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Daemon to facilitate automatically competing in the Numerai machine learning competition

Project description



Numerauto is a Python daemon that facilates automatic weekly participation in the Numerai machine learning competition (

Users can implement custom event handlers to handle new training data, apply models to new tournament data when a new round starts, and more. Example event handlers are included for training SKLearn classifiers and uploading predictions.

If you encounter a problem or have suggestions, feel free to open an issue.


To install the latest release: pip install --upgrade numerauto

If you prefer to use the latest development version, clone this github reposistory: git clone And then run the following command in the numerauto directory. python install



Although Numerauto can be run without any event handlers for testing, it will not do anything except detecting round changes and downloading the new dataset every week.

See for a basic example that trains a scikit-learn logistic regression model and uploads its predictions.

The example uses the PredictionUploader event handler to upload predictions to Numerai. This requires you to register an API key in your Numerai account. This can be done in Account settings -> Your API Keys -> Add. Select 'Upload submissions' to be able to upload predictions using this API key. Replace 'insert your publickey/secretkey here' in the code with your own API public/secret API key pair to allow the example code to upload the prediction to your account.

Custom event handlers

Implementing your own event handler is easy. Simply create a subclass of numerauto.eventhandlers.EventHandler and overload the on_* methods that you need to implement your own functionality. The event handler can then be added to a Numerauto instance using the add_event_handler method. Then start the main loop of the Numerauto daemon by calling the run method. Note that this will keep running indefinitely or until interrupted using a SIGINT (ctrl-c) or SIGTERM signal.

Currently these events are supported:

  • def on_start(self): Called when the daemon starts.
  • def on_shutdown(self): Called when the daemon shuts down.
  • def on_round_begin(self, round_number): Called when a new round has started.
  • def on_new_training_data(self, round_number): Called when the daemon has detected that new training data is available.
  • def on_new_tournament_data(self, round_number): Called every round to signal that there is new tournament data.

Note that event handlers are called in the order they are added to the Numerauto instance. Also note that all handlers for one event are called before the next event is handled, keep this in mind when designing event handlers that interact with one another, or that keep large amounts of data in memory. Ideally, the handler should clean up memory in on_new_tournament_data to prevent memory being used while the daemon is idle and waiting for the next round.

Persistent state: state.pickle

Numerauto stores a persistent state in the state.pickle file in the directory from which the daemon is being run. By default, the Numerauto daemon stores the last round number that was processed (last_round_processed) and the last round number on which training was performed (last_round_trained). You can force the system to reprocess and retrain by stopping the daemon and removing the state.pickle file.

Custom event handlers can store persistent information in the persistent_state dictionary of the Numerauto instance.

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