DataDock is a web file system designed for use by researchers and data scientists. It is essentially a file transfer system with a social media and market aspect. Researchers or data scientists can perform CRUD operations on data, and can also assess the validity of data by creating posts on data sets or ML models or by rating data sets or ML models.

Please note that DataDock used to be called Delta. We are working on renaming the files accordingly. At the moment, there may be some directories / files with Delta in the name.

Please adhere to the guidelines for JavaScript and Python found here

Note the following instructions are designed for *nix machines.

To run, first clone the repository by running: git clone https://github.com/SCCapstone/DataDock

Then cd into DataDock.

You should have installed pipenv. Install following https://pipenv.pypa.io/en/latest/install/ or some other resource online.

When installed, you should be able to run pipenv sync to sync the pipenv file, and then pipenv install to install dependencies.

To run the backend, cd into delta_web with cd delta_web. Change directory into delta with cd delta.

The currect working directory should be something like: [OTHER_DIRECTORIES]/DataDock/delta_web/delta/

Then run pipenv run python3 manage.py runserver. Now the backend should be running.

To set up npm, from the same directory as prior cd into frontend. Install the necessary JavaScript requirements with npm i.

On terminal two, type: npm run dev to begin the front end server.

To view the website, open up a browser and type in the url localhost:8000. You should be directed to a login screen.

In order to build this project, you will first have to install:

• The latest version of Node.js: https://nodejs.org/en/download/
• You can run sudo apt update then sudo apt install nodejs npm
• See here
• The latest version of Python: https://www.python.org/downloads/
• You can run sudo apt update then sudo apt install python3
• See here

Testing the DataDock application includes more than a dozens unit and behavioral tests. To accomplish this, we use a combination of testing libraries, which are listed below.

For behavioral tests we use Jest.

For unit tests we use the standard Django testing framework. You can read more on that here

All unit tests are found in subdirectories of the the delta directory /DataDock/delta_web/delta

Be sure to be in this directory when running the following commands to perform unit tests.

To run the whole test suite, type pipenv run python3 manage.py test. From there the terminal will show what tests are found, what pass, and what warnings or errors are shown. You may also run individual unit tests or directories.

Whole test suite: pipenv run python3 manage.py test

Test directory: pipenv run python3 manage.py test accounts/

A specific test: pipenv run python3 manage.py test [directory_name.test_directory_name.TestCaseName.specific_test_name] i.e. pipenv run python3 manage.py test accounts.tests.RegistrationTestCase.test_registration

Unit tests run against APIs in the following sub-directories:

• accounts/ -- This is under the tests.py file.
• data/ -- This is under the tests.py file.
• organizations/ -- This is under the tests.py file.
• social/ -- This is slightly different and under the tests folder. Within this folder are the test models (test_models.py), the test setup (test_setup.py) and the test views (test_views.py).

Behavioral tests are performed using Jest. You can read more on how Jest is used with React here.

All the behavioral tests can be found in /DataDock/delta_web/delta/frontend/tests/

When running behavior tests, be sure to be in the following directory:

/DataDock/delta_web/delta/frontend/

To run the tests, from the above directory type npm run coverage.

From there the terminal will show what tests are found, what pass, and what warnings or errors are shown.

Note that when making a behavioral test with Jest the JS file must have a .test.js extension.

• DataDock is an ambitious project. As such, there are many things that can be added. Please feel free to open an issue for something you think may be useful. This is intended to be a community project.