  With the loss of a second reaction wheel, resulting in the inability to point
continuously and stably at the same field of view, the NASA Kepler satellite
recently entered a new mode of observation known as the K2 mission. The data
from this redesigned mission present a specific challenge; the targets
systematically drift in position on a ~6 hour time scale, inducing a
significant instrumental signal in the photometric time series --- this greatly
impacts the ability to detect planetary signals and perform asteroseismic
analysis. Here we detail our version of a reduction pipeline for K2 target
pixel data, which automatically: defines masks for all targets in a given
frame; extracts the target's flux- and position time series; corrects the time
series based on the apparent movement on the CCD (either in 1D or 2D) combined
with the correction of instrumental and/or planetary signals via the KASOC
filter (Handberg & Lund 2014), thus rendering the time series ready for
asteroseismic analysis; computes power spectra for all targets, and identifies
potential contaminations between targets. From a test of our pipeline on a
sample of targets from the K2 campaign 0, the recovery of data for multiple
targets increases the amount of potential light curves by a factor ${\geq}10$.
Our pipeline could be applied to the upcoming TESS (Ricker et al. 2014) and
PLATO 2.0 (Rauer et al. 2013) missions.
