  In this paper, we present ManyTypes4Py, a large Python dataset for machine
learning (ML)-based type inference. The dataset contains a total of 5,382
Python projects with more than 869K type annotations. Duplicate source code
files were removed to eliminate the negative effect of the duplication bias. To
facilitate training and evaluation of ML models, the dataset was split into
training, validation and test sets by files. To extract type information from
abstract syntax trees (ASTs), a lightweight static analyzer pipeline is
developed and accompanied with the dataset. Using this pipeline, the collected
Python projects were analyzed and the results of the AST analysis were stored
in JSON-formatted files. The ManyTypes4Py dataset is shared on zenodo and its
tools are publicly available on GitHub.
