AlexDel

from scrapy.xlib.pydispatch import dispatcher
from scrapy import signals
from scrapy.http import FormRequest
from scrapy.selector import Selector

from spider.spiders.basic import StudentSpider
from spider.items import StudentItem
from scrapy import log

class XPATHS:

AlexDel

$('.note-editable').on('keyup', function(){$('[name="fromSummernote"]').val($(this).text())})

AlexDel

//choose the button by id to add "Add type popover" with need parameters
$('#addAccType').addTypePopover({
  //popover header
  popOverHeader: 'Add Type',
  
  //this is the input form id from which new type name is taken
  popOverFormInputId: 'NewType',
  
  //this is the input form name from which new type name is taken
  popOverFormInputName: 'NewType',

AlexDel

people_list = [
{name: 'A',
friends: 'B','C'},
{name: 'D',
friends: 'E','A'},
]

friends_groups = 0

for person1 in people_list:

AlexDel

//http://www.bennadel.com/blog/2404-compiling-optimizing-a-subset-of-a-requirejs-application.htm
({
    //appDir: '../js/apps',
    baseUrl: "../js", // Define our base URL - all module paths are relative to this base directory
    dir: '../www-built/js',
    //dir: '../../server-side/assets/SPAS',
    mainConfigFile: '../src_modules/config-require.js',
    optimizeCss: "none",
    optimize: "none", //"uglify",
    findNestedDependencies: true,

AlexDel

dataset = [
  (vector1, True),
  (vector2, False),
  (vector3, False),
]

train_data = [i[0] for i in dataset]
train_labels = [i[1] for i in dataset]
classifier.fit(train_data, train_labels)

AlexDel

import nltk
from __future__ import division
for genre in nltk.corpus.brown.categories():
	words = nltk.corpus.brown.words(categories = genre)
	print genre +' - ' + str(round((len(set(words))/len(words)),6)*100) + '%'

AlexDel

def top_bigrams(text):
	fdist = nltk.probability.FreqDist(nltk.bigrams(text)) #формируем список кортежей биграмм
	stopwords = nltk.corpus.stopwords.words('english') #формируем стоплист
	top_list = [(x,y) for x,y in fdist.keys() if x.isalpha() and y.isalpha() and x not in stopwords and y not in stopwords] #показываем только если элементы кортежа - слова и невходят в стоплист
	return top_list

AlexDel

def word_freq(word, section):
	freq = nltk.probability.FreqDist(nltk.corpus.brown.words(categories = section))
	word_frequency = freq[word]
	return word_frequency

AlexDel

d = nltk.corpus.cmudict.dict() #получаем объект в виде словаря для удобного доступа
def count_syllables(text): #вводим текст как список слов
	syll_text = [] #исходный массив где будут копиться слоги
	for word in text:
		syll_text.extend(d[word][0]) #к исходному массиву добавляем первый элемент (в случае нескольких произношений)с помощью метода extend
	return len(syll_text)# ву-а-ля