kangjin2014

import math.abs

object Playground {
  def main(args: Array[String]) {

    val tolerance = 0.001

    def isCloseEnough(x: Double, y: Double) =
      abs((x - y) / x) / x < tolerance

kangjin2014

class LoadFiles(object):
    
    def __int__(self):
        self.path_to_dict = 'data/key_skill.csv'
        self.path_to_jobs = 'data/ds.csv'
        self.path_to_resume = 'data/resume_ryan_kang.docx'

    def load_skills_dict(self, path_to_dict):
        df_skills = pd.read_csv(path_to_dict, encoding='latin1', header= None)
        return df_skills

kangjin2014

## __init__.py
def init():
    from <folder> import <file>
    from . import <file> # "." means current folder/module
    a = func_0()
    b = funk_1()

## __main__.py

if __name__ == '__main__':

kangjin2014

from bs4 import BeautifulSoup 
import urllib

def parser_job_link(job_link):
    try:
        html = urllib.request.urlopen(urllib.request.Request(job_link, headers={'User-Agent': 'Mozilla/5.0'})).read()
        soup = BeautifulSoup(html, "html.parser")
        for script in soup(["script", "style"]):
            script.extract()
        text = soup.get_text()

kangjin2014

from sklearn.cluster import KMeans
from sklearn import metrics
from scipy.spatial.distance import cdist
import numpy as np
import matplotlib.pyplot as plt

# k means determine k
distortions = []
K = range(1,10)
for k in K:

kangjin2014

from urllib.request import Request, urlopen

link = 'www.google.com' # define the linnk

req = Request(link, headers={'User-Agent': 'Mozilla/5.0'})

webpage = urlopen(req).read()

kangjin2014

from urllib.request import Request, urlopen

link = 'www.google.com' # define the linnk

req = Request(link, headers={'User-Agent': 'Mozilla/5.0'})

webpage = urlopen(req).read()

kangjin2014

import pandas as pd
import numpy as np
import pdfkit 

# configure the pdf layout
options = {
    'page-size': 'A4',
    'margin-top': '0.75in',
    'margin-right': '0.75in',
    'margin-bottom': '0.75in',

kangjin2014

from selenium import webdriver

driver = webdriver.PhantomJS()    
driver.maximize_window()
driver.get(link)  
scheight = .1

while scheight < 9.9:
    driver.execute_script("window.scrollTo(0, document.body.scrollHeight/%s);" % scheight)
    scheight += .01 

kangjin2014

from scrapy.contrib.linkextractors import LinkExtractor
from scrapy.contrib.spiders import CrawlSpider, Rule

class DomainSpider(CrawlSpider):
    name = 'prof'
    allowed_domains = ['ryerson.ca']
    start_urls = ['http://www.ryerson.ca/']
    rules = (
        Rule(LinkExtractor(allow=r"graduate/"), callback='parse_item', follow=True),
    )