  The International Liquid Mirror Telescope (ILMT) is a 4-meter survey
telescope continuously observing towards the zenith in the SDSS g', r', and i'
bands. This survey telescope is designed to detect various astrophysical
transients (for example, supernovae) and very faint objects like
multiply-imaged quasars and low surface brightness galaxies. A single scan of a
22$'$ strip of sky contains a large amount of photometric information. To
process this type of data, it becomes critical to have tools or pipelines that
can handle it efficiently and accurately with minimal human biases. We offer a
fully automated pipeline generated in Python to perform aperture photometry
over the ILMT data acquired with the CCD in Time Delayed Integration (TDI)
mode. The instrumental magnitudes are calibrated with respect to the
Pan-STARRS-1 catalogue. The light curves generated from the calibrated
magnitudes will allows us to characterize the objects as variable stars or
rapidly decaying transients.
