nojson 0.3.11

A flexible Rust JSON library with no dependencies, no macros, no unsafe and optional no_std support
Documentation 
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name: Benchmark

on:
  workflow_dispatch:
    inputs:
      repeats:
        description: 'BENCH_REPEATS value passed to the benchmark example (best-of reported)'
        default: '30'
        type: string

jobs:
  bench:
    name: ${{ matrix.os }}
    runs-on: ${{ matrix.os }}
    strategy:
      fail-fast: false
      matrix:
        os: [ubuntu-latest, macos-latest]
    steps:
      - name: Checkout sources
        uses: actions/checkout@v6

      - name: Install stable toolchain
        run: |
          rustup update stable
          rustup default stable

      - name: Environment info
        run: |
          echo "=== Runner ==="
          echo "RUNNER_OS=$RUNNER_OS"
          echo "RUNNER_ARCH=$RUNNER_ARCH"
          uname -smr
          echo
          echo "=== rustc ==="
          rustc --version
          echo
          echo "=== CPU ==="
          if [ "$RUNNER_OS" = "Linux" ]; then
            lscpu
          elif [ "$RUNNER_OS" = "macOS" ]; then
            echo "brand: $(sysctl -n machdep.cpu.brand_string)"
            echo "physical cores: $(sysctl -n hw.physicalcpu)"
            echo "logical cores: $(sysctl -n hw.logicalcpu)"
          fi
          echo
          echo "=== Memory ==="
          if [ "$RUNNER_OS" = "Linux" ]; then
            free -h
          elif [ "$RUNNER_OS" = "macOS" ]; then
            mem_bytes=$(sysctl -n hw.memsize)
            mem_gib=$(awk "BEGIN {printf \"%.1f\", $mem_bytes / 1024 / 1024 / 1024}")
            echo "hw.memsize: $mem_bytes bytes (~${mem_gib} GiB)"
          fi

      - name: Run benchmark
        # ubuntu-latest runners use a mix of CPU generations (Skylake /
        # Cascade Lake / Ice Lake / Sapphire Rapids — different Azure VM
        # SKUs). Performance can vary up to ~10-15% between generations,
        # which can swamp small optimizations and look like uniform
        # regressions/wins across unrelated cases. When aggregating
        # multiple runs (e.g., A/B comparing two branches), grep the
        # `cpu:` line from each artifact's bench.txt and group runs by
        # CPU model before computing best-of-N. macos-latest runners are
        # M1, so they're consistent and don't need this treatment.
        env:
          BENCH_REPEATS: ${{ inputs.repeats }}
        run: |
          if [ "$RUNNER_OS" = "Linux" ]; then
            cpu=$(lscpu | awk -F': +' '/^Model name/ {print $2; exit}')
          else
            cpu=$(sysctl -n machdep.cpu.brand_string)
          fi
          {
            echo "cpu: $cpu"
            echo "os: $RUNNER_OS $RUNNER_ARCH"
            echo "rustc: $(rustc --version)"
            echo
            cargo run --release --example benchmark
          } | tee bench.txt

      - name: Upload results
        uses: actions/upload-artifact@v4
        with:
          name: bench-${{ matrix.os }}
          path: bench.txt