Alex Kosmachev ADKosm

## demo.js
async function onPlay() {
    // console.log("Play!")

    const videoEl = $('#inputVideo').get(0)

    let isLoaded = !!faceapi.nets.tinyFaceDetector.params

    if(videoEl.paused || videoEl.ended || !isLoaded) {
        console.log("Is not loaded yet!")
        return setTimeout(() => onPlay())

## demo.html
<!DOCTYPE html>
<html lang="ru">
<head>
    <title>PifPaf</title>
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1, maximum-scale=1, user-scalable=no">

    <script src="faceapi.js"></script>
    <script src="https://ajax.googleapis.com/ajax/libs/jquery/3.6.0/jquery.min.js"></script>

## monad.hs
combinations :: Int -> [(Int, Int)]
combinations n = do
  a <- [1..6]
  b <- [1..6]
  if a + b == n then return (a,b) else []

solve :: [(Int, Int)]
solve = do
  n <- [2..12]
  return (n, length $ combinations n)

## scaling
                   '  ,
                   '
                 ,   ,

        ' ' ;:'dXX:
          0MMMMMMMc
         dNMWMMMMMNNl ,
         WMWMMMMMMMWWc
         oWMMMO:ckMMMO,
          okkO:   NMMM

## map.java
Function<Integer, BinaryClassifier> learnClassicier = (Integer i) -> {
  List<Boolean> booleanLabels = new ArrayList<>(labels.size());
  for (int j = 0; j < labels.size(); j++) {
    booleanLabels.add(labels.get(j) == i);
  }
  BinaryClassifier binaryClassifier = binaryClassifiers.get(i);
  binaryClassifier.fit(train, booleanLabels);
  return binaryClassifier;
}
MyThreadPool.map(learnClassicier, [0, 1, 2, 3, 4, 5, 6, 7, 8, 9])

## pool.py
from multiprocessing import Pool

def f(x):
    return x ** 2

data = [1, 2, 3, 4, 5]

with Pool(processes=4) as pool:
    new_data = pool.map(f, data)

## run jupiter
docker run -i -t -p 8888:8888 continuumio/anaconda /bin/bash -c "/opt/conda/bin/conda install jupyter -y --quiet && mkdir -p /opt/notebooks && /opt/conda/bin/jupyter notebook --notebook-dir=/opt/notebooks --ip='*' --port=8888 --no-browser --allow-root"

## group.py
import re
import sys

patt1 = re.compile('^(.*)(\.|_|-)1.(fastq|fq|fastq.gz|fq.gz)$')
patt2 = re.compile('^(.*)(\.|_|-)2.(fastq|fq|fastq.gz|fq.gz)$')

prev_line = next(sys.stdin)

try:
    for line in sys.stdin:

## Vagrantfile_Ether.rb
# -*- mode: ruby -*-
# vi: set ft=ruby :

# Vagrantfile API/syntax version. Don't touch unless you know what you're doing!
VAGRANTFILE_API_VERSION = "2"

Vagrant.configure(VAGRANTFILE_API_VERSION) do |config|

  config.vm.provider "virtualbox" do |v|
	v.memory = 8096

## logstash_get.rb
#!/usr/bin/ruby

require 'json'
require 'optparse'

options = {}
OptionParser.new do |opt|
  opt.on('-s', '--size SIZE', "Set size of logs. By default 1500") { |o| options[:size] = o }
  opt.on('-q', '--query QUERY', 'Set query to db. By default: { "match_all": {} }') { |o| options[:query] = o }
  opt.on('-d', '--db DB', 'Set database to request. By default: universe-*') { |o| options[:db] = o}
	async function onPlay() {
	// console.log("Play!")

	const videoEl = $('#inputVideo').get(0)

	let isLoaded = !!faceapi.nets.tinyFaceDetector.params

	if(videoEl.paused \|\| videoEl.ended \|\| !isLoaded) {
	console.log("Is not loaded yet!")
	return setTimeout(() => onPlay())
	<!DOCTYPE html>
	<html lang="ru">
	<head>
	<title>PifPaf</title>
	<meta charset="UTF-8">
	<meta name="viewport" content="width=device-width, initial-scale=1, maximum-scale=1, user-scalable=no">

	<script src="faceapi.js"></script>
	<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.6.0/jquery.min.js"></script>
	combinations :: Int -> [(Int, Int)]
	combinations n = do
	a <- [1..6]
	b <- [1..6]
	if a + b == n then return (a,b) else []

	solve :: [(Int, Int)]
	solve = do
	n <- [2..12]
	return (n, length $ combinations n)
	' ,
	'
	, ,

	' ' ;:'dXX:
	0MMMMMMMc
	dNMWMMMMMNNl ,
	WMWMMMMMMMWWc
	oWMMMO:ckMMMO,
	okkO: NMMM
	Function<Integer, BinaryClassifier> learnClassicier = (Integer i) -> {
	List<Boolean> booleanLabels = new ArrayList<>(labels.size());
	for (int j = 0; j < labels.size(); j++) {
	booleanLabels.add(labels.get(j) == i);
	}
	BinaryClassifier binaryClassifier = binaryClassifiers.get(i);
	binaryClassifier.fit(train, booleanLabels);
	return binaryClassifier;
	}
	MyThreadPool.map(learnClassicier, [0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
	from multiprocessing import Pool

	def f(x):
	return x ** 2

	data = [1, 2, 3, 4, 5]

	with Pool(processes=4) as pool:
	new_data = pool.map(f, data)
	import re
	import sys

	patt1 = re.compile('^(.*)(\.\|_\|-)1.(fastq\|fq\|fastq.gz\|fq.gz)$')
	patt2 = re.compile('^(.*)(\.\|_\|-)2.(fastq\|fq\|fastq.gz\|fq.gz)$')

	prev_line = next(sys.stdin)

	try:
	for line in sys.stdin:
	# -- mode: ruby --
	# vi: set ft=ruby :

	# Vagrantfile API/syntax version. Don't touch unless you know what you're doing!
	VAGRANTFILE_API_VERSION = "2"

	Vagrant.configure(VAGRANTFILE_API_VERSION) do \|config\|

	config.vm.provider "virtualbox" do \|v\|
	v.memory = 8096
	#!/usr/bin/ruby

	require 'json'
	require 'optparse'

	options = {}
	OptionParser.new do \|opt\|
	opt.on('-s', '--size SIZE', "Set size of logs. By default 1500") { \|o\| options[:size] = o }
	opt.on('-q', '--query QUERY', 'Set query to db. By default: { "match_all": {} }') { \|o\| options[:query] = o }
	opt.on('-d', '--db DB', 'Set database to request. By default: universe-*') { \|o\| options[:db] = o}