Weizhang2017

def merge_sort(array):
	if len(array) >= 2:
		mid = len(array) // 2
		left = merge_sort(array[:mid])
		right = merge_sort(array[mid:])
		return merge(left, right)
	else:
		return array

def merge(left, right):

Weizhang2017

Scraping dynamic HTML in Python with Selenium

When a web page is opened in a browser, the browser will automatically execute JavaScript and generate dynamic HTML content. It is common to make HTTP request to retrieve the web pages. However, if the web page is dynamically generated by JavasSript, a HTTP request will only get source codes of the page. Many websites implement Ajax to send information to and retrieve data from server without reloading web pages. To scrape Ajax-enabled web pages without losing any data, one solution is to execute JavaScript using Python packages and scrape the web page that is completely loaded. Selenium is a powerful tool to automate browsers and load web pages with the functionality to execute JavaScript.

1. Start Selenium with a WebDriver

Selenium does not contain a web browser. It calls an API on a WebDriver which opens a browser. Both Firefox and Chrome have their own WebDrivers that int

Weizhang2017

[program:tunnel]
command=ssh -L 5432:localhost:5432 remotehost
directory=/home/john
user=wei
autostart=true
autorestart=true
stdout_logfile=/var/log/supervisor/tunnel.log
redirect_stderr=true
numprocs=1

Weizhang2017

[program:EmailValidationFlask]
command=gunicorn -c gunicorn.conf.py wsgi:app
directory=/root/EmailValidationFlask/
user=root
autostart=true
autorestart=true
redirect_stderr=true
stdout_logfile=/root/EmailValidationFlask/gunicorn_supervisor.log
stdout_logfile_maxbytes=100MB

Weizhang2017

def typed_property(name, expected_type):

	storage_name = '_' + name

	@property
	def prop(self):
		return getattr(self, storage_name)

	@prop.setter
	def prop(self, value):

Weizhang2017

- hosts: remote
  handlers:
    - name: update package list
      apt:
        update_cache: yes

  tasks:
    - name: download Oracle java
      get_url:
        url: "{{ java_donwload_url }}"

Weizhang2017

import time
from functools import wraps
import logging

logger = logging.getLogger(__name__)

def retry(retries=3, delay=10, backoff=10, logger=None):
    """Retry calling the decorated function using an exponential backoff.

    :param tries: number of times to try (not retry) before giving up

Weizhang2017

from pymongo import MongoClient
import time

class MongoConnect:
    '''connect to mongodb with context manager'''
    def __init__(self, host='127.0.0.1', port=27017, callbackOnExit=None, waitingTime=0):
        self.host = host
        self.port = port
        self.con = None
        self.callbackOnExit = callbackOnExit

Weizhang2017

#At low level, interacting with a database from SQL statements is straightforward
stocks = [
		('GOOG', 100, 490.1),
		('AAPL', 50, 545.75),
		('FB', 150, 7.45),
		('HPQ', 75, 33.2)
]

import sqlite3
db = sqlite3.connect('database.db')

Weizhang2017

def conver_to_binary(N):
        remainder = list()
        quotient = N // 2
        remainder.append(quotient%2)
        while quotient > 0:
            remainder.append(quotient%2)
            quotient = quotient // 2
        return remainder[::-1]
    binary = conver_to_binary(N)
    zeros = 0