The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
Error code: DatasetGenerationError
Exception: TypeError
Message: int() argument must be a string, a bytes-like object or a real number, not 'NoneType'
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1520, in _prepare_split_single
for key, record in generator:
^^^^^^^^^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 613, in wrapped
for item in generator(*args, **kwargs):
~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 130, in _generate_examples
for example_idx, example in enumerate(self._get_pipeline_from_tar(tar_path, tar_iterator)):
~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 34, in _get_pipeline_from_tar
for filename, f in tar_iterator:
^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/utils/track.py", line 49, in __iter__
for x in self.generator(*self.args):
~~~~~~~~~~~~~~^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/utils/file_utils.py", line 1405, in _iter_from_urlpath
with xopen(urlpath, "rb", download_config=download_config, block_size=0) as f:
~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/utils/file_utils.py", line 982, in xopen
file_obj = fs.open(paths[0], mode)
File "<string>", line 3, in open
File "/usr/local/lib/python3.14/unittest/mock.py", line 1176, in __call__
return self._mock_call(*args, **kwargs)
~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/unittest/mock.py", line 1180, in _mock_call
return self._execute_mock_call(*args, **kwargs)
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/unittest/mock.py", line 1247, in _execute_mock_call
result = effect(*args, **kwargs)
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 786, in wrapped
tracker.files[urlpath] = {"read": 0, "size": int(f.size)}
~~~^^^^^^^^
TypeError: int() argument must be a string, a bytes-like object or a real number, not 'NoneType'
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1369, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
~~~~~~~~~~~~~~~~~~~~~~~~~^
builder, max_dataset_size_bytes=max_dataset_size_bytes
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1382, in _prepare_split
for job_id, done, content in self._prepare_split_single(
~~~~~~~~~~~~~~~~~~~~~~~~~~^
gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
):
^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1560, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
zip unknown | __key__ string | __url__ string |
|---|---|---|
"UEsDBBQAAAAIAMhhuVy+HwLmvoEBAJ6kAwAYAAAAMzZfLTFfMi9maW5pc2hlZF9pcmMudHJqXJ1LkiW5bkTnvYrcQKXx/xm32TO(...TRUNCATED) | 10.1126/sciadv.adg1645/sciadv.adg1645_sm/36_-1_2 | hf://datasets/JawLeighy/GoldDIGR@14b919d4cf1afebde2487c70031a5f554e70dfbb/bundles/bundle_0000.tar |
"UEsDBBQAAAAIAAx/uVzFkw633ggAAG4VAAAYAAAAMDZfLTFfMi9maW5pc2hlZF9pcmMudHJqVZhLkhw7CEXnvYraQFcIJBAae+L(...TRUNCATED) | 10.1126/science.abd8408/abd8408_yang_sm/06_-1_2 | hf://datasets/JawLeighy/GoldDIGR@14b919d4cf1afebde2487c70031a5f554e70dfbb/bundles/bundle_0000.tar |
"UEsDBBQAAAAIAAx/uVzWPzq7fAkAAD0bAAAYAAAAMDNfLTFfMS9maW5pc2hlZF9pcmMudHJqdZlbciM5DkX/axXeQDtIgCCJTUz(...TRUNCATED) | 10.1126/science.aab0204/velian.sm/03_-1_1 | hf://datasets/JawLeighy/GoldDIGR@14b919d4cf1afebde2487c70031a5f554e70dfbb/bundles/bundle_0000.tar |
"UEsDBBQAAAAIAMhhuVzxe8HIBCcAAAZjAAAXAAAAMDRfMV8yL2ZpbmlzaGVkX2lyYy50cmpVnEuSLSuuRPt3FDmBmwYIBHSrOq/(...TRUNCATED) | 10.1126/science.adp5749/science.adp5749_sm/04_1_2 | hf://datasets/JawLeighy/GoldDIGR@14b919d4cf1afebde2487c70031a5f554e70dfbb/bundles/bundle_0000.tar |
"UEsDBBQAAAAIAAx/uVxkGPikLwoAAPEcAAAXAAAAMDNfMF8yL2ZpbmlzaGVkX2lyYy50cmptmdmRHLkORf9lRTsgBbFwc+LF+G/(...TRUNCATED) | 10.1126/science.aab0204/velian.sm/03_0_2 | hf://datasets/JawLeighy/GoldDIGR@14b919d4cf1afebde2487c70031a5f554e70dfbb/bundles/bundle_0000.tar |
"UEsDBBQAAAAIAAx/uVx7ExcJVIAAAL03AQAYAAAAMDRfLTFfMi9maW5pc2hlZF9pcmMudHJqVJ07miRLbqz1WUVvoPvz90MlFUr(...TRUNCATED) | 10.1126/science.adp5749/science.adp5749_sm/04_-1_2 | hf://datasets/JawLeighy/GoldDIGR@14b919d4cf1afebde2487c70031a5f554e70dfbb/bundles/bundle_0000.tar |
"UEsDBBQAAAAIAA1/uVw8jpgAzFIAAHrLAAAXAAAAMzFfMV8yL2ZpbmlzaGVkX2lyYy50cmptnUmyLDluRee1ir+B/Ma+GZeZTCN(...TRUNCATED) | 10.1126/sciadv.adg1645/sciadv.adg1645_sm/31_1_2 | hf://datasets/JawLeighy/GoldDIGR@14b919d4cf1afebde2487c70031a5f554e70dfbb/bundles/bundle_0000.tar |
"UEsDBBQAAAAIAA1/uVyziQHkdUMAAOSvAAAYAAAAMDhfLTFfMi9maW5pc2hlZF9pcmMudHJq7Z1Jsl07jmX7PgpNQDLWRTs60cu(...TRUNCATED) | 10.1126/science.abd8408/abd8408_yang_sm/08_-1_2 | hf://datasets/JawLeighy/GoldDIGR@14b919d4cf1afebde2487c70031a5f554e70dfbb/bundles/bundle_0000.tar |
"UEsDBBQAAAAIAA1/uVwPnjN06IkAAItNAQAXAAAAMTBfMF8xL2ZpbmlzaGVkX2lyYy50cmpUnTmWbbluRP0aRU6gcrFvXH1HniY(...TRUNCATED) | 10.1126/sciadv.adg1645/sciadv.adg1645_sm/10_0_1 | hf://datasets/JawLeighy/GoldDIGR@14b919d4cf1afebde2487c70031a5f554e70dfbb/bundles/bundle_0000.tar |
"UEsDBBQAAAAIAA1/uVydeHuJ3hAAAKsvAAAXAAAAMDNfMV8xL2ZpbmlzaGVkX2lyYy50cmp1mmGOIKmOhP/PKfoCrwUYML7E6t3(...TRUNCATED) | 10.1126/science.aab0204/velian.sm/03_1_1 | hf://datasets/JawLeighy/GoldDIGR@14b919d4cf1afebde2487c70031a5f554e70dfbb/bundles/bundle_0000.tar |
GoldDIGR — DFT Reaction Calculation Dataset
A large open dataset of ~1,000,000 xTB/DFT reaction calculations mined from the
supporting information of published chemistry papers and recomputed with a
uniform pipeline (geometry/TS search, IRC, single-point DFT, and an xTB
spin/structure scan). Each calculation is a self-contained .zip; the corpus is
distributed as 425 .tar bundles (~800 GB total).
Status: continuously updated — new DFT results are injected over time and the affected bundles are re-uploaded (see Updates below).
Quick start
Download and unpack (all bundles extract into one unified tree):
# one bundle
huggingface-cli download <user>/GoldDIGR bundles/bundle_0000.tar --repo-type dataset --local-dir .
tar -xf bundles/bundle_0000.tar # -> 10.<prefix>/<doi>/<stem>/<reaction>.zip
# everything
huggingface-cli download <user>/GoldDIGR --repo-type dataset --local-dir .
for t in bundles/*.tar; do tar -xf "$t"; done
Verify integrity:
cd bundles && sha256sum -c SHA256SUMS
Layout
bundles/
bundle_0000.tar … bundle_0424.tar # the data (≤2500 zips each, ~62 MB–4.3 GB)
bundle_XXXX.tar.sha256 # per-bundle checksum
SHA256SUMS # all checksums combined
bundle_manifest.tsv # key <TAB> bundle_id (every zip -> its bundle)
bundle_lists/bundle_XXXX.paths # the zip list inside each bundle
Inside each bundle, zips are stored at their DOI path:
<DOI_prefix>/<DOI_suffix>/<SI_stem>/<reaction>_<charge>_<multiplicity>.zip
e.g. 10.1039/C8SC02758G/c8sc02758g2/03_1_1.zip
Inside a reaction .zip
<reaction>/
DFT-SinglePoint/ ORCA single-point outputs per stationary point
(.out, .xyz, .inp, CHELPG charges, fuzzy/Mayer/Wiberg
bond-order matrices), and status.json
xTB-scan/ GFN2-xTB spin/structure scan: per-frame geometries,
spin_scan_summary.csv (energies per spin/frame),
bem_snapshots/step_*.json (energy + charges + bond orders)
IRC_Analysis/ IRC frame analysis (json + csv) and reaction summaries
*.trj / *.xyz / *.yaml TS-opt / IRC trajectories and metadata
status.json (in DFT-SinglePoint/) records which stationary points
(input, finished_first, finished_last, *_opt, ts_final_geometry)
completed.
How it was processed
The raw outputs were cleaned losslessly/redundancy-only before release:
ORCA/xTB log banners and citation/grid boilerplate trimmed; uncompressed members
recompressed; intermediate scratch removed (xTB restart files, crashed-run
Hessian .h5); and per-step xTB .out files removed where their energy is
already preserved in spin_scan_summary.csv (energy-verified, never lossy).
All scientific quantities (geometries, energies, charges, bond orders, orbital
energies) are retained.
Updates
The dataset grows as new DFT results are computed. Updates are incremental:
only the bundles containing changed/added reactions are rebuilt and re-uploaded
(tracked via bundle_manifest.tsv; the Hub's Xet backend dedups unchanged data
across versions). Check the commit history for the latest additions.
Citation
@misc{golddigr,
title = {GoldDIGR: A DFT Reaction Calculation Dataset},
author = {<authors>},
year = {<year>},
howpublished = {Hugging Face Hub, <user>/GoldDIGR},
doi = {<Zenodo DOI if minted>}
}
License
Released under <CC-BY-4.0 / your choice>. Underlying structures derive from published SI; please also cite the original papers (DOIs are encoded in each reaction's path).
- Downloads last month
- 23