Type4Py: Practical Deep Similarity Learning-Based Type Inference for Python. (arXiv:2101.04470v3 [cs.LG] UPDATED)

Dynamic languages, such as Python and Javascript, trade static typing for
developer flexibility and productivity. Lack of static typing can cause
run-time exceptions and is a major factor for weak IDE support. To alleviate
these issues, PEP 484 introduced optional type annotations for Python. As
retrofitting types to existing codebases is error-prone and laborious, machine
learning (ML)-based approaches have been proposed to enable automatic type
inference based on existing, partially annotated codebases. However, previous
ML-based approaches are trained and evaluated …

arxiv learning python type