# CustomSpacyNormalizer **`class CustomSpacyNormalizer(config)`** Bases: [`SpacyNormalizer`](squirro.lib.nlp.steps.normalizers.SpacyNormalizer.md#squirro.lib.nlp.steps.normalizers.SpacyNormalizer) Override Spacy Tokenizer to NOT split tokens by / or - characters. Parameters - `step` ([`str`](https://docs.python.org/3.11/library/stdtypes.html#str)`, ``"app"`) – app - `type` ([`str`](https://docs.python.org/3.11/library/stdtypes.html#str)`, ``"query_processing"`) – query_processing - `name` ([`str`](https://docs.python.org/3.11/library/stdtypes.html#str)`, ``"custom_spacy_normalizer"`) – custom_spacy_normalizer - `input_fields` ([`list`](https://docs.python.org/3.11/library/stdtypes.html#list)`,``[``"user_terms_str"``]`) – This step only takes one input field - `(``str` (`infix_split_chars`) – <>=/”): Additional characters that are used to split a single token. - `"` – <>=/”): Additional characters that are used to split a single token. - `merge_noun_chunks` ([`bool`](https://docs.python.org/3.11/library/functions.html#bool)`, ``True`) – merge noun chunks into a single token - `product_recognizer__with_noun_num` ([`bool`](https://docs.python.org/3.11/library/functions.html#bool)`, ``True`) – Recognize consecutive NOUNs followed by a NUM as a PRODUCT entity - `path` ([`str`](https://docs.python.org/3.11/library/stdtypes.html#str)`, ``"."`) – path Methods SummaryMethods Documentation **`customise_spacy(nlp)`** Customise spacy model. Enable custom steps to inherit from this step to customize specific spacy-components, for example the behaviour of the Tokenizer. :type nlp: `Language` :param nlp: :rtype: [`None`](https://docs.python.org/3.11/library/constants.html#None) :return: