Automating Crypto Signals Submission for Numerai Using Python

Automating Numerai Crypto Signals Submission

This script uses Python for API interaction to submit predictions to Numerai's crypto signals tournament. The code focuses on error handling, modularity, and validation.

import pandas as pd
from numerapi import SignalsAPI
import sys
import os
from uuid import uuid4
# Function to load and validate predictions
def load_predictions(file_path):
    if not os.path.exists(file_path):
        raise FileNotFoundError(f"File not found: {file_path}")
    try:
        predictions = pd.read_csv(file_path)
        if "prediction" not in predictions.columns:
            raise ValueError("File must contain a 'prediction' column.")
        return predictions
    except Exception as e:
        raise ValueError(f"Error reading the file: {e}")
# Function to upload predictions
def upload_predictions(api_key, model_id, file_path):
    try:
        api = SignalsAPI(api_key)
        api.upload_predictions(file_path, model_id=model_id)
        print(f"Predictions uploaded successfully for model ID: {model_id}")
    except Exception as e:
        print(f"Failed to upload predictions: {e}")
# Main execution
if __name__ == "__main__":
    if len(sys.argv) != 3:
        print("Usage: python submit_signals.py <api_key> <predictions_file_path>")
        sys.exit(1)
    api_key = sys.argv[1]
    predictions_file_path = sys.argv[2]
    model_id = str(uuid4())  # Replace with actual model ID
    try:
        load_predictions(predictions_file_path)
        upload_predictions(api_key, model_id, predictions_file_path)
    except Exception as e:
        print(f"An error occurred: {e}")

CLI-Based Submission for Numerai Crypto Signals

This example leverages Numerai's CLI for submission, offering a simpler method for users familiar with terminal commands.

#!/bin/bash
# Numerai CLI submission script
# Validate input arguments
if [ "$#" -ne 3 ]; then
    echo "Usage: ./submit.sh <model_id> <api_key> <predictions_file_path>"
    exit 1
fi
MODEL_ID=$1
API_KEY=$2
PREDICTIONS_FILE=$3
# Check if file exists
if [ ! -f "$PREDICTIONS_FILE" ]; then
    echo "Error: File $PREDICTIONS_FILE does not exist."
    exit 1
fi
# Execute Numerai CLI submission
numerai signals upload --model-id "$MODEL_ID" --apikey "$API_KEY" --file "$PREDICTIONS_FILE"
if [ $? -eq 0 ]; then
    echo "Predictions submitted successfully for Model ID: $MODEL_ID"
else
    echo "Submission failed. Check your inputs and try again."
fi

Unit Testing the Python Solution

This section includes a Python unit test script for validating the functionality of the provided Python solution.

import unittest
from unittest.mock import patch
import os
from your_script import load_predictions, upload_predictions
class TestNumeraiSubmission(unittest.TestCase):
    def test_load_predictions_valid(self):
        file_path = "valid_predictions.csv"
        pd.DataFrame({"prediction": [0.1, 0.2]}).to_csv(file_path, index=False)
        try:
            predictions = load_predictions(file_path)
            self.assertIn("prediction", predictions.columns)
        finally:
            os.remove(file_path)
    def test_load_predictions_missing_file(self):
        with self.assertRaises(FileNotFoundError):
            load_predictions("missing_file.csv")
    @patch("your_script.SignalsAPI")
    def test_upload_predictions_success(self, mock_api):
        mock_instance = mock_api.return_value
        mock_instance.upload_predictions.return_value = None
        upload_predictions("dummy_key", "dummy_model", "dummy_path")
        mock_instance.upload_predictions.assert_called_once()
if __name__ == "__main__":
    unittest.main()

Common Questions About Numerai Crypto Signals Automation

1. What is the role of SignalsAPI.upload_predictions() in Numerai submissions?
2. This function uploads your prediction files to Numerai’s platform, making it a key component in automating your submission workflow.
3. Why is my model ID being flagged as invalid?
4. Ensure the model ID matches the one registered on Numerai’s platform. Using a placeholder like uuid4() without updating it will result in an error.
5. How can I validate my prediction file before submission?
6. Use pd.read_csv() to load your file and check for the presence of required columns like "prediction". This prevents format-related errors during submission.
7. Can I automate submissions without Python?
8. Yes, Numerai provides a CLI tool that allows you to use commands like numerai signals upload for submitting predictions directly from the terminal.
9. What are some common debugging strategies for failed submissions?
10. Check your API credentials and ensure the file path is valid. Using traceback.print_exc() in Python can provide detailed error information for troubleshooting.
11. Can I schedule my submissions automatically?
12. Yes, you can use cron jobs (Linux) or Task Scheduler (Windows) to run your script at regular intervals, ensuring timely submissions.
13. What libraries are essential for working with Numerai’s API?
14. Besides numerapi, libraries like pandas and os are crucial for handling files and validating input paths effectively.
15. Is it possible to test my submission process locally?
16. Yes, using mock data and Python’s unittest.mock.patch(), you can simulate API calls to validate your script before actual submission.
17. How can I improve performance when handling large datasets?
18. Optimize your data processing using Pandas methods like DataFrame.apply() and consider saving files in compressed formats.
19. What should I do if my API key is invalid?
20. Generate a new key from your Numerai account and replace it in your script. Keep your keys secure to avoid unauthorized access.

Final Thoughts on Automating Numerai Submissions

Automating your participation in the Numerai tournament can transform a tedious manual process into an efficient workflow. Whether using Python scripts or CLI tools, these solutions simplify submissions and reduce errors. By validating your data and credentials, you set yourself up for consistent success. 😊

Adopting automation not only saves time but also allows you to focus on improving your strategies rather than troubleshooting errors. As you integrate these tools into your workflow, you'll experience greater efficiency, confidence, and reliability in your submissions. Good luck with your crypto predictions! 🚀