Datasets:

LiteFold
/

CycPepMPDB

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
dataset_id: string
row: struct<BCUT2D_CHGHI: string, BCUT2D_CHGLO: string, BCUT2D_LOGPHI: string, BCUT2D_LOGPLOW: string, BC (... 4655 chars omitted)
  child 0, BCUT2D_CHGHI: string
  child 1, BCUT2D_CHGLO: string
  child 2, BCUT2D_LOGPHI: string
  child 3, BCUT2D_LOGPLOW: string
  child 4, BCUT2D_MRHI: string
  child 5, BCUT2D_MRLOW: string
  child 6, BCUT2D_MWHI: string
  child 7, BCUT2D_MWLOW: string
  child 8, BalabanJ: string
  child 9, BertzCT: string
  child 10, CXSMILES: string
  child 11, Chi0: string
  child 12, Chi0n: string
  child 13, Chi0v: string
  child 14, Chi1: string
  child 15, Chi1n: string
  child 16, Chi1v: string
  child 17, Chi2n: string
  child 18, Chi2v: string
  child 19, Chi3n: string
  child 20, Chi3v: string
  child 21, Chi4n: string
  child 22, Chi4v: string
  child 23, Compound_Name: string
  child 24, EState_VSA1: string
  child 25, EState_VSA10: string
  child 26, EState_VSA11: string
  child 27, EState_VSA2: string
  child 28, EState_VSA3: string
  child 29, EState_VSA4: string
  child 30, EState_VSA5: string
  child 31, EState_VSA6: string
  child 32, EState_VSA7: string
  child 33, EState_VSA8: string
  child 34, EState_VSA9: string
  child 35, ExactMolWt: string
  child 36, FpDensityMorgan1: string
  child 37, FpDensityMorgan2: string
  child 38, FpDensityMorgan3: string
  child 39, FractionCSP3: string
  child 40, HallKierAlpha: string
  child 41, HeavyAtomCount: string
  child 42, HeavyAtomMolWt: string
  child 43, ID: string
  child 4
...
d 202, fr_nitro_arom_nonortho: string
  child 203, fr_nitroso: string
  child 204, fr_oxazole: string
  child 205, fr_oxime: string
  child 206, fr_para_hydroxylation: string
  child 207, fr_phenol: string
  child 208, fr_phenol_noOrthoHbond: string
  child 209, fr_phos_acid: string
  child 210, fr_phos_ester: string
  child 211, fr_piperdine: string
  child 212, fr_piperzine: string
  child 213, fr_priamide: string
  child 214, fr_prisulfonamd: string
  child 215, fr_pyridine: string
  child 216, fr_quatN: string
  child 217, fr_sulfide: string
  child 218, fr_sulfonamd: string
  child 219, fr_sulfone: string
  child 220, fr_term_acetylene: string
  child 221, fr_tetrazole: string
  child 222, fr_thiazole: string
  child 223, fr_thiocyan: string
  child 224, fr_thiophene: string
  child 225, fr_unbrch_alkane: string
  child 226, fr_urea: string
  child 227, qed: string
  child 228, replaced_SMILES: string
row_index: int64
source_file: string
category: string
format: 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
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<BCUT2D_CHGHI: string, BCUT2D_CHGLO: string, BCUT2D_LOGPHI: string, BCUT2D_LOGPLOW: string, BC (... 4655 chars omitted)
                child 0, BCUT2D_CHGHI: string
                child 1, BCUT2D_CHGLO: string
                child 2, BCUT2D_LOGPHI: string
                child 3, BCUT2D_LOGPLOW: string
                child 4, BCUT2D_MRHI: string
                child 5, BCUT2D_MRLOW: string
                child 6, BCUT2D_MWHI: string
                child 7, BCUT2D_MWLOW: string
                child 8, BalabanJ: string
                child 9, BertzCT: string
                child 10, CXSMILES: string
                child 11, Chi0: string
                child 12, Chi0n: string
                child 13, Chi0v: string
                child 14, Chi1: string
                child 15, Chi1n: string
                child 16, Chi1v: string
                child 17, Chi2n: string
                child 18, Chi2v: string
                child 19, Chi3n: string
                child 20, Chi3v: string
                child 21, Chi4n: string
                child 22, Chi4v: string
                child 23, Compound_Name: string
                child 24, EState_VSA1: string
                child 25, EState_VSA10: string
                child 26, EState_VSA11: string
                child 27, EState_VSA2: string
                child 28, EState_VSA3: string
                child 29, EState_VSA4: string
                child 30, EState_VSA5: string
                child 31, EState_VSA6: string
                child 32, EState_VSA7: string
                child 33, EState_VSA8: string
                child 34, EState_VSA9: string
                child 35, ExactMolWt: string
                child 36, FpDensityMorgan1: string
                child 37, FpDensityMorgan2: string
                child 38, FpDensityMorgan3: string
                child 39, FractionCSP3: string
                child 40, HallKierAlpha: string
                child 41, HeavyAtomCount: string
                child 42, HeavyAtomMolWt: string
                child 43, ID: string
                child 4
              ...
              d 202, fr_nitro_arom_nonortho: string
                child 203, fr_nitroso: string
                child 204, fr_oxazole: string
                child 205, fr_oxime: string
                child 206, fr_para_hydroxylation: string
                child 207, fr_phenol: string
                child 208, fr_phenol_noOrthoHbond: string
                child 209, fr_phos_acid: string
                child 210, fr_phos_ester: string
                child 211, fr_piperdine: string
                child 212, fr_piperzine: string
                child 213, fr_priamide: string
                child 214, fr_prisulfonamd: string
                child 215, fr_pyridine: string
                child 216, fr_quatN: string
                child 217, fr_sulfide: string
                child 218, fr_sulfonamd: string
                child 219, fr_sulfone: string
                child 220, fr_term_acetylene: string
                child 221, fr_tetrazole: string
                child 222, fr_thiazole: string
                child 223, fr_thiocyan: string
                child 224, fr_thiophene: string
                child 225, fr_unbrch_alkane: string
                child 226, fr_urea: string
                child 227, qed: string
                child 228, replaced_SMILES: string
              row_index: int64
              source_file: string
              category: string
              format: 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
              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

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CycPepMPDB

CycPepMPDB cyclic peptide membrane-permeability dataset (monomers and analogs), normalized to newline-delimited JSON with row-level provenance.

Processed and uploaded by the MegaData post-download pipeline (internal repo). Original source: http://cycpeptmpdb.com/.

Statistics


Table files	99
Total rows	43,514
Total bytes	259.87 MiB (272,498,665)

Tables

Table	Rows	Bytes
`peptide_cycpeptmpdb_CycPeptMPDB_Monomer_All.csv.jsonl`	385	2.23 MiB
`peptide_cycpeptmpdb_CycPeptMPDB_Monomer_Analog_A.csv.jsonl`	34	216.30 KiB
`peptide_cycpeptmpdb_CycPeptMPDB_Monomer_Analog_C.csv.jsonl`	4	22.01 KiB
`peptide_cycpeptmpdb_CycPeptMPDB_Monomer_Analog_D.csv.jsonl`	6	39.63 KiB
`peptide_cycpeptmpdb_CycPeptMPDB_Monomer_Analog_E.csv.jsonl`	5	25.48 KiB
`peptide_cycpeptmpdb_CycPeptMPDB_Monomer_Analog_F.csv.jsonl`	63	364.35 KiB
`peptide_cycpeptmpdb_CycPeptMPDB_Monomer_Analog_G.csv.jsonl`	47	265.58 KiB
`peptide_cycpeptmpdb_CycPeptMPDB_Monomer_Analog_H.csv.jsonl`	3	15.38 KiB
`peptide_cycpeptmpdb_CycPeptMPDB_Monomer_Analog_I.csv.jsonl`	8	46.23 KiB
`peptide_cycpeptmpdb_CycPeptMPDB_Monomer_Analog_K.csv.jsonl`	13	66.15 KiB
`peptide_cycpeptmpdb_CycPeptMPDB_Monomer_Analog_L.csv.jsonl`	19	191.37 KiB
`peptide_cycpeptmpdb_CycPeptMPDB_Monomer_Analog_M.csv.jsonl`	3	15.24 KiB
`peptide_cycpeptmpdb_CycPeptMPDB_Monomer_Analog_N.csv.jsonl`	7	35.72 KiB
`peptide_cycpeptmpdb_CycPeptMPDB_Monomer_Analog_P.csv.jsonl`	12	110.07 KiB
`peptide_cycpeptmpdb_CycPeptMPDB_Monomer_Analog_Q.csv.jsonl`	10	51.57 KiB
`peptide_cycpeptmpdb_CycPeptMPDB_Monomer_Analog_R.csv.jsonl`	4	20.67 KiB
`peptide_cycpeptmpdb_CycPeptMPDB_Monomer_Analog_S.csv.jsonl`	29	151.32 KiB
`peptide_cycpeptmpdb_CycPeptMPDB_Monomer_Analog_T.csv.jsonl`	6	48.74 KiB
`peptide_cycpeptmpdb_CycPeptMPDB_Monomer_Analog_V.csv.jsonl`	15	84.60 KiB
`peptide_cycpeptmpdb_CycPeptMPDB_Monomer_Analog_W.csv.jsonl`	8	41.30 KiB
`peptide_cycpeptmpdb_CycPeptMPDB_Monomer_Analog_X.csv.jsonl`	78	417.57 KiB
`peptide_cycpeptmpdb_CycPeptMPDB_Monomer_Analog_Y.csv.jsonl`	11	58.28 KiB
`peptide_cycpeptmpdb_CycPeptMPDB_Peptide_All.csv.jsonl`	8,466	50.54 MiB
`peptide_cycpeptmpdb_CycPeptMPDB_Peptide_Assay_Caco2.csv.jsonl`	1,332	8.23 MiB
`peptide_cycpeptmpdb_CycPeptMPDB_Peptide_Assay_MDCK.csv.jsonl`	64	396.71 KiB
`peptide_cycpeptmpdb_CycPeptMPDB_Peptide_Assay_PAMPA.csv.jsonl`	7,298	43.31 MiB
`peptide_cycpeptmpdb_CycPeptMPDB_Peptide_Assay_RRCK.csv.jsonl`	186	1.09 MiB
`peptide_cycpeptmpdb_CycPeptMPDB_Peptide_Length_10.csv.jsonl`	1,777	10.82 MiB
`peptide_cycpeptmpdb_CycPeptMPDB_Peptide_Length_11.csv.jsonl`	675	4.23 MiB
`peptide_cycpeptmpdb_CycPeptMPDB_Peptide_Length_12.csv.jsonl`	632	3.98 MiB
`peptide_cycpeptmpdb_CycPeptMPDB_Peptide_Length_13.csv.jsonl`	234	1.49 MiB
`peptide_cycpeptmpdb_CycPeptMPDB_Peptide_Length_14.csv.jsonl`	125	825.96 KiB
`peptide_cycpeptmpdb_CycPeptMPDB_Peptide_Length_15.csv.jsonl`	26	174.11 KiB
`peptide_cycpeptmpdb_CycPeptMPDB_Peptide_Length_2.csv.jsonl`	4	22.71 KiB
`peptide_cycpeptmpdb_CycPeptMPDB_Peptide_Length_3.csv.jsonl`	69	387.80 KiB
`peptide_cycpeptmpdb_CycPeptMPDB_Peptide_Length_4.csv.jsonl`	55	313.75 KiB
`peptide_cycpeptmpdb_CycPeptMPDB_Peptide_Length_5.csv.jsonl`	88	512.88 KiB
`peptide_cycpeptmpdb_CycPeptMPDB_Peptide_Length_6.csv.jsonl`	2,167	12.50 MiB
`peptide_cycpeptmpdb_CycPeptMPDB_Peptide_Length_7.csv.jsonl`	2,071	12.09 MiB
`peptide_cycpeptmpdb_CycPeptMPDB_Peptide_Length_8.csv.jsonl`	120	730.00 KiB
`peptide_cycpeptmpdb_CycPeptMPDB_Peptide_Length_9.csv.jsonl`	423	2.57 MiB
`peptide_cycpeptmpdb_CycPeptMPDB_Peptide_Shape_Circle.csv.jsonl`	5,530	32.46 MiB
`peptide_cycpeptmpdb_CycPeptMPDB_Peptide_Shape_Lariat.csv.jsonl`	2,936	18.15 MiB
`peptide_cycpeptmpdb_CycPeptMPDB_Peptide_Source_2006_Rezai_1.csv.jsonl`	10	60.53 KiB
`peptide_cycpeptmpdb_CycPeptMPDB_Peptide_Source_2006_Rezai_2.csv.jsonl`	11	65.58 KiB
`peptide_cycpeptmpdb_CycPeptMPDB_Peptide_Source_2011_White.csv.jsonl`	10	60.81 KiB
`peptide_cycpeptmpdb_CycPeptMPDB_Peptide_Source_2012_Rand.csv.jsonl`	16	95.80 KiB
`peptide_cycpeptmpdb_CycPeptMPDB_Peptide_Source_2013_CHUGAI.csv.jsonl`	878	5.51 MiB
`peptide_cycpeptmpdb_CycPeptMPDB_Peptide_Source_2013_Zaretsky.csv.jsonl`	2	11.60 KiB
`peptide_cycpeptmpdb_CycPeptMPDB_Peptide_Source_2014_Nielsen.csv.jsonl`	4	23.96 KiB
… 49 more table file(s) …

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/CycPepMPDB --repo-type dataset --local-dir ./cycpeptmpdb

Programmatic streaming:

import json
from pathlib import Path
from huggingface_hub import snapshot_download

local = snapshot_download(repo_id="LiteFold/CycPepMPDB", 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

See upstream license at CycPepMPDB.

Citation

Li J, et al. CycPeptMPDB: A Comprehensive Database of Membrane Permeability of Cyclic Peptides. J. Chem. Inf. Model., 2023.

Provenance

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

Downloads last month: 21

Total file size:

273 MB