Setup the Python Library¶
virtualenv, install the library which contains a client for interacting with our servers as well as a Keras Callback to easily upload your models during training. Install with the Keras extension to install all necessary dependecies.$ pip install fritz fritz[keras]
The library is compatible with Python 3.6 and Python 3.7.
2. Configure your API Key¶
Next, go to the webapp and copy the configuration command from the
The command will look like the following with your credentials filled in:$ fritz config update --api-key <Account API Key> --project-uid <Default Project ID>
Run the command in the same environment you ran the
pip installin the previous step.
This will create a file:
~/.fritzwith your credentials.
The Project ID you configure will determine the default Project to use when uploading models that have not been created.
At any time, you can see your currently configured API Key and selected Project ID:$ fritz config Fritz Configuration =================== API Key: <Your API Key> Project ID: <Your Project ID>