Skip to main content

YAML-driven benchmark sweeps: generate env-file combinations, execute a tool across each, and query DuckDB-backed aggregate stats.

Project description

abench-speckz

Generate Docker env-file combinations from a YAML benchmark spec, execute a benchmark tool across every combination, and query the results.

Install

Requires Python 3.10+.

python -m venv .venv && source .venv/bin/activate
pip install -e '.[dev]'

Note on examples: files under examples/ reference paths like python examples/sample_bench.py. Those paths are relative to the repo root, so the examples run only from a checkout — not from an arbitrary working directory after pip install. Clone the repo and cd into it to follow the examples verbatim.

Workflow

spec.yaml  →  abench-speckz gen  →  out/ (env-files + manifest.json)
                                    ↓
              abench-speckz run  →  results/ (runs.jsonl + aggregates.jsonl)
                                    ↓
              abench-speckz stats →  table / JSON / TSV

Commands

gen — generate env-file combinations

abench-speckz gen spec.yaml --out out/           # write env-files
abench-speckz gen spec.yaml --dry-run            # print summary table
abench-speckz gen spec.yaml --list               # print TSV
abench-speckz gen spec.yaml --profile smoke --out out/
abench-speckz gen spec.yaml --tag stress --out out/
abench-speckz gen spec.yaml --exclude-tag slow --out out/

Each combination is written as a Docker env-file (KEY=value per line). A manifest.json in the output directory maps each filename back to its full variable assignment and tags.

run — execute a tool across every combination

abench-speckz run out/ --tool oha.tool.yaml
abench-speckz run out/ --tool oha.tool.yaml --repeat 5 --warmup 1
abench-speckz run out/ --tool oha.tool.yaml --filter workload=read
abench-speckz run out/ --tool oha.tool.yaml --filter-tag stress
abench-speckz run out/ --tool oha.tool.yaml --filter-exclude-tag slow
abench-speckz run out/ --tool oha.tool.yaml --skip-existing --keep-raw
abench-speckz run out/ --tool oha.tool.yaml --dry-run   # print planned commands

Results are written to results/ (configurable with --results).

stats — aggregate and display results

abench-speckz stats results/
abench-speckz stats results/ --group-by workload --group-by concurrency
abench-speckz stats results/ --metric requests_per_sec --metric p50_ms
abench-speckz stats results/ --where workload=read
abench-speckz stats results/ --filter-tag stress
abench-speckz stats results/ --filter-exclude-tag slow
abench-speckz stats results/ --format json
abench-speckz stats results/ --format tsv
abench-speckz stats results/ --pretty            # use display names from tool YAML
abench-speckz stats results/ --from-raw          # recompute from runs.jsonl
abench-speckz stats results/ --report report.html              # self-contained Chart.js HTML
abench-speckz stats results/ --report report.html --plots plots.yaml  # override tool YAML plots

--report writes a self-contained HTML file with Chart.js plots. Plot definitions come from the tool YAML's plots: list (see below), or from a separate YAML file via --plots. When no plots are defined, a default per-metric bar chart is rendered.

rebuild-aggregates — regenerate aggregates from raw runs

abench-speckz rebuild-aggregates results/

Spec format

static:
  IMAGE: myapp:latest
  REGION: us-east-1

variables:
  workload:    [read, write, mixed]
  concurrency: [1, 8, 64]
  backend:     [postgres, mysql]

# conditional overrides and tagging
when:
  - if:  { workload: write, backend: mysql }
    set: { LOCK_TIMEOUT: "30s" }
    tag: [slow, write-heavy]
  - if:  { concurrency: 64 }
    set: { THREAD_POOL: "${concurrency}" }
    tag: [stress]

# combos to drop entirely
exclude:
  - { backend: mysql, concurrency: 1 }

# tags applied to every combo
tags: [bench]

profiles:
  smoke:
    variables:
      concurrency: [1]
      workload: [read]
  full: {}

default_profile: smoke

Interpolation: use ${var} to reference other variables and ${env:VAR} to read from the process environment. Use $$ for a literal $.

Profiles overlay the base spec — variables, static, when, and exclude lists are merged. The default_profile is used when --profile is not specified.

Tool YAML format

name: oha
command: "oha ${URL} -n ${REQUESTS} -c ${concurrency} --json"
timeout_seconds: 300
version_command: "oha --version"

# extract metrics from JSON stdout via JSONPath
capture:
  requests_per_sec: "$.summary.requestsPerSec"
  p50_ms: "$.latencyPercentiles.p50"
  errors[]: "$.errors[*].message"   # trailing [] collects all matches as a list

# alternative: a custom Python parser function
# parser: "mymodule:parse_fn"       # fn(stdout: str) -> dict

# read extraction input from a file the tool writes, instead of stdout
# output_file: "results.json"       # interpolates ${var} / ${env:VAR}
# output_format: jsonl              # "json" (default) or "jsonl" for one JSON object per line

pretty_names:
  requests_per_sec: "Requests/s"
  p50_ms: "p50 latency"
units:
  p50_ms: ms
higher_is_better:
  requests_per_sec: true
  p50_ms: false

# optional: shell steps run around every rep (warmup and measured)
setup:
  - "docker compose up -d redis"
  - "sleep 1"
teardown:
  - "docker compose down -v"
setup_timeout_seconds: 120   # per-step timeout for setup/teardown (default 120)

# optional: declarative plots used by `stats --report`
plots:
  - id: rps_by_workload
    type: bar                        # bar | stacked-bar | line | scatter
    title: "Throughput by workload"
    x: workload
    y: requests_per_sec
  - id: latency_breakdown
    type: stacked-bar
    title: "Latency percentiles"
    x: workload
    y: [p50_ms, p95_ms, p99_ms]
  - id: rps_vs_concurrency
    type: line
    title: "Throughput scaling"
    x: concurrency
    y: requests_per_sec
    group_by: workload

Setup / teardown. Each rep is wrapped setup → command → teardown. Teardown runs in a finally block, so it also fires on benchmark failure or Ctrl-C. Combo vars (${var}) and ${env:VAR} interpolate in setup/teardown commands. Steps are split with shlex.split and executed without a shell, so chain via multiple list entries rather than &&.

  • Setup failure → the command is skipped, teardown still runs best-effort, and failure_reason is recorded as setup[i]: ….
  • Teardown failure → the benchmark's exit_code and metrics are preserved, but teardown[i]: … is appended to failure_reason (so the run is counted as failed).

Sweep-scoped setup / teardown. setup_per_sweep and teardown_per_sweep run outside the per-rep loop, useful for expensive prep like seeding a database. By default each fires exactly once for the whole sweep. Set per_sweep_var: <name> to scope each fire to a single variable: combos are stably grouped by that variable's value, and the phases fire once per distinct value (around the reps for that group).

setup_per_sweep:    ["seed-db.sh"]              # fires once before any rep
teardown_per_sweep: ["drop-db.sh"]
per_sweep_var:      workload                    # optional; one var only
  • Without per_sweep_var: only ${env:VAR} can be referenced; any ${combo_var} rejected at sweep start.
  • With per_sweep_var: X: only ${X} and ${env:VAR} can be referenced; the current group's value of X is substituted.
  • --skip-existing: if every rep in a group is already recorded, both phases are skipped for that group.
  • Setup failure: all planned reps in that group get a failure row with failure_reason="per_sweep_setup[i]: …"; teardown still runs best-effort. Next group proceeds.
  • Teardown failure: appended to the last rep row in the group's failure_reason.
  • Raw record: raw/sweep.json (Mode A) or raw/sweep-{slug(value)}.json (Mode B) — same shape as per-rep raw files.

Raw output records. When a raw record is written, raw/{run_id}.json is a JSON object with:

  • stdout, stderr — the tool's own streams (always present).
  • output_file{path, content} when output_file is configured in the tool YAML, so the tool's stdout/stderr stay separate from the file content used for extraction.
  • setup, teardown — one entry per step that ran, each with command, exit_code, stdout, stderr.

Results directory layout

results/
  runs.jsonl              # append-only log, one JSON object per run
  aggregates.jsonl        # per-combo stats (n, mean, stddev, p50/95/99, CI95)
  manifest.snapshot.json  # copy of the manifest used
  tools/{name}.yaml       # copy of the tool YAML used
  env.snapshot.json       # host info (OS, CPU, git SHA)
  pretty_names.json       # merged metric display names
  raw/{run_id}.json       # structured raw record (see below); written with
                          # --keep-raw, on extract failure, on tool failure,
                          # or when setup/teardown failed
  raw/sweep[-{slug}].json # per_sweep setup/teardown records; written on
                          # --keep-raw or any per_sweep phase failure

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

abench_speckz-0.2.0.tar.gz (51.1 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

abench_speckz-0.2.0-py3-none-any.whl (39.9 kB view details)

Uploaded Python 3

File details

Details for the file abench_speckz-0.2.0.tar.gz.

File metadata

  • Download URL: abench_speckz-0.2.0.tar.gz
  • Upload date:
  • Size: 51.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.12.12

File hashes

Hashes for abench_speckz-0.2.0.tar.gz
Algorithm Hash digest
SHA256 b1ee7185c3ee1c7f69f9d459fbc3c1d5f38d51bce7b0d70adacf5d9961f6e77c
MD5 87478340ca07e215c67c4d17c3002c42
BLAKE2b-256 42aa23d3da404a0bad9bc5e7d12468bae7eb6c5b1cf78d2e3730fce4a6cde813

See more details on using hashes here.

File details

Details for the file abench_speckz-0.2.0-py3-none-any.whl.

File metadata

  • Download URL: abench_speckz-0.2.0-py3-none-any.whl
  • Upload date:
  • Size: 39.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.12.12

File hashes

Hashes for abench_speckz-0.2.0-py3-none-any.whl
Algorithm Hash digest
SHA256 3a79ecfe220ce28d3878893a2a04f7e91c02716ccb25ba45033f1b6ce572301f
MD5 26fe6e59dd14d86ae242c65aa92b6c4d
BLAKE2b-256 26d58795b0c64599c55c9575085a0fd1dd08c18ded79b613adc3f8e15310e6b2

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page