Triples

Counts RDF triples or quads in files using parallel processing. Supports ZIP, GZIP, and uncompressed files. The output dynamically shows “triples” or “quads” based on the RDF format (quads for nquads and trig, triples for json-ld and turtle).

Usage

uv run python -m oc_meta.run.count.triples <DIRECTORY> [OPTIONS]

Options

Option	Default	Description
--pattern	*.nq.gz	Glob pattern for locating files
--format	nquads	RDF format: nquads, json-ld, turtle, trig
--recursive	false	Search subdirectories recursively
--prov-only	false	Count only files in prov subdirectories
--data-only	false	Count only files not in prov subdirectories
--workers	CPU count	Number of parallel workers
--show-per-file	false	Print count for each file
--keep-going	false	Continue processing even if errors occur

Examples

Count quads in gzip-compressed N-Quads files:

uv run python -m oc_meta.run.count.triples /data/rdf --recursive

Count triples in ZIP files containing JSON-LD:

uv run python -m oc_meta.run.count.triples /data/rdf --pattern "*.zip" --format json-ld --recursive

Count only data (exclude provenance):

uv run python -m oc_meta.run.count.triples /data/rdf --recursive --data-only

Count only provenance:

uv run python -m oc_meta.run.count.triples /data/rdf --recursive --prov-only

Show per-file counts with 8 workers:

uv run python -m oc_meta.run.count.triples /data/rdf --recursive --workers 8 --show-per-file

Count uncompressed Turtle files:

uv run python -m oc_meta.run.count.triples /data/rdf --pattern "*.ttl" --format turtle