When you read a hexadecimal number out loud, how do you pronounce the letters?
At my workplace, I’ve grown used to our custom of pronouncing the letters using the Joint Army/Navy Phonetic Alphabet standardized in 1941. The letter digits are pronounced Able, Baker, Charlie, Dog, Easy and Fox. Under this scheme, the hexadecimal number 0x7F8D3BC0 would be pronounced “Seven Fox Eight Dog Three Baker Charlie Zero.” This was disorienting to me at first, but after eight years this is now so natural that this is how I pronounce the digits in my mind even if I’m not speaking them.
We’ve started collecting Richard Scarry’s children’s books. Richard Scarry writes with a degree of detail and whimsy that holds an adult’s interest — much like old-school Sesame Street. (How far it has fallen — modern-day Sesame Street is much too postmodern, pluralistic, saccharine and juvenile for my taste. I console myself by searching for old Sesame Street clips on Youtube.) Recently I was amused and pleased to discover that one of Richard Scarry’s characters is named Able Baker Charlie! What a strange juxtaposition of worlds for me — programming and children’s books.
Able Baker Charlie is a mouse. He is a baker, and assists Baker Humperdink, a pig. Despite his small size, Able Baker Charlie is capable assisting with any step of the baking process, from stoking the oven, to mixing the dough, to putting loaves in the oven, and even delivering bread around Busytown. Below you may see a picture of Able Baker Charlie ably distributing French baguettes to Louie’s Restaurant.
Richard Scarry served in the U. S. Army during World War II. No doubt this is the source of the Able Baker Charlie aptonym. It still gives me a chuckle every time we read it.
I’ve long been dissatisfied with Courier New as a programming font; I’ve found the characters to be bulky and the serifs distracting. For the past year or so I’ve settled on the beautiful Lucida Console as my favorite font to code in. Lucida Console is bundled with Windows XP and Windows Vista, and unfortunately it doesn’t seem to be available for free redistribution. However, you can find some other aesthetically pleasing fixed-width programming fonts, some of which are available for free download, at Hamstu’s Typography of Code.
Hofstadter, Douglas. Gödel, Escher, Bach: an Eternal Golden Braid. New York: Basic Books, 1999.
This book is an excellent and fun, if lengthy, romp through art (visual, literary, and musical), mathematics, logic, provability and computability, linguistics, cognitive science and artificial intelligence, and more. Hofstadter cleverly explores a myriad of amazing connections between all these fields. And while he ends up drawing no substantive conclusions about his final hypothesis of emergent intelligence, the journey is no less exciting.
I disagree with Hofstadter’s opinion of the nature of intelligence. But I thoroughly enjoyed this book for a number of reasons. First, despite its imposing size, it is accessible; Hofstadter presents mathematical proofs in an easily understood way, using examples, analogies, and much explanatory prose. Second, despite its imposing size, it is delightfully fun; this book is brimming with humor, wit, cleverness, and exciting coincidences. Lastly, it is an excellent introduction to a broad variety of topics.
I first read this book in eighth grade and deeply enjoyed it. In part this book served as my introduction to the exciting fields of logic, mathematics, and computer science.
I’ve implemented a rudimentary persistent object store in Python. It is implemented as a Python extension module that implements a set of persistent types: strings, integers, floats, lists, and dictionaries. Each of these are backed by the persistent object store, which is implemented using a memory-mapped file.
In addition, using a specially crafted Python base class for Python objects, Python objects may be stored in the object store (as dictionaries) and instantiated out of the object store.
The result is an persistent object graph (the root of which is a persistent dictionary) whose objects and attributes may be manipulated in-place using native Python syntax. Rudimentary locking is provided so that multiple Python threads / processes may concurrently manipulate the object store.
Some aspects of this system are:
- It is a Python extension module written in C and C++.
- It is tested on Linux. It will likely work on *BSD systems, though it is possible that the location of the mapped storage may need to be moved.
- It is implemented in a hierarchical manner:
- A page manager handles the allocation of 4kB pages within a memory-mapped file. It is multi-process safe. It is, in a sense, a glorified sbrk() for a memory-mapped file.
- A heap manager abstracts the page manager’s services to manage the allocation and deallocation of arbitrary-sized storage segments within the memory-mapped file. It is essentially a malloc() and free() for a memory-mapped file. This is also multi-process safe.
- An object manager manages five new base types (persistent int, float, string, list, and dictionary) backed by persistent storage, using the heap manager’s services. It also provides rudimentary locking facilities for concurrency-safeness.
- The persist Python extension uses the object manager’s services to implement persistent types that mimic the equivalent Python types. Additionally, it has the ability to reinstantiate a Python object that was stored as a dictionary (using the appropriate Python base class). The object manager’s locking facilities are made available for application usage.
- Only one file may be mapped at a time (because it is mapped to a fixed logical address).
- It is available for use under the MIT license. Contact me if you are interested in using it.
Some examples of its use are a simple counter:
root = persist.root()
try : root['x'] += 1 # Increment counter
except : root['x'] = 1 # First pass; initialize
print "Content-type: text/htmln"
print "<p>You are visitor " + str(root['x']) + " to visit this site!</p>"
and rudimentary objects:
from pbase import pbase
class person (pbase) :
def __init__(self, name = "", age = 0) :
self.name = name
self.age = age
def printAge(self) :
print "<p>" + self.name + " is " + str(self.age) + " years old</p>"
root = persist.root()
if not root.has_key('Joe') : # First time through
root['Joe'] = person('Joe', 27)
if not root.has_key('John') : # First time through
root['John'] = person("John", 29)
# On subsequent passes we will retrieve the objects stored on the first pass.
print "Content-type: text/htmln"