def testValidateUnion(self):
example_schema = """\
["int", "null"]
"""
datum = None
result = avro_io.Validate(schema.Parse(example_schema), datum)
self.assertTrue(result)
def testValidate(self):
passed = 0
for example_schema, datum in SCHEMAS_TO_VALIDATE:
logging.debug('Schema: %r', example_schema)
logging.debug('Datum: %r', datum)
validated = avro_io.Validate(schema.Parse(example_schema), datum)
logging.debug('Valid: %s', validated)
if validated: passed += 1
self.assertEqual(passed, len(SCHEMAS_TO_VALIDATE))
def testValidateUnionError(self):
example_schema = """\
["int", "null"]
"""
datum = "there should not be a string here"
expected_regex = "datum should be one of following: \['int', 'null']"
with self.assertRaisesRegex(avro_io.AvroTypeException, expected_regex):
avro_io.Validate(schema.Parse(example_schema), datum)
def testValidateShouldRaiseFormattedError(self):
example_schema = '{"type": "int"}'
datum = "aaa"
expected_regex = "datum should be int type," \
" but as value we got 'aaa'"
with self.assertRaisesRegex(avro_io.AvroPrimitiveTypeException,
expected_regex):
avro_io.Validate(schema.Parse(example_schema), datum)
def testValidateNestedShouldRaiseFormattedError(self):
example_schema = """\
{"type": "record",
"name": "a",
"fields": [
{"name": "field1", "type": {
"type": "array", "items": "int"}
}
]
}
"""
datum = {"field1": {"field2": "11", "field3": []}}
expected_regex = 'Field "field1"' \
' datum should be list type'
with self.assertRaisesRegex(avro_io.AvroTypeException, expected_regex):
avro_io.Validate(schema.Parse(example_schema), datum)
def testValidateNested(self):
example_schema = """\
{"type": "record",
"name": "a",
"fields": [
{"name": "field1", "type": {
"type": "record", "name": "b", "fields": [
{"name": "field2", "type": "long"},
{"name": "field3", "type": "int"}
]}
}
]
}
"""
datum = {"field1": {"field2": 11, "field3": 11}}
result = avro_io.Validate(schema.Parse(example_schema), datum)
self.assertTrue(result)
coords={
'time':
pd.to_datetime(['2019-01-01', '2019-01-02']),
'asset': np.array(['ASSET1', '2ASSET'])
})
print("check conversion to avro record")
av_record = convert_output_to_avro_record(output)
import json
schema = avs.Parse(json.dumps(output_schema))
reader = aio.DatumReader(schema, schema)
parsed = reader.read(aio.BinaryDecoder(BytesIO(av_record)))
assert aio.Validate(schema, parsed)
assert parsed['coords']['time'] == [
str(i)[0:10] for i in output.coords[ds.TIME].values
]
assert parsed['coords']['asset'] == output.coords[ds.ASSET].values.tolist()
assert parsed['values'] == output.values.reshape([4]).tolist()
print("check conversion from avro record")
output2 = convert_avro_record_to_output(av_record)
assert (output.identical(output2))
print("check conversion to avro file")
avr_file = output_to_avro_file(output)
