Datasets:

saraNour
/

compliments-products-aligned

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
product_id: large_string
retailer_product_id: large_string
brand: large_string
product_name: large_string
price_cad: double
price_currency: large_string
size: large_string
image_url: large_string
category: large_string
is_available: bool
source: large_string
source_url: large_string
scraped_at: large_string
serving_size: large_string
calories: double
carbohydrate_g: double
sugars_g: double
sodium_mg: double
potassium_mg: double
fat_g: double
saturated_fat_g: double
polyunsaturated_fat_g: double
omega6_g: double
omega3_g: double
monounsaturated_fat_g: double
sugar_alcohols_g: double
fibre_g: double
protein_g: double
calcium_mg: double
iron_mg: double
cholesterol_mg: double
name_clean: large_string
size_value: double
size_unit: large_string
is_canadian_brand: bool
pack_count: double
pack_type: large_string
language: large_string
voila_product_url: large_string
match_found: bool
match_confidence: double
auto_assign_upc: bool
upc: large_string
gtin: large_string
safeway_article_number: large_string
safeway_name: large_string
safeway_brand: large_string
safeway_price: double
safeway_url: large_string
safeway_uom: large_string
safeway_amount: double
safeway_weight: large_string
safeway_store_id: large_string
safeway_categories: large_string
safeway_keywords: double
safeway_description: large_string
matching_method: large_string
id_exact_match: bool
hits_considered: double
error: large_string
-- schema metadata --
pandas: '{"index_columns": [], "column_indexes": [], "columns": [{"name":' + 7375
to
{'external_id': Value('string'), 'brand': Value('string'), 'title': Value('string'), 'price': Value('float64'), 'price_currency': Value('string'), 'size': Value('string'), 'size_amount': Value('float64'), 'size_unit': Value('string'), 'size_qty': Value('int64'), 'size_per_unit': Value('float64'), 'size_unit_norm': Value('string'), 'size_total': Value('float64'), 'image_url': Value('string'), 'source': Value('string'), 'source_url': Value('string'), 'category': Value('string'), 'category_path': Value('string'), 'category_l1': Value('string'), 'category_l2': Value('string'), 'category_l3': Value('string'), 'category_source': Value('string'), 'upc': Value('string'), 'gtin': Value('string'), 'match_confidence': Value('float64'), 'match_found': Value('bool'), 'safeway_name': Value('string'), 'safeway_brand': Value('string'), 'safeway_price': Value('float64'), 'safeway_url': Value('string'), 'safeway_article_number': Value('string'), 'safeway_uom': Value('string'), 'safeway_amount': Value('float64'), 'calories': Value('float64'), 'carbohydrate_g': Value('float64'), 'sugars_g': Value('float64'), 'sodium_mg': Value('float64'), 'fat_g': Value('float64'), 'saturated_fat_g': Value('float64'), 'protein_g': Value('float64'), 'fibre_g': Value('float64'), 'calcium_mg': Value('float64'), 'iron_mg': Value('float64'), 'cholesterol_mg': Value('float64'), 'serving_size': 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 478, 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/parquet/parquet.py", line 220, in _generate_tables
                  yield Key(file_idx, batch_idx), self._cast_table(pa_table)
                                                  ~~~~~~~~~~~~~~~~^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/parquet/parquet.py", line 156, 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 2297, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              product_id: large_string
              retailer_product_id: large_string
              brand: large_string
              product_name: large_string
              price_cad: double
              price_currency: large_string
              size: large_string
              image_url: large_string
              category: large_string
              is_available: bool
              source: large_string
              source_url: large_string
              scraped_at: large_string
              serving_size: large_string
              calories: double
              carbohydrate_g: double
              sugars_g: double
              sodium_mg: double
              potassium_mg: double
              fat_g: double
              saturated_fat_g: double
              polyunsaturated_fat_g: double
              omega6_g: double
              omega3_g: double
              monounsaturated_fat_g: double
              sugar_alcohols_g: double
              fibre_g: double
              protein_g: double
              calcium_mg: double
              iron_mg: double
              cholesterol_mg: double
              name_clean: large_string
              size_value: double
              size_unit: large_string
              is_canadian_brand: bool
              pack_count: double
              pack_type: large_string
              language: large_string
              voila_product_url: large_string
              match_found: bool
              match_confidence: double
              auto_assign_upc: bool
              upc: large_string
              gtin: large_string
              safeway_article_number: large_string
              safeway_name: large_string
              safeway_brand: large_string
              safeway_price: double
              safeway_url: large_string
              safeway_uom: large_string
              safeway_amount: double
              safeway_weight: large_string
              safeway_store_id: large_string
              safeway_categories: large_string
              safeway_keywords: double
              safeway_description: large_string
              matching_method: large_string
              id_exact_match: bool
              hits_considered: double
              error: large_string
              -- schema metadata --
              pandas: '{"index_columns": [], "column_indexes": [], "columns": [{"name":' + 7375
              to
              {'external_id': Value('string'), 'brand': Value('string'), 'title': Value('string'), 'price': Value('float64'), 'price_currency': Value('string'), 'size': Value('string'), 'size_amount': Value('float64'), 'size_unit': Value('string'), 'size_qty': Value('int64'), 'size_per_unit': Value('float64'), 'size_unit_norm': Value('string'), 'size_total': Value('float64'), 'image_url': Value('string'), 'source': Value('string'), 'source_url': Value('string'), 'category': Value('string'), 'category_path': Value('string'), 'category_l1': Value('string'), 'category_l2': Value('string'), 'category_l3': Value('string'), 'category_source': Value('string'), 'upc': Value('string'), 'gtin': Value('string'), 'match_confidence': Value('float64'), 'match_found': Value('bool'), 'safeway_name': Value('string'), 'safeway_brand': Value('string'), 'safeway_price': Value('float64'), 'safeway_url': Value('string'), 'safeway_article_number': Value('string'), 'safeway_uom': Value('string'), 'safeway_amount': Value('float64'), 'calories': Value('float64'), 'carbohydrate_g': Value('float64'), 'sugars_g': Value('float64'), 'sodium_mg': Value('float64'), 'fat_g': Value('float64'), 'saturated_fat_g': Value('float64'), 'protein_g': Value('float64'), 'fibre_g': Value('float64'), 'calcium_mg': Value('float64'), 'iron_mg': Value('float64'), 'cholesterol_mg': Value('float64'), 'serving_size': Value('string')}
              because column names don't match

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Compliments Products — Schema-Aligned + Categories + Barcodes

Overview

4,440 Compliments private-label products, aligned to the compliments-products-staging schema structure with added category hierarchy from Safeway.ca and UPC barcodes from cross-source matching.

Schema Alignment

All 15 fields from the staging dataset are preserved with identical names and types. 6 category fields, 4 barcode fields, 7 Safeway cross-reference fields, and 12 nutrition fields are added as enrichment.

Category Coverage

With at least one category: 100.0%
With Safeway breadcrumb path: 100.0%
With complete hierarchy (l1+l2): 98.8%
Categories from Safeway: 99.0%, from Voila fallback: 1.0%

Barcode Coverage

UPCs recovered (≥0.95 confidence): 74.2%
Low-confidence (manual review): 23.1%

Files

data/train-00000-of-00001.parquet — Full aligned dataset (44 columns)
mapping_report.csv — Detailed field mapping from enriched → staging schema
enrichment_report.md — Full report with coverage stats and recommendations

Relationship to Other Datasets

Source: saraNour/voila-compliments-with-barcodes (barcode enrichment phase)
Schema: saraNour/compliments-products-staging (reference schema)

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