pnavarro-algometrics

import sqlite3
import numpy

# Array of 4 columns and 100 rows                                                                                                                                              
data = numpy.random.rand(100, 4)

# Create a sample database                                                                                                                                                     
conn = sqlite3.connect('/tmp/sample.db')
cursor = conn.cursor()

pnavarro-algometrics

# Capture the output of a process                                  

import shlex
import subprocess

cmdline = 'date --help'
p = subprocess.Popen(shlex.split(cmdline), stdout=subprocess.PIPE)

print(p.stdout.read())

pnavarro-algometrics

from numpy import *
from matplotlib.pylab import *
import matplotlib.dates as mdates

data = loadtxt('quotes.csv', delimiter=',')

# Epoch time to number (matlab and matplotlib format)
TIMEZONE_CORRECTION = 60.0 * 60 * 5
time = mdates.epoch2num(data[:, 0] / 1000.0 - TIMEZONE_CORRECTION)
bid  = data[:, 1]