charlesreid1

$ brew install -v svn
==> Downloading http://www.apache.org/dyn/closer.cgi?path=subversion/subversion-1.7.9.tar.bz2
Already downloaded: /Library/Caches/Homebrew/subversion-1.7.9.tar.bz2
tar xf /Library/Caches/Homebrew/subversion-1.7.9.tar.bz2
==> ./configure --disable-debug --prefix=/usr/local/Cellar/subversion/1.7.9 --with-apr=/usr/local/Library/ENV/4.3 --with-ssl --with-zlib=/usr --with-sqlite=/usr/local/opt/sqlite --with-serf=/usr/local/opt/serf --disable-neon-version-check --disable-mod-activation --disable-nls --without-apache-libexecdir --without-berkeley-db
./configure --disable-debug --prefix=/usr/local/Cellar/subversion/1.7.9 --with-apr=/usr/local/Library/ENV/4.3 --with-ssl --with-zlib=/usr --with-sqlite=/usr/local/opt/sqlite --with-serf=/usr/local/opt/serf --disable-neon-version-check --disable-mod-activation --disable-nls --without-apache-libexecdir --without-berkeley-db
configure: Configuring Subversion 1.7.9
configure: creating config.nice
checking for gcc... cc
checking whether the C compiler wo

charlesreid1

$ brew install -v svn
==> Downloading http://www.apache.org/dyn/closer.cgi?path=subversion/subversion-1.7.10.tar.bz2
Already downloaded: /Library/Caches/Homebrew/subversion-1.7.10.tar.bz2
tar xf /Library/Caches/Homebrew/subversion-1.7.10.tar.bz2
==> ./configure --disable-debug --prefix=/usr/local/Cellar/subversion/1.7.10 --with-apr=/usr/local/Library/ENV/4.3 --with-ssl --with-zlib=/usr --with-sqlite=/usr/local/opt/sqlite --with-serf=/usr/local/opt/serf --without-neon --disable-mod-activation --disable-nls --without-apache-libexecdir --without-berkeley-db
./configure --disable-debug --prefix=/usr/local/Cellar/subversion/1.7.10 --with-apr=/usr/local/Library/ENV/4.3 --with-ssl --with-zlib=/usr --with-sqlite=/usr/local/opt/sqlite --with-serf=/usr/local/opt/serf --without-neon --disable-mod-activation --disable-nls --without-apache-libexecdir --without-berkeley-db
configure: Configuring Subversion 1.7.10
configure: creating config.nice
checking for gcc... cc
checking whether the C compiler works... yes

charlesreid1

from pyevolve import G1DBinaryString
from pyevolve import GSimpleGA

# http://pyevolve.sourceforge.net/ simple genetic algorithm example

genome = G1DBinaryString.G1DBinaryString(30)
genome.evaluator.set(lambda chromosome: sum(chromosome))
ga = GSimpleGA.GSimpleGA(genome)
ga.evolve(freq_stats=10)
print ga.bestIndividual()

charlesreid1

# Simplified Dijsktra's Algorithm
# from http://code.activestate.com/recipes/119466/

def shortest_path(G, start, end):
   def flatten(L):       # Flatten linked list of form [0,[1,[2,[]]]]
      while len(L) > 0:
         yield L[0]
         L = L[1]

   q = [(0, start, ())]  # Heap of (cost, path_head, path_rest).

charlesreid1

def Trigger_GC():
	import serial
	import time
	GC_Trigger_Port = serial.Serial(12,9600,timeout = 1)
	bytesEnable = bytearray([254, 248])
	bytesOn = bytearray([254, 1])
	bytesOff = bytearray([254, 0])
	GC_Trigger_Port.write(bytesEnable)
	GC_Trigger_Port.write(bytesOn)
	time.sleep(2)

charlesreid1

class ExpensiveObjectToCreate(object):
    '''Insert code here'''
    pass
    def __init__(self,**kwargs):
        self.params = kwargs

    def check(self):
        print self.params

charlesreid1

== Chess Games and Positions in Neo4j

:neo4j-version: 2.0.0
:author: Wes Freeman
:twitter: @wefreema
:tags: chess

The goal is to load a bunch of chess games into Neo4j for further analysis. Scores listed are Stockfish's take on a position after a 25 move horizon (but this number can be deepened as the graph is filled out or as more processing is done). Positions can also be loaded as alternative moves (not connected to a game) based on suggestions from Stockfish. The positions are recorded as link:http://en.wikipedia.org/wiki/Forsyth%E2%80%93Edwards_Notation[FEN], a human-readable/compressed chess board state notation.

=== Schema diagram

charlesreid1

#include <stdlib.h>
#include <iostream>
#include <fstream>
#include <sstream>
#include <cmath>
#include <string>
using namespace std;

/// The sums() function computes several sums from vectors x and y,
/// and stores the values in a, b, c, d, and e

charlesreid1

NOTE: This how-to was written for the Census API at http://thedataweb.rm.census.gov/ -- it has since been moved to http://api.census.gov/

Mike Stucka, our contact at the Macon Telegraph, sent us a link to the Census's official API which is launching next month. You can skip ahead to the site - http://www.census.gov/developers/ - and get an API key, but also read my notes after using this yesterday:

1. The datasets

--- The 2010 Census Summary comes from everyone filling out census forms, and you can get stats at state level down to a super-detailed block level. Info from this includes population, age, gender, race, home ownership, members of a household, and various combinations of that. Full list: http://www.census.gov/developers/data/sf1.xml

--- The 2006-2010 American Community Survey is a longer form given to fewer households over 5 years (so its numbers are incompatible with the 2010 Census). You can get stats down only to the block group level. In addition to the standard census stats, you get: educa

charlesreid1

import PyADO

#print help(PyADO.connect)

conn = PyADO.connect(None,host='localhost',user='',password='',provider='iHOLEDB.iHistorian.1')
print conn

curs = conn.cursor()
curs.execute("SELECT * FROM ihTags")