  We present the open-source Bayesian Atmospheric Radiative Transfer (BART)
retrieval package, which produces estimates and uncertainties for an
atmosphere's thermal profile and chemical abundances from observations. Several
BART components are also stand-alone packages, including the parallel
Multi-Core Markov chain Monte Carlo (MC3), which implements several Bayesian
samplers; a line-by-line radiative-transfer model, transit; a code that
calculates Thermochemical Equilibrium Abundances, TEA; and a test suite for
verifying radiative-transfer and retrieval codes, BARTTest. The codes are in
Python and C. BART and TEA are under a Reproducible Research (RR) license,
which requires reviewed-paper authors to publish a compendium of all inputs,
codes, and outputs supporting the paper's scientific claims. BART and TEA
produce the compendium's content. Otherwise, these codes are under permissive
open-source terms, as are MC3 and BARTTest, for any purpose. This paper
presents an overview of the code, BARTTest, and an application to eclipse data
for exoplanet HD 189733 b. Appendices address RR methodology for accelerating
science, a reporting checklist for retrieval papers, the spectral resolution
required for synthetic tests, and a derivation of the effective sample size
required to estimate any Bayesian posterior distribution to a given precision,
which determines how many iterations to run. Paper II, by Cubillos et al.,
presents the underlying radiative-transfer scheme and an application to transit
data for exoplanet HAT-P-11b. Paper III, by Blecic et al., discusses the
initialization and post-processing routines, with an application to eclipse
data for exoplanet WASP-43b. We invite the community to use and improve BART
and its components at http://GitHub.com/ExOSPORTS/BART/.
