module main import os import flag import time import term import math import scripting struct CmdResult { mut: runs int cmd string icmd int outputs []string oms map[string][]int summary map[string]Aints timings []int atiming Aints } struct Context { mut: count int series int warmup int show_help bool show_output bool use_newline bool // use \n instead of \r, so the last line is not overwritten fail_on_regress_percent int fail_on_maxtime int // in ms verbose bool commands []string results []CmdResult cmd_template string // {T} will be substituted with the current command cmd_params map[string][]string cline string // a terminal clearing line cgoback string nmins int // number of minimums to discard nmaxs int // number of maximums to discard } [unsafe] fn (mut result CmdResult) free() { unsafe { result.cmd.free() result.outputs.free() result.oms.free() result.summary.free() result.timings.free() result.atiming.free() } } [unsafe] fn (mut context Context) free() { unsafe { context.commands.free() context.results.free() context.cmd_template.free() context.cmd_params.free() context.cline.free() context.cgoback.free() } } struct Aints { values []int mut: imin int imax int average f64 stddev f64 nmins int // number of discarded fastest results nmaxs int // number of discarded slowest results } [unsafe] fn (mut a Aints) free() { unsafe { a.values.free() } } fn new_aints(ovals []int, extreme_mins int, extreme_maxs int) Aints { mut res := Aints{ values: ovals // remember the original values nmins: extreme_mins nmaxs: extreme_maxs } mut sum := i64(0) mut imin := math.max_i32 mut imax := -math.max_i32 // discard the extremes: mut vals := []int{} for x in ovals { vals << x } vals.sort() if vals.len > extreme_mins + extreme_maxs { vals = vals[extreme_mins..vals.len - extreme_maxs].clone() } else { vals = [] } // statistical processing of the remaining values: for i in vals { sum += i if i < imin { imin = i } if i > imax { imax = i } } res.imin = imin res.imax = imax if vals.len > 0 { res.average = sum / f64(vals.len) } // mut devsum := f64(0.0) for i in vals { x := f64(i) - res.average devsum += (x * x) } res.stddev = math.sqrt(devsum / f64(vals.len)) // eprintln('\novals: $ovals\n vals: $vals\n vals.len: $vals.len | res.imin: $res.imin | res.imax: $res.imax | res.average: $res.average | res.stddev: $res.stddev') return res } fn bold(s string) string { return term.colorize(term.bold, s) } fn (a Aints) str() string { return bold('${a.average:6.2f}') + 'ms ± σ: ${a.stddev:4.1f}ms, min: ${a.imin:4}ms, max: ${a.imax:4}ms, runs:${a.values.len:3}, nmins:${a.nmins:2}, nmaxs:${a.nmaxs:2}' } const ( max_fail_percent = 100 * 1000 max_time = 60 * 1000 // ms performance_regression_label = 'Performance regression detected, failing since ' ) fn main() { mut context := Context{} context.parse_options()! context.run() context.show_diff_summary() } fn (mut context Context) parse_options() ! { mut fp := flag.new_flag_parser(os.args) fp.application(os.file_name(os.executable())) fp.version('0.0.1') fp.description('Repeat command(s) and collect statistics. Note: you have to quote each command, if it contains spaces.') fp.arguments_description('CMD1 CMD2 ...') fp.skip_executable() fp.limit_free_args_to_at_least(1)! context.count = fp.int('count', `c`, 10, 'Repetition count.') context.series = fp.int('series', `s`, 2, 'Series count. `-s 2 -c 4 a b` => aaaabbbbaaaabbbb, while `-s 3 -c 2 a b` => aabbaabbaabb.') context.warmup = fp.int('warmup', `w`, 2, 'Warmup runs. These are done *only at the start*, and are ignored.') context.show_help = fp.bool('help', `h`, false, 'Show this help screen.') context.use_newline = fp.bool('newline', `n`, false, 'Use \\n, do not overwrite the last line. Produces more output, but easier to diagnose.') context.show_output = fp.bool('output', `O`, false, 'Show command stdout/stderr in the progress indicator for each command. Note: slower, for verbose commands.') context.verbose = fp.bool('verbose', `v`, false, 'Be more verbose.') context.fail_on_maxtime = fp.int('max_time', `m`, max_time, 'Fail with exit code 2, when first cmd takes above M milliseconds (regression).') context.fail_on_regress_percent = fp.int('fail_percent', `f`, max_fail_percent, 'Fail with exit code 3, when first cmd is X% slower than the rest (regression).') context.cmd_template = fp.string('template', `t`, r'{T}', r'Command template. {T} will be substituted with the current command.') cmd_params := fp.string_multi('parameter', `p`, r'A parameter substitution list. `{p}=val1,val2,val2` means that {p} in the template, will be substituted with each of val1, val2, val3.') context.nmins = fp.int('nmins', `i`, 0, 'Ignore the BOTTOM X results (minimum execution time). Makes the results more robust to performance flukes.') context.nmaxs = fp.int('nmaxs', `a`, 1, 'Ignore the TOP X results (maximum execution time). Makes the results more robust to performance flukes.') for p in cmd_params { parts := p.split(':') if parts.len > 1 { context.cmd_params[parts[0]] = parts[1].split(',') } } if context.show_help { println(fp.usage()) exit(0) } if context.verbose { scripting.set_verbose(true) } commands := fp.finalize() or { eprintln('Error: $err') exit(1) } context.commands = context.expand_all_commands(commands) context.results = []CmdResult{len: context.commands.len, cap: 20, init: CmdResult{ outputs: []string{cap: 500} timings: []int{cap: 500} }} if context.use_newline { context.cline = '\n' context.cgoback = '\n' } else { context.cline = '\r' + term.h_divider('') context.cgoback = '\r' } } fn flushed_print(s string) { print(s) flush_stdout() } fn (mut context Context) clear_line() { flushed_print(context.cline) } fn (mut context Context) expand_all_commands(commands []string) []string { mut all_commands := []string{} for cmd in commands { maincmd := context.cmd_template.replace(r'{T}', cmd) mut substituted_commands := []string{} substituted_commands << maincmd for paramk, paramlist in context.cmd_params { for paramv in paramlist { mut new_substituted_commands := []string{} for cscmd in substituted_commands { scmd := cscmd.replace(paramk, paramv) new_substituted_commands << scmd } for sc in new_substituted_commands { substituted_commands << sc } } } for sc in substituted_commands { all_commands << sc } } mut unique := map[string]int{} for x in all_commands { if x.contains('{') && x.contains('}') { continue } unique[x] = 1 } return unique.keys() } fn (mut context Context) run() { mut run_warmups := 0 for si in 1 .. context.series + 1 { for icmd, cmd in context.commands { mut runs := 0 mut duration := 0 mut sum := 0 mut oldres := '' println('Series: ${si:4}/${context.series:-4}, command: $cmd') if context.warmup > 0 && run_warmups < context.commands.len { for i in 1 .. context.warmup + 1 { flushed_print('${context.cgoback}warming up run: ${i:4}/${context.warmup:-4} for ${cmd:-50s} took ${duration:6} ms ...') mut sw := time.new_stopwatch() res := os.execute(cmd) if res.exit_code != 0 { continue } duration = int(sw.elapsed().milliseconds()) } run_warmups++ } context.clear_line() for i in 1 .. (context.count + 1) { avg := f64(sum) / f64(i) flushed_print('${context.cgoback}Average: ${avg:9.3f}ms | run: ${i:4}/${context.count:-4} | took ${duration:6} ms') if context.show_output { flushed_print(' | result: ${oldres:s}') } mut sw := time.new_stopwatch() res := scripting.exec(cmd) or { continue } duration = int(sw.elapsed().milliseconds()) if res.exit_code != 0 { eprintln('${i:10} non 0 exit code for cmd: $cmd') continue } trimed_output := res.output.trim_right('\r\n') trimed_normalized := trimed_output.replace('\r\n', '\n') lines := trimed_normalized.split('\n') for line in lines { context.results[icmd].outputs << line } context.results[icmd].timings << duration sum += duration runs++ oldres = res.output.replace('\n', ' ') } context.results[icmd].cmd = cmd context.results[icmd].icmd = icmd context.results[icmd].runs += runs context.results[icmd].atiming = new_aints(context.results[icmd].timings, context.nmins, context.nmaxs) context.clear_line() flushed_print(context.cgoback) mut m := map[string][]int{} ioutputs := context.results[icmd].outputs for o in ioutputs { x := o.split(':') if x.len > 1 { k := x[0] v := x[1].trim_left(' ').int() m[k] << v } } mut summary := map[string]Aints{} for k, v in m { // show a temporary summary for the current series/cmd cycle s := new_aints(v, context.nmins, context.nmaxs) println(' $k: $s') summary[k] = s } // merge current raw results to the previous ones old_oms := context.results[icmd].oms.move() mut new_oms := map[string][]int{} for k, v in m { if old_oms[k].len == 0 { new_oms[k] = v } else { new_oms[k] << old_oms[k] new_oms[k] << v } } context.results[icmd].oms = new_oms.move() // println('') } } // create full summaries, taking account of all runs for icmd in 0 .. context.results.len { mut new_full_summary := map[string]Aints{} for k, v in context.results[icmd].oms { new_full_summary[k] = new_aints(v, context.nmins, context.nmaxs) } context.results[icmd].summary = new_full_summary.move() } } fn (mut context Context) show_diff_summary() { context.results.sort_with_compare(fn (a &CmdResult, b &CmdResult) int { if a.atiming.average < b.atiming.average { return -1 } if a.atiming.average > b.atiming.average { return 1 } return 0 }) println('Summary (commands are ordered by ascending mean time), after $context.series series of $context.count repetitions:') base := context.results[0].atiming.average mut first_cmd_percentage := f64(100.0) mut first_marker := '' for i, r in context.results { first_marker = ' ' cpercent := (r.atiming.average / base) * 100 - 100 if r.icmd == 0 { first_marker = bold('>') first_cmd_percentage = cpercent } println(' $first_marker${(i + 1):3} | ${cpercent:5.1f}% slower | ${r.cmd:-57s} | $r.atiming') } $if debugcontext ? { println('context: $context') } if int(base) > context.fail_on_maxtime { flushed_print(performance_regression_label) println('average time: ${base:6.1f} ms > $context.fail_on_maxtime ms threshold.') exit(2) } if context.fail_on_regress_percent == max_fail_percent || context.results.len < 2 { return } fail_threshold_max := f64(context.fail_on_regress_percent) if first_cmd_percentage > fail_threshold_max { flushed_print(performance_regression_label) println('${first_cmd_percentage:5.1f}% > ${fail_threshold_max:5.1f}% threshold.') exit(3) } }