Pydantic AI with Lizard Sandboxes
Lizard (lizard.build) runs agent commands and files in cloud sandboxes. This package supplies a Pydantic AI workspace through the Lizard SDK. It works with workspace tools, including Pydantic AI Harness's Shell, FileSystem, and Coder.
Install
Requires Python 3.11 or later and Pydantic AI 2.57 or later.
pip install pydantic-ai-lizard pydantic-ai-harness 'pydantic-ai-slim[openai]'
Create a project and API key at lizard.build. Set LIZARD_API_KEY and LIZARD_PROJECT_ID on the host. Set OPENAI_API_KEY for the example below. Keep credentials out of prompts and source control.
Run an agent
import asyncio
from pydantic_ai import Agent
from pydantic_ai_harness.filesystem import FileSystem
from pydantic_ai_harness.shell import Shell
from pydantic_ai_lizard import LizardSandboxBackend
async def main():
workspace = LizardSandboxBackend(lifetime_ms=600_000)
agent = Agent("openai:gpt-5", capabilities=[Shell(), FileSystem()])
try:
result = await agent.run(
"Use Python to compute the first ten Fibonacci numbers and save them to fib.txt.",
workspace=workspace,
)
print(result.output)
print(workspace.ref)
finally:
await workspace.destroy()
asyncio.run(main())
No API call happens in the constructor. The first operation creates one sandbox, even when tools start at the same time. Commands run as root in the interpreter template, with /workspace as the default working directory. env= contains only values you pass; the adapter never copies host environment variables into the sandbox.
Reconnect and retain state
Save backend.ref after first use. Pass it to LizardSandboxBackend(ref=ref) to reconnect from a later run. An unknown or expired reference raises WorkspaceUnavailableError; it never creates a replacement. A run ending does not delete its workspace. Call await backend.destroy() when you no longer need it. The default lifetime is one hour; expiration discards the sandbox and its files.
You can also add LizardSandbox() to an agent's capabilities. It supplies the workspace, while Shell, FileSystem, or your own tools use it. LizardSandbox.backend(ref) builds a backend for a saved reference, and await LizardSandbox().destroy(ref) releases it. Deferred loading is unsupported because Pydantic AI selects the workspace before loading deferred tools.
Behavior and limits
- Uses asyncio. The supported sizes are
small,medium, andlarge. - Implements
WorkspaceBackend,SupportsCommands,SupportsFilesystem, andSupportsRealpath. Binary file transfers use the Lizard SDK; guest helpers preserve path errors, symlink behavior, and file metadata. - Pass an argv list for literal arguments, or a string with
shell=Truefor shell syntax. - A nonzero exit returns
CommandResult. Missing programs exit 127. Invalid UTF-8 becomes the replacement character. - A timeout raises
WorkspaceTimeoutErrorwith partial output. Cancellation stops the foreground process group on a best-effort basis. Detached background jobs may continue until cleanup or expiration. - Captures up to 10 MiB per output stream. Larger output raises
WorkspaceOutputLimitError; it never reports truncated output as a successful result. Output uses files inside the sandbox while the command runs. - Does not configure network isolation, install custom images, resume paused sandboxes, or renew a sandbox's lifetime on reconnect. Commands can reach the network. A paused sandbox must be resumed through the Lizard SDK before attaching.
- Commands can access the whole guest filesystem. The sandbox is the host isolation boundary; a working directory is not an access-control boundary.
- The API key stays on the host. Commands, files, and explicitly supplied environment values go to Lizard. See privacy and pricing.
Test
pip install -e '.[dev]'
ruff check .
ruff format --check .
mypy src
pytest tests -m 'not live' --disable-socket --allow-unix-socket
python -m build
twine check dist/*
Set LIZARD_API_KEY, LIZARD_PROJECT_ID, and LIZARD_LIVE_TESTS=1, then run pytest tests -m live to run Pydantic AI's WorkspaceBackendSuite against temporary cloud sandboxes. Cloud tests use billed resources and clean up sandboxes they create. The fixed lifetime bounds resources left by a lost connection.
Source: lizard-build/integrations. Report bugs in the repository's issue tracker. Lizard maintains this package; Pydantic AI reviews catalog submissions separately.
Metadata
Release files for pydantic-ai-lizard 0.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| pydantic_ai_lizard-0.1.0.tar.gz | 16.6 kB | With provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| pydantic_ai_lizard-0.1.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 31.7 kB
Release files / pydantic_ai_lizard-0.1.0.tar.gz
| Download URL | pydantic_ai_lizard-0.1.0.tar.gz |
|---|---|
| Size | 16.6 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
2d49b3993e715852da11fa600e49e48c25f1fcf5933bbe52b9ade32eacf025b1
|
|
BLAKE2b-256 checksum How to use checksums |
2bdb4e59548f1c8bfbe775dab4e5e7240d5eaa4e8a4bdad9d94b87748c549b50
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 20, 2026.
Transparency logRelease files / pydantic_ai_lizard-0.1.0-py3-none-any.whl
| Download URL | pydantic_ai_lizard-0.1.0-py3-none-any.whl |
|---|---|
| Size | 15.1 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
7c53922842e9f84c0fa9686937c5d829f985ef24337a73ae2e19feac8dc3d07e
|
|
BLAKE2b-256 checksum How to use checksums |
913e413c1355bc3aa9875403e0fc0cfac1fcdecb8740ddf84ab48de101077041
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 20, 2026.
Transparency logSecurity for pydantic-ai-lizard 0.1.0
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
Full provenance
All 2 files in this release have been uploaded with provenance metadata.
Attestation for pydantic_ai_lizard-0.1.0.tar.gz
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 20, 2026.
Transparency logA note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.