Installation¶

Setting Up Your Development Environment¶

To get started with using canari-ml, you will need to have Python set-up on your system. This guide walks you through creating either a Mamba/Conda environment or a virtual environment using venv, and installing the latest development versions of the codebase directly from Git. In future, this will be directly installable via pip.

Creating a Virtual Python Environment¶

Using Mamba/Conda¶

Install Miniforge3 (if not already installed):

Follow instructions for your system from the official Miniforge3 GitHub page.
Create and activate a new environment:

You can replace the mamba command with conda if you prefer.
```
mamba create -n canari_ml python=3.11 -y
mamba activate canari_ml
```

Using Python's venv¶

Create a virtual environment:
```
python -m venv venv
```
This requires Python to already be installed on your system. You could use the Python installed by the OS, by MiniForge, or any other approach.

Activate the virtual environment:

macOS/LinuxWindows

source venv/bin/activate

.\venv\Scripts\activate.bat

Installing Canari-ML from Git¶

Install latest default branch directly using pip¶

pip install git+https://github.com/CANARI-ML/canari-ml@main

To install a specific tagged version:

pip install git+https://github.com/CANARI-ML/canari-ml@0.0.1a1

(Optional) Create local clone for development¶

Clone the repository:

git clone git@github.com:CANARI-ML/canari-ml.git
cd canari-ml

To specify the branch to clone:

git clone -b <branch_name> git@github.com:CANARI-ML/canari-ml.git
cd canari-ml

Install in development mode (editable installation):
```
pip install -e .
```
To install for local development, including documentation:
```
pip install -e .[dev,docs]
```
Optional: For development, set up Git pre-commit hooks:

Run pre-commit once to set up the hook to run each time a commit is attempted:
```
pre-commit install
```

Next Steps¶

After setting up your environment, you can proceed with downloading source ERA5 data.