Ciantic

using System;
using Microsoft.AspNetCore.Mvc;
using Microsoft.AspNetCore.Mvc.Filters;

namespace Example
{
    public class ModelStateValidationFilter : Attribute, IActionFilter
    {
        public void OnActionExecuting(ActionExecutingContext context)
        {

natchiketa

Installation

1)

brew install nginx
sudo cp /usr/local/Cellar/nginx/1.8.0/homebrew.mxcl.nginx.plist /Library/LaunchAgents

2)

Replace /usr/local/etc/nginx/nginx.conf with the nginx.conf in this gist. I'm using port 5000 for my current project. Obviously, change server_name as well, and probably the name of its access log.

rodricios

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

"""

pip install networkx distance pattern 

In Flipboard's article[1], they kindly divulge their interpretation
of the summarization technique called LexRank[2].

pyth0nic

# To run this command:
# curl https://gist.githubusercontent.com/tianhuil/0aa9b265f55413dc7198/raw > setup_digitalocean.sh
# . setup_digitalocean.sh

# Update sudo apt-get
sudo apt-get update

# Installing scientific Python
sudo apt-get -y install --fix-missing build-essential python-dev python-numpy python-setuptools python-scipy libatlas-dev
sudo apt-get -y install --fix-missing build-essential python-sklearn

superscott

DAEMON_PATH=/opt/kafka/bin
DAEMON_NAME=kafka
# Check that networking is up.
#[ ${NETWORKING} = "no" ] && exit 0

PATH=$PATH:$DAEMON_PATH

# See how we were called.
case "$1" in
  start)

zlorb

import sys, time, datetime
from copy import copy, deepcopy
from collections import OrderedDict
import string
import math
import win32com.client
import traceback

# Sample code for accessing MSProject
# 2014 (C) Zohar Lorberbaum

evanscottgray

docker ps | awk {' print $1 '} | tail -n+2 > tmp.txt; for line in $(cat tmp.txt); do docker kill $line; done; rm tmp.txt

debasishg

General Background and Overview

1. Probabilistic Data Structures for Web Analytics and Data Mining : A great overview of the space of probabilistic data structures and how they are used in approximation algorithm implementation.
2. Models and Issues in Data Stream Systems
3. Philippe Flajolet’s contribution to streaming algorithms : A presentation by Jérémie Lumbroso that visits some of the hostorical perspectives and how it all began with Flajolet
4. Approximate Frequency Counts over Data Streams by Gurmeet Singh Manku & Rajeev Motwani : One of the early papers on the subject.
5. [Methods for Finding Frequent Items in Data Streams](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.187.9800&rep=rep1&t

ryankurte

#include "uart.h"

#include <sys/types.h>
#include <sys/stat.h>
#include <termios.h>
#include <fcntl.h>
#include <stdio.h>
#include <stdlib.h>