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Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code:   StreamingRowsError
Exception:    TypeError
Message:      Couldn't cast array of type
struct<url: string, title: string, revision_id: int64, license: string>
to
{'url': Value('string'), 'title': Value('string'), 'license': Value('string')}
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 149, 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 129, 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 544, 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 3052, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2559, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2584, 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 558, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 440, 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 361, 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 2381, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2315, in cast_table_to_schema
                  cast_array_to_feature(
                  ~~~~~~~~~~~~~~~~~~~~~^
                      table[name] if name in table_column_names else pa.array([None] * len(table), type=schema.field(name).type),
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                      feature,
                      ^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1861, in wrapper
                  return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
                                           ~~~~^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2161, in cast_array_to_feature
                  raise TypeError(f"Couldn't cast array of type\n{_short_str(array.type)}\nto\n{_short_str(feature)}")
              TypeError: Couldn't cast array of type
              struct<url: string, title: string, revision_id: int64, license: string>
              to
              {'url': Value('string'), 'title': Value('string'), 'license': Value('string')}

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lnxhelp knowledge cards

Verified, step-by-step help cards for beginners on Linux and macOS: one card per task, error message or concept. Each card gives an English canonical text, aliases in several languages (mostly Russian and English), literal error patterns, and the commands with expected output. The cards are the knowledge base of the lnxhelp offline helper.

Licensing is per card and mixed. Read the source.license field of each card before reuse. There is no single license for this dataset (see the table below).

Contents

File Rows / files What it is
cards/ 1,625 JSON files Curated snapshot s2, one card per file, folders linux/, macos/, posix/, authored/
cards.jsonl 1,625 lines The same curated snapshot, one card per line
cards_live.jsonl 2,572 lines The live card set of the repository. Same card JSON, with an added path field (relative path of the source file)
card.schema.json 1 file JSON Schema of a card, schema_version 2 (additionalProperties: false)

cards_live.jsonl is not a superset of s2: it has 947 more cards. Of these, 180 are Fedora cards, which s2 does not contain, and the rest are cards that s2 does not carry (linux 535, posix 140, macos 87, authored 5). The curation step that produced s2 is not documented in this card. Use cards.jsonl for the curated set.

Schema (v2, summary)

Required: schema_version (2), id (slug), platform (linux | macos | posix), kind (task | error | concept), title, summary (no commands), aliases (3 to 30 items, {text, lang}), applies_to.distros (family, optional min/max version), steps, risk (low | medium | high), source (url, title, license, optional revision_id). Optional top-level fields: error_patterns, prerequisites, verify, rollback, warnings, see_also, updated, output_guide, cause. applies_to can also list desktop, display_server and requires. additionalProperties is false at the top level. See card.schema.json for the full definition.

Counts by source and license

Snapshot s2 (cards.jsonl, 1,625 cards), license from source.license:

Folder / platform Cards License
linux (Arch Wiki based) 384 GFDL-1.3-or-later
linux (tldr-pages based) 437 CC-BY-4.0
posix (tldr-pages based) 332 CC-BY-4.0
macos (tldr-pages based) 297 CC-BY-4.0
authored 174 CC-BY-4.0
authored (macOS, Apple reference) 1 LicenseRef-Apple-Support-Copyright

Live set (cards_live.jsonl, 2,572 cards):

Source Cards License
Arch Wiki 858 GFDL-1.3-or-later
tldr-pages, linux 498 CC-BY-4.0
tldr-pages, posix 472 CC-BY-4.0
tldr-pages, macos 384 CC-BY-4.0
Fedora Quick Docs 180 CC-BY-SA-3.0
authored (12 different licenses) 180 CC-BY-4.0 (151), GPL-2.0-or-later (8), GFDL-1.3-or-later (5), GPL-3.0-or-later (5), LicenseRef-Apple-Support-Copyright (3), CC-BY-SA-4.0 (2), GPL-2.0-only, BSD-2-Clause, BSD-3-Clause, HPND, Apache-2.0, NOASSERTION (1 each)

Licensing notes

  • GFDL-1.3-or-later (Arch Wiki): copyleft. Copies and derived works carry the GFDL terms, which the owner should review before any redistribution.
  • CC-BY-SA-3.0 (Fedora Quick Docs): share-alike. Derived cards carry the CC-BY-SA terms.
  • CC-BY-4.0 (tldr-pages): attribution required. Credit: tldr-pages contributors, https://github.com/tldr-pages/tldr.
  • Authored cards: the source.license value is the license of the reference page each card was checked against (a man page or documentation), not necessarily the license of the card text. The GPL, BSD and Apache values here are such references. The Apple-copyright reference (1 card in s2, 3 in the live set) is a copyright notice on Apple's material and needs a decision before any redistribution.
  • No single license has been chosen for this dataset. Treat it as all-rights-reserved until the owner decides.

Provenance

Converted from public sources with a teacher model, then checked by the card contract (schema, grounding in the source text, command checks in Docker sandboxes per distro and on macOS, and deterministic curation). The source text itself is not included here. Forum content is not part of this dataset.

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