Mango is a Python library for parallel hyperparameter tuning of machine learning classifiers. It employs Bayesian optimization with Gaussian processes to efficiently explore continuous, discrete, and categorical search spaces. The library supports scheduling objective functions across local machines, clusters, and cloud infrastructure including Kubernetes deployments, with built-in failure detection for scalability in production environments.