How to use the langcodes.data_dicts.LANGUAGE_REPLACEMENTS.get function in langcodes

data = {}
        # if the complete tag appears as something to normalize, do the
        # normalization right away. Smash case when checking, because the
        # case normalization that comes from parse_tag() hasn't been applied
        # yet.
        tag_lower = tag.lower()
        if normalize and tag_lower in LANGUAGE_REPLACEMENTS:
            tag = LANGUAGE_REPLACEMENTS[tag_lower]

        components = parse_tag(tag)

        for typ, value in components:
            if typ == 'extlang' and normalize and 'language' in data:
                # smash extlangs when possible
                minitag = '%s-%s' % (data['language'], value)
                norm = LANGUAGE_REPLACEMENTS.get(minitag.lower())
                if norm is not None:
                    data.update(
                        Language.get(norm, normalize).to_dict()
                    )
                else:
                    data.setdefault('extlangs', []).append(value)
            elif typ in {'extlang', 'variant', 'extension'}:
                data.setdefault(typ + 's', []).append(value)
            elif typ == 'language':
                if value == 'und':
                    pass
                elif normalize:
                    replacement = LANGUAGE_REPLACEMENTS.get(value.lower())
                    if replacement is not None:
                        # parse the replacement if necessary -- this helps with
                        # Serbian and Moldovan

# smash extlangs when possible
                minitag = '%s-%s' % (data['language'], value)
                norm = LANGUAGE_REPLACEMENTS.get(minitag.lower())
                if norm is not None:
                    data.update(
                        Language.get(norm, normalize).to_dict()
                    )
                else:
                    data.setdefault('extlangs', []).append(value)
            elif typ in {'extlang', 'variant', 'extension'}:
                data.setdefault(typ + 's', []).append(value)
            elif typ == 'language':
                if value == 'und':
                    pass
                elif normalize:
                    replacement = LANGUAGE_REPLACEMENTS.get(value.lower())
                    if replacement is not None:
                        # parse the replacement if necessary -- this helps with
                        # Serbian and Moldovan
                        data.update(
                            Language.get(replacement, normalize).to_dict()
                        )
                    else:
                        data['language'] = value
                else:
                    data['language'] = value
            elif typ == 'region':
                if normalize:
                    data['region'] = REGION_REPLACEMENTS.get(value.lower(), value)
                else:
                    data['region'] = value
            elif typ == 'grandfathered':