Source code for yggdrasil.communication.transforms.MapFieldsTransform

import copy
import numpy as np
from yggdrasil.communication.transforms.TransformBase import TransformBase

[docs]class MapFieldsTransform(TransformBase): r"""Class for mapping a subset of the original fields in an object to a different set of fields. Fields that don't exist in the map are preserved unchanged. Args: map (dict): A mapping from original field name to new field names. """ _transformtype = 'map_fields' _schema_required = ['map'] _schema_properties = {'map': {'type': 'object', 'additionalProperties': {'type': 'string'}}}
[docs] def transform_datatype(self, datatype): r"""Determine the datatype that will result from applying the transform to the supplied datatype. Args: datatype (dict): Datatype to transform. Returns: dict: Transformed datatype. """ if (((datatype.get('type', None) == 'array') and isinstance(datatype.get('items', None), list))): datatype = copy.deepcopy(datatype) for i, x in enumerate(datatype['items']): if x.get('title', 'f%d' % i) in x['title'] =[x['title']] elif datatype.get('type', None) == 'object': datatype = copy.deepcopy(datatype) for kold, knew in datatype['properties'][knew] = datatype['properties'].pop(kold) return datatype
[docs] def evaluate_transform(self, x, no_copy=False): r"""Call transform on the provided message. Args: x (object): Message object to transform. no_copy (bool, optional): If True, the transformation occurs in place. Otherwise a copy is created and transformed. Defaults to False. Returns: object: The transformed message. """ out = x if isinstance(x, dict): if not no_copy: out = copy.deepcopy(x) for kold, knew in out[knew] = out.pop(kold) elif isinstance(x, (list, tuple)): pass elif isinstance(x, np.ndarray): if not no_copy: out = copy.deepcopy(x) new_names = list(x.dtype.names) for kold, knew in new_names[new_names.index(kold)] = knew out.dtype.names = new_names else: raise TypeError("Cannot map fields from object of type '%s'" % type(x)) return out
[docs] @classmethod def get_testing_options(cls): r"""Get testing options for the transform class. Returns: list: Multiple dictionaries of keywords and messages before/after pairs that will result from the transform created by the provided keywords. """ return [{'kwargs': {'map': {'a': 'aa', 'c': 'cc'}}, 'in/out': [(dict(zip('abc', range(3))), {'aa': 0, 'b': 1, 'cc': 2})], 'in/out_t': [ ({'type': 'object', 'properties': { x: {'type': 'int'} for x in 'abc'}}, {'type': 'object', 'properties': { x: {'type': 'int'} for x in ['aa', 'b', 'cc']}})]}, {'kwargs': {'map': {'a': 'aa', 'c': 'cc'}}, 'in/out': [([0, 1, 2], [0, 1, 2])], 'in/out_t': [ ({'type': 'array', 'items': [{'type': 'int', 'title': x} for x in 'abc']}, {'type': 'array', 'items': [{'type': 'int', 'title': x} for x in ['aa', 'b', 'cc']]})]}, {'kwargs': {'map': {'a': 'aa', 'c': 'cc'}}, 'in/out': [(np.zeros(3, np.dtype({'names': ['a', 'b', 'c'], 'formats': ['i4', 'i4', 'i4']})), np.zeros(3, np.dtype({'names': ['aa', 'b', 'cc'], 'formats': ['i4', 'i4', 'i4']})))]}, {'kwargs': {'map': {'a': 'aa', 'c': 'cc'}}, 'in/out': [(None, TypeError)]}]