Introduction
Getting Started
Sign up
Create your free account in the DataShell portal, using your GitHub credentials to authenticate.
Whitelisting your account
Currently, we are controlling the access to the portal, as a way to better measure the overall platform performance, and gather useful feedback from our early adopters. Please complete the registration process, and we'll notify you once your account gets whitelisted.
Once you get access to the portal, follow the prompts to create a new project. The New Project
dialog will ask for a GitHub repository to associate to your new project, as well as credentials for the data warehouse you will be connecting to.
In order to associate a project to a given repository, you need to install the DataShell GitHub App on that repository, or globally within your GitHub account. You can install the DataShell GitHub App either from the New Project
dialog, of from your User Settings
page. We advise you to start with an empty repository, purposely created to develop your data project.
Now that you are all set on the portal, it's time to setup your local enviroment.
Download and Install the DataShell CLI
You'll be using the DataShell CLI to manage and perform operations on your source code. If you haven't done, please install the DataShell CLI by using the command below:
$ pip install datashell
You'll need to connect your local environment with your account, by using your DataShell API key
. Your API key can be found in your User Settings
page, on the portal.
The DataShell CLI will look for a variable named DATASHELL_API_KEY
on the current environment. You can define the variable and export its value by using the command below:
$ export DATASHELL_API_KEY="<your API key here>"
Clone and Initialize Repository
Get a working copy of your repository in your local environment.
$ git clone <your-repo>
For more options about how to clone your GitHub repository, check the GitHub documentation.
Now, let's initialize your repository by executing the command init
and following the prompts:
$ datashell init
That's it! Now you are ready to leverage DataShell to build data solutions, like a software engineer would.