wangg12

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


def make_dot(var, params=None):
    if params is not None:
        assert isinstance(params.values()[0], Variable)
        param_map = {id(v): k for k, v in params.items()}

jjelosua

## convert HTML POST data or HTTP GET query string to JSON

## get the raw post data from the AWS built-in variable and give it a nicer name
#if ($context.httpMethod == "POST")
 #set($rawAPIData = $input.path('$'))
#elseif ($context.httpMethod == "GET")
 #set($rawAPIData = $input.params().querystring)
 #set($rawAPIData = $rawAPIData.toString())
 #set($rawAPIDataLength = $rawAPIData.length() - 1)
 #set($rawAPIData = $rawAPIData.substring(1, $rawAPIDataLength))

niranjv

# A virtualenv running Python3.6 on Amazon Linux/EC2 (approximately) simulates the Python 3.6 Docker container used by Lambda
# and can be used for developing/testing Python 3.6 Lambda functions
# This script installs Python 3.6 on an EC2 instance running Amazon Linux and creates a virtualenv running this version of Python
# This is required because Amazon Linux does not come with Python 3.6 pre-installed 
# and several packages available in Amazon Linux are not available in the Lambda Python 3.6 runtime

# The script has been tested successfully on a t2.micro EC2 instance (Root device type: ebs; Virtualization type: hvm)
# running Amazon Linux AMI 2017.03.0 (HVM), SSD Volume Type - ami-c58c1dd3
# and was developed with the help of AWS Support

mountainstorm

# coding: utf-8

# Copyright (c) 2013 Mountainstorm
# 
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:

ishassan

//CHECK ishassan/build.sbt as well
import org.apache.hadoop.hbase.client._
import org.apache.hadoop.hbase.util.Bytes
import org.apache.hadoop.hbase.{CellUtil, HBaseConfiguration, TableName}
import org.apache.hadoop.conf.Configuration
import scala.collection.JavaConverters._

object ScalaHBaseExample extends App{

  def printRow(result : Result) = {

mrthomaskim

### prerequisites
sudo yum groupinstall "Development Tools"
git --version
gcc --version
bash --version
python --version # (system)
sudo yum install -y openssl-devel readline-devel zlib-devel
sudo yum update

### install `pyenv`

dannvix

Use nginx as Non-Transparent SSL Proxy

Introduction

Many mobile apps have back-end API servers. They usually rely on the API replies to determine whether certain information is supposed to be shown. If the API responses could be manipulated on the fly, we may easily fool an unmodified app to expose some private data.

This manual guides you to set up nginx as non-transparent SSL proxy, which just subsitutes strings in the server responses (i.e. man-in-the-middle attack ourself). For both server-side (their API servers) and client-side (your device), the whole process is almost transparent.

copumpkin

module Prime where

open import Coinduction

open import Data.Empty
open import Data.Nat
open import Data.Nat.Properties
open import Data.Nat.Divisibility
open import Data.Fin hiding (pred; _+_; _<_; _≤_; compare)
open import Data.Fin.Props hiding (_≟_)

johnhw

### JHW 2018
import numpy as np
import umap



# This code from the excellent module at:
# https://stackoverflow.com/questions/4643647/fast-prime-factorization-module
    
import random

johnynek

/**
 git clone https://github.com/twitter/scalding.git
 cd scalding
 ./sbt scalding-repl/console
*/

import scala.io.Source
val alice = Source.fromURL("http://www.gutenberg.org/files/11/11.txt").getLines
// Add the line numbers, which we might want later
val aliceLineNum = alice.zipWithIndex.toList