miku

  ## ngram following http://tidytextmining.com/ngrams.html
    library(dplyr)
    library(tidytext)
    library(tidyr)

    # load manually downloaded web of science data dump
    tt <- jsonlite::stream_in(file("data/wos_total.json"), verbose = FALSE) %>% 
      filter(!is.na(AB))

miku

Install

Either copy the aliases from the .gitconfig or run the commands in add-pr-alias.sh

Usage

Easily checkout local copies of pull requests from remotes:

• git pr 4 - creates local branch pr/4 from the github upstream(if it exists) or origin remote and checks it out
• git pr 4 someremote - creates local branch pr/4 from someremote remote and checks it out

miku

Latency Comparison Numbers
--------------------------
L1 cache reference                           0.5 ns
Branch mispredict                            5   ns
L2 cache reference                           7   ns                      14x L1 cache
Mutex lock/unlock                           25   ns
Main memory reference                      100   ns                      20x L2 cache, 200x L1 cache
Compress 1K bytes with Zippy             3,000   ns        3 us
Send 1K bytes over 1 Gbps network       10,000   ns       10 us
Read 4K randomly from SSD*             150,000   ns      150 us          ~1GB/sec SSD

miku

package main

import (
	"io"
	"log"
	"mime/multipart"
	"net/http"
	"os"
	"path/filepath"
	"runtime"

miku

package main

import (
	"bufio"
	"fmt"
	"io"
	"io/ioutil"
	"log"
	"net/http"
	"sync"

miku

// Pipe creates a synchronous in-memory pipe.
// It can be used to connect code expecting an io.Reader
// with code expecting an io.Writer.
// Reads on one end are matched with writes on the other,
// copying data directly between the two; there is no internal buffering.
// It is safe to call Read and Write in parallel with each other or with
// Close. Close will complete once pending I/O is done. Parallel calls to
// Read, and parallel calls to Write, are also safe:
// the individual calls will be gated sequentially.

miku

# Add field
echo '{"hello": "world"}' | jq --arg foo bar '. + {foo: $foo}'
# {
#   "hello": "world",
#   "foo": "bar"
# }

# Override field value
echo '{"hello": "world"}' | jq --arg foo bar '. + {hello: $foo}'
{

miku

#!/usr/bin/env python
"""
xlsx2tsv  filename.xlsx  [sheet number or name]

Parse a .xlsx (Excel OOXML, which is not OpenOffice) into tab-separated values.
If it has multiple sheets, need to give a sheet number or name.
Outputs honest-to-goodness tsv, no quoting or embedded \\n\\r\\t.

One reason I wrote this is because Mac Excel 2008 export to csv or tsv messes
up encodings, converting everything to something that's not utf8 (macroman

miku

# Greatest common divisor of more than 2 numbers.  Am I terrible for doing it this way?

def gcd(*numbers):
    """Return the greatest common divisor of the given integers"""
    from fractions import gcd
    return reduce(gcd, numbers)

# Least common multiple is not in standard libraries? It's in gmpy, but this is simple enough:

def lcm(*numbers):

miku

OS X Screencast to animated GIF

This gist shows how to create a GIF screencast using only free OS X tools: QuickTime, ffmpeg, and gifsicle.

Instructions

To capture the video (filesize: 19MB), using the free "QuickTime Player" application: