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Alexander Kalinin AlexDel

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AlexDel / gist:67c993556e897039c871
Created November 10, 2014 09:27
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
AlexDel / gist:5b273a93a332bd150dc3
Created December 30, 2014 13:14
$('.note-editable').on('keyup', function(){$('[name="fromSummernote"]').val($(this).text())})
@AlexDel
AlexDel / gist:c3b713c9ffde0f7589e7
Created December 30, 2014 13:23
contracted popover
//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
AlexDel / gist:947e8b588cedd8b61b02
Created January 13, 2015 08:03
people_list = [
{name: 'A',
friends: 'B','C'},
{name: 'D',
friends: 'E','A'},
]
friends_groups = 0
for person1 in people_list:
@AlexDel
AlexDel / gist:680f22703e95fd7d9715
Created April 29, 2015 09:18
//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
AlexDel / 1
Last active August 29, 2015 14:22
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
AlexDel / gist:1588878
Created January 10, 2012 12:45
Genre diversity score. Считаем лексическую насыщенность в корпусе Брауна и выводим данные. NLTK Упр 2.16
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
AlexDel / gist:1589515
Created January 10, 2012 15:10
NLTK. Ex 2.18 Write a program to print the 50 most frequent bigrams (pairs of adjacent words) of a text, omitting bigrams that contain stopwords.
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
AlexDel / gist:1593588
Created January 11, 2012 07:39
NLTK EX 2.20 Write a function word_freq() that takes a word and the name of a section of the Brown Corpus as arguments, and computes the frequency of the word in that section of the corpus.
def word_freq(word, section):
freq = nltk.probability.FreqDist(nltk.corpus.brown.words(categories = section))
word_frequency = freq[word]
return word_frequency
@AlexDel
AlexDel / gist:1593818
Created January 11, 2012 09:05
NLTK Ex 2.21 Write a program to guess the number of syllables contained in a text, making use of the CMU Pronouncing Dictionary
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