  We present a data reduction pipeline written in Python for data obtained with
the near-infrared cross-dispersed echelle spectrograph, WINERED, which yields a
0.91$-$1.35 $\mu$m spectrum with the resolving power of $R_{\text{max}} \equiv
\lambda / \Delta \lambda = 28,000$ or 70,000 depending on the observing mode.
The pipeline was developed to efficiently extract the spectrum from the raw
data with high quality. It comprises two modes: the calibration and the science
mode. The calibration mode automatically produces the flat-fielding image, bad
pixel map, echellogram distortion map and the dispersion solution from the set
of the calibration data. Using calibration images and parameters, the science
data of astronomical objects can be reduced automatically using the science
mode. The science mode is also used for the real-time quick look at the data
during observations. An example of the spectra reduced with WARP is presented.
The effect of the highly inclined slit image on the spectral resolution is
discussed.
