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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 reclassify(layer, exposure_key=None):
 """Reclassify a continuous vector layer. This function will modify the input. For instance if you want to reclassify like this table : Original Value | Class - ∞ < val <= 0 | 1 0 < val <= 0.5 | 2 0.5 < val <= 5 | 3 5 < val < + ∞ | 6 You need a dictionary : ranges = OrderedDict() ranges[1] = [None, 0] ranges[2] = [0.0, 0.5] ranges[3] = [0.5, 5] ranges[6] = [5, None] :param layer: The raster layer. :type layer: QgsRasterLayer :param exposure_key: The exposure key. :type exposure_key: str :return: The classified vector layer. :rtype: QgsVectorLayer .. versionadded:: 4.0 """

    output_layer_name = reclassify_vector_steps['output_layer_name']
    output_layer_name = output_layer_name % layer.keywords['title']

    # This layer should have this keyword, or it's a mistake from the dev.
    inasafe_fields = layer.keywords['inasafe_fields']
    continuous_column = inasafe_fields[hazard_value_field['key']]

    if exposure_key:
        classification_key = active_classification(
            layer.keywords, exposure_key)
        thresholds = active_thresholds_value_maps(layer.keywords, exposure_key)
        layer.keywords['thresholds'] = thresholds
        layer.keywords['classification'] = classification_key
    else:
        classification_key = layer.keywords.get('classification')
        thresholds = layer.keywords.get('thresholds')

    if not thresholds:
        raise InvalidKeywordsForProcessingAlgorithm(
            'thresholds are missing from the layer %s'
            % layer.keywords['layer_purpose'])

    continuous_index = layer.fields().lookupField(continuous_column)

    classified_field = QgsField()
    classified_field.setType(hazard_class_field['type'])
    classified_field.setName(hazard_class_field['field_name'])
    classified_field.setLength(hazard_class_field['length'])
    classified_field.setPrecision(hazard_class_field['precision'])

    layer.startEditing()
    layer.addAttribute(classified_field)

    classified_field_index = layer.fields(). \
        lookupField(classified_field.name())

    for feature in layer.getFeatures():
        attributes = feature.attributes()
        source_value = attributes[continuous_index]
        classified_value = reclassify_value(source_value, thresholds)
        if (classified_value is None
                or (hasattr(classified_value, 'isNull')
                    and classified_value.isNull())):
            layer.deleteFeature(feature.id())
        else:
            layer.changeAttributeValue(
                feature.id(), classified_field_index, classified_value)

    layer.commitChanges()
    layer.updateFields()

    # We transfer keywords to the output.
    inasafe_fields[hazard_class_field['key']] = (
        hazard_class_field['field_name'])

    value_map = {}

    hazard_classes = definition(classification_key)['classes']
    for hazard_class in reversed(hazard_classes):
        value_map[hazard_class['key']] = [hazard_class['value']]

    layer.keywords['value_map'] = value_map
    layer.keywords['title'] = output_layer_name

    check_layer(layer)
    return layer