# Query and Download Contributed Data

## Interactively

{% hint style="danger" %}
Under Construction. We are working on enabling CSV/JSON download buttons for entire projects or specific queries. The downloads will also function as versioned snapshots for each project.
{% endhint %}

## Programmatically

Querying MPContribs data programmatically involves the following steps:

* Install the python package [mpcontribs-client](https://pypi.org/project/mpcontribs-client/).
* Initialize the client with your API key and a project
* Check `client.available_query_params()` for available query parameters
* Build up a query dictionary
* Decide which fields to retrieve
* Run `client.query_contributions()`

Here's an example for the `carrier_transport` dataset:

```graphql
from mpcontribs.client import Client
client = Client(apikey="your-api-key-here", project="carrier_transport")
client.available_query_params()  # print list of available query parameters
query = {"formula__contains": "Au", "data__PF__p__value__lt": 10}
fields = ["identifier", "formula", "data.metal", "data.S.n.value"]
data = client.query_contributions(
    query=query, fields=fields, sort="-data.S.n.value", paginate=True
)
```

By default, `paginate` is `False` which will only retrieve the first page of results and should be used to test the `query`, `fields` and `sort` parameters before paginating through all results.

If entire projects or large subsets of contributed data are downloaded for later use, it is often more efficient to use the `client.download_contributions()` function. It also takes a `query` as argument and downloads all results as `json.gz` files behind the scenes. Only locally missing data is downloaded when `download_contributions` is run and contributions are loaded from disk. This function always retrieves all fields included in the `data` component, so the `fields` argument is not available/needed. Additional components (i.e. `structures`, `tables`, and `attachments`) can be included in the downloads through the `include` argument:

```graphql
data = client.download_contributions(query=query, include=["tables"])
```


---

# 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.materialsproject.org/downloading-data/query-and-download-contributed-data.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.