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# 02. Using Environments

Source:
- https://meta-pytorch.org/OpenEnv/auto_getting_started/plot_02_using_environments.html



## Main idea



This page is about how users consume an existing OpenEnv environment.



The docs highlight three connection methods:



1. from Hugging Face Hub

2. from Docker image

3. from direct base URL



## Connection methods



### 1. From Hugging Face Hub



The easiest route for end users.



Typical flow:



- pull the image from the HF registry

- start the container locally

- connect to it

- clean it up on close



The docs show the pattern conceptually as:



```python

MyEnv.from_hub("owner/env-name")
```



## 2. From Docker image



Useful when:



- you already built the image locally

- you want reproducible local runs

- you do not want to depend on a live remote Space



Typical pattern:



```python

MyEnv.from_docker_image("my-env:latest")

```

## 3. Direct URL connection

Useful when:

- the server is already running
- you want to connect to localhost or a deployed Space

Typical pattern:

```python

MyEnv(base_url="http://localhost:8000")

```

## WebSocket model

The docs emphasize that OpenEnv uses WebSocket-backed sessions for persistent environment interaction.

Why this matters:

- lower overhead than stateless HTTP on every step
- cleaner session management
- better fit for multi-step RL loops

## Environment loop

The intended use pattern is:

1. connect
2. reset
3. repeatedly call `step(action)`
4. inspect `reward`, `done`, and `observation`
5. close cleanly

## What this means for `python_env`



Your environment should be easy to consume in all three modes:



- local URL

- local Docker image

- HF Space



That means the most important user-facing checks are:



- `reset()` works

- `step()` works

- the client can parse the observation correctly

- Docker image starts cleanly

- deployed Space responds on `/health`, `/docs`, and session routes



For hackathon validation, this page is basically the “user experience” standard you need to match.