pykinbiont

pykinbiont is a Python interface designed to run the full KinBiont microbial kinetics analysis pipeline from within Python environments. jl’s modeling capabilities while keeping all numerical computation in Julia through the juliacall bridge. 10 or higher installed separately, as pykinbiont delegates all heavy computation to Julia and automatically installs KinBiont and its dependencies on first use.

The tool supports loading plate-reader data, fitting a variety of growth models, clustering growth curves, and exporting results. It offers one-call fitting by allowing users to provide growth data, model specifications, and fitting options, returning results with the best model for each curve selected according to AICc. The supported models include log-linear, logistic, Gompertz, Richards, ODEs, and others, all accessible via a model registry. Users can also define custom growth models in Python, either as nonlinear models or in-place ODEs, with the Julia bridge handling callbacks seamlessly.

For preprocessing, pykinbiont provides a pure-Python pipeline that includes smoothing, blank subtraction, correction of negative values, stationary-phase trimming, and k-means clustering. The output is designed to be tidy and ready for further analysis, with functions to convert results to pandas DataFrames or save them as CSV files. The workflow is illustrated through examples such as basic logistic fitting, custom Python growth models, preprocessing pipelines, and CSV-based data handling.

pykinbiont is suitable for researchers and developers who require an integrated approach to microbial kinetics analysis from Python, leveraging Julia’s computational strengths without leaving the Python ecosystem. The documentation and examples guide users through installation, configuration, and typical analysis tasks.