  We present allesfitter, a public and open-source python software for flexible
and robust inference of stars and exoplanets given photometric and radial
velocity data. Allesfitter offers a rich selection of orbital and
transit/eclipse models, accommodating multiple exoplanets, multi-star systems,
transit-timing variations, phase curves, stellar variability, star spots,
stellar flares, and various systematic noise models including Gaussian
Processes. It features both parameter estimation and Bayesian model selection,
allowing to easily run either a Markov Chain Monte Carlo (MCMC) or Nested
Sampling fit. For novice users, a graphical user interface allows to specify
all input and perform analyses; for python users, all modules can be readily
imported in any existing scripts. Allesfitter also produces publication-ready
tables, LaTeX commands, and figures. The software is publicly available
(https://github.com/MNGuenther/allesfitter), pip-installable (pip install
allesfitter) and well documented (www.allesfitter.com). Finally, we demonstrate
the software's capabilities on several examples and provide updates to the
literature where possible for Pi Mensae, TOI-216, WASP-18, KOI-1003 and GJ
1243.
