In this talk, I will present our group's work in developing and disseminating three open-source tools for materials informatics: the atomate software (https://atomate.org) for running high-throughput calculations, the matminer software (https://hackingmaterials.github.io/matminer/) for data mining structure-property relationships, and the matscholar software (https://github.com/materialsintelligence/matscholar) for searching and analyzing text data. I will describe usage of these tools and their impact in helping users learn and perform materials informatics studies. For example, atomate makes it possible for users to generate data with high-throughput density functional theory using a high-level software framework. Matminer implements many of the feature extraction routines reported in the materials informatics literature, making it possible for users to rapidly test many different such algorithms for their study, and also collects together sample data sets for testing new algorithms. Matscholar makes it possible for researchers to search for information across millions of published abstracts. Finally, I will discuss usage of these tools with the Materials Project database and their past and potential future role in educational curricula.