.. highlight:: sh

Accessing data
==============

Uploading a new dataset
-----------------------

Click on the `Datasets` button in the tab on the left-hand side of your
workspace.  This will lead you to the `Datasets` page:

.. thumbnail:: images/datasets_page.png

Select the directory where you would like to upload data and click the `Upload
file` button at the top of the page.

.. thumbnail:: images/upload_file_icon.png

A dialog box will appear and selecting `Choose file` will direct you to a file
picker. Pick the file you wish to upload and confirm your choice by clicking `Upload`.

Moving data to the workspace
----------------------------

Files can be moved from the `Datasets` page to the workspace using the
`faculty.datasets` Python package.

For example, you can move a `data.csv` file from the `input` folder in
datasets to the workspace by opening a notebook and using:

.. code-block:: python

   import faculty.datasets as datasets

   datasets.get('/input/data.csv', 'data.csv')

For a detailed explanation of SFS check out this :ref:`quickstart tutorial <getting-started-datasets>`.

Downloading data
----------------

Files can be downloaded from the workspace into your local computer by using
Faculty's command line interface `faculty`. To find out how to install this
utility, take a look at this :ref:`quickstart tutorial <command-line-interface>`.

As a first step, you need to sign into Faculty from the terminal of your
local computer, via `faculty`. Then, you make a note of the path in Faculty
corresponding to the file that you wish to download (e.g.
:code:`path/on/faculty`). In addition, you select the path for the directory
on your computer where files will be placed (e.g.  :code:`path/on/local`).
Finally, in the terminal of your local machine you run:

.. code-block:: bash

   $ faculty file get project path/on/faculty path/on/local

Here, :code:`project` is the name of the project that contains the file.