pdftract/tests/fixtures/grep-corpus/README.md
jedarden a0c3ebb237 feat(bf-5for4): design manifest schema for grep-corpus
- Add manifest.csv with header row: filename,source_url,page_count,file_size,checksum,license
- Update README.md with comprehensive schema documentation and field descriptions
- Schema supports provenance tracking, integrity verification, and license compliance

Closes bf-5for4
2026-07-05 12:21:25 -04:00

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pdftract grep-corpus

Benchmark corpus for pdftract-grep-1000 CI benchmark.

Purpose

This corpus contains 1000 PDFs (~100 MB total) used to benchmark and validate the grep feature's performance and correctness.

Structure

tests/fixtures/grep-corpus/
├── corpus/              # Actual PDF files
├── manifest.csv         # File metadata and expected match counts
├── regenerate.sh        # Script to rebuild the corpus
└── README.md            # This file

Usage

Running the benchmark

cargo bench --bench grep_1000

Regenerating the corpus

cd tests/fixtures/grep-corpus
./regenerate.sh

Corpus Requirements

The corpus must satisfy:

  • Size: 1000 PDF files, ~100 MB total
  • Content: Mix of vector and scanned PDFs
  • License: Public domain or permissive (CC BY-SA, MIT, etc.)
  • Determinism: Regenerable from source (no manual uploads)

CI Gates

The benchmark enforces these gates on every PR:

  1. Throughput: ≥ 50 MB/s on 4-core CI machine
  2. vs pdfgrep: ≥ 2× faster
  3. vs pdftotext+ripgrep: ≥ 3× faster
  4. Regression: ≤ 10% vs historical main

Status

TODO: Populate corpus (blocks on 7.8.1-7.8.9 grep implementation).

Sources (TODO)

Potential corpus sources:

  • arXiv API (public domain metadata)
  • Wikipedia article exports (CC BY-SA)
  • Synthetic PDFs via pdfjoin

Manifest Format

filename,source_url,page_count,file_size,checksum,license
doc001.pdf,https://example.com/doc001.pdf,10,102400,abc123...,public-domain
doc002.pdf,https://arxiv.org/pdf/1234.5678.pdf,15,98304,def456...,cc-by-4.0
...

Fields

  • filename: Relative path from corpus/ directory (e.g., doc001.pdf)
  • source_url: URL where the PDF was downloaded from
  • page_count: Number of pages in the PDF
  • file_size: File size in bytes
  • checksum: SHA256 hash of the file contents (for integrity verification)
  • license: License identifier:
    • public-domain: Public domain
    • cc-by-4.0: Creative Commons Attribution 4.0
    • cc-by-sa-4.0: Creative Commons Attribution-ShareAlike 4.0
    • mit: MIT License
    • other: Other permissive license (document in source_url comments)