NeuronQ

#include <iostream>

#include <GL/glew.h>
#include <GLFW/glfw3.h>

using namespace std;

static unsigned int CompileShader(unsigned int type, const string& source) {
    unsigned int id = glCreateShader(type);
    const char* src = source.c_str();

NeuronQ

import sys
import traceback

import gi
gi.require_version('Gst', '1.0')
from gi.repository import Gst, GObject  # noqa


INPUT_VIDEO_FILE_PATH = '/opt/app/data/video_file.mp4'
PLACEHOLDER_FILE_PATH = '/opt/app/data/tvlogo.png'

NeuronQ

## AUTHOR: Andrei Anton
## LICENSE: MIT

## USAGE EXAMPLE:
# @model_with_json_fields
# class MyThing(models.Model):
#     JSON_FIELDS = (
#         ['data', dict(default=dict, blank=True)],
#         ['errors', dict(null=True, blank=True)],
#     )

NeuronQ

async def main_concurrent():
    t = time.perf_counter()
    tasks = [asyncio.create_task(handle_url(url))
             for url in urls]

    ## All of the variants below would wait for everything:

    # V1: this will wait as little as possible
    #   (point of this is to show that tasks start executing when created)
    # for task in tasks:

NeuronQ

// async_scrape.js (tested with node 11.3)
const sleep = ts => new Promise(resolve => setTimeout(resolve, ts * 1000));

async function fetchUrl(url) {
    console.log(`~ executing fetchUrl(${url})`);
    console.time(`fetchUrl(${url})`);
    await sleep(1 + Math.random() * 4);
    console.timeEnd(`fetchUrl(${url})`);
    return `<em>fake</em> page html for ${url}`;
}

NeuronQ

# async_scrape.py (requires Python 3.7+)
import asyncio, random, time

async def fetch_url(url):
    print(f"~ executing fetch_url({url})")
    t = time.perf_counter()
    await asyncio.sleep(random.randint(1, 5))
    print(f"time of fetch_url({url}): {time.perf_counter() - t:.2f}s")
    return f"<em>fake</em> page html for {url}"

NeuronQ

// async_scrape.js (tested with node 11.3)
const sleep = ts => new Promise(resolve => setTimeout(resolve, ts * 1000));

async function fetchUrl(url) {
    console.log(`~ executing fetchUrl(${url})`);
    console.time(`fetchUrl(${url})`);
    await sleep(1 + Math.random() * 4);
    console.timeEnd(`fetchUrl(${url})`);
    return `<em>fake</em> page html for ${url}`;
}

NeuronQ

# async_scrape.py (requires Python 3.7+)
import asyncio, random, time

async def fetch_url(url):
    print(f"~ executing fetch_url({url})")
    t = time.perf_counter()
    await asyncio.sleep(random.randint(1, 5))
    print(f"time of fetch_url({url}): {time.perf_counter() - t:.2f}s")
    return f"<em>fake</em> page html for {url}"

NeuronQ

// callbacks_async_scrape.js (tested with node 11.3)
const http = require('http');
const https = require('https');

const fetchUrl = (url, onSuccess, onError) => {
    console.time(`fetchUrl(${url})`);
    (url.indexOf('https') === 0 ? https : http).get(url, resp => {
        let html = '';
        resp.on('data', chunk => html += chunk);
        resp.on('end', () => {

NeuronQ

// sync_scrape.js (tested with node 11.3)
const request = require("sync-request");

const fetchUrl = url => {
  console.time(`fetchUrl(${url})`);
  const html = request("GET", url).getBody();
  console.timeEnd(`fetchUrl(${url})`);
  return html;
};