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triyambakam
/
reposage-data

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ml-intern
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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
time: timestamp[s]
repo: string
target: string
files: int64
engine: string
bounty_engine: struct<contacts: int64, emails_per_day: int64, seo_pages: int64, workflows: int64, bug_targets: int6 (... 36 chars omitted)
  child 0, contacts: int64
  child 1, emails_per_day: int64
  child 2, seo_pages: int64
  child 3, workflows: int64
  child 4, bug_targets: int64
  child 5, status: string
  child 6, last_run: string
teams: int64
repos_scanned: int64
revenue_usd: double
paid: int64
updated_at: timestamp[s]
risks_found: int64
to
{'repos_scanned': Value('int64'), 'risks_found': Value('int64'), 'teams': Value('int64'), 'paid': Value('int64'), 'revenue_usd': Value('float64'), 'bounty_engine': {'contacts': Value('int64'), 'emails_per_day': Value('int64'), 'seo_pages': Value('int64'), 'workflows': Value('int64'), 'bug_targets': Value('int64'), 'status': Value('string'), 'last_run': Value('string')}, 'updated_at': Value('timestamp[s]')}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
                  return get_rows(
                         ^^^^^^^^^
                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 77, in get_rows
                  rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
                                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2690, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2227, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2251, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 494, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 384, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 299, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 128, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2321, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2249, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              time: timestamp[s]
              repo: string
              target: string
              files: int64
              engine: string
              bounty_engine: struct<contacts: int64, emails_per_day: int64, seo_pages: int64, workflows: int64, bug_targets: int6 (... 36 chars omitted)
                child 0, contacts: int64
                child 1, emails_per_day: int64
                child 2, seo_pages: int64
                child 3, workflows: int64
                child 4, bug_targets: int64
                child 5, status: string
                child 6, last_run: string
              teams: int64
              repos_scanned: int64
              revenue_usd: double
              paid: int64
              updated_at: timestamp[s]
              risks_found: int64
              to
              {'repos_scanned': Value('int64'), 'risks_found': Value('int64'), 'teams': Value('int64'), 'paid': Value('int64'), 'revenue_usd': Value('float64'), 'bounty_engine': {'contacts': Value('int64'), 'emails_per_day': Value('int64'), 'seo_pages': Value('int64'), 'workflows': Value('int64'), 'bug_targets': Value('int64'), 'status': Value('string'), 'last_run': Value('string')}, 'updated_at': Value('timestamp[s]')}
              because column names don't match

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triyambakam/reposage-data

Generated by ML Intern

This dataset repository was generated by ML Intern, an agent for machine learning research and development on the Hugging Face Hub.

Usage 

from datasets import load_dataset

dataset = load_dataset("triyambakam/reposage-data")
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