mateisuica

https://blog.mindorks.com/how-to-become-more-productive-in-android-with-android-studio-plugins-3beb3861fa7,1
https://blog.aritraroy.in/30-bite-sized-pro-tips-to-become-a-better-android-developer-b311fd641089,1
https://blog.aritraroy.in/what-my-2-years-of-android-development-have-taught-me-the-hard-way-52b495ba5c51,1
https://betterhumans.coach.me/how-to-get-over-the-habit-hump-e8c037aacc25,0
https://betterhumans.coach.me/developing-mindfulness-using-a-didgeridoo-just-dont-call-it-that-e3bc3fa61f2c,0
https://betterhumans.coach.me/how-a-break-from-alcohol-can-unlock-peak-performance-in-business-and-life-ae75d2cbfc9e,0
https://m.signalvnoise.com/basecamp-3-for-ios-hybrid-architecture-afc071589c25,0
https://android.jlelse.eu/make-robolectric-compatible-with-latest-gradle-tools-3-0-0-eca085681b3b,1
https://blog.mindorks.com/kotlin-weekly-update-6-64c3a7f1063c,1
https://m.signalvnoise.com/peaked-78ec0b147aeb,0

mateisuica

import csv

sites = []

with open('data.csv', 'rt') as csvfile:
    spamreader = csv.reader(csvfile)
    for row in spamreader:
        sites.append(row)

mateisuica

import urllib.request

def loadPage( site ):
    
    hdr = {'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8','User-Agent':'Mozilla/5.0'}
    request=urllib.request.Request(site,None,hdr) #The assembled request
    response = urllib.request.urlopen(request)
    page = response.read() # The data u need

    return page

mateisuica

from bs4 import BeautifulSoup

def parseContent( content ):
     # parse the html using beautiful soap and store in variable `soup`
    soup = BeautifulSoup(content, 'html.parser')

    # Take out the <div> of name and get its value
    content = soup.find_all(['h1','h2','h3','h4','h5', 'p','a'])

    text = ""

mateisuica

final_data = []
target = []

for link in sites:
    print(link[0])
    page = loadPage(link[0])
    data = parseContent(page)
    final_data.append(data)
    target.append(link[1])

mateisuica

from sklearn.feature_extraction.text import CountVectorizer
from sklearn.feature_extraction.text import TfidfTransformer
from sklearn.naive_bayes import MultinomialNB
from sklearn.pipeline import Pipeline

text_clf = Pipeline([('vect', CountVectorizer()),
                     ('tfidf', TfidfTransformer()),
                      ('clf', MultinomialNB()),
])

mateisuica

test = loadPage('http://www.mateisuica.com')
predicted = text_clf.predict([test])
print(predicted)

mateisuica

// Kotlin
var bob : User? = null
...
fun printBob() {
  someOutput(bob?.name)
  someOutput(bob?.surname)
  if(bob?.age == 5) { // does this even work? I need to null check separately, right?
    doSomeMoreStuff(bob?.dateOfBirth)
  }
}