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: CastError
Message: Couldn't cast
scenario_id: string
scenario_label: string
industry: string
stress_scenario: string
service_level_target: double
horizon_days: int64
budget_limit: double
description: string
skus: list<item: struct<sku_id: string, name: string, category: string, unit_cost: double, demand_mean: do (... 187 chars omitted)
child 0, item: struct<sku_id: string, name: string, category: string, unit_cost: double, demand_mean: double, deman (... 175 chars omitted)
child 0, sku_id: string
child 1, name: string
child 2, category: string
child 3, unit_cost: double
child 4, demand_mean: double
child 5, demand_std: double
child 6, lead_time_days: double
child 7, lead_time_std: double
child 8, current_stock: double
child 9, warehouse_id: string
child 10, shelf_life_days: int64
child 11, min_order_qty: int64
child 12, order_multiple: int64
warehouses: list<item: struct<warehouse_id: string, name: string, region: string, capacity_units: double, holdin (... 93 chars omitted)
child 0, item: struct<warehouse_id: string, name: string, region: string, capacity_units: double, holding_cost_rate (... 81 chars omitted)
child 0, warehouse_id: string
child 1, name: string
child 2, region: string
child 3, capacity_units: double
child 4, holding_cost_rate: double
child 5, transfer_cost_per_unit: double
child 6, is_primary: bool
child 7, availability: double
costs: struct<ordering_cost: double
...
t<type: string>
child 0, type: string
child 6, lead_time_days: struct<type: string>
child 0, type: string
child 7, current_stock: struct<type: string>
child 0, type: string
child 8, warehouse_id: struct<type: string>
child 0, type: string
child 9, shelf_life_days: struct<type: list<item: string>>
child 0, type: list<item: string>
child 0, item: string
child 2, required: list<item: string>
child 0, item: string
child 3, warehouses: struct<type: string, items: struct<type: string, properties: struct<warehouse_id: struct<type: strin (... 107 chars omitted)
child 0, type: string
child 1, items: struct<type: string, properties: struct<warehouse_id: struct<type: string>, name: struct<type: strin (... 78 chars omitted)
child 0, type: string
child 1, properties: struct<warehouse_id: struct<type: string>, name: struct<type: string>, capacity_units: struct<type: (... 44 chars omitted)
child 0, warehouse_id: struct<type: string>
child 0, type: string
child 1, name: struct<type: string>
child 0, type: string
child 2, capacity_units: struct<type: string>
child 0, type: string
child 3, availability: struct<type: string>
child 0, type: string
to
{'$schema': Value('string'), 'title': Value('string'), 'type': Value('string'), 'properties': {'scenario_id': {'type': Value('string')}, 'industry': {'type': Value('string')}, 'skus': {'type': Value('string'), 'items': {'type': Value('string'), 'properties': {'sku_id': {'type': Value('string')}, 'name': {'type': Value('string')}, 'category': {'type': Value('string')}, 'unit_cost': {'type': Value('string')}, 'demand_mean': {'type': Value('string')}, 'demand_std': {'type': Value('string')}, 'lead_time_days': {'type': Value('string')}, 'current_stock': {'type': Value('string')}, 'warehouse_id': {'type': Value('string')}, 'shelf_life_days': {'type': List(Value('string'))}}, 'required': List(Value('string'))}}, 'warehouses': {'type': Value('string'), 'items': {'type': Value('string'), 'properties': {'warehouse_id': {'type': Value('string')}, 'name': {'type': Value('string')}, 'capacity_units': {'type': Value('string')}, 'availability': {'type': Value('string')}}}}}}
because column names don't match
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 2297, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
scenario_id: string
scenario_label: string
industry: string
stress_scenario: string
service_level_target: double
horizon_days: int64
budget_limit: double
description: string
skus: list<item: struct<sku_id: string, name: string, category: string, unit_cost: double, demand_mean: do (... 187 chars omitted)
child 0, item: struct<sku_id: string, name: string, category: string, unit_cost: double, demand_mean: double, deman (... 175 chars omitted)
child 0, sku_id: string
child 1, name: string
child 2, category: string
child 3, unit_cost: double
child 4, demand_mean: double
child 5, demand_std: double
child 6, lead_time_days: double
child 7, lead_time_std: double
child 8, current_stock: double
child 9, warehouse_id: string
child 10, shelf_life_days: int64
child 11, min_order_qty: int64
child 12, order_multiple: int64
warehouses: list<item: struct<warehouse_id: string, name: string, region: string, capacity_units: double, holdin (... 93 chars omitted)
child 0, item: struct<warehouse_id: string, name: string, region: string, capacity_units: double, holding_cost_rate (... 81 chars omitted)
child 0, warehouse_id: string
child 1, name: string
child 2, region: string
child 3, capacity_units: double
child 4, holding_cost_rate: double
child 5, transfer_cost_per_unit: double
child 6, is_primary: bool
child 7, availability: double
costs: struct<ordering_cost: double
...
t<type: string>
child 0, type: string
child 6, lead_time_days: struct<type: string>
child 0, type: string
child 7, current_stock: struct<type: string>
child 0, type: string
child 8, warehouse_id: struct<type: string>
child 0, type: string
child 9, shelf_life_days: struct<type: list<item: string>>
child 0, type: list<item: string>
child 0, item: string
child 2, required: list<item: string>
child 0, item: string
child 3, warehouses: struct<type: string, items: struct<type: string, properties: struct<warehouse_id: struct<type: strin (... 107 chars omitted)
child 0, type: string
child 1, items: struct<type: string, properties: struct<warehouse_id: struct<type: string>, name: struct<type: strin (... 78 chars omitted)
child 0, type: string
child 1, properties: struct<warehouse_id: struct<type: string>, name: struct<type: string>, capacity_units: struct<type: (... 44 chars omitted)
child 0, warehouse_id: struct<type: string>
child 0, type: string
child 1, name: struct<type: string>
child 0, type: string
child 2, capacity_units: struct<type: string>
child 0, type: string
child 3, availability: struct<type: string>
child 0, type: string
to
{'$schema': Value('string'), 'title': Value('string'), 'type': Value('string'), 'properties': {'scenario_id': {'type': Value('string')}, 'industry': {'type': Value('string')}, 'skus': {'type': Value('string'), 'items': {'type': Value('string'), 'properties': {'sku_id': {'type': Value('string')}, 'name': {'type': Value('string')}, 'category': {'type': Value('string')}, 'unit_cost': {'type': Value('string')}, 'demand_mean': {'type': Value('string')}, 'demand_std': {'type': Value('string')}, 'lead_time_days': {'type': Value('string')}, 'current_stock': {'type': Value('string')}, 'warehouse_id': {'type': Value('string')}, 'shelf_life_days': {'type': List(Value('string'))}}, 'required': List(Value('string'))}}, 'warehouses': {'type': Value('string'), 'items': {'type': Value('string'), 'properties': {'warehouse_id': {'type': Value('string')}, 'name': {'type': Value('string')}, 'capacity_units': {'type': Value('string')}, 'availability': {'type': 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.
InventOpt Sample Catalog
Synthetic SKU and warehouse catalog for the InventOpt — Inventory & Replenishment Optimizer demo by Aria AI.
Overview
| Property | Value |
|---|---|
| Industries | 8 (retail, pharma, spare parts, food, hospital, factory, e-commerce, industrial) |
| Stress Scenarios | 6 (baseline, demand spike, supplier delay, budget cap, warehouse outage, transfer) |
| SKUs per scenario | 4–12 (configurable) |
| Data type | Synthetic — no real company data |
Files
| File | Description |
|---|---|
catalog_schema.json |
JSON schema for SKU and warehouse records |
sample_retail.json |
Sample retail scenario with 8 SKUs |
sample_pharma.json |
Sample pharma scenario with perishable SKUs |
Usage
import json
catalog = json.load(open("sample_retail.json"))
License
Apache 2.0 — Aria AI Engineering Team
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