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.

本文介绍了 ManyTypes4Py，这是一个用于基于机器学习的类型推理的大型 Python 数据集。该数据集包含了 5,382 个 Python 项目，共有超过 869K 的类型注释。为了消除重复偏差的负面影响，去除了重复源代码文件。为了方便机器学习模型的训练和评估，数据集按文件被分为训练、验证和测试集。我们开发了一个轻量级静态分析器管道来从 AST 中提取类型信息，并附带了数据集。使用这个管道，收集的 Python 项目进行了分析，并将 AST 分析结果存储为 JSON 格式的文件。ManyTypes4Py 数据集在 zenodo 上共享，并且其工具在 GitHub 上公开可用。