Update Environment

POST/v1/environments/{environment_id}

Update an environment. Omitted fields preserve their existing values.

Path Parameters

Parameter	Type	Required	Description
environment_id	string	✅	The environment ID (env_...)

Request Parameters

Parameter	Type	Required	Description
name	string	❌	Updated name. Omit to preserve.
description	string	❌	Updated description. Omit to preserve.
config	object	❌	Updated configuration. Omitted nested fields preserve their existing values.
metadata	object	❌	Metadata patch. Set a key to null or empty string to delete it. Omit to preserve.

Field preservation

Within config, omitted fields preserve the existing value. For example, sending only networking leaves packages unchanged. To clear a package list, send an empty array for that manager.

Request Examples

Python

from anthropic import Anthropic

client = Anthropic(
    api_key="sk-sb-YOUR_KEY",
    base_url="https://api.sandbase.ai"
)

env = client.beta.environments.update(
    environment_id="env_011CZkZ9X2dpNyB7HsEFoRfW",
    config={
        "type": "cloud",
        "packages": { "type": "packages", "pip": ["pandas", "numpy", "scikit-learn"] }
    }
)
print(env.updated_at)

cURL

curl -X POST https://api.sandbase.ai/v1/environments/env_011CZkZ9X2dpNyB7HsEFoRfW \
  -H "Authorization: Bearer sk-sb-YOUR_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "config": {
      "type": "cloud",
      "packages": { "type": "packages", "pip": ["pandas", "numpy", "scikit-learn"] }
    }
  }'

Response

Returns the updated Environment object.

{
  "id": "env_011CZkZ9X2dpNyB7HsEFoRfW",
  "type": "environment",
  "name": "python-data-analysis",
  "description": "Python environment with data-analysis packages.",
  "config": {
    "type": "cloud",
    "networking": {
      "type": "limited",
      "allowed_hosts": ["api.example.com"],
      "allow_mcp_servers": false,
      "allow_package_managers": true
    },
    "packages": {
      "type": "packages",
      "apt": [], "cargo": [], "gem": [], "go": [], "npm": [],
      "pip": ["pandas", "numpy", "scikit-learn"]
    }
  },
  "metadata": {},
  "archived_at": null,
  "created_at": "2026-05-29T10:00:00Z",
  "updated_at": "2026-05-29T11:00:00Z"
}

Errors

Status	Type	Description
400	invalid_request	Invalid config or field values
401	authentication_error	Invalid or missing API key
404	not_found	Environment not found