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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 main():
 """ NAME gaussian.py DESCRIPTION generates set of normally distribed data from specified distribution INPUT (COMMAND LINE ENTRY) OUTPUT x SYNTAX gaussian.py [command line options] OPTIONS -h prints help message and quits -s specify standard deviation as next argument, default is 1 -n specify N as next argument, default is 100 -m specify mean as next argument, default is 0 -F specify output file """

    N,mean,sigma=100,0,1.
    outfile=""
    if '-h' in sys.argv:
        print(main.__doc__)
        sys.exit()
    else:
        if '-s' in sys.argv:
            ind=sys.argv.index('-s')
            sigma=float(sys.argv[ind+1])
        if '-n' in sys.argv:
            ind=sys.argv.index('-n')
            N=int(sys.argv[ind+1])
        if '-m' in sys.argv:
            ind=sys.argv.index('-m')
            mean=float(sys.argv[ind+1])
        if '-F' in sys.argv:
            ind=sys.argv.index('-F')
            outfile=sys.argv[ind+1]
            out=open(outfile,'w')
    for k in range(N): 
        x='%f'%(pmag.gaussdev(mean,sigma))  # send kappa to fshdev
        if outfile=="":
            print(x)
        else:
           out.write(x+'\n')