Getting Started with Moose
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Open Docker Desktop if its not already running.
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Create and Activate a Virtual Environment
Navigate to the directory where you want to create your Moose project, then run:
python3 -m venv .venv && source .venv/bin/activate
Install Moose CLI
In your virtual environment, run:
pip install moose-cli
Create an Empty Moose Project
moose-cli init moose-github-analytics python --empty
npx create-moose-app@latest moose-github-analytics ts --empty
This Moose CLI helper function creates a new Moose app with the proper conventions for the basic directory structure. This includes an /app
folder which contains the heart of your new Moose app. Each sub-folder hosts one type of Moose primitive.
cd
into your Moose Project and Install Dependencies
cd moose-github-analytics && pip install -e .
cd moose-github-analytics && npm install
Run the Moose Development Server
moose-cli dev
npm run dev
You must be in your project directory in order to start the development server
You should expect to see the following printed to your terminal:
You have set up a Moose instance at http://localhost:4000
It provides the following infrastructure:
- OLAP Database (Clickhouse) to store and analyze your data
- Streaming Data Platform (Redpanda) to buffer and transform incoming data
- Ingestion and Consumption APIs to get data in and out of your database
As you develop, the dev server automatically updates with your latest changes, providing a real-time view of your Moose application locally.
Open Project in IDE
With VSCode, for example:
code .
Click 'Install' on the pop-up window located in the bottom right corner of the screen. Moose will automatically configure these extensions for you.