Datasets:

LiteFold
/

DisProt

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
dataset_id: string
row: struct<data: list<item: struct<UniParc: string, __v: int64, acc: string, creator: string, dataset: l (... 3982 chars omitted)
  child 0, data: list<item: struct<UniParc: string, __v: int64, acc: string, creator: string, dataset: list<item: str (... 3955 chars omitted)
      child 0, item: struct<UniParc: string, __v: int64, acc: string, creator: string, dataset: list<item: string>, date: (... 3943 chars omitted)
          child 0, UniParc: string
          child 1, __v: int64
          child 2, acc: string
          child 3, creator: string
          child 4, dataset: list<item: string>
              child 0, item: string
          child 5, date: string
          child 6, disorder_content: double
          child 7, disprot_consensus: struct<Structural state: list<item: struct<end: int64, start: int64, type: string>>, full: list<item (... 452 chars omitted)
              child 0, Structural state: list<item: struct<end: int64, start: int64, type: string>>
                  child 0, item: struct<end: int64, start: int64, type: string>
                      child 0, end: int64
                      child 1, start: int64
                      child 2, type: string
              child 1, full: list<item: struct<end: int64, start: int64, type: string>>
                  child 0, item: struct<end: int64, start: int64, type: string>
                      child 0, end: int64
                      child 1, start: int64
                      child 2, type: string
...
_binding: bool
                  child 35, term_is_obsolete: bool
                  child 36, term_not_annotate: bool
                  child 37, unpublished: bool
                  child 38, term_go_domain: string
                  child 39, term_xref: string
                  child 40, sequence_construct: string
                  child 41, confidence: list<item: struct<tag: string>>
                      child 0, item: struct<tag: string>
                          child 0, tag: string
          child 16, regions_counter: int64
          child 17, released: string
          child 18, sequence: string
          child 19, taxonomy: list<item: string>
              child 0, item: string
          child 20, uniref100: string
          child 21, uniref50: string
          child 22, uniref90: string
          child 23, alphafold_very_low_content: string
          child 24, uniparc: string
  child 1, size: int64
row_index: int64
source_file: string
tables: list<item: struct<bytes: int64, category: string, dataset_id: string, output_file: string, rows: int (... 41 chars omitted)
  child 0, item: struct<bytes: int64, category: string, dataset_id: string, output_file: string, rows: int64, source_ (... 29 chars omitted)
      child 0, bytes: int64
      child 1, category: string
      child 2, dataset_id: string
      child 3, output_file: string
      child 4, rows: int64
      child 5, source_file: string
      child 6, status: string
format: string
total_rows: int64
category: string
to
{'category': Value('string'), 'dataset_id': Value('string'), 'format': Value('string'), 'tables': List({'bytes': Value('int64'), 'category': Value('string'), 'dataset_id': Value('string'), 'output_file': Value('string'), 'rows': Value('int64'), 'source_file': Value('string'), 'status': Value('string')}), 'total_rows': Value('int64')}
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
              dataset_id: string
              row: struct<data: list<item: struct<UniParc: string, __v: int64, acc: string, creator: string, dataset: l (... 3982 chars omitted)
                child 0, data: list<item: struct<UniParc: string, __v: int64, acc: string, creator: string, dataset: list<item: str (... 3955 chars omitted)
                    child 0, item: struct<UniParc: string, __v: int64, acc: string, creator: string, dataset: list<item: string>, date: (... 3943 chars omitted)
                        child 0, UniParc: string
                        child 1, __v: int64
                        child 2, acc: string
                        child 3, creator: string
                        child 4, dataset: list<item: string>
                            child 0, item: string
                        child 5, date: string
                        child 6, disorder_content: double
                        child 7, disprot_consensus: struct<Structural state: list<item: struct<end: int64, start: int64, type: string>>, full: list<item (... 452 chars omitted)
                            child 0, Structural state: list<item: struct<end: int64, start: int64, type: string>>
                                child 0, item: struct<end: int64, start: int64, type: string>
                                    child 0, end: int64
                                    child 1, start: int64
                                    child 2, type: string
                            child 1, full: list<item: struct<end: int64, start: int64, type: string>>
                                child 0, item: struct<end: int64, start: int64, type: string>
                                    child 0, end: int64
                                    child 1, start: int64
                                    child 2, type: string
              ...
              _binding: bool
                                child 35, term_is_obsolete: bool
                                child 36, term_not_annotate: bool
                                child 37, unpublished: bool
                                child 38, term_go_domain: string
                                child 39, term_xref: string
                                child 40, sequence_construct: string
                                child 41, confidence: list<item: struct<tag: string>>
                                    child 0, item: struct<tag: string>
                                        child 0, tag: string
                        child 16, regions_counter: int64
                        child 17, released: string
                        child 18, sequence: string
                        child 19, taxonomy: list<item: string>
                            child 0, item: string
                        child 20, uniref100: string
                        child 21, uniref50: string
                        child 22, uniref90: string
                        child 23, alphafold_very_low_content: string
                        child 24, uniparc: string
                child 1, size: int64
              row_index: int64
              source_file: string
              tables: list<item: struct<bytes: int64, category: string, dataset_id: string, output_file: string, rows: int (... 41 chars omitted)
                child 0, item: struct<bytes: int64, category: string, dataset_id: string, output_file: string, rows: int64, source_ (... 29 chars omitted)
                    child 0, bytes: int64
                    child 1, category: string
                    child 2, dataset_id: string
                    child 3, output_file: string
                    child 4, rows: int64
                    child 5, source_file: string
                    child 6, status: string
              format: string
              total_rows: int64
              category: string
              to
              {'category': Value('string'), 'dataset_id': Value('string'), 'format': Value('string'), 'tables': List({'bytes': Value('int64'), 'category': Value('string'), 'dataset_id': Value('string'), 'output_file': Value('string'), 'rows': Value('int64'), 'source_file': Value('string'), 'status': Value('string')}), 'total_rows': Value('int64')}
              because column names don't match

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DisProt

DisProt curated intrinsically disordered protein annotations, normalized to newline-delimited JSON with row-level provenance.

Processed and uploaded by the MegaData post-download pipeline (internal repo). Original source: https://disprot.org/.

Statistics


Table files	1
Total rows	1
Total bytes	25.58 MiB (26,821,358)

Tables

Table	Rows	Bytes
`annotation_disprot_disprot_current.json.jsonl`	1	25.58 MiB

Layout

.
├── _MANIFEST.json                 # aggregate manifest (per-table counts)
└── tables/<source_slug>.jsonl    # normalized rows (one JSON object per line)

Each line in a tables/*.jsonl file is a JSON object with at least dataset_id, row (the raw upstream row), row_index, and source_file fields, so every row carries its upstream provenance.

Loading

hf download LiteFold/DisProt --repo-type dataset --local-dir ./disprot

Programmatic streaming:

import json
from pathlib import Path
from huggingface_hub import snapshot_download

local = snapshot_download(repo_id="LiteFold/DisProt", repo_type="dataset")
for jsonl in sorted(Path(local, "tables").glob("*.jsonl")):
    with jsonl.open() as f:
        for line in f:
            row = json.loads(line)
            ...  # row["row"] is the upstream record

License

CC BY 4.0 (DisProt).

Citation

Quaglia F, et al. DisProt in 2022: improved quality and accessibility of protein intrinsic disorder annotation. Nucleic Acids Research, 50(D1):D480-D487, 2022.

Provenance

Built from the local manifest entry disprot of manifests/atlas_download_plan.json. Pipeline source: megadata-post normalize --dataset disprot --tables-only.

Downloads last month: 25

Total file size:

26.8 MB