Flowerowl

#!/bin/bash

if [[ $EUID -ne 0 ]]; then
    echo -e "
    ROOT PRIVILEDGES NEEDED!
    You have to run this script as root.
    Aborting...
    "
    exit 1
else

Flowerowl

# List unique values in a DataFrame column
pd.unique(df.column_name.ravel())

# Convert Series datatype to numeric, getting rid of any non-numeric values
df['col'] = df['col'].astype(str).convert_objects(convert_numeric=True)

# Grab DataFrame rows where column has certain values
valuelist = ['value1', 'value2', 'value3']
df = df[df.column.isin(valuelist)]

Flowerowl

# -*- coding: utf-8 -*-
import os
import sys

try:
    import pkg_resources
    get_module_res = lambda *res: pkg_resources.resource_stream(__name__,
                                                                os.path.join(*res))
except ImportError:
    get_module_res = lambda *res: open(os.path.normpath(os.path.join(

Flowerowl

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

"""
This code implements a basic, Twitter-aware tokenizer.

A tokenizer is a function that splits a string of text into words. In
Python terms, we map string and unicode objects into lists of unicode
objects.

Flowerowl

#!/usr/bin/env python
# encoding: utf-8

states = ('Rainy', 'Sunny')

observations = ('walk', 'shop', 'clean')

start_probability = {'Rainy': 0.6, 'Sunny': 0.4}

transition_probability = {

Flowerowl

pixelToPoint = function(point, zoom, center, bounds) {
    // 像素到坐标
    if (!point) {
        return
    }
    var zoomUnits = getZoomUnits(zoom);
    var mercatorLng = center.lng + zoomUnits * (point.x - bounds.width / 2);
    var mercatorLat = center.lat - zoomUnits * (point.y - bounds.height / 2);
    var mercatorLngLat = {lng: mercatorLng, lat: mercatorLat};
    return mercatorToLngLat(mercatorLngLat)

Flowerowl

import itertools as IT
import multiprocessing as mp
import csv

def worker(chunk):
    return len(chunk)

def main():
    # num_procs is the number of workers in the pool
    num_procs = mp.cpu_count()

Flowerowl

import multiprocessing as mp
import itertools
import time
import csv

def worker(chunk):
    # `chunk` will be a list of CSV rows all with the same name column
    # replace this with your real computation
    # print(chunk)
    return len(chunk)  

Flowerowl

package main

import (
    "fmt"
    "io/ioutil"
    "log"
    "net/http"
    "sync"
)

Flowerowl

 1 #!/usr/bin/env python
 2 # monkey-patch
 3 import gevent.monkey
 4 gevent.monkey.patch_all()
 5 
 6 import sys
 7 import hashlib
 8 import re
 9 
10 import requests