benhoyt

# NOTES
"before" is Go version go1.19-dd97871282, before the switch jump tables commits
"after" is Go version go1.19-78bea702cd, after the switch jump tables commits


# GOAWK'S GO MICROBENCHMARKS
$ benchstat -sort=delta -geomean benchmarks_before.txt benchmarks_after.txt 
name                    old time/op  new time/op  delta
IncrDecr-8               141ns ± 1%   160ns ± 2%  +13.59%  (p=0.008 n=5+5)
IfStatement-8            147ns ± 1%   157ns ± 2%   +6.59%  (p=0.008 n=5+5)

benhoyt

package main

import (
	"fmt"
	"os"
	"path/filepath"
)

func main() {
	if len(os.Args) != 2 {

benhoyt

"""Calculate the probability of generating a duplicate random number after
generating "n" random numbers in the range "d".

Usage: python birthday_probability.py n [d=365]

Each value can either be an integer directly, or in the format "2**x", where
x is the number of bits in the value.

For example, to calculate the probability that two people will have the same
birthday in a room with 23 people:

benhoyt

BEGIN {
	FS = ","
}

{
	nf = csvify(fields)

	for (i=1; i<=nf; i++) {
		printf "|%s|\n", fields[i]
	}

benhoyt

package main

import (
	"fmt"
	"net/http"
	"strconv"
)

func main() {
	http.HandleFunc("/multiply", func(w http.ResponseWriter, r *http.Request) {

benhoyt

// A little "Connect Four" game

package main

import (
	"bufio"
	"flag"
	"fmt"
	"os"
	"strconv"

benhoyt

package model

import (
	"database/sql"
	"errors"
	"fmt"
	"reflect"
	"sync"
)

benhoyt

"""Efficient sliding-window sorting of time-series data in CSV file.

Demo for http://stackoverflow.com/a/42398981/68707

Tested on Python 3.5.
"""

import collections
import csv
import datetime

benhoyt

import collections, random, sys, textwrap

# Build possibles table indexed by pair of prefix words (w1, w2)
w1 = w2 = ''
possibles = collections.defaultdict(list)
for line in sys.stdin:
    for word in line.split():
        possibles[w1, w2].append(word)
        w1, w2 = w2, word

benhoyt

"""Speed up os.walk() significantly by using file attributes that
FindFirst/Next give us instead of doing an extra stat(). Can also do the same
thing with opendir/readdir on Linux.

This is doubly useful when the user (caller of os.walk) is doing *another*
stat() to get say the file sizes.

On my tests (Windows 64-bit) our walk() is about 5x as fast as os.walk() for
large directory trees, and 9x as fast if you're doing the file size thing.
Note that these timings are "once it's in the cache", not first-time timings.