Google IDX (Integrated Development Experience) is a cloud-based integrated development environment (IDE) provided by Google, designed to simplify the setup, management, and collaboration of projects entirely in the cloud. IDX shows promising potential to establish itself over time, offering an intriguing cloud alternative similar to Visual Studio Code or Anaconda.
Jupyter Notebooks are widely used for interactive computing and data analysis, ideal for tasks ranging from data exploration to developing machine learning models. Setting up your environment in Google IDX for Jupyter Notebooks or Python projects is straightforward and provides the advantage of cloud-based programming.
- Go to https://idx.dev/ and get started.
- Click on "See all templates".
- Select "Misc".
- Click on "Blank Workspace".
- Name your workspace and create it.
- In IDX, navigate to
.idx/dev.nixand enable:pkgs.python311pkgs.python311Packages.pip
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Click on "Rebuild Environment".
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Open a new terminal (Ctrl+Shift+` ) to verify the Python version and installed packages with pip
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Create and activate a virtual environment (venv).
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Install Python libraries/frameworks/dependencies using pip in the terminal.
- Create a jupyter notebook by clicking
new fileicon on explorer panel and select the kernel (venv). Allow to install the Jupyter extensions.
- Write code directly or ask Gemini (Ctrl + i) to assist and run it.
- Some dependencies may install the first time you run the code.
Now You have a basic python cloud-environment on Google IDX ready for developing jupyter notebooks or python scripts.
Take a look at a machine learning project I developed at IDX a couple of weeks ago: https://github.com/ScinDBad/churn_prediction_fitness
open Developer Tools and you will likely see the same issues I wrote about earlier this week