feat(ci): add a manual public benchmark workflow - #197
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benchmarks/public_benchmark.py runs the two existing harnesses in subprocesses - bench_report.py (CSV ingest, profile, null-fill, import time, peak memory; balanced vs aggressive) and bench.py run/report (the per-fixture table) - and writes one shareable public-benchmark.md/.json stamped with the freshdata version, commit, CPU/RAM and package versions. `--scale ci` (default) keeps the scaling cases inside a hosted runner; `--scale full` uses the harness defaults. .github/workflows/public-benchmark.yml is workflow_dispatch only (scale and repeat inputs), installs from constraints/ci.txt, appends the report to the job summary and uploads it as public-benchmark-<run id>. It never runs on push or pull requests. docs/benchmarks.md explains how to refresh.
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FreshData benchmark report —
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| fixture | n_rows | n_cols | p50 s | p95 s | peak MB | repair % | false-repair % | preserve % | trust | monotonic | export % |
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Authored-code reduction (Metric 6)
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Closes #4.
Summary
#4 asked for a manually triggered workflow whose artifact holds the benchmark table and the freshdata version, and that never blocks CI. The script it named (
benchmarks/public_benchmark.py) didn't exist, and the "Strategic-report scaling benchmarks" table indocs/benchmarks.mdstill reads not yet measured.benchmarks/public_benchmark.pyA thin orchestrator with no new measurement code. It runs the existing harnesses in subprocesses:
benchmarks/bench_report.py allcovers the scaling cases (CSV ingest + clean, mixed-schema profile, null-fill, import time, peak memory), balanced vs aggressive.benchmarks/bench.py run --repeat N+reportproduces the per-fixture speed/quality table.It writes
public-benchmark.mdandpublic-benchmark.json, stamped with the freshdata version, commit, CPU count and RAM, Python and platform, and pandas/numpy/pyarrow/polars/duckdb versions.Flags:
--scale ci(default: 50 MB CSV, 1M rows), sized for a 2-core / 7 GB hosted runner--scale full(harness defaults, incl. 10M-row null-fill)--csv-mb,--rows,--repeat,--size,--skip-scaling,--skip-fixtures,--output-dir.github/workflows/public-benchmark.ymlworkflow_dispatchonly, withscale(ci/full) andrepeatinputs. It never runs on push or pull requests, so it can't block CI.-c constraints/ci.txt. Actions are SHA-pinned,contents: read, 120-minute timeout.public-benchmark-<run id>(md, json,report_bench.json).docs/benchmarks.mdgains a short "Refreshing the public numbers" section.Verification
tests/benchmark/test_public_benchmark.py(8 tests):ci/full,--skip-scaling, both-skipped error)workflow_dispatchonly, uploads an artifactruff checkclean; the workflow parses as YAML.python benchmarks/public_benchmark.py --csv-mb 1 --rows 20000 --repeat 1 --size 2000completed in about 18s. It rendered all five scaling rows and six fixture rows under the freshdata 2.0.0 / commit / hardware header, and wrote nothing outside the git-ignoredbenchmarks/results/.Once this merges, run
gh workflow run public-benchmark.ymlfor the first hosted numbers.