Dataset Viewer
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
schema: string
id: string
starts_at_utc: timestamp[s]
ends_at_utc: timestamp[s]
submission_deadline_utc: timestamp[s]
created_at_utc: string
grid: struct<width: int64, height: int64, crs: string, transform: list<item: double>>
child 0, width: int64
child 1, height: int64
child 2, crs: string
child 3, transform: list<item: double>
child 0, item: double
mask_path: string
mask_sha256: string
max_cells: int64
max_bytes: int64
windows: list<item: struct<lead_hours: int64, start_utc: timestamp[s], end_utc: timestamp[s]>>
child 0, item: struct<lead_hours: int64, start_utc: timestamp[s], end_utc: timestamp[s]>
child 0, lead_hours: int64
child 1, start_utc: timestamp[s]
child 2, end_utc: timestamp[s]
method: string
track: string
model_execution: bool
public_predictions: bool
deferred_checks: int64
updated_at_utc: string
dataset: string
rounds: list<item: struct<schema: string, id: string, starts_at_utc: timestamp[s], ends_at_utc: timestamp[s] (... 404 chars omitted)
child 0, item: struct<schema: string, id: string, starts_at_utc: timestamp[s], ends_at_utc: timestamp[s], submissio (... 392 chars omitted)
child 0, schema: string
child 1, id: string
child 2, starts_at_utc: timestamp[s]
child 3, ends_at_utc: timestamp[s]
child 4, submission_deadline_utc: timestamp[s]
child 5, created_at_utc: string
child 6, grid: struct<width: int64, height: int64, crs: string, transform: list<item: double>>
child 0, width: int64
child 1, height: int64
child 2, crs: string
child 3, transform: list<item: double>
child 0, item: double
child 7, mask_path: string
child 8, mask_sha256: string
child 9, max_cells: int64
child 10, max_bytes: int64
child 11, windows: list<item: struct<lead_hours: int64, start_utc: timestamp[s], end_utc: timestamp[s]>>
child 0, item: struct<lead_hours: int64, start_utc: timestamp[s], end_utc: timestamp[s]>
child 0, lead_hours: int64
child 1, start_utc: timestamp[s]
child 2, end_utc: timestamp[s]
child 12, method: string
child 13, track: string
child 14, model_execution: bool
child 15, public_predictions: bool
reference_status: string
results: list<item: null>
child 0, item: null
to
{'schema': Value('string'), 'updated_at_utc': Value('string'), 'dataset': Value('string'), 'method': Value('string'), 'model_execution': Value('bool'), 'reference_status': Value('string'), 'deferred_checks': Value('int64'), 'rounds': List({'schema': Value('string'), 'id': Value('string'), 'starts_at_utc': Value('timestamp[s]'), 'ends_at_utc': Value('timestamp[s]'), 'submission_deadline_utc': Value('timestamp[s]'), 'created_at_utc': Value('string'), 'grid': {'width': Value('int64'), 'height': Value('int64'), 'crs': Value('string'), 'transform': List(Value('float64'))}, 'mask_path': Value('string'), 'mask_sha256': Value('string'), 'max_cells': Value('int64'), 'max_bytes': Value('int64'), 'windows': List({'lead_hours': Value('int64'), 'start_utc': Value('timestamp[s]'), 'end_utc': Value('timestamp[s]')}), 'method': Value('string'), 'track': Value('string'), 'model_execution': Value('bool'), 'public_predictions': Value('bool')}), 'results': List(Value('null'))}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 149, 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 129, 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 544, 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 3052, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2559, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2584, 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 558, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 440, 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 361, 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 2381, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2309, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
schema: string
id: string
starts_at_utc: timestamp[s]
ends_at_utc: timestamp[s]
submission_deadline_utc: timestamp[s]
created_at_utc: string
grid: struct<width: int64, height: int64, crs: string, transform: list<item: double>>
child 0, width: int64
child 1, height: int64
child 2, crs: string
child 3, transform: list<item: double>
child 0, item: double
mask_path: string
mask_sha256: string
max_cells: int64
max_bytes: int64
windows: list<item: struct<lead_hours: int64, start_utc: timestamp[s], end_utc: timestamp[s]>>
child 0, item: struct<lead_hours: int64, start_utc: timestamp[s], end_utc: timestamp[s]>
child 0, lead_hours: int64
child 1, start_utc: timestamp[s]
child 2, end_utc: timestamp[s]
method: string
track: string
model_execution: bool
public_predictions: bool
deferred_checks: int64
updated_at_utc: string
dataset: string
rounds: list<item: struct<schema: string, id: string, starts_at_utc: timestamp[s], ends_at_utc: timestamp[s] (... 404 chars omitted)
child 0, item: struct<schema: string, id: string, starts_at_utc: timestamp[s], ends_at_utc: timestamp[s], submissio (... 392 chars omitted)
child 0, schema: string
child 1, id: string
child 2, starts_at_utc: timestamp[s]
child 3, ends_at_utc: timestamp[s]
child 4, submission_deadline_utc: timestamp[s]
child 5, created_at_utc: string
child 6, grid: struct<width: int64, height: int64, crs: string, transform: list<item: double>>
child 0, width: int64
child 1, height: int64
child 2, crs: string
child 3, transform: list<item: double>
child 0, item: double
child 7, mask_path: string
child 8, mask_sha256: string
child 9, max_cells: int64
child 10, max_bytes: int64
child 11, windows: list<item: struct<lead_hours: int64, start_utc: timestamp[s], end_utc: timestamp[s]>>
child 0, item: struct<lead_hours: int64, start_utc: timestamp[s], end_utc: timestamp[s]>
child 0, lead_hours: int64
child 1, start_utc: timestamp[s]
child 2, end_utc: timestamp[s]
child 12, method: string
child 13, track: string
child 14, model_execution: bool
child 15, public_predictions: bool
reference_status: string
results: list<item: null>
child 0, item: null
to
{'schema': Value('string'), 'updated_at_utc': Value('string'), 'dataset': Value('string'), 'method': Value('string'), 'model_execution': Value('bool'), 'reference_status': Value('string'), 'deferred_checks': Value('int64'), 'rounds': List({'schema': Value('string'), 'id': Value('string'), 'starts_at_utc': Value('timestamp[s]'), 'ends_at_utc': Value('timestamp[s]'), 'submission_deadline_utc': Value('timestamp[s]'), 'created_at_utc': Value('string'), 'grid': {'width': Value('int64'), 'height': Value('int64'), 'crs': Value('string'), 'transform': List(Value('float64'))}, 'mask_path': Value('string'), 'mask_sha256': Value('string'), 'max_cells': Value('int64'), 'max_bytes': Value('int64'), 'windows': List({'lead_hours': Value('int64'), 'start_utc': Value('timestamp[s]'), 'end_utc': Value('timestamp[s]')}), 'method': Value('string'), 'track': Value('string'), 'model_execution': Value('bool'), 'public_predictions': Value('bool')}), 'results': List(Value('null'))}
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.
Fire-eye weekly forecast challenge
Public forecast data, immutable receipts, rounds, observed-fire evidence and comparisons. Participants run their own models. No model code or weights are executed here. Regional 5 km submissions contain fourteen 12-hour windows covering seven days. Comparisons use documented wildfire-discovery cells and show FireWx-FM only where an advance reference exists.
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