The Multiscale Solar Water Heating (MSWH) package simulates individual and community-scale solar water heating projects and allows for a comparison with the simulation performance of conventional natural gas tank water heaters (WH). The package contains a Jupyter notebook with examples, a graphical user interface (GUI) developed using Django Framework and both functional and unit tests. System performance time series visualizations are available both in example notebooks and through the GUI, either spun off locally or using a web deployed version. The package was developed in the scope of a California Energy Commission (CEC) funded project looking at costs and benefits of using community versus individual scale solar thermal water heating systems. The database included in the MSWH software focuses primarily on California-specific hot water use profiles and climate data, but can structurally accommodate any further climate zones. The scale refers to the number of households served by a single system. Therefore, one can apply the models to explore the benefits of grouping multiple households to be served by a single solar water heating system in comparison to a system installed in a single household. Another example application of the models is to enable calculation of gas savings when switching from a gas WH to a solar WH in a single household. The preconfigured system simulation models provided in the package include base-case gas tank WH and the following solar WH configurations with solar storage tanks: • Solar thermal collector WH with either a tankless or a tank gas WH backup. • Solar electric photovoltaic WH with a heat pump storage tank and an electric resistance backup. This documentation page provides more details about the implemented models, the modeling approach, and the references used in some of the model development. To evaluate a solar water heating project at the design phase by looking at its simulation performance the user should create a system instance for each compared system. This is described in detail in our example notebooks. The user needs to specify the following: • The project location by choosing one of the climate zones for which data is available in our database. • For each household: count of people supplied by the system and whether there is any daytime household occupancy.