the grading service by running this script : https://github.com/crowdAI/osim-rl/blob/master/osim/redis/service.py

The client and the grading service communicate with each other by pointing to the same redis server.

"""

"""

Please ensure that `visualize=False`, else there might be unexpected errors in your submission

"""

env = RunEnv(visualize=False)

client = Client()

# Create environment

observation = client.env_create()

"""

The grader runs N simulations of at most 1000 steps each. We stop after the last one

A new simulation start when `clinet.env_step` returns `done==True`

and all the simulatiosn end when the subsequent `client.env_reset()` returns a False

"""

while True:

    _action = env.action_space.sample().tolist()

    [observation, reward, done, info] = client.env_step(_action)

    print(observation)

    if done:

        observation = client.env_reset()

        if not observation:

            break

client.submit()