| title | emoji | colorFrom | colorTo | sdk | pinned | app_port | base_path | tags | |
|---|---|---|---|---|---|---|---|---|---|
Coding Environment Server |
💻 |
blue |
blue |
docker |
false |
8000 |
/web |
|
A Python code execution environment that runs arbitrary Python code and returns results. Perfect for testing code execution infrastructure and demonstrating environment usage patterns.
The simplest way to use the Coding environment is through the CodingEnv class. The client is async by default:
import asyncio
from coding_env import CodeAction, CodingEnv
async def main():
# Create environment from Docker image
client = await CodingEnv.from_docker_image("coding-env:latest")
async with client:
# Reset
result = await client.reset()
print(f"Reset complete: exit_code={result.observation.exit_code}")
# Execute Python code
code_samples = [
"print('Hello, World!')",
"x = 5 + 3\nprint(f'Result: {x}')",
"import math\nprint(math.pi)"
]
for code in code_samples:
result = await client.step(CodeAction(code=code))
print(f"Code: {code}")
print(f" → stdout: {result.observation.stdout.strip()}")
print(f" → exit_code: {result.observation.exit_code}")
asyncio.run(main())For synchronous usage, use the .sync() wrapper:
from coding_env import CodeAction, CodingEnv
with CodingEnv(base_url="http://localhost:8000").sync() as client:
result = client.reset()
result = client.step(CodeAction(code="print('Hello!')"))
print(result.observation.stdout)The CodingEnv.from_docker_image() method handles:
- Starting the Docker container
- Waiting for the server to be ready
- Connecting to the environment
- Container cleanup when the context manager exits
Before using the environment, you need to build the Docker image:
# From project root
docker build -t coding-env:latest -f envs/coding_env/server/Dockerfile .CodeAction: Contains a single field
code(str) - The Python code to execute
CodeObservation: Contains the execution results
stdout(str) - Standard output from code executionstderr(str) - Standard error from code executionexit_code(int) - Exit code (0 for success, non-zero for errors)
CodeState: Tracks execution state
episode_id(str) - Unique identifier for the episodestep_count(int) - Number of steps takenlast_exit_code(int) - Exit code from the last execution
If you already have a Coding environment server running, you can connect directly:
from coding_env import CodeAction, CodingEnv
# Async usage
async with CodingEnv(base_url="http://localhost:8000") as client:
result = await client.reset()
result = await client.step(CodeAction(code="print('Hello!')"))
# Sync usage
with CodingEnv(base_url="http://localhost:8000").sync() as client:
result = client.reset()
result = client.step(CodeAction(code="print('Hello!')"))Note: When connecting to an existing server, closing the client will NOT stop the server.
Install the coding_env package with dev dependencies and run the tests from the repo root:
# Install coding_env with dev dependencies (includes smolagents and pytest)
uv pip install -e "envs/coding_env[dev]"
# Run unit tests (no Docker required)
uv run pytest tests/envs/test_python_codeact_reset.py tests/envs/test_python_codeact_rewards.py -v
# Run integration tests (requires Docker image to be built)
docker build -t coding-env:latest -f envs/coding_env/server/Dockerfile .
SKIP_DOCKER_TESTS=0 uv run pytest tests/envs/test_coding_env_integration.py -vRun the complete example that demonstrates the full workflow:
python3 envs/coding_env/client/example_usage.pyThis example shows:
- Creating an environment from a Docker image
- Resetting and executing code through the environment
- Automatic cleanup with
close()
coding_env/
├── README.md # This file
├── models.py # Action, Observation, and State models
├── client/
│ ├── coding_env_client.py # CodingEnv client implementation
│ └── example_usage.py # Usage examples
└── server/
├── python_codeact_env.py # Core environment logic
├── app.py # FastAPI application
├── transforms.py # Observation transforms
├── Dockerfile # Container image definition
└── README.md # Server-specific documentation