Dataset Viewer
The dataset viewer is not available for this split.
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 string to null
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 489, 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 2818, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2355, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2380, 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 536, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, 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 2369, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2303, 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 1852, 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 2059, in cast_array_to_feature
_c(array.field(name) if name in array_fields else null_array, subfeature)
~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1854, in wrapper
return func(array, *args, **kwargs)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2109, in cast_array_to_feature
casted_array_values = _c(array.values, feature.feature)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1854, in wrapper
return func(array, *args, **kwargs)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2143, in cast_array_to_feature
return array_cast(
array,
...<2 lines>...
allow_decimal_to_str=allow_decimal_to_str,
)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1854, in wrapper
return func(array, *args, **kwargs)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2005, in array_cast
raise TypeError(f"Couldn't cast array of type {_short_str(array.type)} to {_short_str(pa_type)}")
TypeError: Couldn't cast array of type string to nullNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
French Synthetic Document Test Samples
Six small, fully synthetic French business documents for testing document-processing workflows. Each PDF is paired with JSON ground truth and scenario context so that an OCR, information-extraction, search, reconciliation, or QA pipeline can be checked deterministically.
The repository contains two examples from each domain:
| Folder | Domain | Documents | Expected outcome |
|---|---|---|---|
samples/ecommerce/ |
E-commerce | 2 invoices | one clean case, one duplicate-invoice-number case |
samples/construction/ |
Construction / BTP | 2 invoices | one clean case, one incorrect-VAT-amount case |
samples/restaurant/ |
Restaurant | 2 supplier invoices | one clean case, one printed-total-mismatch case |
What is in every sample folder
pdf/— fictional French documents in PDF format;ground_truth/— one JSON record per PDF, including expected fields, computed totals, printed totals, relations, and intended findings;source_data/— scenario-level context and expected result;DATA_DICTIONARY.md— field definitions and VAT representation;README.md— a short description of the domain sample.
Each document_id is stable and is the key used to reconcile the PDF, its ground truth, and its scenario. Monetary values in the computed data are integers in cents. VAT rates are basis points (2000 = 20%, 1000 = 10%, 550 = 5.5%).
Intended uses
- smoke-testing PDF ingestion and text extraction;
- checking field extraction for dates, amounts, VAT, invoice numbers, and line items;
- validating document matching and reconciliation rules;
- testing alert handling with known anomalies;
- building demos without exposing customer, supplier, or accounting records.
Important limitations
- Every company, person, identifier, address, amount, and document in this repository is fictional and synthetic.
- These are test artifacts, not genuine accounting documents, legal advice, or evidence of regulatory compliance.
- They are not a Factur-X, e-invoicing, or OCR benchmark, and no extraction-performance claim is made.
- The PDFs are text-based test documents; they are not scans or photographs.
Full editions
This is the free evaluation sample for three larger commercial packs. The full editions add linked document flows, scenario documentation, integrity reports, and additional known anomalies:
| Full edition | Contents | Price | Checkout |
|---|---|---|---|
| E-commerce Document Test Pack FR | 27 PDF/JSON pairs | EUR 29 | Buy the E-commerce pack |
| BTP Document Test Pack FR | 24 PDF/JSON pairs | EUR 29 | Buy the BTP pack |
| Restauration Document Test Pack FR | 26 PDF/JSON pairs | EUR 29 | Buy the Restaurant pack |
| Bundle — 3 sectors | 77 PDF/JSON pairs | EUR 69 | Buy the 3-sector bundle |
The bundle is EUR 18 less than purchasing the three sector packs separately.
License
The files in this free sample are released under CC BY 4.0. Keep the attribution and the synthetic-data notice when redistributing a sample. The commercial full editions have their own separate internal-use licence.
Citation
If this sample is useful in a public demo, article, or tool documentation, please link to this repository as: djo33350/French-Synthetic-Document-Test-Samples.
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