lbolla

Asynchronous programming with Tornado

Asynchronous programming can be tricky for beginners, therefore I think it's useful to iron some basic concepts to avoid common pitfalls.

For an explanation about generic asynchronous programming, I recommend you one of the [many][2] [resources][3] [online][4].

I will focus on solely on asynchronous programming in [Tornado][1]. From Tornado's homepage:

paulmach

/*
Serve is a very simple static file server in go
Usage:
	-p="8100": port to serve on
	-d=".":    the directory of static files to host

Navigating to http://localhost:8100 will display the index.html or directory
listing file.
*/
package main

kendellfab

func readLine(path string) {
  inFile, _ := os.Open(path)
  defer inFile.Close()
  scanner := bufio.NewScanner(inFile)
	scanner.Split(bufio.ScanLines) 
  
  for scanner.Scan() {
    fmt.Println(scanner.Text())
  }
}

bonzanini

# You need to install scikit-learn:
# sudo pip install scikit-learn
#
# Dataset: Polarity dataset v2.0
# http://www.cs.cornell.edu/people/pabo/movie-review-data/
#
# Full discussion:
# https://marcobonzanini.wordpress.com/2015/01/19/sentiment-analysis-with-python-and-scikit-learn

molivier

# Edit ~/.bash_profile 

export GOPATH=/Users/$USER/go
export PATH=$GOPATH/bin:$PATH

# Reload profile : source ~/.bash_profile

Restuta

Below is the list of modern JS frameworks and almost frameworks – React, Vue, Angular, Ember and others.

All files were downloaded from https://cdnjs.com and named accordingly. Output from ls command is stripped out (irrelevant stuff)

As-is (minified)

$ ls -lhS
566K Jan 4 22:03 angular2.min.js

claudijd

# A proof of concept to demonstrate TOTP bruteforcing concepts

# Parameters to control simulation behavior###
request_rate = 4
totp_validity_window = 90 #in seconds
totp_guesses_per_auth_session = request_rate * totp_validity_window # number of totp guesses per auth session
simulated_logins = 100 # number of simulated logins to help determine average rate of TOTP collision
##############################################

# Helper Methods

j314erre

import tensorflow as tf
import numpy as np


class TextCNN(object):
    """
    A CNN for text classification.
    Uses an embedding layer, followed by a convolutional, max-pooling and softmax layer.
    """
    def __init__(

pylover

#! /usr/bin/env python3
"""Fixing bluetooth stereo headphone/headset problem in debian distros.

Workaround for bug: https://bugs.launchpad.net/ubuntu/+source/indicator-sound/+bug/1577197
Run it with python3.5 or higher after pairing/connecting the bluetooth stereo headphone.

This will be only fixes the bluez5 problem mentioned above .

Licence: Freeware

mjdietzx

#!/bin/bash

# install CUDA Toolkit v8.0
# instructions from https://developer.nvidia.com/cuda-downloads (linux -> x86_64 -> Ubuntu -> 16.04 -> deb (network))
CUDA_REPO_PKG="cuda-repo-ubuntu1604_8.0.61-1_amd64.deb"
wget http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/${CUDA_REPO_PKG}
sudo dpkg -i ${CUDA_REPO_PKG}
sudo apt-get update
sudo apt-get -y install cuda