How to use the ms2pip.cython_modules.ms2pip_pyx function in ms2pip

def process_peptides(worker_num, data, afile, modfile, modfile2, PTMmap, model):
    """
	Function for each worker to process a list of peptides. The models are
	chosen based on model. PTMmap, Ntermmap and Ctermmap determine the
	modifications applied to each peptide sequence. Returns the predicted
	spectra for all the peptides.
	"""

    ms2pip_pyx.ms2pip_init(
        bytearray(afile.encode()),
        bytearray(modfile.encode()),
        bytearray(modfile2.encode()),
    )

    pcount = 0

    # Prepare output variables
    mz_buf = []
    prediction_buf = []
    peplen_buf = []
    charge_buf = []
    pepid_buf = []

    # transform pandas dataframe into dictionary for easy access
    if "ce" in data.columns:

)
                    )
                else:
                    # Predict the b- and y-ion intensities from the peptide
                    pepid_buf.append(title)
                    peplen_buf.append(len(peptide) - 2)
                    charge_buf.append(charge)

                    # get/append ion mzs, targets and predictions
                    targets = ms2pip_pyx.get_targets(
                        modpeptide, msms, peaks, float(fragerror), peaks_version
                    )
                    target_buf.append([np.array(t, dtype=np.float32) for t in targets])
                    mzs = ms2pip_pyx.get_mzs(modpeptide, peaks_version)
                    mz_buf.append([np.array(m, dtype=np.float32) for m in mzs])
                    predictions = ms2pip_pyx.get_predictions(
                        peptide, modpeptide, charge, model_id, peaks_version, colen
                    )  # SD: added colen
                    prediction_buf.append(
                        [np.array(p, dtype=np.float32) for p in predictions]
                    )

                pcount += 1
                if (pcount % 500) == 0:
                    sys.stdout.write("(%i)%i " % (worker_num, pcount))
                    sys.stdout.flush()

    f.close()
    if tableau:
        ft.close()
        ft2.close()