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Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
0: int64
1: int64
2: int64
3: int64
4: int64
5: int64
6: int64
7: int64
8: int64
9: int64
10: int64
11: int64
12: int64
13: int64
14: int64
15: int64
16: int64
17: int64
18: int64
19: int64
20: int64
21: int64
22: int64
23: int64
24: int64
25: int64
26: int64
27: int64
28: int64
29: int64
30: int64
31: int64
32: int64
33: int64
34: int64
35: int64
36: int64
37: int64
38: int64
39: int64
40: int64
41: int64
42: int64
43: int64
44: int64
45: int64
46: int64
47: int64
48: int64
49: int64
50: int64
51: int64
52: int64
53: int64
54: int64
55: int64
56: int64
57: int64
58: int64
59: int64
60: int64
61: int64
62: int64
63: int64
64: int64
65: int64
66: int64
67: int64
68: int64
69: int64
70: int64
71: int64
72: int64
73: int64
74: int64
75: int64
76: int64
77: int64
78: int64
79: int64
80: int64
81: int64
82: int64
83: int64
84: int64
85: int64
86: int64
87: int64
88: int64
89: int64
90: int64
91: int64
92: int64
93: int64
94: int64
95: int64
96: int64
97: int64
98: int64
99: int64
100: int64
101: int64
102: int64
103: int64
104: int64
105: int64
106: int64
107: int64
108: int64
109: int64
110: int64
111: int64
112: int64
113: int64
114: int64
115: int64
116: int64
117: int64
118: int64
119: int64
120: int64
121: int64
122: int64
123: int64
124: int64
125: int64
126: int64
127: int64
128: int64
129: int64
130: int64
131: int64
132: int64
133: int64
134: int64
135: int64
136: int64
137: int64
138: int64
139: int64
140: int64
141: int64
142: int64
143: int64
144: int64
145: int64
146:
...
1045: int64
1046: int64
1047: int64
1048: int64
1049: int64
1050: int64
1051: int64
1052: int64
1053: int64
1054: int64
1055: int64
1056: int64
1057: int64
1058: int64
1059: int64
1060: int64
1061: int64
1062: int64
1063: int64
1064: int64
1065: int64
1066: int64
1067: int64
1068: int64
1069: int64
1070: int64
1071: int64
1072: int64
1073: int64
1074: int64
1075: int64
1076: int64
1077: int64
1078: int64
1079: int64
1080: int64
1081: int64
1082: int64
1083: int64
1084: int64
1085: int64
1086: int64
1087: int64
1088: int64
1089: int64
1090: int64
1091: int64
1092: int64
1093: int64
1094: int64
depth_bias: list<item: double>
child 0, item: double
model: string
kind: string
tchp: struct<rule: string, offset: double, rmse_band: double, bias: double, how: string>
child 0, rule: string
child 1, offset: double
child 2, rmse_band: double
child 3, bias: double
child 4, how: string
mld: string
fit: struct<fit_profiles: int64, fit_floats: int64, fit_dates: string, scored_profiles: int64, scored_fro (... 153 chars omitted)
child 0, fit_profiles: int64
child 1, fit_floats: int64
child 2, fit_dates: string
child 3, scored_profiles: int64
child 4, scored_from: timestamp[s]
child 5, scored_floats: int64
child 6, unseen_rmse_raw: double
child 7, unseen_rmse_corrected: double
child 8, gain: double
child 9, gain_ci95: list<item: double>
child 0, item: double
child 10, rule: string
depths: list<item: int64>
child 0, item: int64
depth_bias_applies: string
to
{'model': Value('string'), 'kind': Value('string'), 'depths': List(Value('int64')), 'depth_bias': List(Value('float64')), 'depth_bias_applies': Value('string'), 'mld': Value('string'), 'tchp': {'rule': Value('string'), 'offset': Value('float64'), 'rmse_band': Value('float64'), 'bias': Value('float64'), 'how': Value('string')}, 'fit': {'fit_profiles': Value('int64'), 'fit_floats': Value('int64'), 'fit_dates': Value('string'), 'scored_profiles': Value('int64'), 'scored_from': Value('timestamp[s]'), 'scored_floats': Value('int64'), 'unseen_rmse_raw': Value('float64'), 'unseen_rmse_corrected': Value('float64'), 'gain': Value('float64'), 'gain_ci95': List(Value('float64')), 'rule': Value('string')}}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
return get_rows(
dataset=dataset,
...<4 lines>...
column_names=column_names,
)
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
File "/src/services/worker/src/worker/utils.py", line 127, in get_rows
rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
File "/src/services/worker/src/worker/utils.py", line 483, in safe_iter
yield from ds.decode(False) if ds.features else ds
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2840, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2373, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2398, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
0: int64
1: int64
2: int64
3: int64
4: int64
5: int64
6: int64
7: int64
8: int64
9: int64
10: int64
11: int64
12: int64
13: int64
14: int64
15: int64
16: int64
17: int64
18: int64
19: int64
20: int64
21: int64
22: int64
23: int64
24: int64
25: int64
26: int64
27: int64
28: int64
29: int64
30: int64
31: int64
32: int64
33: int64
34: int64
35: int64
36: int64
37: int64
38: int64
39: int64
40: int64
41: int64
42: int64
43: int64
44: int64
45: int64
46: int64
47: int64
48: int64
49: int64
50: int64
51: int64
52: int64
53: int64
54: int64
55: int64
56: int64
57: int64
58: int64
59: int64
60: int64
61: int64
62: int64
63: int64
64: int64
65: int64
66: int64
67: int64
68: int64
69: int64
70: int64
71: int64
72: int64
73: int64
74: int64
75: int64
76: int64
77: int64
78: int64
79: int64
80: int64
81: int64
82: int64
83: int64
84: int64
85: int64
86: int64
87: int64
88: int64
89: int64
90: int64
91: int64
92: int64
93: int64
94: int64
95: int64
96: int64
97: int64
98: int64
99: int64
100: int64
101: int64
102: int64
103: int64
104: int64
105: int64
106: int64
107: int64
108: int64
109: int64
110: int64
111: int64
112: int64
113: int64
114: int64
115: int64
116: int64
117: int64
118: int64
119: int64
120: int64
121: int64
122: int64
123: int64
124: int64
125: int64
126: int64
127: int64
128: int64
129: int64
130: int64
131: int64
132: int64
133: int64
134: int64
135: int64
136: int64
137: int64
138: int64
139: int64
140: int64
141: int64
142: int64
143: int64
144: int64
145: int64
146:
...
1045: int64
1046: int64
1047: int64
1048: int64
1049: int64
1050: int64
1051: int64
1052: int64
1053: int64
1054: int64
1055: int64
1056: int64
1057: int64
1058: int64
1059: int64
1060: int64
1061: int64
1062: int64
1063: int64
1064: int64
1065: int64
1066: int64
1067: int64
1068: int64
1069: int64
1070: int64
1071: int64
1072: int64
1073: int64
1074: int64
1075: int64
1076: int64
1077: int64
1078: int64
1079: int64
1080: int64
1081: int64
1082: int64
1083: int64
1084: int64
1085: int64
1086: int64
1087: int64
1088: int64
1089: int64
1090: int64
1091: int64
1092: int64
1093: int64
1094: int64
depth_bias: list<item: double>
child 0, item: double
model: string
kind: string
tchp: struct<rule: string, offset: double, rmse_band: double, bias: double, how: string>
child 0, rule: string
child 1, offset: double
child 2, rmse_band: double
child 3, bias: double
child 4, how: string
mld: string
fit: struct<fit_profiles: int64, fit_floats: int64, fit_dates: string, scored_profiles: int64, scored_fro (... 153 chars omitted)
child 0, fit_profiles: int64
child 1, fit_floats: int64
child 2, fit_dates: string
child 3, scored_profiles: int64
child 4, scored_from: timestamp[s]
child 5, scored_floats: int64
child 6, unseen_rmse_raw: double
child 7, unseen_rmse_corrected: double
child 8, gain: double
child 9, gain_ci95: list<item: double>
child 0, item: double
child 10, rule: string
depths: list<item: int64>
child 0, item: int64
depth_bias_applies: string
to
{'model': Value('string'), 'kind': Value('string'), 'depths': List(Value('int64')), 'depth_bias': List(Value('float64')), 'depth_bias_applies': Value('string'), 'mld': Value('string'), 'tchp': {'rule': Value('string'), 'offset': Value('float64'), 'rmse_band': Value('float64'), 'bias': Value('float64'), 'how': Value('string')}, 'fit': {'fit_profiles': Value('int64'), 'fit_floats': Value('int64'), 'fit_dates': Value('string'), 'scored_profiles': Value('int64'), 'scored_from': Value('timestamp[s]'), 'scored_floats': Value('int64'), 'unseen_rmse_raw': Value('float64'), 'unseen_rmse_corrected': Value('float64'), 'gain': Value('float64'), 'gain_ci95': List(Value('float64')), 'rule': Value('string')}}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
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