russell@unturf.com
33cc466b3a
vagrant-0001: bundler.rb plugin loader runs Array#include? against plugins.keys / system_plugins inside per-spec loops. O(S*P) per vagrant command. Fix: hoist Set.new outside the loop, O(1) per spec lookup. Bench: 127x at S=2000 P=1000. wave5-cicd-iac-survey.md: documents 32 projects scanned across deployment (Spinnaker, fluxcd, Argo Rollouts/Events), modern CI/CD (Earthly, Dagger, Buck2), container runtime (containerd, crun, skopeo, ko, kaniko, buildah), local k8s (kind, minikube, k3s), IaC + testing (Packer, Vagrant, ansible-lint, Molecule, InSpec, Terratest), contract/mutation testing (Pact, Stryker, mutmut, PIT), security (Semgrep, Bandit, gosec), Java quality (Spotbugs, Checkstyle, chart-testing). Clean-scan honor roll +4: chart-testing, kind, ko, pact-ruby.
55 lines
1.7 KiB
Python
55 lines
1.7 KiB
Python
#!/usr/bin/env python3
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# bench-vagrant-0001.py
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# Bundler plugin loader: plugins.keys.include?(spec.name) inside a per-spec
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# loop. O(S*P) for S resolved specs and P plugins. Fix: hoist Set, O(1)
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# per spec.
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import sys
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import time
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def bench_defective(s_specs, p_plugins):
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plugin_keys = [f"plugin_{i:03d}" for i in range(p_plugins)]
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specs = [f"plugin_{(i * 7) % p_plugins:03d}" for i in range(s_specs)]
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t0 = time.perf_counter()
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matched = []
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for spec in specs:
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# Ruby Array#include? = Python list __contains__ = O(P)
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if spec in plugin_keys:
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matched.append(spec)
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return time.perf_counter() - t0
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def bench_fixed(s_specs, p_plugins):
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plugin_keys = [f"plugin_{i:03d}" for i in range(p_plugins)]
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specs = [f"plugin_{(i * 7) % p_plugins:03d}" for i in range(s_specs)]
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t0 = time.perf_counter()
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plugin_set = set(plugin_keys)
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matched = []
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for spec in specs:
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if spec in plugin_set: # Set#include? = O(1)
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matched.append(spec)
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return time.perf_counter() - t0
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TRIALS = 3
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CASES = [(50, 50), (200, 100), (500, 200), (1000, 500), (2000, 1000)]
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def run():
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lines = []
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header = "=== vagrant-0001: Bundler plugin Array#include? vs Set#include? ==="
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print(header); lines.append(header)
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for s, p in CASES:
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df = min(bench_defective(s, p) for _ in range(TRIALS))
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fx = min(bench_fixed(s, p) for _ in range(TRIALS))
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speedup = (df / fx) if fx > 0 else float("inf")
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line = f"S={s:<5} P={p:<5}: defective={df*1000:.3f}ms fixed={fx*1000:.3f}ms speedup={speedup:.1f}x"
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print(line); lines.append(line); sys.stdout.flush()
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return lines
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if __name__ == "__main__":
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run()
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