You should test this by closing VSCode, then opening the jaffle_shop repo Extensions dbtenv and each line should begin with (.dbtenv) any terminal you open will auto-activate your.the Python extension activates right away (do you see the Python version listed alongside your environment name on the bottom info bar?).Now that you’ve done these two things, everytime you open the jaffle_shop/ dir, in VSCode two things should happen: "python.pythonPath": "./.dbtenv/bin/python", vscode/settings.json and add the Python path to the settings.json (more on VSCode settings later!) (optional) add to the requirements.txt what packages w/ versions you plan to do in this project (example below).add a requirements.txt to you the top level of the repo ( pip docs on requirements.txt files).To make this auto-env selection persist, you must do two things: However, this behavior will not persist the next time you open this repo in VSCode. This is huge because now all your terminals in the VSCode will always have your dbt package available. ensure that all new terminals opened in VSCode will auto-activate your.activate the Python extension if it hasn’t been already.dbtenv environment (should be the first result) search for “Python: Select Interpreter”, and.bring up the command pallette ( CMD+SHIFT+P).Once you’ve done this you should now be able to: # make Git ignore all these newly created files Pip install dbt-synapse # or dbt-sqlserver or whatever # Create and activate virtual environment Open a terminal with `CTRL+`` (which should open within the jaffle_shop directory) and do the following steps: # make sure you have Python at least 3.6 and less than 3.10 I’m going to only talk about venv because it comes built-in with Python Our team uses conda envs because we have many different projects with different sets of package requirements, but if dbt is 1) your only use case for Python, or 2) your first Python-based use case, you’ll likely have a better time with virtualenvs. Three popular tools are venv's, virtualenv's and conda environments. It’s better practice to have a dedicated dbt environment. You OS likely already has a version of python installed, but this can be troublesome because you don’t control it’s version. Python can be tricky get working in VSCode (and trickier to work on Windows). Some folks deem this problem so difficult as to justify having users use Docker containers, but I have yet to be convinced of that yet. More context is that some folks have bundled this set up process into bash scripts and Docker containers. Sounds simple, but below is a one-time setup guide on how to make it work. The goal of this section is to ensure that the right version of Python and dbt are always available right away when you open your dbt project in VSCode. Then, open the jaffle_shop/ directory in VSCode. You can use the Git CLI or the VSCode Git extension to Git Clone command in VSCode git clone To get started, we’ll use the jaffle_shop repo, a self-contained project. vscode directory that contains a settings.json and an extensions.json Getting started In VSCode you’ll also need to install the Python extension If you already know VSCode You should also have the following installed: It covers a lot of the basics like installing Python, the Python extension, and the command pallette. If you’ve never used VSCode with Python, I strongly recommend at least the first half of Dan Taylor’s Get Productive with Python in Visual Studio Code talks.
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