hyperfine أوامر

hyperfine هي أداة قياس أداء سطر الأوامر مكتوبة بلغة Rust. توفر تحليلاً إحصائياً لأوقات تنفيذ الأوامر، وتتعامل مع تشغيلات الإحماء، وتدعم اختبارات الأداء ذات المعاملات، وتصدّر النتائج بصيغ متعددة.

التثبيت

Linux/Ubuntu

# Ubuntu/Debian
sudo apt install hyperfine

# Fedora
sudo dnf install hyperfine

# Arch Linux
sudo pacman -S hyperfine

# Cargo (Rust)
cargo install hyperfine

# From GitHub releases
wget https://github.com/sharkdp/hyperfine/releases/latest/download/hyperfine_1.19.0_amd64.deb
sudo dpkg -i hyperfine_1.19.0_amd64.deb

# Verify
hyperfine --version

قياس الأداء الأساسي

# Benchmark a single command
hyperfine 'sleep 0.5'

# Benchmark with a specific number of runs
hyperfine --runs 20 'my_command'

# Benchmark with minimum number of runs
hyperfine --min-runs 50 'my_command'

# Set minimum benchmark time (seconds)
hyperfine --min-benchmarking-time 10 'my_command'

مقارنة الأوامر

# Compare two commands
hyperfine 'find . -name "*.py"' 'fd -e py'

# Compare multiple commands
hyperfine 'grep -r TODO .' 'rg TODO' 'ag TODO'

# Compare with readable labels
hyperfine --command-name 'GNU grep' 'grep -r TODO .' \
          --command-name 'ripgrep' 'rg TODO' \
          --command-name 'silver searcher' 'ag TODO'

# Compare sorting implementations
hyperfine 'sort large_file.txt' 'sort --parallel=4 large_file.txt'

# Compare different compilers
hyperfine 'gcc -O2 -o test test.c && ./test' \
          'clang -O2 -o test test.c && ./test'

تشغيلات الإحماء

# Run warmup iterations before benchmarking (populates caches)
hyperfine --warmup 5 'cat large_file.txt | wc -l'

# Warmup is essential for:
# - Filesystem cache warming
# - JIT compilation warmup
# - DNS cache population
hyperfine --warmup 10 'curl -s http://localhost:8080/api/data > /dev/null'

# Prepare command (run before each benchmark, not timed)
hyperfine --prepare 'sync; echo 3 | sudo tee /proc/sys/vm/drop_caches' \
          'cat large_file.txt | wc -l'

الإعداد والتنظيف

# Run a setup command before the benchmark suite
hyperfine --setup 'make build' './my_program'

# Run a prepare command before EACH iteration (not timed)
hyperfine --prepare 'cp original.txt test.txt' 'sort -o test.txt test.txt'

# Run a cleanup command after each iteration
hyperfine --cleanup 'rm -f output.txt' 'my_command > output.txt'

# Combine setup, prepare, and cleanup
hyperfine \
  --setup 'gcc -O2 -o benchmark benchmark.c' \
  --prepare 'echo 3 | sudo tee /proc/sys/vm/drop_caches > /dev/null' \
  --cleanup 'rm -f /tmp/bench_output' \
  './benchmark > /tmp/bench_output'

قوائم المعاملات

# Benchmark with a range of parameter values
hyperfine --parameter-scan threads 1 8 './my_program --threads {threads}'

# Parameter scan with step size
hyperfine --parameter-scan size 100 1000 --parameter-step-size 100 \
          './process --size {size}'

# Parameter list (explicit values)
hyperfine --parameter-list lang 'python3,node,ruby' '{lang} script.{lang}'

# Multiple parameter lists
hyperfine --parameter-list compiler 'gcc,clang' \
          --parameter-list opt '0,1,2,3' \
          '{compiler} -O{opt} -o test test.c && ./test'

# Benchmark different file sizes
hyperfine --parameter-list size 'small,medium,large' \
          --prepare 'cp data_{size}.csv input.csv' \
          './process input.csv'

صيغ التصدير

# Export as JSON (most detailed)
hyperfine --export-json results.json 'my_command'

# Export as CSV
hyperfine --export-csv results.csv 'my_command'

# Export as Markdown table
hyperfine --export-markdown results.md 'command1' 'command2'

# Export as AsciiDoc
hyperfine --export-asciidoc results.adoc 'command1' 'command2'

# Export all formats at once
hyperfine \
  --export-json results.json \
  --export-csv results.csv \
  --export-markdown results.md \
  'command1' 'command2'

# The JSON output includes:
# - Mean, median, min, max times
# - Standard deviation
# - Individual run times
# - Parameter values (if used)

التحليل الإحصائي

# Show statistical outlier detection
hyperfine 'my_command'
# Output shows: mean, min, max, and flags outliers

# Increase precision with more runs
hyperfine --runs 100 'my_command'

# Ignore the first N runs as outliers
hyperfine --ignore-failure 'my_command'

# Show individual run times
hyperfine --show-output 'my_command'

# Time the shell startup overhead
hyperfine --shell=none 'my_command'

# Use a specific shell
hyperfine --shell /bin/bash 'my_command'
hyperfine --shell /bin/zsh 'my_command'

# No shell (direct execution — avoids shell overhead)
hyperfine -N './my_binary arg1 arg2'

التحكم في المخرجات

# Show command output (don't suppress stdout/stderr)
hyperfine --show-output 'echo hello'

# Style options
hyperfine --style full 'my_command'      # Full progress bar (default)
hyperfine --style basic 'my_command'     # Simple text output
hyperfine --style nocolor 'my_command'   # No ANSI colors
hyperfine --style color 'my_command'     # Colored output
hyperfine --style none 'my_command'      # Minimal output

# Sort results by mean time
hyperfine --sort mean-time 'cmd1' 'cmd2' 'cmd3'

# Sort by command name
hyperfine --sort command 'cmd1' 'cmd2' 'cmd3'

أمثلة عملية

# Compare JSON parsers
hyperfine --warmup 3 \
  'python3 -c "import json; json.load(open(\"data.json\"))"' \
  'python3 -c "import orjson; orjson.loads(open(\"data.json\",\"rb\").read())"'

# Benchmark database queries
hyperfine --warmup 2 --runs 30 \
  'psql -c "SELECT count(*) FROM users" mydb' \
  'psql -c "SELECT count(*) FROM users WHERE active = true" mydb'

# Compare file compression
hyperfine --warmup 1 --prepare 'cp original.tar test.tar' \
  'gzip test.tar' \
  --prepare 'cp original.tar test.tar' \
  'zstd test.tar' \
  --prepare 'cp original.tar test.tar' \
  'lz4 test.tar'

# Benchmark Docker build cache
hyperfine --warmup 1 --runs 5 \
  'docker build -t test .'

# Compare regex engines
hyperfine \
  "grep -cP '\d{3}-\d{3}-\d{4}' large_log.txt" \
  "rg -c '\d{3}-\d{3}-\d{4}' large_log.txt"

# Benchmark HTTP endpoints
hyperfine --warmup 5 \
  'curl -s http://localhost:8080/api/v1/users > /dev/null' \
  'curl -s http://localhost:8080/api/v2/users > /dev/null'

# Test I/O performance with cold cache
hyperfine \
  --prepare 'sync; echo 3 | sudo tee /proc/sys/vm/drop_caches > /dev/null' \
  'cat /path/to/large/file > /dev/null'

تفسير النتائج

# Example output:
# Benchmark 1: fd -e py
#   Time (mean +/- sigma):     12.3 ms +/-  1.2 ms    [User: 8.1 ms, System: 4.0 ms]
#   Range (min ... max):       10.5 ms ... 16.8 ms    50 runs
#
# - mean: average execution time
# - sigma: standard deviation (lower = more consistent)
# - User: CPU time in user mode
# - System: CPU time in kernel mode
# - Range: fastest and slowest runs
# - "X runs" were performed for statistical significance
#
# Summary:
#   fd -e py ran 12.45 +/- 3.21 times faster than find . -name "*.py"

مرجع سريع

Flag	Purpose
--runs N	Set exact number of benchmark runs
--warmup N	Warmup runs before measuring
--prepare CMD	Run before each benchmark iteration
--cleanup CMD	Run after each benchmark iteration
--setup CMD	Run once before the entire suite
--parameter-scan	Iterate over a numeric range
--parameter-list	Iterate over explicit values
--export-json	Export detailed JSON results
--export-csv	Export CSV results
--export-markdown	Export Markdown table
--command-name	Label for display
-N / --shell=none	Skip shell, run binary directly
--show-output	Don’t suppress stdout/stderr
--ignore-failure	Continue on non-zero exit codes