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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def check_overscan(xstart, xsize, total_prescan_pixels=24, total_science_pixels=4096):
 """Check image for bias columns. Parameters xstart : int Starting column of the readout in detector coordinates. xsize : int Number of columns in the readout. total_prescan_pixels : int Total prescan pixels for a single amplifier on a detector. Default is 24 for WFC. total_science_pixels : int Total science pixels across a detector. Default is 4096 for WFC (across two amplifiers). Returns ------- hasoverscan : bool Indication if there are bias columns in the image. leading : int Number of bias columns on the A/C amplifiers side of the CCDs ("TRIMX1" in ``OSCNTAB``). trailing : int Number of bias columns on the B/D amplifiers side of the CCDs ("TRIMX2" in ``OSCNTAB``). """

    hasoverscan = False
    leading = 0
    trailing = 0

    if xstart < total_prescan_pixels:
        hasoverscan = True
        leading = abs(xstart - total_prescan_pixels)

    if (xstart + xsize) > total_science_pixels:
        hasoverscan = True
        trailing = abs(total_science_pixels -
                       (xstart + xsize - total_prescan_pixels))

    return hasoverscan, leading, trailing