crowding

library(microbenchmark)

lru_cache <- function(cache.size = 1000) {
  lru <- new.env(hash=TRUE, parent=emptyenv(), size=cache.size)
  pred <- new.env(hash=TRUE, parent=emptyenv(), size=cache.size)
  succ <- new.env(hash=TRUE, parent=emptyenv(), size=cache.size)

  pred$TAIL <- "HEAD"
  succ$HEAD <- "TAIL"

crowding

'dot;color black' plot (; 50&}.@:((**(1-]))^:(i. 200)&0.25)) 2.4 ([+-~*((%~i.)100)) 4
NB.                                     100 numbers in [0,1)            ^^^^^^^^^
NB.                                     rescaled to               ^^^^^
NB.                                  100 numbers in [2.4,4)  ^^^                    ^
NB.                                             makes "x",   ^^^^^^^^^^^^^^^^^^^^^^^^
NB.                               ^^^^^^^^^ function y -> y * (1-y)*x
NB.                                        ^^^^^^^^^^ applied 200 times
NB.                                                  ^^^^^ starting with y=0.25
NB.                       ^^^^^^^ then dropping first 50 iterations
NB.                     ^ put original "x" alongside result

crowding

all: text.pdf text.html

text.pdf: bib.bib text.tex
	git clean -f -e text.pdf -e text.html
	latexmk -pdf text.tex  -pdflatex="pdflatex -halt-on-error -interaction=nonstopmode"

text.image.html: text.pdf
	cp text.bbl text.hbbl
	hevea text.tex -o text.html < /dev/null

crowding

library(vadr)
library(plyr)

# do "chain" arguments ever feature a dot on the second level (not in
# its own chain?) Answer by walking over expressions to pull out
# examples of usages.

dirs = c("~/analysis", "~/analysis/writing")

globs = c("*.r", "*.R")

crowding

See video file

crowding

#!/usr/bin/env python3

# Usage: python3 import_bibdesk_dates.py path/to/zotero.sqlite
# Will only touch records that have not been synced (i.e. "version" == 0)

import sqlite3
import re
import datetime
import pytz
import dateutil.parser