EZInput: A Cross-Environment Python Library for Easy UI Generation in Scientific Computing
For algorithm developers and researchers, EZInput lowers the barrier to using computational tools by eliminating the need for programming skills and manual parameter entry, though it is an incremental improvement over existing UI generation approaches.
EZInput is a Python library that automatically generates graphical user interfaces for computational algorithms, enabling non-programmers to configure parameters across Jupyter, Colab, and terminal environments. It reduces redundant input and enhances reproducibility through declarative specification and session persistence.
Researchers face a persistent barrier when applying computational algorithms with parameter configuration typically demanding programming skills, interfaces differing across environments, and settings rarely persisting between sessions. This fragmentation forces repetitive input, slows iterative exploration, and undermines reproducibility because parameter choices are difficult to record, share, and reuse. We present EZInput, a cross-runtime environment Python library enabling algorithm developers to automatically generate graphical user interfaces that make their computational tools accessible to end-users without programming expertise. EZInput employs a declarative specification system where developers define input requirements and validation constraints once; the library then handles environment detection, interface rendering, parameter validation, and session persistence across Jupyter notebooks, Google Colab, and terminal environments. This "write once, run anywhere" architecture enables researchers to prototype in notebooks and deploy identical parameter configurations for batch execution on remote systems without code changes or manual transcription. Parameter persistence, inspired by ImageJ/FIJI and adapted to Python workflows, saves and restores user configurations via lightweight YAML files, eliminating redundant input and producing shareable records that enhance reproducibility. EZInput supports diverse input types essential for scientific computing and it also includes built-in validation that ensures data integrity and clear feedback that reduces user friction.