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GravixLayer Python SDK

PyPI version Python 3.9+ License: Apache 2.0

Official Python client for GravixLayer. Create isolated cloud runtimes, run code and commands in them, build reusable images, and deploy agents.

pip install gravixlayer
export GRAVIXLAYER_API_KEY="your-api-key"
from gravixlayer import GravixLayer

client = GravixLayer()
sandbox = client.runtime.create()  # defaults to template="base-small"

result = sandbox.run_code(code="print('Hello from GravixLayer')")
print(result.text)

sandbox.kill()

Cloud and region default to aws / us-east-1. Override with GRAVIXLAYER_CLOUD / GRAVIXLAYER_REGION, or pass them to the client.

Docs: docs.gravixlayer.ai · Examples: examples/

Configuration

from gravixlayer import GravixLayer

client = GravixLayer(
    api_key="your-api-key",          # or GRAVIXLAYER_API_KEY
    base_url="https://api.gravixlayer.ai",
    cloud="aws",
    region="us-east-1",
)
Option Default
api_key GRAVIXLAYER_API_KEY Required.
base_url GRAVIXLAYER_BASE_URL, then https://api.gravixlayer.ai
cloud GRAVIXLAYER_CLOUD, then aws Runtimes and template builds.
region GRAVIXLAYER_REGION, then us-east-1 Runtimes and template builds.
timeout 60 Per request, in seconds.
max_retries 3 Transient failures only.

Construct the client once and reuse it. Call client.warmup() at startup if you want TCP and TLS paid before the first request that matters. HTTP/2 is the default over HTTPS — concurrent requests spread across a small pool of connections; pass http2=False for a plain HTTP/1.1 pool.

Runtimes

A sandbox is an isolated virtual machine that boots from a template. It runs until you stop it, or until a timeout you set expires.

sandbox = client.runtime.create(
    template="base-small",
    env_vars={"APP_ENV": "staging"},
    timeout=600,
)

Use a context manager when you want it stopped automatically:

from gravixlayer import Runtime

with Runtime.create(template="base-small") as sandbox:
    print(sandbox.run_code("print(2 + 2)").text)

Code and commands

result = sandbox.run_code("print(sum(range(100)))")
print(result.text)

# Pass args when any part comes from user input — nothing in the list is
# interpreted by a shell.
sandbox.run_cmd("python", args=["--version"])

Guest egress is deny-by-default. Installing a package or reaching the internet needs a network policy.

Files

sandbox.file.write("/workspace/note.txt", "hello\n")
text = sandbox.file.read("/workspace/note.txt").content

Also: list, upload, download, write_many, move, copy, find, replace, watch, delete. See examples/runtimes/07_file_operations.py.

State, ports, git, SSH

# Interpreter state that survives between run_code calls.
ctx = client.runtime.create_context(sandbox.runtime_id)
client.runtime.run_code(sandbox.runtime_id, "x = 1", context_id=ctx.context_id)

# Publish a guest port on https://*.service.gravixlayer.ai
with sandbox.service(8000) as api:
    print(api.web_url)
    api.get("/items")

sandbox.git.clone("https://github.com/org/repo.git", "/workspace/repo", depth=1)

ssh = sandbox.enable_ssh()
print(ssh.connect_cmd)

Templates

Build an image once so runtimes start with everything already installed. Placement follows the client (aws / us-east-1 unless you override it).

from gravixlayer import TemplateBuilder

template = (
    TemplateBuilder("data-science", "Pandas and friends")
    .from_image("python:3.12-slim")
    .vcpu(2)
    .memory(2048)
    .apt_install("git")
    .pip_install("pandas", "matplotlib")
    .start_cmd("python -m http.server 8080")
    .ready_cmd(TemplateBuilder.wait_for_port(8080), timeout_secs=300)
)

status = client.templates.build_and_wait(template)
sandbox = client.runtime.create(template=status.template_id)

Snapshots

client.snapshots.create(sandbox.runtime_id, "ready-to-work", kind="cold")
restored = client.runtime.create(snapshot="ready-to-work")

A cold snapshot stores the filesystem; a hot snapshot stores memory too, so the restored sandbox resumes mid-process.

Agents

agent = client.agents.deploy(source="./my-agent", name="my-agent", is_public=True)
reply = client.agents.invoke(agent.agent_id, input={"prompt": "hello"})

Network policies

A sandbox starts fail-closed. Grant access explicitly:

policy = client.network_policies.create(
    name="model-access",
    egress_mode="allowlist",
    rules=[{"destination": "api.example.com", "port": 443, "protocol": "tcp"}],
)

sandbox = client.runtime.create(
    template="base-small",
    network_policy_ids=[policy.id],
)

Attaching several policies applies the most restrictive of them, so adding one can only narrow access.

Storage mounts

Managed buckets, links to buckets you already own, and git repositories can mount into a sandbox at boot or while it runs:

bucket = client.storage.buckets.create("datasets")

sandbox = client.runtime.create(mounts=[
    {"kind": "bucket", "path": "/mnt/data", "mode": "rw", "bucket": bucket.id},
    {"kind": "git", "path": "/mnt/repo", "url": "https://example.com/org/repo.git"},
])

# Hot-attach, inspect, detach on a running sandbox.
mount = sandbox.mounts.attach(
    {"kind": "bucket", "path": "/mnt/more", "link": "byo-data"}
)
print(mount.state, mount.provenance)
sandbox.mounts.detach(mount.id)

Bring your own bucket with a link — credentials live in a secret provider and are referenced by name, never passed through the SDK:

link = client.storage.links.create(
    "byo-data", "acme-data",
    provider="s3_compatible",
    endpoint="https://objects.example.com",
    path_style=True,
    secret_provider_id=provider.id,
    access_key_secret="AWS_ACCESS_KEY_ID",
    secret_key_secret="AWS_SECRET_ACCESS_KEY",
)

Secrets

provider = client.identity.providers.create(
    "Model API",
    secrets=[{"key": "MODEL_API_KEY", "value": "..."}],
)

sandbox = client.runtime.create(
    template="base-small",
    providers=[provider.id],
)

Values are write-only. What comes back is masked.

Async

import asyncio
from gravixlayer import AsyncGravixLayer

async def main():
    async with AsyncGravixLayer() as client:
        sandbox = await client.runtime.create(template="base-small")
        result = await client.runtime.run_code(
            sandbox.runtime_id, "print('hello')"
        )
        print(result.stdout_text)
        await client.runtime.kill(sandbox.runtime_id)

asyncio.run(main())

Errors

from gravixlayer import GravixLayerError, GravixLayerRateLimitError

try:
    client.runtime.create(template="base-small")
except GravixLayerRateLimitError as exc:
    print(exc.retry_after_seconds)
except GravixLayerError as exc:
    print(exc)          # product line, e.g. "CPU quota exceeded. …"
    print(exc.status)   # 403
    print(exc.code)     # quota_exceeded

Connection failures and 429 / 502 / 503 / 504 are retried automatically. HTTP 403 (quota or permission) is not retried.

Examples

Runnable scripts for every surface live in examples/. Start with examples/README.md.

Development

pip install -e ".[test]"
pytest tests/unit_tests

See tests/README.md for layout and live integration tests.

Support

License

Apache License 2.0 — see LICENSE. Copyright 2026 Gravix Layer.

Metadata

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