kpykc

import numpy as np

rng = np.random.RandomState(0)

print "Trace"
A = rng.rand(3, 3)
print np.trace(A)
print np.einsum("ii", A)
print

kpykc

import numpy as np
from collections import defaultdict as _dd

def rolling_window(array, window=(0,), asteps=None, wsteps=None, axes=None, toend=True):
    """Create a view of `array` which for every point gives the n-dimensional
    neighbourhood of size window. New dimensions are added at the end of
    `array` or after the corresponding original dimension.
    
    Parameters
    ----------

kpykc

-- Two dashes start a one-line comment.

--[[
     Adding two ['s and ]'s makes it a
     multi-line comment.
--]]

----------------------------------------------------
-- 1. Variables and flow control.
----------------------------------------------------

kpykc

kpykc

# Author: Vlad Niculae <vlad@vene.ro>
# Makes use of memory_profiler from Fabian Pedregosa
# available at https://github.com/fabianp/memory_profiler

from IPython.core.magic import Magics, line_magic, magics_class


class MemMagics(Magics):
    @line_magic
    def memit(self, line='', setup='pass'):

kpykc

#coding: utf-8
import keyring
from cStringIO import StringIO
from email.mime.multipart import MIMEMultipart
from email.mime.text import MIMEText
from email.header import Header
from email import Charset
from email.generator import Generator
import smtplib

kpykc

import requests
import json
from time import sleep

data = []

print("Fetching page #%s" % 1)

r = requests.get("http://declarations.com.ua/search?format=json").json()
data += r["results"]["object_list"]

kpykc

// example appsrc for gstreamer 1.0 with own mainloop & external buffers. based on example from gstreamer docs.
// public domain, 2015 by Florian Echtler <floe@butterbrot.org>. compile with:
// gcc --std=c99 -Wall $(pkg-config --cflags gstreamer-1.0) -o gst gst.c $(pkg-config --libs gstreamer-1.0) -lgstapp-1.0

#include <gst/gst.h>
#include <gst/app/gstappsrc.h>

#include <stdint.h>

int want = 1;

kpykc

import zmq
import time
from multiprocessing import Process
import numpy as np
from pprint import pprint
import json

np.set_printoptions(precision=3)

kpykc

import zmq
import time
from multiprocessing import Process
import numpy as np

np.set_printoptions(precision=3)

def send_array(socket, A, flags=0, copy=True, track=False):
    """send a numpy array with metadata"""
    md = dict(dtype=str(A.dtype), shape=A.shape)