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
dataset_id: string
row: struct<mutant: struct<deletions: list<item: null>, experiment: struct<annotations: list<item: struct (... 2160 chars omitted)
child 0, mutant: struct<deletions: list<item: null>, experiment: struct<annotations: list<item: struct<numValue: doub (... 1399 chars omitted)
child 0, deletions: list<item: null>
child 0, item: null
child 1, experiment: struct<annotations: list<item: struct<numValue: double, strValue: string, type: string>>, dataset: s (... 370 chars omitted)
child 0, annotations: list<item: struct<numValue: double, strValue: string, type: string>>
child 0, item: struct<numValue: double, strValue: string, type: string>
child 0, numValue: double
child 1, strValue: string
child 2, type: string
child 1, dataset: string
child 2, id: int64
child 3, measurements: list<item: struct<datasets: list<item: string>, id: int64, numValue: double, references: list<item: (... 39 chars omitted)
child 0, item: struct<datasets: list<item: string>, id: int64, numValue: double, references: list<item: null>, strV (... 27 chars omitted)
child 0, datasets: list<item: string>
child 0, item: string
child 1, id: int64
child 2, numValue: double
child 3, references: list<item: null>
child 0, item: null
...
ring, referen (... 73 chars omitted)
child 0, item: struct<isoform: int64, protein: struct<id: int64, name: string, organism: string, references: list<i (... 61 chars omitted)
child 0, isoform: int64
child 1, protein: struct<id: int64, name: string, organism: string, references: list<item: struct<accession: string, n (... 28 chars omitted)
child 0, id: int64
child 1, name: string
child 2, organism: string
child 3, references: list<item: struct<accession: string, name: string, type: string>>
child 0, item: struct<accession: string, name: string, type: string>
child 0, accession: string
child 1, name: string
child 2, type: string
child 4, structures: list<item: null>
child 0, item: null
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
category: string
total_rows: int64
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<mutant: struct<deletions: list<item: null>, experiment: struct<annotations: list<item: struct (... 2160 chars omitted)
child 0, mutant: struct<deletions: list<item: null>, experiment: struct<annotations: list<item: struct<numValue: doub (... 1399 chars omitted)
child 0, deletions: list<item: null>
child 0, item: null
child 1, experiment: struct<annotations: list<item: struct<numValue: double, strValue: string, type: string>>, dataset: s (... 370 chars omitted)
child 0, annotations: list<item: struct<numValue: double, strValue: string, type: string>>
child 0, item: struct<numValue: double, strValue: string, type: string>
child 0, numValue: double
child 1, strValue: string
child 2, type: string
child 1, dataset: string
child 2, id: int64
child 3, measurements: list<item: struct<datasets: list<item: string>, id: int64, numValue: double, references: list<item: (... 39 chars omitted)
child 0, item: struct<datasets: list<item: string>, id: int64, numValue: double, references: list<item: null>, strV (... 27 chars omitted)
child 0, datasets: list<item: string>
child 0, item: string
child 1, id: int64
child 2, numValue: double
child 3, references: list<item: null>
child 0, item: null
...
ring, referen (... 73 chars omitted)
child 0, item: struct<isoform: int64, protein: struct<id: int64, name: string, organism: string, references: list<i (... 61 chars omitted)
child 0, isoform: int64
child 1, protein: struct<id: int64, name: string, organism: string, references: list<item: struct<accession: string, n (... 28 chars omitted)
child 0, id: int64
child 1, name: string
child 2, organism: string
child 3, references: list<item: struct<accession: string, name: string, type: string>>
child 0, item: struct<accession: string, name: string, type: string>
child 0, accession: string
child 1, name: string
child 2, type: string
child 4, structures: list<item: null>
child 0, item: null
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
category: string
total_rows: int64
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 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.
FireProtDB
FireProtDB protein stability mutation dataset, normalized to newline-delimited JSON with row-level provenance.
Processed and uploaded by the MegaData post-download pipeline (internal repo). Original source: https://loschmidt.chemi.muni.cz/fireprotdb/.
Statistics
| Table files | 1 |
| Total rows | 5,465,660 |
| Total bytes | 8.48 GiB (9,105,270,725) |
Tables
| Table | Rows | Bytes |
|---|---|---|
labeled_fireprotdb_fireprotdb_search_all.jsonl.jsonl |
5,465,660 | 8.48 GiB |
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/FireProtDB --repo-type dataset --local-dir ./fireprotdb
Programmatic streaming:
import json
from pathlib import Path
from huggingface_hub import snapshot_download
local = snapshot_download(repo_id="LiteFold/FireProtDB", 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 (FireProtDB).
Citation
Stourac J, et al. FireProtDB: database of manually curated protein stability data. Nucleic Acids Research, 49(D1):D319-D324, 2021.
Provenance
Built from the local manifest entry fireprotdb of manifests/atlas_download_plan.json.
Pipeline source: megadata-post normalize --dataset fireprotdb --tables-only.
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