rcalsaverini

#!/usr/bin/env python
# -*- coding: utf-8 -*-

from subprocess   import check_output
from sys          import argv
from time         import time

cmd = lambda pid:  "stat -t /proc/%s | awk '{print $14}'" % (pid,)

rcalsaverini

#!/bin/bash
pidlist=`ps ax | grep -i -E $1 | grep -v grep | awk '{print $1}' | grep -v PID | xargs echo`
for pid in $pidlist; do
    sincetime $pid
done

rcalsaverini

-- basic imports
import XMonad

-- needed for layouts
import XMonad.Layout.Grid

-- needed for hot keys
import XMonad.Util.EZConfig(additionalKeys)
import XMonad.Actions.CycleWS (nextWS, prevWS, shiftToNext, shiftToPrev)

rcalsaverini

import pymc
import numpy


def model(disasters):
    size = len(disasters)
    low  = pymc.Exponential('low',  beta=1.)
    high = pymc.Exponential('high', beta=2.)

    @pymc.stochastic(dtype=int)

rcalsaverini

import pymongo
import re
import time
from datetime import datetime, timedelta

patt = re.compile("\d*/\d*\s\d*%")

class Operations(object):
    def __init__(self, db, host='localhost'):
        self.conn = pymongo.Connection(host)

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class Singleton(type):
""" This is a Singleton metaclass. All classes affected by this metaclass 
have the property that only one instance is created for each set of arguments 
passed to the class constructor."""

    def __init__(cls, name, bases, dict):
        super(Singleton, cls).__init__(cls, bases, dict)
        cls._instanceDict = {}

    def __call__(cls, *args, **kwargs):

rcalsaverini

import pandas
import datetime
from pylab import *

data = pandas.read_csv('file.csv', index_col = 0, header = 0, sep = '\t')
timesIndex = data.index
dynamapsIndex = data.columns
levels = map(lambda x : round(x,1), linspace(data.min().min(), data.max().max(), 101))

contourf(data, levels = levels, cmap=plt.cm.jet_r, interpolation = 'bicubic')

rcalsaverini

from mpl_toolkits.basemap import Basemap
import numpy as np
import matplotlib.pyplot as plt

m = Basemap(llcrnrlon=-73.45,llcrnrlat=-35,urcrnrlon=-30.1,urcrnrlat=6, resolution='i',projection='lcc',lon_0=-45,lat_0=-23.7)
m.drawcoastlines()
m.fillcontinents(color='beige',lake_color='aqua')
# draw parallels and meridians.
m.drawparallels(np.arange(-40,10,1.))
m.drawmeridians(np.arange(-80.,-0,1.))

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#Based on an answer by John Machin on Stack Overflow (http://stackoverflow.com/users/84270/john-machin)
#http://stackoverflow.com/questions/8733233/filtering-out-certain-bytes-in-python

def isValidXMLChar(char):
  codepoint = ord(char)
  return 0x20 <= codepoint <= 0xD7FF or   \
         codepoint in (0x9, 0xA, 0xD) or  \
         0xE000 <= codepoint <= 0xFFFD or \
         0x10000 <= codepoint <= 0x10FFFF

rcalsaverini

"""
Crawling brazilian soccer results from
http://futpedia.globo.com/campeonato/campeonato-brasileiro/2011#/fase=fase-unica/rodada=1

With:
http://www.clips.ua.ac.be/pages/pattern-web
"""

import pandas
from pattern import web