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This Zenodo repository contains the full open-source software package and supporting materials for the democratic detrender, a Python-based framework for detrending and systematics removal in time-series photometric data. Stellar time-series photometry is a combination of periodic, quasi-periodic, and non-periodic variations caused by both physical and instrumental factors, and there is thus no “perfect” model for this nuisance signal. To mitigate model dependency, the democratic detrender performs detrending using a novel ensemble-based “voting” approach via a community-of-models. This detrending package has been extensively tested on thousands of TESS and Kepler light curves. For more information, please see the paper describing the methodology. This repository accompanies the article, to be published in ApJS, and provides the code necessary to reproduce the detrending methodology and apply it to similar datasets. The upload includes the following types of files and formats: Python source code (.py) implementing the core Democratic Detrender algorithms, including regression-based detrending, ensemble correction, and model evaluation tools. Project configuration files specifying dependencies and runtime requirements for executing the software in a scientific Python environment. Example scripts and workflow modules demonstrating typical usage, including loading input light curves, applying detrending procedures, and exporting corrected time-series products. Documentation source files (.rst, .md) used to generate the online ReadTheDocs manual, including tutorials, API references, and explanatory background. Supporting utilities and test modules for validation, extension, and integration into other astronomical analysis pipelines. The software is intended to be run within a standard scientific Python ecosystem (e.g., NumPy, SciPy, Astropy, Matplotlib). The included scripts and modules allow users to parse input time-series data, apply the detrending framework described in the associated publication, and reuse the methodology to space-based time-series photometric data. The relationship between the uploaded materials and the associated article is direct: this repository provides the reference implementation of the democratic detrender approach presented in the paper, along with the tools needed to reproduce results, validate the method, and support transparent reuse by the community. Full documentation and usage examples are available at:https://democratic-detrender.readthedocs.io/ Source code repository:https://github.com/dyahalomi/democratic_detrender