bruce30262

Setting up Qemu with a tap interface

There are two parts to networking within QEMU:

• The virtual network device that is provided to the guest (e.g. a PCI network card).
• The network backend that interacts with the emulated NIC (e.g. puts packets onto the host's network).

Example: User mode network

NaniteFactory

package main

import "syscall"

func main() {
  
	// equivalent to (HANDLE)GetModuleHandle(NULL); in C
	handle, _, _ := syscall.Syscall(
		syscall.NewLazyDLL("kernel32.dll").NewProc("GetModuleHandleW").Addr(),
		1, 0, 0, 0,

dgadiraju

path = "/public/yelp-dataset/yelp_review.csv"

yelpReview = sc.newAPIHadoopFile(path, 
  'org.apache.hadoop.mapreduce.lib.input.TextInputFormat', 
  'org.apache.hadoop.io.LongWritable', 
  'org.apache.hadoop.io.Text', 
  conf={'textinputformat.record.delimiter' : '\r'})
  
yelpReview.count()

mariocesar

#!/usr/bin/env bash

catch_kill() {
  echo "Caught SIGKILL signal!"
  kill -KILL "$pid" 2>/dev/null
}

catch_term() {
  echo "Caught SIGTERM signal!"
  kill -TERM "$pid" 2>/dev/null

extremecoders-re

Setting up Qemu with a tap interface

There are two parts to networking within QEMU:

• The virtual network device that is provided to the guest (e.g. a PCI network card).
• The network backend that interacts with the emulated NIC (e.g. puts packets onto the host's network).

Example: User mode network

hivefans

package main

import (
	"bufio"
	"fmt"
	"io"
	"os"
	"os/exec"
	"strings"
)

dmyersturnbull

import pandas as pd
import itertools
import time
import multiprocessing
from typing import Callable, Tuple, Union

def groupby_parallel(
  groupby_df: pd.core.groupby.DataFrameGroupBy,
  func: Callable[[Tuple[str, pd.DataFrame]], Union[pd.DataFrame, pd.Series]],
  num_cpus: int = multiprocessing.cpu_count() - 1,

rinchik

from selenium import webdriver
from selenium.webdriver.common.action_chains import ActionChains

def enter_hours(self, cell, amount):
    #Double-click
    actions = ActionChains(self.driver)
    actions.move_to_element(cell)
    actions.double_click(cell)
    actions.perform()
    

vinhkhuc

"""
Vanilla Char-RNN using TensorFlow by Vinh Khuc (@knvinh).
Adapted from Karpathy's min-char-rnn.py
https://gist.github.com/karpathy/d4dee566867f8291f086
Requires tensorflow>=1.0
BSD License
"""
import random
import numpy as np
import tensorflow as tf

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)