---
title: Using uv with Coiled
description:
  A complete guide to using uv with Coiled to manage Python dependencies and deploy serverless
  scripts.
---

# Using uv with Coiled

[Coiled](https://coiled.io?utm_source=uv-docs) is a serverless, UX-focused cloud computing platform
that makes it easy to run code on cloud hardware (AWS, GCP, and Azure).

This guide shows how to run Python scripts on the cloud using uv for dependency management and
Coiled for cloud deployment.

## Managing script dependencies with uv

!!! note

    We'll use this concrete example throughout this guide, but any Python script can be used with
    uv and Coiled.

We'll use the following script as an example:

```python title="process.py" hl_lines="1-8"
# /// script
# requires-python = ">=3.12"
# dependencies = [
#   "pandas",
#   "pyarrow",
#   "s3fs",
# ]
# ///

import pandas as pd

df = pd.read_parquet(
    "s3://coiled-data/uber/part.0.parquet",
    storage_options={"anon": True},
)
print(df.head())
```

The script uses [`pandas`](https://pandas.pydata.org/docs/) to load a Parquet file hosted in a
public bucket on S3, then prints the first few rows. It uses
[inline script metadata](https://peps.python.org/pep-0723/) to enumerate its dependencies.

When running this script locally, e.g., with:

```bash
$ uv run process.py
```

uv will automatically create a virtual environment and installs its dependencies.

To learn more about using inline script metadata with uv, see the
[script guide](../scripts.md#declaring-script-dependencies).

## Running scripts on the cloud with Coiled

Using inline script metadata makes the script fully self-contained: it includes the information that
is needed to run it. This makes it easier to run on other machines, like a machine in the cloud.

There are many use cases where resources beyond what's available on a local workstation are needed,
e.g.:

- Processing large amounts of cloud-hosted data
- Needing accelerated hardware like GPUs or a big machine with more memory
- Running the same script with hundreds or thousands of different inputs, in parallel

Coiled makes it simple to run code on cloud hardware.

First, authenticate with Coiled using
[`coiled login`](https://docs.coiled.io/user_guide/api.html?utm_source=uv-docs#coiled-login) :

```bash
$ uvx coiled login
```

You'll be prompted to create a Coiled account if you don't already have one — it's free to start
using Coiled.

To instruct Coiled to run the script on a virtual machine on AWS, add two comments to the top:

```python title="process.py" hl_lines="1-2"
# COILED container ghcr.io/astral-sh/uv:debian-slim
# COILED region us-east-2

# /// script
# requires-python = ">=3.12"
# dependencies = [
#   "pandas",
#   "pyarrow",
#   "s3fs",
# ]
# ///

import pandas as pd

df = pd.read_parquet(
    "s3://coiled-data/uber/part.0.parquet",
    storage_options={"anon": True},
)
print(df.head())
```

!!! tip

    While Coiled supports AWS, GCP, and Azure, this example assumes AWS is being used
    (see the `region` option above). If you're new to Coiled, you'll automatically have
    access to a free account running on AWS. If you're not running on AWS, you can either use
    a valid `region` for your cloud provider or remove the `region` line above.

The comments tell Coiled to use the official [uv Docker image](../integration/docker.md) when
running the script (ensuring uv is available) and to run in the `us-east-2` region on AWS (where
this example data file happens to live) to avoid any data egress.

To submit a batch job for Coiled to run, use
[`coiled batch run`](https://docs.coiled.io/user_guide/api.html?utm_source=uv-docs#coiled-batch-run)
to execute the `uv run` command in the cloud:

```bash hl_lines="1"
$ uvx coiled batch run \
    uv run process.py
```

The same process that previously ran locally is now running on a remote cloud VM on AWS.

You can monitor the progress of the batch job in the UI at
[cloud.coiled.io](https://cloud.coiled.io) or from the terminal using the `coiled batch status`,
`coiled batch wait`, and `coiled batch logs` commands.

![Coiled UI](https://docs.coiled.io/_images/uv-coiled.png)

Note there's additional configuration we could have specified, e.g., the instance type (the default
is a 4-core virtual machine with 16 GiB of memory), disk size, whether to use spot instance, and
more. See the
[Coiled Batch documentation](https://docs.coiled.io/user_guide/batch.html?utm_source=uv-docs) for
more details.

For more details on Coiled, and how it can help with other use cases, see the
[Coiled documentation](https://docs.coiled.io?utm_source=uv-docs).