pdf58.1 KB

Cedar Street Tacos — Operating report PDF

Operating report PDF for Cedar Street Tacos. Three readable pages summarize the same model, chart, source tables and usage instructions. Supplier spend=4,122.61 CAD; Net menu sales=19,374.60 CAD; Menu items sold=1,540.00 items; Guest reviews=18.00 records.

Data import

Rendered preview of Cedar Street Tacos — Operating report PDF

Rendered preview of the pdf file (58.1 KB). Download above for the original.

Specifications

Kit: restaurant-food-truck
Industry: food-service
Schema Version: 1
Synthetic: true
As Of: 2026-09-08
Pages: 3

Testing contract

Expected to pass

Scenario: Use operating report pdf in the Cedar Street Tacos purchasing, price-history, menu-costing, inventory, sales, reviews, modifiers, refunds, reservations, staffing, stock-movements, menu-pricing workflow.
Expected result: Three readable pages summarize the same model, chart, source tables and usage instructions. Supplier spend=4,122.61 CAD; Net menu sales=19,374.60 CAD; Menu items sold=1,540.00 items; Guest reviews=18.00 records.

What is a .pdf file?

PDF (Portable Document Format) is a page-oriented format that fixes layout, fonts, and vector and raster graphics so a page renders identically anywhere. A `%PDF-` header is followed by numbered objects, a cross-reference table mapping each to a byte offset, and a trailer; edits append incremental updates rather than rewrite the file. Page content is a stream of drawing operators, so a PDF holds no words or paragraphs, only positioned glyph runs. Adobe released it in 1993 and gave it to ISO as ISO 32000-1 in 2008.

How to use this file

Use an example PDF to test text extraction, rendering, metadata parsing, AcroForm handling, and OCR pipelines: checking that extraction reconstructs reading order from glyph positions, that a scanned page yields no text, and that an incremental update leaves earlier revisions in the file.

How to use this file for testing

“Cedar Street Tacos — Operating report PDF” is a deterministic Novus Examples fixture for Data import. Realistic faker-generated datasets with documented schemas for testing import and ETL flows.

Documented properties for this file: 3 pages. 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.

Document fixtures list their internal structure (pages, fields, tracked changes, embedded objects) in the spec table. Test extractors, converters, and OCR against that known structure, and compare searchable↔scanned or format-twin companions when present.

Code examples

import pdfplumber  # pip install pdfplumber

with pdfplumber.open("report.pdf") as pdf:
    print(len(pdf.pages), "pages")
    print(pdf.pages[0].extract_text())

Generated by generation/business_fixtures.py. Free for any use, no attribution required, license.