Ember Lane Pizza: Inventory variance as an OpenDocument spreadsheet
Inventory variance as an OpenDocument spreadsheet for Ember Lane Pizza. Two tables. Theoretical closing, the variance quantity, the variance at standard cost and the total are live ODF formulas over 6 ingredients. The same figures in value form are in inventory-count-sheet.csv.
Rendered preview of the ods file (2.6 KB). Download above for the original.
Specifications
- Kit
- restaurant-pizzeria
- Industry
- food-service
- Schema Version
- 1
- Synthetic
- true
- As Of
- 2026-09-08
- Currency
- CAD
- Period Start
- 2026-08-20
- Period End
- 2026-09-02
- Tables
- 2
- Cached Values
- false
- Formula Syntax
- OpenFormula (of:=)
Testing contract
Expected to pass- Scenario
- Use inventory variance as an opendocument spreadsheet in the Ember Lane Pizza costing and daily operations workflow.
- Expected result
- Two tables. Theoretical closing, the variance quantity, the variance at standard cost and the total are live ODF formulas over 6 ingredients. The same figures in value form are in inventory-count-sheet.csv.
What is a .ods file?
ODS is the OpenDocument Spreadsheet format, an ISO-standardized spreadsheet stored as a ZIP archive of XML. It is the native spreadsheet format of LibreOffice and OpenOffice Calc, supporting multiple sheets, formulas, and formatting. It is the open-standard counterpart to XLSX.
How to use this file
Use an example ODS to test OpenDocument spreadsheet parsing, formula and multi-sheet handling, and converters between ODS and XLSX or CSV.
How to use this file for testing
“Ember Lane Pizza: Inventory variance as an OpenDocument spreadsheet” is a deterministic Novus Examples fixture for Spreadsheet testing, Data import. Multi-sheet workbooks with documented formulas and plain sheets for testing spreadsheet parsers and importers.
Documented properties for this file: ODS · 2,638 bytes. Compare results against paired or grouped companions on this page when present (clean↔damaged, searchable↔scanned, or format twins) so scores stay reproducible across runs.
Download the file once, keep the path stable in CI or local scripts, and treat the spec table as the contract: dimensions, seeds, field lists, and roles are intentional. Corrupt or invalid samples are labelled as such, expect parsers to fail loudly rather than silently accept them.
This template ships filled with realistic sample content and documented fields and formulas. Download it as a starting point, or point a converter/parser at it, format twins (for example DOCX↔PDF) let you diff conversion fidelity.
Code examples
import pandas as pd # pip install odfpy
df = pd.read_excel("inventory-variance.ods", engine="odf")
print(df.head())Related files
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Generated by generation/restaurant_costing.py. Free for any use, no attribution required, license.