mark padgham mpadge

Hofstadter on Lisp

In the mid-80s, while reading through my roommate's collection of Scientific American back issues, I encountered this introduction to Lisp written by Douglas Hofstadter. I found it very charming at the time, and provide it here (somewhat illegally) for the edification of a new generation of Lispers.

In a testament to the timelessness of Lisp, you can still run all the examples below in emacs if you install these aliases:

(defalias 'plus #'+)
(defalias 'quotient #'/)
(defalias 'times #'*)
(defalias 'difference #'-)

Alice's Laws

You can only count on yourself.
Never reveal more than you have to.
Execution is nine-tenths of the job.
Give credit where credit is due.
When all else fails, do it yourself.
90% of a project takes 90% of the time.
The remaining 10% takes an additional 90% of the time.
Never date a co-worker.

Using Git Commit Message Templates to Write Better Commit Messages

The always enthusiastic and knowledgeable mr. @jasaltvik shared with our team an article on writing (good) Git commit messages: How to Write a Git Commit Message. This excellent article explains why good Git commit messages are important, and explains what constitutes a good commit message. I wholeheartedly agree with what @cbeams writes in his article. (Have you read it yet? If not, go read it now. I'll wait.) It's sensible stuff. So I decided to start following the

	#!/bin/bash
	# AUTHOR: Bob Rudis <[email protected]> (@hrbrmstr)
	# LICENSE: MIT + file zLICENSE

	TODAY=`date +%Y-%m-%d`
	TODAY_MD=`date +%B\ %d,\ %Y`
	YEAR=`date +%Y`

	PACKAGENAME=$1

	library(silicate)

	data("wrld_simpl", package = "maptools")
	#edges are unique segments (undirected)
	#segments are directed instances of edges, belonging to arcs/ways or feature boundaries
	library(silicate)
	library(sf)
	x <- PATH(st_as_sf(wrld_simpl))
	#x <- PATH(minimal_mesh)

	# progress information in parallel processes (that use the same filesystem)

	# the master function sets up a tempfile for each process, spawns processes, and
	# passes the corresponding tempfile location to each; each process dumps
	# progress information into its tempfile; the master function polls those files
	# for the progress information and returns it to the screen; the previous line
	# is overwritten, as for progress bars
	library (future)

	# an environment to stash file info in, to hack around scoping issues. A package

	# plotting multiple progress bars on the same line, as a precursor to running
	# the progress bars in parallel

	library (progress)
	library (future)
	library (R6)

	new_connection <- function () {
	f <- tempfile()
	file.create(f)


	####
	# Dependencies
	####

	library(tidyverse)
	library(igraph)

	####
	# The pattern is to identify points to extend the structure of

	# Add this to your .Rprofile
	options(
	error = quote(rlang::entrace()),
	rlang__backtrace_on_error = "collapse" # or "branch" or "full"
	)