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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 _process_stocks(self, limit):
 """ Stock definitions. Here we instantiate them as instances of the given taxon. :param limit: :return: """

        if self.test_mode:
            graph = self.testgraph
        else:
            graph = self.graph
        model = Model(graph)
        line_counter = 0

        raw = '/'.join((self.rawdir, 'stock'))
        LOG.info("building labels for stocks")

        with open(raw, 'r') as f:
            f.readline()  # read the header row; skip
            filereader = csv.reader(f, delimiter='\t', quotechar='\"')
            for line in filereader:
                line_counter += 1

                (stock_id, dbxref_id, organism_id, name, uniquename,
                 description, type_id, is_obsolete) = line
# 2       12153979        1       2       FBst0000002     w[*]; betaTub60D[2] Kr[If-1]/CyO        10670

                stock_num = stock_id
                stock_id = 'FlyBase:'+uniquename
                self.idhash['stock'][stock_num] = stock_id
                stock_label = description

                organism_key = organism_id
                taxon = self.idhash['organism'][organism_key]

                # from what i can tell, the dbxrefs are just more FBst,
                # so no added information vs uniquename

                if not self.test_mode and limit is not None and line_counter > limit:
                    pass
                else:
                    if self.test_mode \
                            and int(stock_num) not in self.test_keys['strain']:
                        continue

                    # tax_label = self.label_hash[taxon]  # unused
                    # add the tax in case it hasn't been already
                    model.addClassToGraph(taxon)
                    model.addIndividualToGraph(stock_id, stock_label, taxon)
                    if is_obsolete == 't':
                        model.addDeprecatedIndividual(stock_id)

        return