Sandbox configuration

This guide covers sandbox configuration options, including resources, mounted files, ports, annotations, and timeouts. Use it as a reference when you need to tailor a sandbox’s runtime environment to match the requirements of a workload, such as reserving GPU capacity, exposing a service, or setting operation timeouts. This page is for developers who use the cwsandbox Python SDK to launch and manage sandboxes.

Choose authentication

These examples run on serverless capacity unless a section specifies CKS. Choose the credential for the account that owns your sandboxes. See Choose and get credentials to obtain a key or token. Run the installation commands in an active Python virtual environment. Save the Python code from your credential tab as sandbox_auth.py beside the Python scripts you run from this page. It stores the authentication choice, not your credential. The examples import AUTH from that file and pass it explicitly to each new sandbox or session.

Forge API key
CoreWeave API access token

Use your Forge API key through the SDK’s W&B authentication strategy:

uv pip install 'cwsandbox[wandb]>=1.14.2'
export WANDB_API_KEY="[WANDB-API-KEY]"

sandbox_auth.py

from cwsandbox import AuthStrategy

AUTH = AuthStrategy.WANDB

Use the token for your CoreWeave organization:

uv pip install 'cwsandbox>=1.14.2'
export CWSANDBOX_API_KEY="[API-ACCESS-TOKEN]"

sandbox_auth.py

from cwsandbox import AuthStrategy

AUTH = AuthStrategy.COREWEAVE_API_KEY

For CKS placement, choose the CoreWeave token, enable a runner, and set placement_mode="cks" on sandbox creation or in SandboxDefaults. Creating a session with auth=AUTH also authenticates the sandboxes it owns. Keep the same credential when reconnecting, listing, or cleaning up sandboxes.

Overview

You can set sandbox configuration in three places, listed from broadest to most specific scope:

SandboxDefaults: Shared defaults for all sandboxes in a session.
Sandbox.run() kwargs: Per-sandbox overrides.
@session.function() kwargs: Function-specific configuration.

from sandbox_auth import AUTH
from cwsandbox import ResourceOptions, Sandbox, SandboxDefaults, Session

# Via SandboxDefaults
defaults = SandboxDefaults(
    container_image="python:3.11",
    max_lifetime_seconds=3600,
    resources=ResourceOptions(
        requests={"cpu": "2", "memory": "2Gi"},
        limits={"cpu": "2", "memory": "2Gi"},
    ),
)

# Via Sandbox.run() kwargs
sandbox = Sandbox.run(
    defaults=defaults,
    resources=ResourceOptions(
        requests={"cpu": "4", "memory": "4Gi"},
        limits={"cpu": "4", "memory": "4Gi"},
    ),
    auth=AUTH,
)

# Via @session.function() kwargs
with Session(defaults, auth=AUTH) as session:
    @session.function(resources={"cpu": "1", "memory": "1Gi"})
    def compute(x: int) -> int:
        return x * 2

The following sections describe each configuration area in detail.

Resources

Configure CPU, memory, and GPU resources using the ResourceOptions dataclass or a plain dict. Serverless is the default placement mode. For serverless sandboxes, set equal CPU and memory requests and limits. For unequal requests and limits, use CKS placement with a runner whose policy permits them. Do not rely on serverless to normalize unequal values. Successful creation with unequal requests and limits does not establish support for resource bursting. The following examples use equal requests and limits:

from sandbox_auth import AUTH
from cwsandbox import ResourceOptions, Sandbox

# Using ResourceOptions
sandbox = Sandbox.run(
    resources=ResourceOptions(
        requests={"cpu": "2", "memory": "2Gi"},
        limits={"cpu": "2", "memory": "2Gi"},
    ),
    auth=AUTH,
)

# Using dict
sandbox = Sandbox.run(
    resources={
        "requests": {"cpu": "2", "memory": "2Gi"},
        "limits": {"cpu": "2", "memory": "2Gi"},
    },
    auth=AUTH,
)

Both forms are equivalent: the SDK automatically converts dicts to ResourceOptions internally. ResourceOptions separates resource requests from limits. Requests tell the scheduler what the sandbox needs. Limits set the maximum it can use. For background on how Kubernetes uses requests and limits to assign Quality of Service classes, see the Kubernetes documentation.

ResourceOptions fields

Field	Type	Description
`requests`	`dict[str, str] \| None`	CPU and memory requests for scheduling (for example, `{"cpu": "500m", "memory": "512Mi"}`).
`limits`	`dict[str, str] \| None`	CPU and memory limits the sandbox cannot exceed (for example, `{"cpu": "2", "memory": "2Gi"}`).
`gpu`	`dict[str, Any] \| None`	GPU configuration (for example, `{"count": 1, "type": "H100"}`).

All fields are optional in the client and default to None. The resolved allocation must satisfy the applicable policy. If you omit the resource allocation, complete, positive CPU and memory defaults from that policy supply both requests and limits.

Guaranteed QoS

Guaranteed Quality of Service depends on the resources of every container in the Pod. With container-level allocations, each container must have positive CPU and memory requests, with matching limits for each resource. This includes init containers and sidecars. Equal values for your workload container alone do not establish the QoS class of the whole sandbox Pod. A sandbox that tries to use more CPU than its limit is still throttled.

from sandbox_auth import AUTH
sandbox = Sandbox.run(
    resources=ResourceOptions(
        requests={"cpu": "2", "memory": "4Gi"},
        limits={"cpu": "2", "memory": "4Gi"},
    ),
    auth=AUTH,
)

For equal requests and limits, a flat dict shorthand is available. The SDK normalizes flat dicts by setting both requests and limits to the same values.

from sandbox_auth import AUTH
# Flat dict shorthand: requests and limits are set to identical values
sandbox = Sandbox.run(
    resources={"cpu": "2", "memory": "4Gi"},
    auth=AUTH,
)

Burstable QoS

On a CKS runner whose policy permits unequal requests and limits, lower requests give the sandbox a Burstable Quality of Service class. Lower requests let the scheduler bin-pack more sandboxes, but each sandbox can burst up to its limit if capacity is available. Complete Use your own compute and set CWSANDBOX_API_KEY to a CoreWeave API access token. Replace [RUNNER-ID] with the ID of a CKS runner whose policy permits these requests and limits:

from cwsandbox import AuthStrategy, ResourceOptions, Sandbox

sandbox = Sandbox.run(
    auth=AuthStrategy.COREWEAVE_API_KEY,
    placement_mode="cks",
    runner_ids=["[RUNNER-ID]"],
    resources=ResourceOptions(
        requests={"cpu": "500m", "memory": "512Mi"},
        limits={"cpu": "4", "memory": "4Gi"},
    ),
)

CPU values

Specify CPU in millicores or whole cores. For details, see Resource units in Kubernetes.

Value	Meaning
`"100m"`	100 millicores (0.1 CPU)
`"500m"`	500 millicores (0.5 CPU)
`"1000m"` or `"1"`	1 full CPU core
`"2000m"` or `"2"`	2 CPU cores

Memory values

Memory uses standard Kubernetes memory units:

Value	Meaning
`"128Mi"`	128 mebibytes
`"512Mi"`	512 mebibytes
`"1Gi"`	1 gibibyte
`"4Gi"`	4 gibibytes

GPU

Request GPU resources alongside CPU and memory. A GPU request reserves GPUs only, so set CPU and memory explicitly.

from sandbox_auth import AUTH
sandbox = Sandbox.run(
    resources=ResourceOptions(
        requests={"cpu": "4", "memory": "16Gi"},
        limits={"cpu": "4", "memory": "16Gi"},
        gpu={"count": 1},
    ),
    auth=AUTH,
)

GPU configuration keys:

Key	Type	Description
`count`	`int`	Number of GPUs to request.
`type`	`str`	GPU type, matched exactly against the types a runner advertises in discovery. Leave unset on serverless capacity, which assigns the GPU type for you. See Run a GPU sandbox.
`memory_gb`	`int`	Minimum GPU memory in GB. Selects a GPU type on the runner with at least this much memory. When more than one type qualifies, which one you get isn’t defined.

type and memory_gb are alternatives. Set at most one of them.

Inspect confirmed resources

After a sandbox starts, inspect the confirmed resource allocation. This example uses unequal requests and limits on CKS. Complete the CKS setup and set CWSANDBOX_API_KEY to a CoreWeave API access token. Replace [RUNNER-ID] with the ID of a CKS runner that has GPU capacity and a policy that permits these resources:

from cwsandbox import AuthStrategy, ResourceOptions, Sandbox

with Sandbox.run(
    auth=AuthStrategy.COREWEAVE_API_KEY,
    placement_mode="cks",
    runner_ids=["[RUNNER-ID]"],
    resources=ResourceOptions(
        requests={"cpu": "500m", "memory": "512Mi"},
        limits={"cpu": "2", "memory": "2Gi"},
        gpu={"count": 1},
    ),
) as sb:
    print(sb.resource_requests)  # {"cpu": "500m", "memory": "512Mi"}
    print(sb.resource_limits)    # {"cpu": "2", "memory": "2Gi"}
    print(sb.resource_gpu)       # {"count": 1}

Configuration library interop

All configuration types (NetworkOptions, Secret, ResourceOptions) accept either the dataclass or a plain dict. This means ML configuration libraries that resolve configs to dicts or dict-like objects can pass values directly to the SDK without manual conversion. SandboxDefaults.from_dict() accepts a plain dict or an OmegaConf DictConfig and coerces nested fields automatically. It converts network and secret configurations to their SDK types and resource mappings to plain dicts. The SDK normalizes those resource dicts to ResourceOptions when it constructs a sandbox.

# sandbox.yaml
container_image: "pytorch/pytorch:2.8.0-cuda12.8-cudnn9-runtime"
max_lifetime_seconds: 3600
tags:
  - training
  - experiment-42
resources:
  requests:
    cpu: "4"
    memory: "8Gi"
  limits:
    cpu: "4"
    memory: "8Gi"
  gpu:
    count: 1
network:
  egress:
    - dns_name: "pypi.org"
    - dns_name: "files.pythonhosted.org"
environment_variables:
  LOG_LEVEL: "info"

from sandbox_auth import AUTH
from omegaconf import OmegaConf
from cwsandbox import Sandbox, SandboxDefaults

cfg = OmegaConf.load("sandbox.yaml")
defaults = SandboxDefaults.from_dict(cfg)

with Sandbox.run(defaults=defaults, auth=AUTH) as sb:
    result = sb.exec(["python", "train.py"]).result()

Individual fields also accept dicts when you pass them directly to Sandbox.run() or session.sandbox(). The nested dict form for resources maps to ResourceOptions fields. The flat dict form ({"cpu": "1", "memory": "1Gi"}) sets matching CPU and memory requests and limits for the workload container. The Guaranteed QoS requirements still apply to every container in the Pod.

Mounted files

Mounted files let you provide configuration files, scripts, or other read-only assets to the sandbox at startup, without baking them into a container image.

from sandbox_auth import AUTH
sandbox = Sandbox.run(
    mounted_files=[
        {
            "mount_path": "/app/config.json",
            "file_content": b'{"debug": true}',
        },
        {
            "mount_path": "/app/script.py",
            "file_content": b"print('hello')",
        },
    ],
    resources={"cpu": "1", "memory": "1Gi"},
    auth=AUTH,
)

# Files are available immediately
result = sandbox.exec(["python", "/app/script.py"]).result()

Mount options

Field	Type	Description
`mount_path`	`str`	Absolute path in sandbox.
`file_content`	`bytes`	File content.

Mounted files are read-only. Use write_file() for files that require modification.

Ports

Declare ports with services=[Service(...)]. A declaration such as Service(port=8080, name="web"), with neither visibility nor endpoint set, remains container-local and doesn’t request external exposure. To serve HTTP to internet clients, request a public HTTPS endpoint. This example runs on serverless capacity, starts an HTTP server on port 8080, and requests its assigned HTTPS URL from your local machine. The platform terminates TLS and forwards HTTP to the container port. The example uses EndpointAuth.OPEN, so anyone with the URL can access it without a credential. It uses the demonstration container’s /tmp directory as its document root. The credential used with auth=AUTH authorizes sandbox creation and deletion. It isn’t required for requests to this OPEN endpoint.

import time
from urllib.error import URLError
from urllib.request import urlopen

from sandbox_auth import AUTH
from cwsandbox import (
    Endpoint,
    EndpointAuth,
    EndpointKind,
    Sandbox,
    Service,
    ServiceProtocol,
    ServiceVisibility,
)

sandbox = Sandbox.run(
    "python", "-m", "http.server", "8080", "--directory", "/tmp",
    container_image="python:3.11",
    placement_mode="serverless",
    services=[
        Service(
            port=8080,
            name="web",
            protocol=ServiceProtocol.TCP,
            visibility=ServiceVisibility.PUBLIC,
            endpoint=Endpoint(kind=EndpointKind.HTTPS, auth=EndpointAuth.OPEN),
        ),
    ],
    resources={"cpu": "1", "memory": "1Gi"},
    max_lifetime_seconds=300,
    auth=AUTH,
)

try:
    deadline = time.monotonic() + 120
    while time.monotonic() < deadline:
        sandbox.get_status()
        if sandbox.service_urls:
            url = sandbox.service_urls[0][2]
            try:
                with urlopen(url, timeout=10) as response:
                    body = response.read().decode("utf-8")
                    assert response.status == 200
                    assert "Directory listing for /" in body
                    print("HTTP 200: directory listing received")
                    break
            except (URLError, TimeoutError):
                pass  # The URL can appear before the application is ready.
        time.sleep(2)
    else:
        raise TimeoutError("The HTTPS service did not become reachable")
finally:
    Sandbox.delete(sandbox.sandbox_id, auth=AUTH).result()

The script retries while the URL and HTTP server become ready, prints HTTP 200: directory listing received on success, and deletes the sandbox after the access attempt. The 5-minute lifetime also bounds how long it can run.

Service fields

Field	Type	Description
`port`	`int`	Port the workload listens on inside the sandbox.
`name`	`str \| None`	Optional service name. Must be unique within the sandbox.
`protocol`	`ServiceProtocol \| str \| None`	Layer 4 protocol. Defaults to TCP. Must be TCP or unset when `endpoint` is set.
`visibility`	`ServiceVisibility \| str \| None`	Reachability setting. Must be `PUBLIC` when `endpoint` is set. Plain services can also use `PRIVATE`, `PUBLIC`, or `CUSTOM`. Their reachability depends on the deployment.
`endpoint`	`Endpoint \| dict \| None`	Optional public HTTPS or TLS passthrough endpoint. Visibility alone doesn’t request an HTTPS URL or TLS passthrough address.

A plain service has no endpoint value. For rules about combining plain services and endpoints in one sandbox, see Declare an endpoint. For HTTPS, EndpointAuth.OPEN allows unauthenticated access. EndpointAuth.SHARE_TOKEN requires a share token returned at creation, Python SDK 1.16.0 or later, and a deployment that supports share-token HTTPS. TLS passthrough leaves endpoint authentication unset. Your workload handles TLS termination and access control. See Public endpoints for endpoint routing and authentication. The generated Service reference and Endpoint reference describe SDK version 1.14.2, which supports OPEN but predates SHARE_TOKEN.

Network

Configure outbound and inbound traffic using the NetworkOptions dataclass or a plain dict. Egress and ingress rules grant access over a default-deny baseline. A nonempty egress list replaces the runner policy’s default destination grants. Hostname grants require a runner that supports hostname-based HTTPS egress and a policy that permits every requested destination. For CKS placement, ask your administrator to check the runner’s network constraints. For serverless placement, CoreWeave manages the pool and its policy. If the pool rejects these hostname rules, contact CoreWeave support. To download packages from PyPI, allow both pypi.org for the package index and files.pythonhosted.org for package files. The pypi.org and *.pypi.org grants don’t cover files.pythonhosted.org:

from sandbox_auth import AUTH
from cwsandbox import EgressRule, NetworkOptions, Sandbox

# Using NetworkOptions
sandbox = Sandbox.run(
    network=NetworkOptions(
        egress=[
            EgressRule(dns_name="pypi.org"),
            EgressRule(dns_name="*.pypi.org"),
            EgressRule(dns_name="files.pythonhosted.org"),
        ],
    ),
    resources={"cpu": "1", "memory": "1Gi"},
    auth=AUTH,
)

# Using dict
sandbox = Sandbox.run(
    network={
        "egress": [
            {"dns_name": "pypi.org"},
            {"dns_name": "*.pypi.org"},
            {"dns_name": "files.pythonhosted.org"},
        ],
    },
    resources={"cpu": "1", "memory": "1Gi"},
    auth=AUTH,
)

Both forms are equivalent: the SDK automatically converts dicts to NetworkOptions internally.

NetworkOptions fields

Field	Type	Description
`deny_egress`	`bool \| None`	When `True`, suppresses default and declared egress destination grants. DNS access is controlled separately and remains allowed unless the policy denies DNS. Can’t be combined with a nonempty `egress` list. An empty list is accepted.
`deny_ingress`	`bool \| None`	When `True`, denies ingress to `CUSTOM`-visibility ports instead of applying the runner policy default.
`egress`	`Sequence[EgressRule \| dict] \| None`	Egress grants. A DNS name grants HTTPS (TCP 443) only.
`ingress`	`Sequence[IngressRule \| dict] \| None`	Ingress sources for `CUSTOM`-visibility ports.

All fields are optional and default to None, which leaves the runner policy default in effect. For every EgressRule and IngressRule field, see Network rules.

Set network in SandboxDefaults

Set a default network configuration for all sandboxes:

from sandbox_auth import AUTH
from cwsandbox import EgressRule, NetworkOptions, SandboxDefaults, Session

defaults = SandboxDefaults(
    network=NetworkOptions(
        egress=[
            EgressRule(dns_name="pypi.org"),
            EgressRule(dns_name="files.pythonhosted.org"),
        ],
    ),
    resources={"cpu": "1", "memory": "1Gi"},
)

with Session(defaults, auth=AUTH) as session:
    # All sandboxes inherit the network config
    sb1 = session.sandbox()
    sb2 = session.sandbox()

    # Suppress destination grants for this sandbox. DNS is controlled separately
    sb3 = session.sandbox(network=NetworkOptions(deny_egress=True))

Annotations

Add Kubernetes pod annotations to sandboxes. Annotations are key-value string pairs attached to the underlying pod, useful for integrations that read pod metadata, such as schedulers, cost-allocation tools, or external automation.

from sandbox_auth import AUTH
sandbox = Sandbox.run(
    annotations={
        "team": "ml-infra",
        "experiment": "training-run-42",
    },
    resources={"cpu": "1", "memory": "1Gi"},
    auth=AUTH,
)

Session-level defaults

Set default annotations for all sandboxes in a session:

from sandbox_auth import AUTH
defaults = SandboxDefaults(
    annotations={
        "team": "ml-infra",
        "managed-by": "sandbox-sdk",
    },
    resources={"cpu": "1", "memory": "1Gi"},
)

with Session(defaults, auth=AUTH) as session:
    # Inherits default annotations
    sb1 = session.sandbox()

    # Merge: explicit annotations override defaults on key collision
    sb2 = session.sandbox(
        annotations={"experiment": "run-42", "team": "ml-research"},
    )
    # sb2 receives: team=ml-research, managed-by=sandbox-sdk, experiment=run-42

Merge behavior

When you provide both SandboxDefaults.annotations and per-sandbox annotations, the SDK merges them. Explicit per-sandbox values win on key collision, matching the same semantics as environment_variables.

SUNK integration

To pass Slurm context as pod annotations for SUNK integration, see the SUNK Pod Scheduler integration guide.

Validation

The SDK does not validate annotation keys or values. The server handles validation of reserved key prefixes, value format, and maximum entry count.

Secrets

For Forge team secret injection, authentication requirements, and Python and TypeScript examples, see Use Forge secrets.

Timeouts

Three settings control how long a sandbox and its operations run. The names are similar, so the following table maps each one to what it bounds.

Setting	Bounds	Enforced by	Default
`max_lifetime_seconds`	Total sandbox lifetime before automatic termination	Server	Runner-policy default, or 10 minutes if none is set
`timeout_seconds`	A single `exec()`, `read_file()`, or `write_file()` call	Client	Falls back to `request_timeout_seconds`
`request_timeout_seconds`	Client-side HTTP timeout for most remote procedure calls (RPCs)	Client	300 seconds

Only max_lifetime_seconds terminates a sandbox. The other two bound individual requests and leave the sandbox running.

max_lifetime_seconds

max_lifetime_seconds sets the total wall-clock lifetime of a sandbox. When a sandbox reaches this age, the platform terminates it even if work is still in progress. If you don’t set max_lifetime_seconds, the runner-policy default applies. If no positive policy default supplies a lifetime, the platform uses 10 minutes. Set the value explicitly for long-running work:

from sandbox_auth import AUTH
from cwsandbox import Sandbox

with Sandbox.run(
    max_lifetime_seconds=7200,  # 2 hours
    resources={"cpu": "1", "memory": "1Gi"},
    auth=AUTH,
) as sandbox:
    sandbox.exec(["python", "train.py"], timeout_seconds=7000).result()

To apply one lifetime to every sandbox a session creates, set it in SandboxDefaults:

from sandbox_auth import AUTH
from cwsandbox import Sandbox, SandboxDefaults

defaults = SandboxDefaults(
    container_image="python:3.11",
    max_lifetime_seconds=3600,  # 1 hour
    resources={"cpu": "1", "memory": "1Gi"},
)

with Sandbox.run(defaults=defaults, auth=AUTH) as sandbox:
    sandbox.exec(["python", "-c", "print('working')"]).result()

An explicit max_lifetime_seconds argument on Sandbox.run() takes precedence over the value in defaults. Because the argument’s default is None, you can’t use it to remove a lifetime that defaults already sets. The longest lifetime you can request is 30 days (2,592,000 seconds), for both serverless and CKS placement. The platform rejects larger requests.

You can’t change max_lifetime_seconds after a sandbox starts. No API extends the lifetime of a running sandbox, so choose the value when you create it. To keep working past the limit, capture what you need and start a new sandbox with a lifetime of up to 30 days.

For creation examples and CKS runner-policy defaults, see Run long-running sandboxes.

Behavior when the lifetime expires

The platform enforces the lifetime by terminating the sandbox’s underlying Kubernetes Job, so termination is immediate rather than graceful. Two consequences matter in practice:

Processes inside the sandbox don’t receive the grace period that stop() provides. Anything not already written out is lost.
The client doesn’t receive a distinct error or reason for the termination. The SDK reports no termination reason on a Sandbox, so you can’t distinguish lifetime expiry from other failures programmatically. Track the age of long-lived sandboxes yourself.

Set a lifetime that comfortably exceeds the work you expect, and stop sandboxes explicitly when you finish rather than relying on expiry.

timeout_seconds

timeout_seconds bounds a single operation on a running sandbox:

result = sandbox.exec(
    ["python", "long_script.py"],
    timeout_seconds=300,  # 5 minutes
).result()

This controls how long the client waits for a response. If the wait exceeds the timeout, the SDK raises SandboxTimeoutError. The sandbox keeps running. The clock starts only after the sandbox reaches RUNNING, so startup time doesn’t count against it. Keep timeout_seconds below the sandbox’s max_lifetime_seconds. A command whose timeout exceeds the sandbox’s remaining lifetime stops when the sandbox terminates.

request_timeout_seconds

request_timeout_seconds is the client-side HTTP timeout applied to most RPCs, and it’s the fallback when a call doesn’t pass its own timeout_seconds. Set it in SandboxDefaults:

defaults = SandboxDefaults(
    request_timeout_seconds=600.0,
    resources={"cpu": "1", "memory": "1Gi"},
)

Status polling uses poll_rpc_timeout_seconds instead, so a stalled poll fails fast rather than blocking for the full request timeout. For the full set of client-side tuning options, see the SandboxDefaults reference.

Complete example

The following example combines defaults, per-sandbox overrides, mounted files, and service declarations. It downloads packages from PyPI and imports them to check the installation. The serverless pool must meet the hostname grant requirements. This example declares a service port but doesn’t start a server or create a public endpoint:

from sandbox_auth import AUTH
from cwsandbox import (
    EgressRule,
    NetworkOptions,
    ResourceOptions,
    Sandbox,
    SandboxDefaults,
    Service,
)

defaults = SandboxDefaults(
    container_image="python:3.11",
    max_lifetime_seconds=1800,  # 30 minutes
    tags=("production", "ml-pipeline"),
    resources=ResourceOptions(
        requests={"cpu": "4", "memory": "8Gi"},
        limits={"cpu": "4", "memory": "8Gi"},
    ),
    network=NetworkOptions(
        egress=[
            EgressRule(dns_name="pypi.org"),
            EgressRule(dns_name="*.pypi.org"),
            EgressRule(dns_name="files.pythonhosted.org"),
        ],
    ),
)

with Sandbox.run(
    defaults=defaults,
    mounted_files=[
        {
            "mount_path": "/app/config.yaml",
            "file_content": b"model: gpt-4\nmax_tokens: 1000",
        },
    ],
    services=[
        Service(port=8000, name="api"),
    ],
    auth=AUTH,
) as sandbox:
    # Install dependencies without cached downloads
    sandbox.exec(
        ["pip", "install", "--no-cache-dir", "fastapi", "uvicorn"],
        check=True,
    ).result()

    # Verify the installed dependencies
    result = sandbox.exec(
        ["python", "-c", "import fastapi, uvicorn; print('Dependencies imported')"],
        check=True,
        timeout_seconds=60,
    ).result()
    print(result.stdout)

Sandboxes

Use sandboxes

Manage sandboxes

Reference

Choose authentication

Overview

Resources

ResourceOptions fields

Guaranteed QoS

Burstable QoS

CPU values

Memory values

GPU

Inspect confirmed resources

Configuration library interop

Mounted files

Mount options

Ports

Service fields

Network

NetworkOptions fields

Set network in SandboxDefaults

Annotations

Session-level defaults

Merge behavior

SUNK integration

Validation

Secrets

Timeouts

max_lifetime_seconds

Behavior when the lifetime expires

timeout_seconds

request_timeout_seconds

Complete example

​Choose authentication

​Overview

​Resources

​ResourceOptions fields

​Guaranteed QoS

​Burstable QoS

​CPU values

​Memory values

​GPU

​Inspect confirmed resources

​Configuration library interop

​Mounted files

​Mount options

​Ports

​Service fields

​Network

​NetworkOptions fields

​Set network in SandboxDefaults

​Annotations

​Session-level defaults

​Merge behavior

​SUNK integration

​Validation

​Secrets

​Timeouts

​max_lifetime_seconds

​Behavior when the lifetime expires

​timeout_seconds

​request_timeout_seconds

​Complete example

Choose authentication

Overview

Resources

ResourceOptions fields

Guaranteed QoS

Burstable QoS

CPU values

Memory values

GPU

Inspect confirmed resources

Configuration library interop

Mounted files

Mount options

Ports

Service fields

Network

NetworkOptions fields

Set network in SandboxDefaults

Annotations

Session-level defaults

Merge behavior

SUNK integration

Validation

Secrets

Timeouts

max_lifetime_seconds

Behavior when the lifetime expires

timeout_seconds

request_timeout_seconds

Complete example