> For the complete documentation index, see [llms.txt](https://icij.gitbook.io/datashare/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://icij.gitbook.io/datashare/developers/introduction-to-tarentula.md).

# CLI with Tarentula

Datashare Tarentula is a powerful command-line toolbelt designed to streamline bulk operations against any Datashare instance.

Whether you need to count indexed files, download large datasets, batch-tag records, or run complex Elasticsearch aggregations, Tarentula provides a consistent, scriptable interface with flexible query support, and Docker compatibility.

It also exposes a Python API for embedding automated workflows directly into your data pipelines.\
With commands like `count`, `download`, `aggregate`, and `tagging-by-query`, you can handle millions of records in a single invocation, or integrate Tarentula into CI/CD pipelines for reproducible data tasks.

You can install Tarentula with your favorite package manager:

```
pip3 install --user tarentula
```

Or alternatively with Docker:

```
docker run icij/datashare-tarentula
```

For the complete list of commands, options, and example, read the documentation or Github:

{% embed url="<https://github.com/ICIJ/datashare-tarentula>" %}


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

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

Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters:

```
GET https://icij.gitbook.io/datashare/developers/introduction-to-tarentula.md?ask=<question>&goal=<user_goal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case.

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.