mlsanityData to 14 Oct 2026

ManyTypes4Py: A Benchmark Python Dataset for Machine Learning-based Type Inference

arXiv 2104.04706 ↗First posted 10 Apr 2021cs.SE cs.LG cs.PLcited by 9

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Abstract (arXiv)

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.

Key facts. Cited by 9 papers in the map (data through 14 Oct 2026). Builds on 5 of its 15 references that are in the map. First posted on arXiv 10 Apr 2021.

Builds on

5 of 15 references.

References · 5

  1. 2017Revisiting Unreasonable Effectiveness of Data in Deep Learning Eracited by 919
  2. 2018The Adverse Effects of Code Duplication in Machine Learning Models of Codecited by 126
  3. 2019Pythia: AI-assisted Code Completion Systemcited by 55
  4. 2019TypeWriter: Neural Type Prediction with Search-based Validationcited by 32
  5. 2020Typilus: Neural Type Hintscited by 29

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2022: 2; 2023: 2; 2024: 1; 2025: 2; 2026: 2.

9 papers.

  1. 2023TypeT5: Seq2seq Type Inference using Static Analysiscited by 12
  2. 2023Type Prediction With Program Decomposition and Fill-in-the-Type Trainingcited by 6
  3. 2024Understanding How CodeLLMs (Mis)Predict Types with Activation Steeringcited by 5
  4. 2022JEMMA: An Extensible Java Dataset for ML4Code Applicationscited by 2
  5. 2022Cross-Domain Evaluation of a Deep Learning-Based Type Inference Systemcited by 1
  6. 2025TypyBench: Evaluating LLM Type Inference for Untyped Python Repositoriescited by 0
  7. 2025Automated Type Annotation in Python Using Large Language Modelscited by 0
  8. 2026Extending LLM Context via Associative Recurrent Memorycited by 0
  9. 2026On the Lexical Superstition of Large Language Models for Code Comprehension: Re-evaluation on Code of Low Lexical Qualitycited by 0