From the course: End-to-End Data Engineering Project

Project setup

From the course: End-to-End Data Engineering Project

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Project setup

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- [Instructor] Now let's roll up our sleeves and dive right in. First, go to the project repo in GitHub and let's create a fork. Forking generates your own copy of the repo in GitHub. Your own copy means that you will be able to contribute changes to your own repo without affecting the original one. Now uncheck the Copy the main branch only. So you bring all the branches and then click on Create fork. And now let's clone the project repo in our local machine. In your fork repo, click on the Code section and then copy the HTTPS URL. And now let's go to the terminal. Start by typing git clone, and then paste the URL we just copied. Next, navigate into the newly created directory and let's open the project in Visual Studio Code. Now let's create a Python Virtual Environment. The environment will help manage the project dependencies separately from any other Python projects you may have. Open a terminal in Visual Studio Code and then create the environment with the following command. Now let's activate our environment. And next, let's select a Python interpreter for our project. Open the command palette, and look for Python Select Interpreter, and choose the one that is tied to our virtual environment. Our last step is to install the project dependencies. To do that, execute the following command. This will install all the project dependencies. It is possible that after installing all these dependencies, you will still see an error saying that dbt is not installed. You can fix this by restarting Visual Studio Code and we are all set. Our Python Project Environment is set up and ready to go.

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