  Optimizing one's observing strategy while at the telescope relies on knowing
the current observing conditions and the obtained data quality. In particular
the latter is not straight forward with current wide-field imagers, such as the
WIYN One Degree Imager (ODI), currently consisting of 13 detectors, each of
them read out in 64 independent cells.
  Here we present a fast data reduction software for ODI, optimized for a first
data inspection during acquisition at the the telescope, but capable enough for
science-quality data reductions. The pipeline is coded in pure python with
minimal additional requirements. It is installed on the ODI observer's
interface and publicly available from the author's webpage. It performs all
basic reduction steps as well as more advanced corrections for pupil-ghost
removal, fringe correction and masking of persistent pixels. Additional
capabilities include adding an accurate astrometric WCS solution based on the
2MASS reference system as well as photometric zeropoint calibration for frames
covered by the SDSS foot-print.
  The pipeline makes use of multiple CPU-cores wherever possible, resulting in
an execution time of only a few seconds per frame. As such this QuickReduce
pipeline offers the ODI observer a convenient way to closely monitor data
quality, a necessity to optimize the observing strategy during the night.
