The dataset viewer is not available for this split.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
digest: string
kind: string
path: string
payload_sha3: string
prev: string
seq: int64
ts: timestamp[s]
sbom_written: bool
total: int64
failed: int64
python: string
passed: int64
all_passed: bool
method: struct<aggregate_rule: string, excluded: string, reproduce: string, thresholds_note: string>
child 0, aggregate_rule: string
child 1, excluded: string
child 2, reproduce: string
child 3, thresholds_note: string
schema: string
root: string
benchmarks: list<item: struct<evidence: struct<ceilings: struct<max_files: int64, max_lines: int64, min_lines: i (... 3044 chars omitted)
child 0, item: struct<evidence: struct<ceilings: struct<max_files: int64, max_lines: int64, min_lines: int64>, code (... 3032 chars omitted)
child 0, evidence: struct<ceilings: struct<max_files: int64, max_lines: int64, min_lines: int64>, code_lines: int64, co (... 2961 chars omitted)
child 0, ceilings: struct<max_files: int64, max_lines: int64, min_lines: int64>
child 0, max_files: int64
child 1, max_lines: int64
child 2, min_lines: int64
child 1, code_lines: int64
child 2, command: string
child 3, counts_command: string
child 4, files_source: int64
child 5, files_tests: int64
child 6, files_total: int64
child 7, method: string
child 8, test_to_source_line_ratio: double
child 9, total_lines: int64
child 10, a_licences: list<item: string>
...
: string
child 1, evidence_path: string
child 2, present: bool
child 6, rerunnable_verification: struct<detail: string, evidence_path: string, present: bool>
child 0, detail: string
child 1, evidence_path: string
child 2, present: bool
child 7, versioning: struct<detail: string, evidence_path: string, present: bool>
child 0, detail: string
child 1, evidence_path: string
child 2, present: bool
child 62, criteria_missing: list<item: null>
child 0, item: null
child 63, criteria_satisfied: int64
child 64, criteria_total: int64
child 65, framework_controls_verified: int64
child 66, ladder: string
child 67, observed_level: int64
child 68, source: string
child 69, trL9_claimed: bool
child 70, trL9_reason: string
child 1, id: string
child 2, ok: bool
child 3, status: string
child 4, title: string
failed_ids: list<item: null>
child 0, item: null
platform: string
version: string
source: struct<git: struct<head: string, url: string, branch: string, sha_verified_from: string>>
child 0, git: struct<head: string, url: string, branch: string, sha_verified_from: string>
child 0, head: string
child 1, url: string
child 2, branch: string
child 3, sha_verified_from: string
to
{'all_passed': Value('bool'), 'benchmarks': List({'evidence': {'ceilings': {'max_files': Value('int64'), 'max_lines': Value('int64'), 'min_lines': Value('int64')}, 'code_lines': Value('int64'), 'command': Value('string'), 'counts_command': Value('string'), 'files_source': Value('int64'), 'files_tests': Value('int64'), 'files_total': Value('int64'), 'method': Value('string'), 'test_to_source_line_ratio': Value('float64'), 'total_lines': Value('int64'), 'a_licences': List(Value('string')), 'b_licences': List(Value('string')), 'default_for_unknown_is_C': Value('bool'), 'mismatches': {}, 'observed': {'agpl3': Value('string'), 'apache2': Value('string'), 'bsd3': Value('string'), 'commons_clause': Value('string'), 'garbage': Value('string'), 'gpl3': Value('string'), 'isc': Value('string'), 'lgpl': Value('string'), 'mit': Value('string'), 'mpl2': Value('string'), 'noncommercial': Value('string'), 'proprietary': Value('string'), 'sspl': Value('string'), 'unknown_absent': Value('string')}, 'only_class_A_may_relicense': Value('bool'), 'policy_probes': {'agpl3': Value('string'), 'apache2': Value('string'), 'bsd3': Value('string'), 'commons_clause': Value('string'), 'garbage': Value('string'), 'gpl3': Value('string'), 'isc': Value('string'), 'lgpl': Value('string'), 'mit': Value('string'), 'mpl2': Value('string'), 'noncommercial': Value('string'), 'proprietary': Value('string'), 'sspl': Value('string'), 'unknown_absent': Value('string')}, 'project_licence': {'LICENSE': Value('string'), '
...
Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}, 'qualification_environment_pinned': {'detail': Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}, 'reproducible_tests': {'detail': Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}, 'rerunnable_verification': {'detail': Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}, 'versioning': {'detail': Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}}, 'criteria_missing': List(Value('null')), 'criteria_satisfied': Value('int64'), 'criteria_total': Value('int64'), 'framework_controls_verified': Value('int64'), 'ladder': Value('string'), 'observed_level': Value('int64'), 'source': Value('string'), 'trL9_claimed': Value('bool'), 'trL9_reason': Value('string')}, 'id': Value('string'), 'ok': Value('bool'), 'status': Value('string'), 'title': Value('string')}), 'failed': Value('int64'), 'failed_ids': List(Value('null')), 'method': {'aggregate_rule': Value('string'), 'excluded': Value('string'), 'reproduce': Value('string'), 'thresholds_note': Value('string')}, 'passed': Value('int64'), 'platform': Value('string'), 'python': Value('string'), 'root': Value('string'), 'sbom_written': Value('bool'), 'schema': Value('string'), 'total': Value('int64'), 'version': Value('string'), 'source': {'git': {'head': Value('string'), 'url': Value('string'), 'branch': Value('string'), 'sha_verified_from': Value('string')}}}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
return get_rows(
dataset=dataset,
...<4 lines>...
column_names=column_names,
)
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 127, in get_rows
rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
File "/src/services/worker/src/worker/utils.py", line 483, in safe_iter
yield from ds.decode(False) if ds.features else ds
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2951, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2461, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2486, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 547, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 430, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
digest: string
kind: string
path: string
payload_sha3: string
prev: string
seq: int64
ts: timestamp[s]
sbom_written: bool
total: int64
failed: int64
python: string
passed: int64
all_passed: bool
method: struct<aggregate_rule: string, excluded: string, reproduce: string, thresholds_note: string>
child 0, aggregate_rule: string
child 1, excluded: string
child 2, reproduce: string
child 3, thresholds_note: string
schema: string
root: string
benchmarks: list<item: struct<evidence: struct<ceilings: struct<max_files: int64, max_lines: int64, min_lines: i (... 3044 chars omitted)
child 0, item: struct<evidence: struct<ceilings: struct<max_files: int64, max_lines: int64, min_lines: int64>, code (... 3032 chars omitted)
child 0, evidence: struct<ceilings: struct<max_files: int64, max_lines: int64, min_lines: int64>, code_lines: int64, co (... 2961 chars omitted)
child 0, ceilings: struct<max_files: int64, max_lines: int64, min_lines: int64>
child 0, max_files: int64
child 1, max_lines: int64
child 2, min_lines: int64
child 1, code_lines: int64
child 2, command: string
child 3, counts_command: string
child 4, files_source: int64
child 5, files_tests: int64
child 6, files_total: int64
child 7, method: string
child 8, test_to_source_line_ratio: double
child 9, total_lines: int64
child 10, a_licences: list<item: string>
...
: string
child 1, evidence_path: string
child 2, present: bool
child 6, rerunnable_verification: struct<detail: string, evidence_path: string, present: bool>
child 0, detail: string
child 1, evidence_path: string
child 2, present: bool
child 7, versioning: struct<detail: string, evidence_path: string, present: bool>
child 0, detail: string
child 1, evidence_path: string
child 2, present: bool
child 62, criteria_missing: list<item: null>
child 0, item: null
child 63, criteria_satisfied: int64
child 64, criteria_total: int64
child 65, framework_controls_verified: int64
child 66, ladder: string
child 67, observed_level: int64
child 68, source: string
child 69, trL9_claimed: bool
child 70, trL9_reason: string
child 1, id: string
child 2, ok: bool
child 3, status: string
child 4, title: string
failed_ids: list<item: null>
child 0, item: null
platform: string
version: string
source: struct<git: struct<head: string, url: string, branch: string, sha_verified_from: string>>
child 0, git: struct<head: string, url: string, branch: string, sha_verified_from: string>
child 0, head: string
child 1, url: string
child 2, branch: string
child 3, sha_verified_from: string
to
{'all_passed': Value('bool'), 'benchmarks': List({'evidence': {'ceilings': {'max_files': Value('int64'), 'max_lines': Value('int64'), 'min_lines': Value('int64')}, 'code_lines': Value('int64'), 'command': Value('string'), 'counts_command': Value('string'), 'files_source': Value('int64'), 'files_tests': Value('int64'), 'files_total': Value('int64'), 'method': Value('string'), 'test_to_source_line_ratio': Value('float64'), 'total_lines': Value('int64'), 'a_licences': List(Value('string')), 'b_licences': List(Value('string')), 'default_for_unknown_is_C': Value('bool'), 'mismatches': {}, 'observed': {'agpl3': Value('string'), 'apache2': Value('string'), 'bsd3': Value('string'), 'commons_clause': Value('string'), 'garbage': Value('string'), 'gpl3': Value('string'), 'isc': Value('string'), 'lgpl': Value('string'), 'mit': Value('string'), 'mpl2': Value('string'), 'noncommercial': Value('string'), 'proprietary': Value('string'), 'sspl': Value('string'), 'unknown_absent': Value('string')}, 'only_class_A_may_relicense': Value('bool'), 'policy_probes': {'agpl3': Value('string'), 'apache2': Value('string'), 'bsd3': Value('string'), 'commons_clause': Value('string'), 'garbage': Value('string'), 'gpl3': Value('string'), 'isc': Value('string'), 'lgpl': Value('string'), 'mit': Value('string'), 'mpl2': Value('string'), 'noncommercial': Value('string'), 'proprietary': Value('string'), 'sspl': Value('string'), 'unknown_absent': Value('string')}, 'project_licence': {'LICENSE': Value('string'), '
...
Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}, 'qualification_environment_pinned': {'detail': Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}, 'reproducible_tests': {'detail': Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}, 'rerunnable_verification': {'detail': Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}, 'versioning': {'detail': Value('string'), 'evidence_path': Value('string'), 'present': Value('bool')}}, 'criteria_missing': List(Value('null')), 'criteria_satisfied': Value('int64'), 'criteria_total': Value('int64'), 'framework_controls_verified': Value('int64'), 'ladder': Value('string'), 'observed_level': Value('int64'), 'source': Value('string'), 'trL9_claimed': Value('bool'), 'trL9_reason': Value('string')}, 'id': Value('string'), 'ok': Value('bool'), 'status': Value('string'), 'title': Value('string')}), 'failed': Value('int64'), 'failed_ids': List(Value('null')), 'method': {'aggregate_rule': Value('string'), 'excluded': Value('string'), 'reproduce': Value('string'), 'thresholds_note': Value('string')}, 'passed': Value('int64'), 'platform': Value('string'), 'python': Value('string'), 'root': Value('string'), 'sbom_written': Value('bool'), 'schema': Value('string'), 'total': Value('int64'), 'version': Value('string'), 'source': {'git': {'head': Value('string'), 'url': Value('string'), 'branch': Value('string'), 'sha_verified_from': Value('string')}}}
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.
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
ENDF_PARSERPY
Governed Anticloud packaging of the upstream project
ENDF_PARSERPYin category NUCLEAR. check results: see ISOLATED_LAB_RESULTS. Every number below traces to a named file + run stamp; nothing is borrowed from other projects.
Upstream: ENDF_PARSERPY · Upstream pin: e96cd6e03c551f3360261a8a70702b7b31dfc25b · Category: NUCLEAR · Vendor: Anticloud FZ LLE · Licence: MIT
What This Project Does
endf-parserpy - an ENDF-6 toolkit for Python
endf-parserpy is a Python package for reading
and writing ENDF-6 files.
This functionality in combination with Python's
powerful facilities for data handling enables you to
perform various actions on ENDF-6 files, such as:
- Easily access any information
- Modify, delete and insert data
- Perform format validation
- Convert to and from other file formats, such as JSON
- Merge data from various ENDF-6 files into a single one
- Read and write files bundling several materials (tapes)
- Compare ENDF-6 files with meaningful reporting on differences
- Construct ENDF-6 files from scratch
Many of these actions can also be performed from the command line
through the endf-cli tool.
The support for the ENDF-6 format is comprehensive, and some special
NJOY2016 output formats are supported as well. The package has been
tested on the various sublibraries of the major nuclear data
libraries, such as
ENDF/B,
JEFF,
and JENDL.
Files that bundle several materials — including PENDF tapes
that repeat the same material at different temperatures — are
supported both as plain lists of materials and through a lazy,
memory-bounded EndfFile interface for large files.
Install endf-parserpy
This package is available on the
Python Package Index
and can be installed using pip:
python -m pip install endf-parserpy --upgrade
Documentation
The documentation is available online
@readthedocs.
See the README.md in the docs/ subdirectory
for instructions on building the documentation locally.
Simple example
The following code snippet demonstrates
how to read an ENDF-6 file, change the
AWR variable in the MF3/MT1 section
and write the modified data to a new
ENDF-6 file:
from endf_parserpy import EndfParserFactory
parser = EndfParserFactory.create()
endf_dict = parser.parsefile('input.endf')
endf_dict[3][1]['AWR'] = 99.99
parser.writefile('output.endf', endf_dict)
Citation
If you want to cite this package, please use the following reference:
G. Schnabel, D. L. Aldama, R. Capote, "How to explain ENDF-6 to computers: A formal ENDF format description language", arXiv:2312.08249, DOI:10.48550/arXiv.2312.08249
License
This code is distributed under the MIT license augmented by an IAEA clause, see the accompanying license file for more information.
Copyright (c) International Atomic Energy Agency (IAEA)
Acknowledgments
Daniel Lopez Aldama made significant contributions to the development of this package. He debugged the ENDF-6 recipe files and helped in numerous discussions to convey a good understanding of the technical details of the ENDF-6 format that enabled the creation of this package.
Installation
This package is available on the
Python Package Index
and can be installed using pip:
python -m pip install endf-parserpy --upgrade
Usage
The following code snippet demonstrates
how to read an ENDF-6 file, change the
AWR variable in the MF3/MT1 section
and write the modified data to a new
ENDF-6 file:
from endf_parserpy import EndfParserFactory
parser = EndfParserFactory.create()
endf_dict = parser.parsefile('input.endf')
endf_dict[3][1]['AWR'] = 99.99
parser.writefile('output.endf', endf_dict)
API
endf-parserpy is a Python package for reading
and writing ENDF-6 files.
This functionality in combination with Python's
powerful facilities for data handling enables you to
perform various actions on ENDF-6 files, such as:
- Easily access any information
- Modify, delete and insert data
- Perform format validation
- Convert to and from other file formats, such as JSON
- Merge data from various ENDF-6 files into a single one
- Read and write files bundling several materials (tapes)
- Compare ENDF-6 files with meaningful reporting on differences
- Construct ENDF-6 files from scratch
Many of these actions can also be performed from the command line
through the endf-cli tool.
The support for the ENDF-6 format is comprehensive, and some special
NJOY2016 output formats are supported as well. The package has been
tested on the various sublibraries of the major nuclear data
libraries, such as
ENDF/B,
JEFF,
and JENDL.
Files that bundle several materials — including PENDF tapes
that repeat the same material at different temperatures — are
supported both as plain lists of materials and through a lazy,
memory-bounded EndfFile interface for large files.
Dependencies
| Metric | Value |
|---|---|
| Files | unknown |
| Lines of Code | unknown |
| Dependencies | unknown |
| Upstream license (harvested) | MIT |
| Overlay license | Anticommons 0.1.0 |
Dependency manifests live in UPSTREAM_CLONE/; pinned lockfile in anticloud/ where applicable.
Configuration
See upstream source in UPSTREAM_CLONE/ and the quoted documentation above.
Contributing
to the development of this package. He debugged the ENDF-6 recipe files and helped in numerous discussions to convey a good understanding of the technical details of the ENDF-6 format that enabled the creation of this package.
License
Upstream © its respective contributors under MIT (harvested MIT/Apache-2.0/BSD source; see UPSTREAM_CLONE/LICENSE). This packaging overlay is licensed under Anticommons 0.1.0.
Upstream
- project: ENDF_PARSERPY
- Pinned SHA:
e96cd6e03c551f3360261a8a70702b7b31dfc25b - source:
UPSTREAM_CLONE/(pinned at the SHA above) - Upstream README source:
UPSTREAM_CLONE/README.md
Benchmarks
Measured by the Anticloud assurance suite. Every value below is read from this
project's BENCH.json, produced by a real run — the SHA3-256 of that file is
4fedf61be21a1fedb14dffa8f7d479a511120950d05bddacec5dd0e1b69619fe.
| Framework | Controls | Evidence | Coverage | Result |
|---|---|---|---|---|
| OWASP Top 10 for LLM Applications | 10 controls mapped | 10 with evidence | 100.0% | PASS |
| OWASP Top 10 (2021) | 9 controls mapped | 9 with evidence | 100.0% | PASS |
| SOC 2 Type II readiness | 9 controls mapped | 9 with evidence | 100.0% | PASS |
| NIST AI Risk Management Framework | 8 controls mapped | 8 with evidence | 100.0% | PASS |
| NIST SP 800-53 Rev. 5 | 12 controls mapped | 12 with evidence | 100.0% | PASS |
| NIST Cybersecurity Framework 2.0 | 8 controls mapped | 8 with evidence | 100.0% | PASS |
| FedRAMP Rev. 5 | 10 controls mapped | 10 with evidence | 100.0% | PASS |
| PCI DSS v4.0.1 | 11 controls mapped | 11 with evidence | 100.0% | PASS |
| ISO/IEC 27001:2022 | 9 controls mapped | 9 with evidence | 100.0% | PASS |
| MITRE ATT&CK v16 | 12 controls mapped | 12 with evidence | 100.0% | PASS |
| ML Technology Readiness Level | TRL 8 | 8/8 criteria | PASS |
Overall: 16/16 checks passing.
See ISOLATED_LAB_RESULTS/03_Result_Register.md for the 16-check register with pass condition, command and observed value per check.
Framework folders in OFFICIAL_BENCHMARKS/ state the control set and the
evidence source bound to each control. This project does not claim an audit
opinion, a SOC report, a FedRAMP authorisation or a PCI attestation — those are
issued by an independent assessor.
Archives and Permanent Records
| Platform | Identifier | Volume |
|---|---|---|
| Harvard Dataverse | DOI 10.7910/DVN/YMJKOG | 145 citable datasets |
| AIOSS verification kit | DOI 10.7910/DVN/OORKNJ | Offline hash verification |
| Zenodo (CERN) | — | 146 records, DOI-registered |
| OSF | — | 144 preregistered records |
| Figshare | author 20849885 | Research data and figures |
| Internet Archive | aioss-format, Anticode | Permanent binary specification |
| ORCID | 0009-0009-2233-6107 | Permanent researcher ID |
| Kaggle | pax-millennium-20 | Reproducible T4 benchmark run |
Press and Independent Publication
The PAX benchmark release was distributed by Newsfile wire to 336 outlets (312 Web, 23 Terminal, 1 Application), including Yahoo Finance, The Globe and Mail, Business Insider, National Post, Financial Post, StreetInsider, Digital Journal, Barchart, International Business Times, and fox47 · National Law Review. Wire distribution makes the announcement dated, public, and indexed, which makes the claim checkable.
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