/
_helpers.py
745 lines (581 loc) · 23.7 KB
/
_helpers.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
# Copyright 2015 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Shared helper functions for BigQuery API classes."""
import base64
import datetime
import decimal
import re
from google.cloud._helpers import UTC
from google.cloud._helpers import _date_from_iso8601_date
from google.cloud._helpers import _datetime_from_microseconds
from google.cloud._helpers import _RFC3339_MICROS
from google.cloud._helpers import _RFC3339_NO_FRACTION
from google.cloud._helpers import _to_bytes
_RFC3339_MICROS_NO_ZULU = "%Y-%m-%dT%H:%M:%S.%f"
_TIMEONLY_WO_MICROS = "%H:%M:%S"
_TIMEONLY_W_MICROS = "%H:%M:%S.%f"
_PROJECT_PREFIX_PATTERN = re.compile(
r"""
(?P<project_id>\S+\:[^.]+)\.(?P<dataset_id>[^.]+)(?:$|\.(?P<custom_id>[^.]+)$)
""",
re.VERBOSE,
)
def _not_null(value, field):
"""Check whether 'value' should be coerced to 'field' type."""
return value is not None or (field is not None and field.mode != "NULLABLE")
def _int_from_json(value, field):
"""Coerce 'value' to an int, if set or not nullable."""
if _not_null(value, field):
return int(value)
def _float_from_json(value, field):
"""Coerce 'value' to a float, if set or not nullable."""
if _not_null(value, field):
return float(value)
def _decimal_from_json(value, field):
"""Coerce 'value' to a Decimal, if set or not nullable."""
if _not_null(value, field):
return decimal.Decimal(value)
def _bool_from_json(value, field):
"""Coerce 'value' to a bool, if set or not nullable."""
if _not_null(value, field):
return value.lower() in ["t", "true", "1"]
def _string_from_json(value, _):
"""NOOP string -> string coercion"""
return value
def _bytes_from_json(value, field):
"""Base64-decode value"""
if _not_null(value, field):
return base64.standard_b64decode(_to_bytes(value))
def _timestamp_from_json(value, field):
"""Coerce 'value' to a datetime, if set or not nullable."""
if _not_null(value, field):
# value will be a integer in seconds, to microsecond precision, in UTC.
return _datetime_from_microseconds(int(value))
def _timestamp_query_param_from_json(value, field):
"""Coerce 'value' to a datetime, if set or not nullable.
Args:
value (str): The timestamp.
field (google.cloud.bigquery.schema.SchemaField):
The field corresponding to the value.
Returns:
Optional[datetime.datetime]:
The parsed datetime object from
``value`` if the ``field`` is not null (otherwise it is
:data:`None`).
"""
if _not_null(value, field):
# Canonical formats for timestamps in BigQuery are flexible. See:
# g.co/cloud/bigquery/docs/reference/standard-sql/data-types#timestamp-type
# The separator between the date and time can be 'T' or ' '.
value = value.replace(" ", "T", 1)
# The UTC timezone may be formatted as Z or +00:00.
value = value.replace("Z", "")
value = value.replace("+00:00", "")
if "." in value:
# YYYY-MM-DDTHH:MM:SS.ffffff
return datetime.datetime.strptime(value, _RFC3339_MICROS_NO_ZULU).replace(
tzinfo=UTC
)
else:
# YYYY-MM-DDTHH:MM:SS
return datetime.datetime.strptime(value, _RFC3339_NO_FRACTION).replace(
tzinfo=UTC
)
else:
return None
def _datetime_from_json(value, field):
"""Coerce 'value' to a datetime, if set or not nullable.
Args:
value (str): The timestamp.
field (google.cloud.bigquery.schema.SchemaField):
The field corresponding to the value.
Returns:
Optional[datetime.datetime]:
The parsed datetime object from
``value`` if the ``field`` is not null (otherwise it is
:data:`None`).
"""
if _not_null(value, field):
if "." in value:
# YYYY-MM-DDTHH:MM:SS.ffffff
return datetime.datetime.strptime(value, _RFC3339_MICROS_NO_ZULU)
else:
# YYYY-MM-DDTHH:MM:SS
return datetime.datetime.strptime(value, _RFC3339_NO_FRACTION)
else:
return None
def _date_from_json(value, field):
"""Coerce 'value' to a datetime date, if set or not nullable"""
if _not_null(value, field):
# value will be a string, in YYYY-MM-DD form.
return _date_from_iso8601_date(value)
def _time_from_json(value, field):
"""Coerce 'value' to a datetime date, if set or not nullable"""
if _not_null(value, field):
if len(value) == 8: # HH:MM:SS
fmt = _TIMEONLY_WO_MICROS
elif len(value) == 15: # HH:MM:SS.micros
fmt = _TIMEONLY_W_MICROS
else:
raise ValueError("Unknown time format: {}".format(value))
return datetime.datetime.strptime(value, fmt).time()
def _record_from_json(value, field):
"""Coerce 'value' to a mapping, if set or not nullable."""
if _not_null(value, field):
record = {}
record_iter = zip(field.fields, value["f"])
for subfield, cell in record_iter:
converter = _CELLDATA_FROM_JSON[subfield.field_type]
if subfield.mode == "REPEATED":
value = [converter(item["v"], subfield) for item in cell["v"]]
else:
value = converter(cell["v"], subfield)
record[subfield.name] = value
return record
_CELLDATA_FROM_JSON = {
"INTEGER": _int_from_json,
"INT64": _int_from_json,
"FLOAT": _float_from_json,
"FLOAT64": _float_from_json,
"NUMERIC": _decimal_from_json,
"BIGNUMERIC": _decimal_from_json,
"BOOLEAN": _bool_from_json,
"BOOL": _bool_from_json,
"STRING": _string_from_json,
"GEOGRAPHY": _string_from_json,
"BYTES": _bytes_from_json,
"TIMESTAMP": _timestamp_from_json,
"DATETIME": _datetime_from_json,
"DATE": _date_from_json,
"TIME": _time_from_json,
"RECORD": _record_from_json,
}
_QUERY_PARAMS_FROM_JSON = dict(_CELLDATA_FROM_JSON)
_QUERY_PARAMS_FROM_JSON["TIMESTAMP"] = _timestamp_query_param_from_json
def _field_to_index_mapping(schema):
"""Create a mapping from schema field name to index of field."""
return {f.name: i for i, f in enumerate(schema)}
def _field_from_json(resource, field):
converter = _CELLDATA_FROM_JSON.get(field.field_type, lambda value, _: value)
if field.mode == "REPEATED":
return [converter(item["v"], field) for item in resource]
else:
return converter(resource, field)
def _row_tuple_from_json(row, schema):
"""Convert JSON row data to row with appropriate types.
Note: ``row['f']`` and ``schema`` are presumed to be of the same length.
Args:
row (Dict): A JSON response row to be converted.
schema (Sequence[Union[ \
:class:`~google.cloud.bigquery.schema.SchemaField`, \
Mapping[str, Any] \
]]): Specification of the field types in ``row``.
Returns:
Tuple: A tuple of data converted to native types.
"""
from google.cloud.bigquery.schema import _to_schema_fields
schema = _to_schema_fields(schema)
row_data = []
for field, cell in zip(schema, row["f"]):
row_data.append(_field_from_json(cell["v"], field))
return tuple(row_data)
def _rows_from_json(values, schema):
"""Convert JSON row data to rows with appropriate types.
Args:
values (Sequence[Dict]): The list of responses (JSON rows) to convert.
schema (Sequence[Union[ \
:class:`~google.cloud.bigquery.schema.SchemaField`, \
Mapping[str, Any] \
]]):
The table's schema. If any item is a mapping, its content must be
compatible with
:meth:`~google.cloud.bigquery.schema.SchemaField.from_api_repr`.
Returns:
List[:class:`~google.cloud.bigquery.Row`]
"""
from google.cloud.bigquery import Row
from google.cloud.bigquery.schema import _to_schema_fields
schema = _to_schema_fields(schema)
field_to_index = _field_to_index_mapping(schema)
return [Row(_row_tuple_from_json(r, schema), field_to_index) for r in values]
def _int_to_json(value):
"""Coerce 'value' to an JSON-compatible representation."""
if isinstance(value, int):
value = str(value)
return value
def _float_to_json(value):
"""Coerce 'value' to an JSON-compatible representation."""
return value if value is None else float(value)
def _decimal_to_json(value):
"""Coerce 'value' to a JSON-compatible representation."""
if isinstance(value, decimal.Decimal):
value = str(value)
return value
def _bool_to_json(value):
"""Coerce 'value' to an JSON-compatible representation."""
if isinstance(value, bool):
value = "true" if value else "false"
return value
def _bytes_to_json(value):
"""Coerce 'value' to an JSON-compatible representation."""
if isinstance(value, bytes):
value = base64.standard_b64encode(value).decode("ascii")
return value
def _timestamp_to_json_parameter(value):
"""Coerce 'value' to an JSON-compatible representation.
This version returns the string representation used in query parameters.
"""
if isinstance(value, datetime.datetime):
if value.tzinfo not in (None, UTC):
# Convert to UTC and remove the time zone info.
value = value.replace(tzinfo=None) - value.utcoffset()
value = "%s %s+00:00" % (value.date().isoformat(), value.time().isoformat())
return value
def _timestamp_to_json_row(value):
"""Coerce 'value' to an JSON-compatible representation."""
if isinstance(value, datetime.datetime):
# For naive datetime objects UTC timezone is assumed, thus we format
# those to string directly without conversion.
if value.tzinfo is not None:
value = value.astimezone(UTC)
value = value.strftime(_RFC3339_MICROS)
return value
def _datetime_to_json(value):
"""Coerce 'value' to an JSON-compatible representation."""
if isinstance(value, datetime.datetime):
# For naive datetime objects UTC timezone is assumed, thus we format
# those to string directly without conversion.
if value.tzinfo is not None:
value = value.astimezone(UTC)
value = value.strftime(_RFC3339_MICROS_NO_ZULU)
return value
def _date_to_json(value):
"""Coerce 'value' to an JSON-compatible representation."""
if isinstance(value, datetime.date):
value = value.isoformat()
return value
def _time_to_json(value):
"""Coerce 'value' to an JSON-compatible representation."""
if isinstance(value, datetime.time):
value = value.isoformat()
return value
# Converters used for scalar values marshalled as row data.
_SCALAR_VALUE_TO_JSON_ROW = {
"INTEGER": _int_to_json,
"INT64": _int_to_json,
"FLOAT": _float_to_json,
"FLOAT64": _float_to_json,
"NUMERIC": _decimal_to_json,
"BIGNUMERIC": _decimal_to_json,
"BOOLEAN": _bool_to_json,
"BOOL": _bool_to_json,
"BYTES": _bytes_to_json,
"TIMESTAMP": _timestamp_to_json_row,
"DATETIME": _datetime_to_json,
"DATE": _date_to_json,
"TIME": _time_to_json,
# Make sure DECIMAL and BIGDECIMAL are handled, even though
# requests for them should be converted to NUMERIC. Better safe
# than sorry.
"DECIMAL": _decimal_to_json,
"BIGDECIMAL": _decimal_to_json,
}
# Converters used for scalar values marshalled as query parameters.
_SCALAR_VALUE_TO_JSON_PARAM = _SCALAR_VALUE_TO_JSON_ROW.copy()
_SCALAR_VALUE_TO_JSON_PARAM["TIMESTAMP"] = _timestamp_to_json_parameter
def _scalar_field_to_json(field, row_value):
"""Maps a field and value to a JSON-safe value.
Args:
field (google.cloud.bigquery.schema.SchemaField):
The SchemaField to use for type conversion and field name.
row_value (Any):
Value to be converted, based on the field's type.
Returns:
Any: A JSON-serializable object.
"""
converter = _SCALAR_VALUE_TO_JSON_ROW.get(field.field_type)
if converter is None: # STRING doesn't need converting
return row_value
return converter(row_value)
def _repeated_field_to_json(field, row_value):
"""Convert a repeated/array field to its JSON representation.
Args:
field (google.cloud.bigquery.schema.SchemaField):
The SchemaField to use for type conversion and field name. The
field mode must equal ``REPEATED``.
row_value (Sequence[Any]):
A sequence of values to convert to JSON-serializable values.
Returns:
List[Any]: A list of JSON-serializable objects.
"""
values = []
for item in row_value:
values.append(_single_field_to_json(field, item))
return values
def _record_field_to_json(fields, row_value):
"""Convert a record/struct field to its JSON representation.
Args:
fields (Sequence[google.cloud.bigquery.schema.SchemaField]):
The :class:`~google.cloud.bigquery.schema.SchemaField`s of the
record's subfields to use for type conversion and field names.
row_value (Union[Tuple[Any], Mapping[str, Any]):
A tuple or dictionary to convert to JSON-serializable values.
Returns:
Mapping[str, Any]: A JSON-serializable dictionary.
"""
isdict = isinstance(row_value, dict)
# If row is passed as a tuple, make the length sanity check to avoid either
# uninformative index errors a few lines below or silently omitting some of
# the values from the result (we cannot know exactly which fields are missing
# or redundant, since we don't have their names).
if not isdict and len(row_value) != len(fields):
msg = "The number of row fields ({}) does not match schema length ({}).".format(
len(row_value), len(fields)
)
raise ValueError(msg)
record = {}
if isdict:
processed_fields = set()
for subindex, subfield in enumerate(fields):
subname = subfield.name
subvalue = row_value.get(subname) if isdict else row_value[subindex]
# None values are unconditionally omitted
if subvalue is not None:
record[subname] = _field_to_json(subfield, subvalue)
if isdict:
processed_fields.add(subname)
# Unknown fields should not be silently dropped, include them. Since there
# is no schema information available for them, include them as strings
# to make them JSON-serializable.
if isdict:
not_processed = set(row_value.keys()) - processed_fields
for field_name in not_processed:
value = row_value[field_name]
if value is not None:
record[field_name] = str(value)
return record
def _single_field_to_json(field, row_value):
"""Convert a single field into JSON-serializable values.
Ignores mode so that this can function for ARRAY / REPEATING fields
without requiring a deepcopy of the field. See:
https://github.com/googleapis/python-bigquery/issues/6
Args:
field (google.cloud.bigquery.schema.SchemaField):
The SchemaField to use for type conversion and field name.
row_value (Any):
Scalar or Struct to be inserted. The type
is inferred from the SchemaField's field_type.
Returns:
Any: A JSON-serializable object.
"""
if row_value is None:
return None
if field.field_type == "RECORD":
return _record_field_to_json(field.fields, row_value)
return _scalar_field_to_json(field, row_value)
def _field_to_json(field, row_value):
"""Convert a field into JSON-serializable values.
Args:
field (google.cloud.bigquery.schema.SchemaField):
The SchemaField to use for type conversion and field name.
row_value (Union[Sequence[List], Any]):
Row data to be inserted. If the SchemaField's mode is
REPEATED, assume this is a list. If not, the type
is inferred from the SchemaField's field_type.
Returns:
Any: A JSON-serializable object.
"""
if row_value is None:
return None
if field.mode == "REPEATED":
return _repeated_field_to_json(field, row_value)
return _single_field_to_json(field, row_value)
def _snake_to_camel_case(value):
"""Convert snake case string to camel case."""
words = value.split("_")
return words[0] + "".join(map(str.capitalize, words[1:]))
def _get_sub_prop(container, keys, default=None):
"""Get a nested value from a dictionary.
This method works like ``dict.get(key)``, but for nested values.
Args:
container (Dict):
A dictionary which may contain other dictionaries as values.
keys (Iterable):
A sequence of keys to attempt to get the value for. Each item in
the sequence represents a deeper nesting. The first key is for
the top level. If there is a dictionary there, the second key
attempts to get the value within that, and so on.
default (Optional[object]):
Value to returned if any of the keys are not found.
Defaults to ``None``.
Examples:
Get a top-level value (equivalent to ``container.get('key')``).
>>> _get_sub_prop({'key': 'value'}, ['key'])
'value'
Get a top-level value, providing a default (equivalent to
``container.get('key', default='default')``).
>>> _get_sub_prop({'nothere': 123}, ['key'], default='not found')
'not found'
Get a nested value.
>>> _get_sub_prop({'key': {'subkey': 'value'}}, ['key', 'subkey'])
'value'
Returns:
object: The value if present or the default.
"""
sub_val = container
for key in keys:
if key not in sub_val:
return default
sub_val = sub_val[key]
return sub_val
def _set_sub_prop(container, keys, value):
"""Set a nested value in a dictionary.
Args:
container (Dict):
A dictionary which may contain other dictionaries as values.
keys (Iterable):
A sequence of keys to attempt to set the value for. Each item in
the sequence represents a deeper nesting. The first key is for
the top level. If there is a dictionary there, the second key
attempts to get the value within that, and so on.
value (object): Value to set within the container.
Examples:
Set a top-level value (equivalent to ``container['key'] = 'value'``).
>>> container = {}
>>> _set_sub_prop(container, ['key'], 'value')
>>> container
{'key': 'value'}
Set a nested value.
>>> container = {}
>>> _set_sub_prop(container, ['key', 'subkey'], 'value')
>>> container
{'key': {'subkey': 'value'}}
Replace a nested value.
>>> container = {'key': {'subkey': 'prev'}}
>>> _set_sub_prop(container, ['key', 'subkey'], 'new')
>>> container
{'key': {'subkey': 'new'}}
"""
sub_val = container
for key in keys[:-1]:
if key not in sub_val:
sub_val[key] = {}
sub_val = sub_val[key]
sub_val[keys[-1]] = value
def _del_sub_prop(container, keys):
"""Remove a nested key fro a dictionary.
Args:
container (Dict):
A dictionary which may contain other dictionaries as values.
keys (Iterable):
A sequence of keys to attempt to clear the value for. Each item in
the sequence represents a deeper nesting. The first key is for
the top level. If there is a dictionary there, the second key
attempts to get the value within that, and so on.
Examples:
Remove a top-level value (equivalent to ``del container['key']``).
>>> container = {'key': 'value'}
>>> _del_sub_prop(container, ['key'])
>>> container
{}
Remove a nested value.
>>> container = {'key': {'subkey': 'value'}}
>>> _del_sub_prop(container, ['key', 'subkey'])
>>> container
{'key': {}}
"""
sub_val = container
for key in keys[:-1]:
if key not in sub_val:
sub_val[key] = {}
sub_val = sub_val[key]
if keys[-1] in sub_val:
del sub_val[keys[-1]]
def _int_or_none(value):
"""Helper: deserialize int value from JSON string."""
if isinstance(value, int):
return value
if value is not None:
return int(value)
def _str_or_none(value):
"""Helper: serialize value to JSON string."""
if value is not None:
return str(value)
def _split_id(full_id):
"""Helper: split full_id into composite parts.
Args:
full_id (str): Fully-qualified ID in standard SQL format.
Returns:
List[str]: ID's parts separated into components.
"""
with_prefix = _PROJECT_PREFIX_PATTERN.match(full_id)
if with_prefix is None:
parts = full_id.split(".")
else:
parts = with_prefix.groups()
parts = [part for part in parts if part]
return parts
def _parse_3_part_id(full_id, default_project=None, property_name="table_id"):
output_project_id = default_project
output_dataset_id = None
output_resource_id = None
parts = _split_id(full_id)
if len(parts) != 2 and len(parts) != 3:
raise ValueError(
"{property_name} must be a fully-qualified ID in "
'standard SQL format, e.g., "project.dataset.{property_name}", '
"got {}".format(full_id, property_name=property_name)
)
if len(parts) == 2 and not default_project:
raise ValueError(
"When default_project is not set, {property_name} must be a "
"fully-qualified ID in standard SQL format, "
'e.g., "project.dataset_id.{property_name}", got {}'.format(
full_id, property_name=property_name
)
)
if len(parts) == 2:
output_dataset_id, output_resource_id = parts
else:
output_project_id, output_dataset_id, output_resource_id = parts
return output_project_id, output_dataset_id, output_resource_id
def _build_resource_from_properties(obj, filter_fields):
"""Build a resource based on a ``_properties`` dictionary, filtered by
``filter_fields``, which follow the name of the Python object.
"""
partial = {}
for filter_field in filter_fields:
api_field = obj._PROPERTY_TO_API_FIELD.get(filter_field)
if api_field is None and filter_field not in obj._properties:
raise ValueError("No property %s" % filter_field)
elif api_field is not None:
partial[api_field] = obj._properties.get(api_field)
else:
# allows properties that are not defined in the library
# and properties that have the same name as API resource key
partial[filter_field] = obj._properties[filter_field]
return partial
def _verify_job_config_type(job_config, expected_type, param_name="job_config"):
if not isinstance(job_config, expected_type):
msg = (
"Expected an instance of {expected_type} class for the {param_name} parameter, "
"but received {param_name} = {job_config}"
)
raise TypeError(
msg.format(
expected_type=expected_type.__name__,
param_name=param_name,
job_config=job_config,
)
)