def calculate_row_delta(row, cached_row, data_key_col, timestamp):
assert type(row) is OrderedDict or dict
assert type(cached_row) is OrderedDict or dict or None, "cached row must be dict even if empty"
delta_row = DeltaRow(data_key_col, timestamp)
# Calculate only delta for each value which is not the key column
non_key_data = {key: val for (key, val) in row.items() if key != data_key_col}
for field_name, measured_value in non_key_data.items():
delta_field = StatCalculator.get_delta_field(cached_row, field_name, measured_value)
delta_row.add_field(delta_field)
# Append the key
# each call to get_delta will result in one row, but it might contain only the key
delta_row.add_field(DeltaField(field_name=data_key_col, measured=row[data_key_col]))
return delta_row
def test_should_serialize_delta_row_to_dict(self):
dr = DeltaRow("a", "timestamp")
dr.add_field(DeltaField("a", measured="key value"))
dr.add_field(DeltaField("b", measured=100, delta=50, previous=75))
actual = dr.as_dict()
self.assertEquals(
actual,
{
"a_measured": "key value",
"b_measured": 100,
"b_delta": 50,
"b_previous": 75,
"timestamp": "timestamp",
"key_col": "key value",
},
)