zollinger

from PIL import Image, ImageDraw
import argparse
import sys

def get_colors(image_file, numcolors=10, resize=150):
    # Resize image to speed up processing
    img = Image.open(image_file)
    img = img.copy()
    img.thumbnail((resize, resize))

andrewschoen

# -*- coding: utf-8 -*-
import os
import StringIO
import hashlib

try:
    from boto.s3.connection import S3Connection
    from boto.s3.key import Key
except ImportError:
    raise ImproperlyConfigured, "Could not load Boto's S3 bindings."

cshtdd

import signal

class InterruptableRegion(object):
    def __init__(self, sig=signal.SIGINT):
        self.sig = sig
        self.interrupted = False
        self.released = False
        self.original_handler = None

    def __enter__(self):

jdiscar

""" 
Original Author  Ernesto P. Adorio, Ph.D 
Original Source: http://my-other-life-as-programmer.blogspot.com/2012/02/python-finding-nearest-matching-color.html
Modifed By: JDiscar

This class maps an RGB value to the nearest color name it can find. Code is modified to include 
ImageMagick names and WebColor names.  

1. Modify the minimization criterion to use least sum of squares of the differences.
2. Provide error checking for input R, G, B values to be within the interval [0, 255].

hmartiro

ZeroMQ vs Redis

This document is research for the selection of a communication platform for robot-net.

Goal

The purpose of this component is to enable rapid, reliable, and elegant communication between the various nodes of the network, including controllers, sensors, and actuators (robot drivers). It will act as the core of robot-net to create a standardized infrastructure for robot control.

Requirements:

karpathy

"""
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
BSD License
"""
import numpy as np

# data I/O
data = open('input.txt', 'r').read() # should be simple plain text file
chars = list(set(data))
data_size, vocab_size = len(data), len(chars)

xflr6

"""Benchmark PostgreSQL array vs. join performance.

Replicate http://shon.github.io/2015/12/21/postgres_array_performance.html
with proper join table indexes (uniqueness constraints) using SQLAlchemy.

$ python -i bench_pg_array.py
>>> setup()

$ python -m timeit -s "import bench_pg_array" "bench_pg_array.test_join()"
500 loops, best of 5: 445 usec per loop

alexproca

#!/usr/bin/env bash

#copy this in a folder from path ex: /usr/local/bin
#usage: docker-machine-rename default my-default

# Authors
#
# alexproca initial script
# eurythmia sed magic

schickling

docker-machine import/export

Script to import and export docker-machine configurations to sync between hosts/collaborators

Export (on host A)

$ docker-machine ls
NAME       ACTIVE   DRIVER         STATE     URL                            SWARM   DOCKER    ERRORS
dev        -        digitalocean   Running   tcp://example.com:2376                 v1.10.1

apaszke

from graphviz import Digraph
import torch
from torch.autograd import Variable, Function

def iter_graph(root, callback):
    queue = [root]
    seen = set()
    while queue:
        fn = queue.pop()
        if fn in seen: