Cedar Street Tacos: Till import with a duplicate item code
Till import with a duplicate item code for Cedar Street Tacos. Intentionally invalid. 22 rows where pos-import.csv has 21. item_code MENU-02 appears on line 3 at 11.00 CAD and again on line 23 at 12.00 CAD, which is the proposed price in the shared menu_price_changes table. It is the only repeated code in the file, so an importer that keeps the last row it reads silently ships the later price.
item_code,item_name,category,price,tax_code,modifier_group
MENU-01,Chicken taco trio,Tacos,13.50,GST5,MG-MENU-01
MENU-02,Bean taco trio,Tacos,11.00,GST5,MG-MENU-02
MENU-03,Chicken bowl,Bowls,14.50,GST5,MG-MENU-03
MENU-04,Bean bowl,Bowls,12.00,GST5,MG-MENU-04
MOD-01,Extra portion,Modifier,2.50,GST5,MG-MENU-01
MOD-02,Takeaway packaging,Modifier,0.50,GST5,MG-MENU-01
MOD-03,Extra portion,Modifier,2.50,GST5,MG-MENU-02
MOD-04,Takeaway packaging,Modifier,0.50,GST5,MG-MENU-02
MOD-05,Extra portion,Modifier,2.50,GST5,MG-MENU-03
MOD-06,Takeaway packaging,Modifier,0.50,GST5,MG-MENU-03
MOD-07,Extra portion,Modifier,2.50,GST5,MG-MENU-04
MOD-08,Takeaway packaging,Modifier,0.50,GST5,MG-MENU-04
DRK-01G,"Horchata jug, 200 ml",By the glass,2.50,GST5,
DRK-02G,"Agua fresca de jamaïca, 200 ml",By the glass,2.25,GST5,
DRK-03G,"Lime soda, 150 ml",By the glass,2.00,GST5,
DRK-04G,"Iced coffee, 400 ml",By the glass,4.25,GST5,
DRK-01B,"Horchata jug, 1000 ml",By the bottle,12.00,GST5,
DRK-02B,"Agua fresca de jamaïca, 1000 ml",By the bottle,11.00,GST5,
DRK-03B,"Lime soda, 750 ml",By the bottle,9.00,GST5,
DRK-05B,"Cola, 355 ml",By the bottle,3.50,GST5,
GIFT-25,Gift card 25,Stored value,25.00,EXEMPT,
MENU-02,Bean taco trio,Tacos,12.00,GST5,MG-MENU-02
Specifications
- Kit
- restaurant-food-truck
- Industry
- food-service
- Schema Version
- 1
- Synthetic
- true
- As Of
- 2026-09-08
- Currency
- CAD
- Menu Items
- 4
- Rows
- 22
- Columns
- 6
- Intentionally Invalid
- true
- Defect
- duplicate-item-code
- Duplicate Item Code
- MENU-02
- First Line
- 3
- Second Line
- 23
- Delimiter
- ,
- Encoding
- UTF-8
- Line Endings
- LF
Testing contract
Expected to fail- Scenario
- Use till import with a duplicate item code in the Cedar Street Tacos menu, allergen and till import workflow.
- Expected result
- Intentionally invalid. 22 rows where pos-import.csv has 21. item_code MENU-02 appears on line 3 at 11.00 CAD and again on line 23 at 12.00 CAD, which is the proposed price in the shared menu_price_changes table. It is the only repeated code in the file, so an importer that keeps the last row it reads silently ships the later price.
What is a .csv file?
CSV (Comma-Separated Values) is a plain-text tabular format where rows are lines and fields are separated by commas, with quoting rules for values that contain delimiters, quotes, or newlines. It has no formal type system and depends on encoding and dialect conventions. It is the most portable format for tabular data exchange.
How to use this file
Use an example CSV to test parsers against quoting and embedded-delimiter edge cases, header handling, encoding detection, and import pipelines into databases or spreadsheets.
How to use this file for testing
“Cedar Street Tacos: Till import with a duplicate item code” is a deterministic Testaroo fixture for Data import, Error handling, CSV parsing. Realistic faker-generated datasets with documented schemas for testing import and ETL flows.
Documented properties for this file: 22 rows · 6 columns · UTF-8 · LF. 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.
Data fixtures document their exact quirks (delimiters, encodings, null handling, schema, and row counts) in the spec table. Point your parser or importer at the file and assert it handles the documented edge cases; clean and deliberately-messy siblings make before/after diffs straightforward.
Code examples
import pandas as pd
df = pd.read_csv("pos-import-duplicate-code.csv")
print(df.head())
print(df.dtypes)Generated by generation/restaurant_menus.py. Free for any use, no attribution required, license.
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