tobigue

#!/bin/bash
# step through commits showing the commit information

BASE_REV=$1;
skip=true;

for rev in $(git log --pretty=oneline --reverse --abbrev-commit | awk '{print $1}'); do
    if [ "$rev" = "$BASE_REV" ] ; then
        skip=false;
    fi

tobigue

import sys, io, csv, subprocess

VLC = "C:\\Program Files (x86)\\VideoLAN\\VLC\\vlc.exe"

programs = """
Programm,Frequenz,SID
Das Erste,522,14
ZDF,570,514
RTL Television,506,16405
SAT.1,658,16408

tobigue

from __future__ import print_function
import argparse
import sys
import time
from copy import deepcopy
from datetime import datetime
from elasticsearch import Elasticsearch
from elasticsearch.exceptions import NotFoundError
from elasticsearch.helpers import reindex

tobigue

#!/usr/bin/env bash

mkdir -p /home/$USER/Desktop/apachenpub/

date >> /home/$USER/Desktop/apachenpub/__LOG__.txt ;
find /home/$USER/Desktop -maxdepth 1 -type f -atime +14 -exec mv -v {} /home/$USER/Desktop/apachenpub/ \; >> /home/$USER/Desktop/apachenpub/__LOG__.txt ;

tobigue

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

import pygame
from pygame.locals import *
from evdev import InputDevice, categorize, ecodes, list_devices


pygame.init()

tobigue

python -c "
import flask
f=flask.Flask('a', static_folder='./')
@f.route('/<path:p>')
def s(p): return f.send_static_file(p)
f.run()
"

tobigue

import os
import random
import string
from subprocess import call

import numpy as np

from sklearn.base import BaseEstimator, ClassifierMixin
from sklearn.datasets import dump_svmlight_file

tobigue

from sklearn.linear_model import SGDClassifier
from sklearn import cross_validation
from sklearn import metrics
from sklearn.grid_search import GridSearchCV

from sklearn.datasets import load_iris

data = load_iris()
sample_vector = data.data
targets = data.target