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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 readDivPressure(fileName):
 """Reads in diversifying pressures from some file. Scale diversifying pressure values so absolute value of the max value is 1, unless all values are zero. Args: `fileName` (string or readable file-like object) File holding diversifying pressure values. Can be comma-, space-, or tab-separated file. The first column is the site (consecutively numbered, sites starting with one) and the second column is the diversifying pressure values. Returns: `divPressure` (dict keyed by ints) `divPressure[r][v]` is the diversifying pressure value of site `r`. """

    try:
        df = pandas.read_csv(fileName, sep=None, engine='python')
        pandasformat = True
    except ValueError:
        pandasformat = False
    df.columns = ['site', 'divPressureValue']
    scaleFactor = max(df["divPressureValue"].abs())
    if scaleFactor > 0:
        df["divPressureValue"] = [x / scaleFactor for x in df["divPressureValue"]]
    assert len(df['site'].tolist()) == len(set(df['site'].tolist())),"There is at least one non-unique site in {0}".format(fileName)
    assert max(df["divPressureValue"].abs()) <= 1, "The scaling produced a diversifying pressure value with an absolute value greater than one."
    sites = df['site'].tolist()
    divPressure = {}
    for r in sites:
        divPressure[r] = df[df['site'] == r]["divPressureValue"].tolist()[0]
    return divPressure