Visions – User defined data type systems
Visions is a python library for working with user defined data type systems. Out of the box, it provides type inference and automated data cleaning of sequence data with backend specific implementations for pandas, spark, python, and numpy. We often use it as a first pass cleaning step when working with tabular data and to simplify the backend logic of both pandas-profiling[1] and our tabular data compression library compressio[2]. Because data types are user defined, we can build user customizable libraries based around types without adding code complexity. In the case of compressio that…
Visions – User defined data type systems launched on February 1, 2022 with 45 votes, #915 of 2,645 launches that month and more than 75% of that year's launches. The site was still online in September 2026, 4 years on.
In plain words
Visions is a Python library that enables type inference and automated data cleaning for sequence data across pandas, Spark, Python, and NumPy backends. It uses user-defined data type systems to simplify tabular data processing as an initial cleaning step. The library allows developers to build customizable, type-based tools without increasing code complexity, making it useful for data profiling and compression tasks where users can define custom type-to-algorithm mappings.
written from the facts on this page · September 2026
From the sources
Type System for Data Analysis in Python. Contribute to dylan-profiler/visions development by creating an account on GitHub.
In the maker’s words, at launch
Visions is a python library for working with user defined data type systems. Out of the box, it provides type inference and automated data cleaning of sequence data with backend specific implementations for pandas, spark, python, and numpy. We often use it as a first pass cleaning step when working with tabular data…
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