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The dataset generation failed
Error code: DatasetGenerationError
Exception: CastError
Message: Couldn't cast
all_sibling_languages_strict_exact: bool
created_utc: timestamp[s]
engine: struct<projection_api: string, public_cnl_contains_private_cst_transport: bool, requested_languages: (... 40 chars omitted)
child 0, projection_api: string
child 1, public_cnl_contains_private_cst_transport: bool
child 2, requested_languages: list<item: string>
child 0, item: string
child 3, row_schema: string
language: string
plaincode_cnl: string
proof: struct<byte_exact_ok: bool, char_exact_ok: bool, exact_ok: bool, reverse_ast_ok: bool, reverse_byte_ (... 214 chars omitted)
child 0, byte_exact_ok: bool
child 1, char_exact_ok: bool
child 2, exact_ok: bool
child 3, reverse_ast_ok: bool
child 4, reverse_byte_count: int64
child 5, reverse_char_count: int64
child 6, reverse_compile_error: null
child 7, reverse_compile_ok: bool
child 8, reverse_sha256: string
child 9, sha_exact_ok: bool
child 10, source_byte_count: int64
child 11, source_char_count: int64
child 12, source_sha256: string
python_source_id: string
python_source_index: int64
roundtrip_python: string
row_id: string
row_sha256: string
run_id: string
semantic_family: struct<ast_node_count: int64, ast_top_counts: string, families: list<item: string>, primary_family: (... 7 chars omitted)
child 0, ast_node_count: int64
child 1, ast_top_counts: string
child 2, families: list<item: string>
child 0, item: string
child 3, primary_family: string
sibling_language_count: int64
sibling_languages: lis
...
source_id: string, python_source_index: int64, run_id: string, created (... 19 chars omitted)
child 0, row_id: string
child 1, python_source_id: string
child 2, python_source_index: int64
child 3, run_id: string
child 4, created_utc: timestamp[s]
source_stats: struct<sha256: string, char_count: int64, byte_count: int64, line_count: int64, compile_ok: bool, co (... 18 chars omitted)
child 0, sha256: string
child 1, char_count: int64
child 2, byte_count: int64
child 3, line_count: int64
child 4, compile_ok: bool
child 5, compile_error: null
source_code: string
source_metadata: struct<repo_name: string, path: string, license: string, language: string, size: int64, source_datas (... 114 chars omitted)
child 0, repo_name: string
child 1, path: string
child 2, license: string
child 3, language: string
child 4, size: int64
child 5, source_dataset: string
child 6, source_config: string
child 7, source_split: string
child 8, source_label: string
child 9, source_index_seen_in_stream: int64
cnl: struct<language: string, text: string>
child 0, language: string
child 1, text: string
cnl_siblings: struct<sibling_language_count: int64, sibling_languages: list<item: string>, all_sibling_languages_s (... 18 chars omitted)
child 0, sibling_language_count: int64
child 1, sibling_languages: list<item: string>
child 0, item: string
child 2, all_sibling_languages_strict_exact: bool
roundtrip: struct<python: string>
child 0, python: string
to
{'source_code': Value('string'), 'cnl': {'language': Value('string'), 'text': Value('string')}, 'ids': {'row_id': Value('string'), 'python_source_id': Value('string'), 'python_source_index': Value('int64'), 'run_id': Value('string'), 'created_utc': Value('timestamp[s]')}, 'cnl_siblings': {'sibling_language_count': Value('int64'), 'sibling_languages': List(Value('string')), 'all_sibling_languages_strict_exact': Value('bool')}, 'roundtrip': {'python': Value('string')}, 'proof': {'source_sha256': Value('string'), 'reverse_sha256': Value('string'), 'source_char_count': Value('int64'), 'reverse_char_count': Value('int64'), 'source_byte_count': Value('int64'), 'reverse_byte_count': Value('int64'), 'sha_exact_ok': Value('bool'), 'char_exact_ok': Value('bool'), 'byte_exact_ok': Value('bool'), 'exact_ok': Value('bool'), 'reverse_compile_ok': Value('bool'), 'reverse_compile_error': Value('null'), 'reverse_ast_ok': Value('bool')}, 'strict_exact': Value('bool'), 'source_stats': {'sha256': Value('string'), 'char_count': Value('int64'), 'byte_count': Value('int64'), 'line_count': Value('int64'), 'compile_ok': Value('bool'), 'compile_error': Value('null')}, 'source_metadata': {'repo_name': Value('string'), 'path': Value('string'), 'license': Value('string'), 'language': Value('string'), 'size': Value('int64'), 'source_dataset': Value('string'), 'source_config': Value('string'), 'source_split': Value('string'), 'source_label': Value('string'), 'source_index_seen_in_stream': Value('int64')}, 'semantic_family': {'families': List(Value('string')), 'primary_family': Value('string'), 'ast_node_count': Value('int64'), 'ast_top_counts': Json(decode=True)}, 'engine': {'projection_api': Value('string'), 'requested_languages': List(Value('string')), 'row_schema': Value('string'), 'public_cnl_contains_private_cst_transport': Value('bool')}, 'row_sha256': Value('string')}
because column names don't match
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1779, in _prepare_split_single
for key, table in generator:
^^^^^^^^^
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
all_sibling_languages_strict_exact: bool
created_utc: timestamp[s]
engine: struct<projection_api: string, public_cnl_contains_private_cst_transport: bool, requested_languages: (... 40 chars omitted)
child 0, projection_api: string
child 1, public_cnl_contains_private_cst_transport: bool
child 2, requested_languages: list<item: string>
child 0, item: string
child 3, row_schema: string
language: string
plaincode_cnl: string
proof: struct<byte_exact_ok: bool, char_exact_ok: bool, exact_ok: bool, reverse_ast_ok: bool, reverse_byte_ (... 214 chars omitted)
child 0, byte_exact_ok: bool
child 1, char_exact_ok: bool
child 2, exact_ok: bool
child 3, reverse_ast_ok: bool
child 4, reverse_byte_count: int64
child 5, reverse_char_count: int64
child 6, reverse_compile_error: null
child 7, reverse_compile_ok: bool
child 8, reverse_sha256: string
child 9, sha_exact_ok: bool
child 10, source_byte_count: int64
child 11, source_char_count: int64
child 12, source_sha256: string
python_source_id: string
python_source_index: int64
roundtrip_python: string
row_id: string
row_sha256: string
run_id: string
semantic_family: struct<ast_node_count: int64, ast_top_counts: string, families: list<item: string>, primary_family: (... 7 chars omitted)
child 0, ast_node_count: int64
child 1, ast_top_counts: string
child 2, families: list<item: string>
child 0, item: string
child 3, primary_family: string
sibling_language_count: int64
sibling_languages: lis
...
source_id: string, python_source_index: int64, run_id: string, created (... 19 chars omitted)
child 0, row_id: string
child 1, python_source_id: string
child 2, python_source_index: int64
child 3, run_id: string
child 4, created_utc: timestamp[s]
source_stats: struct<sha256: string, char_count: int64, byte_count: int64, line_count: int64, compile_ok: bool, co (... 18 chars omitted)
child 0, sha256: string
child 1, char_count: int64
child 2, byte_count: int64
child 3, line_count: int64
child 4, compile_ok: bool
child 5, compile_error: null
source_code: string
source_metadata: struct<repo_name: string, path: string, license: string, language: string, size: int64, source_datas (... 114 chars omitted)
child 0, repo_name: string
child 1, path: string
child 2, license: string
child 3, language: string
child 4, size: int64
child 5, source_dataset: string
child 6, source_config: string
child 7, source_split: string
child 8, source_label: string
child 9, source_index_seen_in_stream: int64
cnl: struct<language: string, text: string>
child 0, language: string
child 1, text: string
cnl_siblings: struct<sibling_language_count: int64, sibling_languages: list<item: string>, all_sibling_languages_s (... 18 chars omitted)
child 0, sibling_language_count: int64
child 1, sibling_languages: list<item: string>
child 0, item: string
child 2, all_sibling_languages_strict_exact: bool
roundtrip: struct<python: string>
child 0, python: string
to
{'source_code': Value('string'), 'cnl': {'language': Value('string'), 'text': Value('string')}, 'ids': {'row_id': Value('string'), 'python_source_id': Value('string'), 'python_source_index': Value('int64'), 'run_id': Value('string'), 'created_utc': Value('timestamp[s]')}, 'cnl_siblings': {'sibling_language_count': Value('int64'), 'sibling_languages': List(Value('string')), 'all_sibling_languages_strict_exact': Value('bool')}, 'roundtrip': {'python': Value('string')}, 'proof': {'source_sha256': Value('string'), 'reverse_sha256': Value('string'), 'source_char_count': Value('int64'), 'reverse_char_count': Value('int64'), 'source_byte_count': Value('int64'), 'reverse_byte_count': Value('int64'), 'sha_exact_ok': Value('bool'), 'char_exact_ok': Value('bool'), 'byte_exact_ok': Value('bool'), 'exact_ok': Value('bool'), 'reverse_compile_ok': Value('bool'), 'reverse_compile_error': Value('null'), 'reverse_ast_ok': Value('bool')}, 'strict_exact': Value('bool'), 'source_stats': {'sha256': Value('string'), 'char_count': Value('int64'), 'byte_count': Value('int64'), 'line_count': Value('int64'), 'compile_ok': Value('bool'), 'compile_error': Value('null')}, 'source_metadata': {'repo_name': Value('string'), 'path': Value('string'), 'license': Value('string'), 'language': Value('string'), 'size': Value('int64'), 'source_dataset': Value('string'), 'source_config': Value('string'), 'source_split': Value('string'), 'source_label': Value('string'), 'source_index_seen_in_stream': Value('int64')}, 'semantic_family': {'families': List(Value('string')), 'primary_family': Value('string'), 'ast_node_count': Value('int64'), 'ast_top_counts': Json(decode=True)}, 'engine': {'projection_api': Value('string'), 'requested_languages': List(Value('string')), 'row_schema': Value('string'), 'public_cnl_contains_private_cst_transport': Value('bool')}, 'row_sha256': Value('string')}
because column names don't match
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 1348, in compute_config_parquet_and_info_response
parquet_operations = convert_to_parquet(builder)
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 980, in convert_to_parquet
builder.download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 882, in download_and_prepare
self._download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 943, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1646, in _prepare_split
for job_id, done, content in self._prepare_split_single(
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1832, 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.
source_code string | cnl dict | ids dict | cnl_siblings dict | roundtrip dict | proof dict | strict_exact bool | source_stats dict | source_metadata dict | semantic_family dict | engine dict | row_sha256 string |
|---|---|---|---|---|---|---|---|---|---|---|---|
import numpy as np
import pandas as pd
from pandas import Series, DataFrame
from scipy.spatial import distance
import matplotlib.pyplot as plt
from sklearn.cluster import DBSCAN
from sklearn import metrics
from sklearn.datasets.samples_generator import make_blobs
from sklearn.preprocessing import StandardScaler
from s... | {
"language": "en",
"text": "Load numpy, referred to as np.\nLoad pandas, referred to as pd.\nLoad Series, DataFrame from pandas.\nLoad distance from scipy.spatial.\nLoad matplotlib.pyplot, referred to as plt.\nLoad DBSCAN from sklearn.cluster.\nLoad metrics from sklearn.\nLoad make_blobs from sklearn.datasets.samp... | {
"row_id": "pc_cnl100k_000000_en_a0e561623699",
"python_source_id": "pc_src100k_000000_a0e561623699",
"python_source_index": 0,
"run_id": "run_20260530_153047_utc",
"created_utc": "2026-05-30T15:31:09"
} | {
"sibling_language_count": 6,
"sibling_languages": [
"en",
"es",
"fr",
"pt",
"zh",
"hi"
],
"all_sibling_languages_strict_exact": true
} | {
"python": "import numpy as np\nimport pandas as pd\nfrom pandas import Series, DataFrame\nfrom scipy.spatial import distance\nimport matplotlib.pyplot as plt\n\nfrom sklearn.cluster import DBSCAN\nfrom sklearn import metrics\nfrom sklearn.datasets.samples_generator import make_blobs\nfrom sklearn.preprocessing impo... | {
"source_sha256": "a0e56162369928d35e38e19a24ee57376c55158ef8f01353e0c45273aa9f3ab9",
"reverse_sha256": "a0e56162369928d35e38e19a24ee57376c55158ef8f01353e0c45273aa9f3ab9",
"source_char_count": 1450,
"reverse_char_count": 1450,
"source_byte_count": 1450,
"reverse_byte_count": 1450,
"sha_exact_ok": true,
... | true | {
"sha256": "a0e56162369928d35e38e19a24ee57376c55158ef8f01353e0c45273aa9f3ab9",
"char_count": 1450,
"byte_count": 1450,
"line_count": 51,
"compile_ok": true,
"compile_error": null
} | {
"repo_name": "banacer/door-wiz",
"path": "src/identification/Identifier.py",
"license": "mit",
"language": "Python",
"size": 1449,
"source_dataset": "codeparrot/github-code-clean",
"source_config": "Python-mit",
"source_split": "train",
"source_label": "github_code_clean_python_mit_single",
"sourc... | {
"families": [
"classes",
"functions",
"imports"
],
"primary_family": "functions",
"ast_node_count": 123,
"ast_top_counts": {
"Name": 18,
"Constant": 17,
"alias": 15,
"Load": 14,
"ImportFrom": 9,
"Assign": 9,
"Store": 9,
"Import": 5,
"arg": 5,
"keyword": 4,... | {
"projection_api": "plaincode.api.project_python_dataset_rows",
"requested_languages": [
"en",
"es",
"fr",
"pt",
"zh",
"hi"
],
"row_schema": "source-code-first-one-language-per-row-v2",
"public_cnl_contains_private_cst_transport": false
} | 8fba304f90570adea937bb9205a1ac469e5f553e0a723fe98ab3ac10beaec0f5 |
import numpy as np
import pandas as pd
from pandas import Series, DataFrame
from scipy.spatial import distance
import matplotlib.pyplot as plt
from sklearn.cluster import DBSCAN
from sklearn import metrics
from sklearn.datasets.samples_generator import make_blobs
from sklearn.preprocessing import StandardScaler
from s... | {
"language": "es",
"text": "Importar numpy, referido como np.\nImportar pandas, referido como pd.\nImportar Series, DataFrame desde pandas.\nImportar distance desde scipy.spatial.\nImportar matplotlib.pyplot, referido como plt.\nImportar DBSCAN desde sklearn.cluster.\nImportar metrics desde sklearn.\nImportar make... | {
"row_id": "pc_cnl100k_000000_es_a0e561623699",
"python_source_id": "pc_src100k_000000_a0e561623699",
"python_source_index": 0,
"run_id": "run_20260530_153047_utc",
"created_utc": "2026-05-30T15:31:09"
} | {
"sibling_language_count": 6,
"sibling_languages": [
"en",
"es",
"fr",
"pt",
"zh",
"hi"
],
"all_sibling_languages_strict_exact": true
} | {
"python": "import numpy as np\nimport pandas as pd\nfrom pandas import Series, DataFrame\nfrom scipy.spatial import distance\nimport matplotlib.pyplot as plt\n\nfrom sklearn.cluster import DBSCAN\nfrom sklearn import metrics\nfrom sklearn.datasets.samples_generator import make_blobs\nfrom sklearn.preprocessing impo... | {
"source_sha256": "a0e56162369928d35e38e19a24ee57376c55158ef8f01353e0c45273aa9f3ab9",
"reverse_sha256": "a0e56162369928d35e38e19a24ee57376c55158ef8f01353e0c45273aa9f3ab9",
"source_char_count": 1450,
"reverse_char_count": 1450,
"source_byte_count": 1450,
"reverse_byte_count": 1450,
"sha_exact_ok": true,
... | true | {
"sha256": "a0e56162369928d35e38e19a24ee57376c55158ef8f01353e0c45273aa9f3ab9",
"char_count": 1450,
"byte_count": 1450,
"line_count": 51,
"compile_ok": true,
"compile_error": null
} | {
"repo_name": "banacer/door-wiz",
"path": "src/identification/Identifier.py",
"license": "mit",
"language": "Python",
"size": 1449,
"source_dataset": "codeparrot/github-code-clean",
"source_config": "Python-mit",
"source_split": "train",
"source_label": "github_code_clean_python_mit_single",
"sourc... | {
"families": [
"classes",
"functions",
"imports"
],
"primary_family": "functions",
"ast_node_count": 123,
"ast_top_counts": {
"Name": 18,
"Constant": 17,
"alias": 15,
"Load": 14,
"ImportFrom": 9,
"Assign": 9,
"Store": 9,
"Import": 5,
"arg": 5,
"keyword": 4,... | {
"projection_api": "plaincode.api.project_python_dataset_rows",
"requested_languages": [
"en",
"es",
"fr",
"pt",
"zh",
"hi"
],
"row_schema": "source-code-first-one-language-per-row-v2",
"public_cnl_contains_private_cst_transport": false
} | 8bfb3d8ac1c3c76ab4dec1ca274c40539eaea11c7ddf6fed9554fdbe15bb603a |
import numpy as np
import pandas as pd
from pandas import Series, DataFrame
from scipy.spatial import distance
import matplotlib.pyplot as plt
from sklearn.cluster import DBSCAN
from sklearn import metrics
from sklearn.datasets.samples_generator import make_blobs
from sklearn.preprocessing import StandardScaler
from s... | {
"language": "fr",
"text": "Charger numpy, référé comme np.\nCharger pandas, référé comme pd.\nCharger Series, DataFrame depuis pandas.\nCharger distance depuis scipy.spatial.\nCharger matplotlib.pyplot, référé comme plt.\nCharger DBSCAN depuis sklearn.cluster.\nCharger metrics depuis sklearn.\nCharger make_blobs ... | {
"row_id": "pc_cnl100k_000000_fr_a0e561623699",
"python_source_id": "pc_src100k_000000_a0e561623699",
"python_source_index": 0,
"run_id": "run_20260530_153047_utc",
"created_utc": "2026-05-30T15:31:09"
} | {
"sibling_language_count": 6,
"sibling_languages": [
"en",
"es",
"fr",
"pt",
"zh",
"hi"
],
"all_sibling_languages_strict_exact": true
} | {
"python": "import numpy as np\nimport pandas as pd\nfrom pandas import Series, DataFrame\nfrom scipy.spatial import distance\nimport matplotlib.pyplot as plt\n\nfrom sklearn.cluster import DBSCAN\nfrom sklearn import metrics\nfrom sklearn.datasets.samples_generator import make_blobs\nfrom sklearn.preprocessing impo... | {
"source_sha256": "a0e56162369928d35e38e19a24ee57376c55158ef8f01353e0c45273aa9f3ab9",
"reverse_sha256": "a0e56162369928d35e38e19a24ee57376c55158ef8f01353e0c45273aa9f3ab9",
"source_char_count": 1450,
"reverse_char_count": 1450,
"source_byte_count": 1450,
"reverse_byte_count": 1450,
"sha_exact_ok": true,
... | true | {
"sha256": "a0e56162369928d35e38e19a24ee57376c55158ef8f01353e0c45273aa9f3ab9",
"char_count": 1450,
"byte_count": 1450,
"line_count": 51,
"compile_ok": true,
"compile_error": null
} | {
"repo_name": "banacer/door-wiz",
"path": "src/identification/Identifier.py",
"license": "mit",
"language": "Python",
"size": 1449,
"source_dataset": "codeparrot/github-code-clean",
"source_config": "Python-mit",
"source_split": "train",
"source_label": "github_code_clean_python_mit_single",
"sourc... | {
"families": [
"classes",
"functions",
"imports"
],
"primary_family": "functions",
"ast_node_count": 123,
"ast_top_counts": {
"Name": 18,
"Constant": 17,
"alias": 15,
"Load": 14,
"ImportFrom": 9,
"Assign": 9,
"Store": 9,
"Import": 5,
"arg": 5,
"keyword": 4,... | {
"projection_api": "plaincode.api.project_python_dataset_rows",
"requested_languages": [
"en",
"es",
"fr",
"pt",
"zh",
"hi"
],
"row_schema": "source-code-first-one-language-per-row-v2",
"public_cnl_contains_private_cst_transport": false
} | 8048d63e51fe9c772a6dd9086518f00e98b464c54eb9a59ae06c6d742303d429 |
import numpy as np
import pandas as pd
from pandas import Series, DataFrame
from scipy.spatial import distance
import matplotlib.pyplot as plt
from sklearn.cluster import DBSCAN
from sklearn import metrics
from sklearn.datasets.samples_generator import make_blobs
from sklearn.preprocessing import StandardScaler
from s... | {
"language": "pt",
"text": "Importar numpy, com o nome np.\nImportar pandas, com o nome pd.\nImportar Series, DataFrame de pandas.\nImportar distance de scipy atributo spatial.\nImportar matplotlib atributo pyplot, com o nome plt.\nImportar DBSCAN de sklearn atributo cluster.\nImportar metrics de sklearn.\nImporta... | {
"row_id": "pc_cnl100k_000000_pt_a0e561623699",
"python_source_id": "pc_src100k_000000_a0e561623699",
"python_source_index": 0,
"run_id": "run_20260530_153047_utc",
"created_utc": "2026-05-30T15:31:09"
} | {
"sibling_language_count": 6,
"sibling_languages": [
"en",
"es",
"fr",
"pt",
"zh",
"hi"
],
"all_sibling_languages_strict_exact": true
} | {
"python": "import numpy as np\nimport pandas as pd\nfrom pandas import Series, DataFrame\nfrom scipy.spatial import distance\nimport matplotlib.pyplot as plt\n\nfrom sklearn.cluster import DBSCAN\nfrom sklearn import metrics\nfrom sklearn.datasets.samples_generator import make_blobs\nfrom sklearn.preprocessing impo... | {
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"reverse_sha256": "a0e56162369928d35e38e19a24ee57376c55158ef8f01353e0c45273aa9f3ab9",
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"source_config": "Python-mit",
"source_split": "train",
"source_label": "github_code_clean_python_mit_single",
"sou... | {
"families": [
"imports"
],
"primary_family": "imports",
"ast_node_count": 1029,
"ast_top_counts": {
"Load": 285,
"Name": 198,
"Constant": 114,
"Attribute": 79,
"Call": 77,
"Store": 59,
"Assign": 42,
"Expr": 35,
"Tuple": 34,
"Subscript": 24,
"Slice": 24,
"B... | {
"projection_api": "plaincode.api.project_python_dataset_rows",
"requested_languages": [
"en",
"es",
"fr",
"pt",
"zh",
"hi"
],
"row_schema": "source-code-first-one-language-per-row-v2",
"public_cnl_contains_private_cst_transport": false
} | 560c7db42f4bb2689b179104ad47fdd8847a116bebbf0e18d9e120fa7b5a0455 |
End of preview.
Plaincode CNL 100k
This dataset is generated with Plaincode by streaming Python source files, projecting each accepted Python module/function into the current controlled-natural-language surfaces, and enforcing strict exact Python roundtrip proof for every emitted language. The public row schema is one language per row: one accepted Python source emits sibling rows for en/es/fr/pt/zh/hi linked by python_source_id.
Included surfaces
- Python source
- English CNL (
en) - Spanish CNL (
es) - French CNL (
fr) - Portuguese CNL (
pt) - Mandarin CNL (
zh) - Hindi CNL (
hi)
Acceptance gate
A row is accepted only when every requested CNL surface reverses back to the exact original Python bytes through Plaincode proof:
sha_exact_ok == truechar_exact_ok == truebyte_exact_ok == trueexact_ok == truereverse_ast_ok == truereverse_compile_ok == true
The public CNL fields must not contain private CST/proof transport markers.
Schema
Each row is ordered for readability and training use:
source_code: the original Python source, first in the JSON objectcnl:{"language": "en/es/fr/pt/zh/hi", "text": "..."}ids: row/source/run IDs linking sibling rows from the same Python sourcecnl_siblings: sibling language list/count and all-language strictness flagroundtrip,proof,strict_exact: reverse/proof datasource_stats,source_metadata,semantic_family,engine,row_sha256: inspection metadata at the bottom
The data shard writer preserves JSON key order. It does not sort keys alphabetically.
Generation stats
{
"accepted_python_sources": 5756,
"accepted_rows": 5756,
"completed": false,
"completed_shards": [
"train-00000.jsonl.gz",
"train-00001.jsonl.gz"
],
"duplicates": 0,
"emitted_language_rows": 34536,
"family_counts": {
"async": 62,
"classes": 2997,
"comprehensions": 950,
"context_managers": 678,
"exceptions": 1488,
"functions": 4439,
"generators": 216,
"imports": 5286,
"lambda": 357,
"loops": 2202,
"simple_module": 124
},
"filter_reasons": {
"auto_generated": 368,
"skipped_path_pattern": 372,
"syntax_error:\"\\ \" is an invalid escape sequence. Did you mean \"\\\\ \"? A raw string is also an option.": 2,
"syntax_error:\"\\$\" is an invalid escape sequence. Did you mean \"\\\\$\"? A raw string is also an option.": 1,
"syntax_error:\"\\%\" is an invalid escape sequence. Did you mean \"\\\\%\"? A raw string is also an option.": 2,
"syntax_error:\"\\(\" is an invalid escape sequence. Did you mean \"\\\\(\"? A raw string is also an option.": 4,
"syntax_error:\"\\*\" is an invalid escape sequence. Did you mean \"\\\\*\"? A raw string is also an option.": 1,
"syntax_error:\"\\+\" is an invalid escape sequence. Did you mean \"\\\\+\"? A raw string is also an option.": 1,
"syntax_error:\"\\-\" is an invalid escape sequence. Did you mean \"\\\\-\"? A raw string is also an option.": 3,
"syntax_error:\"\\.\" is an invalid escape sequence. Did you mean \"\\\\.\"? A raw string is also an option.": 16,
"syntax_error:\"\\/\" is an invalid escape sequence. Did you mean \"\\\\/\"? A raw string is also an option.": 4,
"syntax_error:\"\\:\" is an invalid escape sequence. Did you mean \"\\\\:\"? A raw string is also an option.": 1,
"syntax_error:\"\\<\" is an invalid escape sequence. Did you mean \"\\\\<\"? A raw string is also an option.": 2,
"syntax_error:\"\\?\" is an invalid escape sequence. Did you mean \"\\\\?\"? A raw string is also an option.": 1,
"syntax_error:\"\\A\" is an invalid escape sequence. Did you mean \"\\\\A\"? A raw string is also an option.": 3,
"syntax_error:\"\\D\" is an invalid escape sequence. Did you mean \"\\\\D\"? A raw string is also an option.": 1,
"syntax_error:\"\\M\" is an invalid escape sequence. Did you mean \"\\\\M\"? A raw string is also an option.": 1,
"syntax_error:\"\\S\" is an invalid escape sequence. Did you mean \"\\\\S\"? A raw string is also an option.": 3,
"syntax_error:\"\\W\" is an invalid escape sequence. Did you mean \"\\\\W\"? A raw string is also an option.": 4,
"syntax_error:\"\\[\" is an invalid escape sequence. Did you mean \"\\\\[\"? A raw string is also an option.": 3,
"syntax_error:\"\\]\" is an invalid escape sequence. Did you mean \"\\\\]\"? A raw string is also an option.": 1,
"syntax_error:\"\\c\" is an invalid escape sequence. Did you mean \"\\\\c\"? A raw string is also an option.": 1,
"syntax_error:\"\\d\" is an invalid escape sequence. Did you mean \"\\\\d\"? A raw string is also an option.": 29,
"syntax_error:\"\\h\" is an invalid escape sequence. Did you mean \"\\\\h\"? A raw string is also an option.": 1,
"syntax_error:\"\\i\" is an invalid escape sequence. Did you mean \"\\\\i\"? A raw string is also an option.": 1,
"syntax_error:\"\\j\" is an invalid escape sequence. Did you mean \"\\\\j\"? A raw string is also an option.": 1,
"syntax_error:\"\\l\" is an invalid escape sequence. Did you mean \"\\\\l\"? A raw string is also an option.": 2,
"syntax_error:\"\\m\" is an invalid escape sequence. Did you mean \"\\\\m\"? A raw string is also an option.": 3,
"syntax_error:\"\\o\" is an invalid escape sequence. Did you mean \"\\\\o\"? A raw string is also an option.": 2,
"syntax_error:\"\\p\" is an invalid escape sequence. Did you mean \"\\\\p\"? A raw string is also an option.": 1,
"syntax_error:\"\\s\" is an invalid escape sequence. Did you mean \"\\\\s\"? A raw string is also an option.": 16,
"syntax_error:\"\\w\" is an invalid escape sequence. Did you mean \"\\\\w\"? A raw string is also an option.": 13,
"syntax_error:\"\\y\" is an invalid escape sequence. Did you mean \"\\\\y\"? A raw string is also an option.": 1,
"syntax_error:\"\\|\" is an invalid escape sequence. Did you mean \"\\\\|\"? A raw string is also an option.": 2,
"syntax_error:\"is not\" with 'int' literal. Did you mean \"!=\"?": 3,
"syntax_error:\"is not\" with 'str' literal. Did you mean \"!=\"?": 3,
"syntax_error:\"is\" with 'int' literal. Did you mean \"==\"?": 7,
"syntax_error:\"is\" with 'str' literal. Did you mean \"==\"?": 8,
"syntax_error:'(' was never closed": 19,
"syntax_error:'bool' object is not callable; perhaps you missed a comma?": 1,
"syntax_error:'break' in a 'finally' block": 1,
"syntax_error:'return' in a 'finally' block": 7,
"syntax_error:'return' outside function": 1,
"syntax_error:'u' and 'r' prefixes are incompatible": 5,
"syntax_error:'yield from' inside async function": 1,
"syntax_error:Expected one or more names after 'import'": 1,
"syntax_error:Function parameters cannot be parenthesized": 4,
"syntax_error:Lambda expression parameters cannot be parenthesized": 1,
"syntax_error:Missing parentheses in call to 'exec'. Did you mean exec(...)?": 1,
"syntax_error:Missing parentheses in call to 'print'. Did you mean print(...)?": 696,
"syntax_error:expected ':'": 5,
"syntax_error:expected an indented block after class definition on line 5": 1,
"syntax_error:expected an indented block after function definition on line 13": 1,
"syntax_error:expected an indented block after function definition on line 25": 1,
"syntax_error:inconsistent use of tabs and spaces in indentation": 28,
"syntax_error:invalid character '…' (U+2026)": 1,
"syntax_error:invalid decimal literal": 12,
"syntax_error:invalid hexadecimal literal": 3,
"syntax_error:invalid non-printable character U+00A0": 1,
"syntax_error:invalid syntax": 62,
"syntax_error:invalid syntax. Perhaps you forgot a comma?": 5,
"syntax_error:leading zeros in decimal integer literals are not permitted; use an 0o prefix for octal integers": 8,
"syntax_error:unexpected indent": 7,
"syntax_error:unindent does not match any outer indentation level": 1,
"syntax_error:unmatched ')'": 4,
"syntax_error:unmatched '}'": 1,
"syntax_error:unterminated string literal (detected at line 116)": 1,
"syntax_error:unterminated triple-quoted string literal (detected at line 19)": 1,
"syntax_error:unterminated triple-quoted string literal (detected at line 430)": 1,
"syntax_error:unterminated triple-quoted string literal (detected at line 81)": 1,
"too_large": 534,
"too_many_ast_nodes": 3,
"too_many_lines": 34,
"too_small": 162
},
"filtered_candidates": 2504,
"finished_utc": "2026-05-30T15:40:07+00:00",
"hf_repo_id": "CircularBalls/plaincode-cnl-100k-by-language",
"languages": [
"en",
"es",
"fr",
"pt",
"zh",
"hi"
],
"projection_failures": 3,
"resume_accepted_rows": 0,
"resume_skipped_accepted_rows": 0,
"resume_start_shard": 0,
"row_schema": "source-code-first-one-language-per-row-v2",
"run_id": "run_20260530_153047_utc",
"seen_candidates": 8264,
"shards_completed": 2,
"source_label_counts": {
"github_code_clean_python_mit_single": 5756
},
"source_specs": [
{
"config": "Python-mit",
"dataset": "codeparrot/github-code-clean",
"enabled": true,
"label": "github_code_clean_python_mit_single",
"split": "train",
"trust_remote_code": false,
"weight": 1
}
],
"started_utc": "2026-05-30T15:30:49+00:00",
"strict_gate_failures": 0,
"target_accepted_rows": 100000,
"updated_utc": "2026-05-30T15:40:07+00:00"
}
Intended use
Training/evaluating semantic projection, code-to-CNL, CNL-to-code, multilingual controlled-language alignment, and exact roundtrip experiments.
Source/license note
Rows retain source metadata where available, including license fields exposed by upstream datasets. The default generator configuration prioritizes permissive-ish Python source configs. Review upstream licenses before redistribution or commercial use.
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