jul

from pylab import *
_value=[ 26.190, 26.964, 27.504, 27.692, 29.121,  30.657, 79.694]
_title=['dict +nc','dict' , 'repoze', 'fixed', 'repoze - mono', 'beaker', 'nocache' ]
figure(1)
lim=7
pos = arange(len(_value[:lim]))+.5
xticks(pos,_title[:lim])
ylabel("execution time (seconds)")
title("Impact of different caches on parsing 193114 lines with yahi")
rect=bar(pos,_value[:lim],align='center',width=.8)

jul

from repoze.lru import LRUCache, _MARKER
from repoze.lru import ExpiringLRUCache,lru_cache,_DEFAULT_TIMEOUT
"""A (decorator) cache maker for lru.repoze so you can clear 
your cache if needed"""


class CacheMaker():
    def __init__(self,default={}):
        self._maxsize=default.get("maxsize",_MARKER)
        self._time_out=default.get("time_out",_DEFAULT_TIMEOUT)

jul

from scikits.audiolab import Sndfile
import numpy as np
import pylab as plt
from numpy import fft

koln=Sndfile("test.wav")
sample=koln.read_frames(18300000)
plt.specgram(sample[:,1])
plt.show()

jul

from scikits.audiolab import Sndfile
import numpy as np
import pylab as plt
import csv
import matplotlib.mlab as mlab
from math import floor, log
#NFFT windows make calculus faster if a power of 2 
closest_2_power=lambda x : 1<<int(floor(log(x,2)))

def load_freq(fn="freq.csv"):

jul

#!/usr/bin/perl
sub a_p_p {
    ($x,$n)=@_;
    return ($x>>$n)%2 && a_p_p($x^(1<<$n),a_p_p($n)) || $x|($x^(1<<$n))
}
a_p_p($A)

jul

q = 0 or """ #=;$A=41;sub A { ~-$A+2};  A() && q' """
A=lambda A: -~A  #';
print A(41) # python + perl = <3

jul

from flask import Flask, flash, redirect, url_for
from flask import render_template, safe_join
from flask import Markup
from patch import Proxied
import os
_cdir="content"
conf={ 
    '_cdir' : "content" 
}

jul

#!/usr/bin/env python
# -*- coding: utf8 -*-

class decorate(object):
    def __init__(self,name="must have key",hook=None, api_hook=None,):
        self.hook=hook
        self.name=name
        self.api_hook=api_hook
        
    def __call__(self,*pos,**named):

jul

import sys
from time import clock
from random import randint as rand
from math import sqrt

sample = [ rand(0,(1<<16) - 1 )  for i in range(0,10000000 ) ]
fsample=map(lambda x : .0001 *x,  sample)

def time_me(sample, tag,op):
    start=clock()

jul

#!/usr/bin/python
# -*- coding: utf-8 -*-
import matplotlib.pyplot as plt
from scipy.signal import medfilt 
import numpy as np


NOISE_AMPLITUDE = 4.0
PERIOD = 200
PRESENCE_PROBABILITY = .4