# Using Valohai Ecosystem Libraries

Valohai maintains a collection of pre-built library steps for common workflows. These are production-ready and available to all organizations.

## Available libraries

### Database Connectors

Run SQL queries and save results to your data store:

* [BigQuery Connector](/reusable-step-libraries/ecosystem-libraries/bigquery.md)
* [AWS Redshift Connector](/reusable-step-libraries/ecosystem-libraries/redshift.md)
* [Snowflake Connector](/reusable-step-libraries/ecosystem-libraries/snowflake.md)

All database connectors:

* Accept SQL queries as parameters
* Save results as CSV outputs
* Support both credential-based and machine identity authentication
* Automatically version query results in your data store

### Docker Image Builder

Build and push Docker images without installing Docker locally:

* [Docker Image Builder](/reusable-step-libraries/build-your-own-library/docker-image-builder.md)

Supports AWS ECR, GCP Artifact Registry, and Docker Hub.

## How to use ecosystem libraries

Ecosystem libraries are automatically available in your organization. No setup required.

### Run a library step

1. Open your project
2. Click **Create Execution** under the Executions tab
3. Expand the step library by clicking the **+** next to **valohai-ecosystem** in the left panel
4. Select a library step (e.g., `bigquery-query`)
5. Configure parameters and environment variables
6. Click **Create Execution**

Library steps run like any other execution—same logs, same outputs, same metadata tracking.

## Example: Query BigQuery

Let's run a BigQuery query and save the results:

### Add environment variables

Under your project Settings or as an organization-wide environment variable group:

* `GCP_PROJECT` — Your GCP project ID
* `GCP_IAM` — Set to `1` to use machine identity, or `0` for keyfile auth
* `GCP_KEYFILE_CONTENTS_JSON` — (If using keyfile) Service account JSON

### Create the execution

1. Select the `bigquery-query` step from **valohai-ecosystem**
2. Write your SQL query in the **query** parameter:

```sql
SELECT user_id, COUNT(*) as events
FROM `my-project.analytics.events`
WHERE date >= '2025-01-01'
GROUP BY user_id
ORDER BY events DESC
LIMIT 100
```

3. (Optional) Set an output path like `top_users.csv`
4. (Optional) Add a datum alias like `latest-user-stats` for easy reference
5. Click **Create Execution**

The query runs on BigQuery, and results are saved to your data store. Use the output in other executions with `datum://latest-user-stats`.

## Why use ecosystem libraries?

**No setup needed:** No YAML to write, no Git repository to manage. Just run.

**Battle-tested:** These steps are maintained by Valohai and used across hundreds of organizations.

**Versioned results:** Query outputs are automatically tracked and versioned in your data store.

**Consistent patterns:** All connectors work the same way—write a query, get a CSV. Easy to learn once and reuse everywhere.

## Next steps

**Database connectors:**

* [BigQuery](/reusable-step-libraries/ecosystem-libraries/bigquery.md)
* [AWS Redshift](/reusable-step-libraries/ecosystem-libraries/redshift.md)
* [Snowflake](/reusable-step-libraries/ecosystem-libraries/snowflake.md)

**Build custom images:**

* [Docker Image Builder](/reusable-step-libraries/build-your-own-library/docker-image-builder.md)

**Create your own:**

* [Build Your Own Library](/reusable-step-libraries/build-your-own-library.md)


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.valohai.com/reusable-step-libraries/ecosystem-libraries.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.