liquidgenius

# Install chromedriver from https://sites.google.com/a/chromium.org/chromedriver/downloads

import os  

from optparse import OptionParser

from selenium import webdriver  
from selenium.webdriver.chrome.options import Options

CHROME_PATH = '/usr/bin/google-chrome'

liquidgenius

# Import unittest module for creating unit tests
import unittest

# Import time module to implement 
import time

# Import the Selenium 2 module (aka "webdriver")
from selenium import webdriver

# For automating data input

liquidgenius

#!/usr/bin/env bash
# https://developers.supportbee.com/blog/setting-up-cucumber-to-run-with-Chrome-on-Linux/
# https://gist.github.com/curtismcmullan/7be1a8c1c841a9d8db2c
# http://stackoverflow.com/questions/10792403/how-do-i-get-chrome-working-with-selenium-using-php-webdriver
# http://stackoverflow.com/questions/26133486/how-to-specify-binary-path-for-remote-chromedriver-in-codeception
# http://stackoverflow.com/questions/40262682/how-to-run-selenium-3-x-with-chrome-driver-through-terminal
# http://askubuntu.com/questions/760085/how-do-you-install-google-chrome-on-ubuntu-16-04

# Versions
CHROME_DRIVER_VERSION=`curl -sS chromedriver.storage.googleapis.com/LATEST_RELEASE`

liquidgenius

API workthough

1. Open a browser

   # start an instance of firefox with selenium-webdriver
   driver = Selenium::WebDriver.for :firefox
   # :chrome -> chrome
   # :ie     -> iexplore
   

• Go to a specified URL

liquidgenius

from selenium import webdriver
from selenium.webdriver.common.keys import Keys
from bs4 import BeautifulSoup
import re
import pandas as pd
from tabulate import tabulate
import os

#launch url
url = "http://kanview.ks.gov/PayRates/PayRates_Agency.aspx"

liquidgenius

Amazon Rekognition - Python Code Samples

1. Labels Detection
2. Faces Detection
3. Faces Comparison
4. Faces Indexing
5. Faces Search

liquidgenius

# List unique values in a DataFrame column
# h/t @makmanalp for the updated syntax!
df['Column Name'].unique()

# Convert Series datatype to numeric (will error if column has non-numeric values)
# h/t @makmanalp
pd.to_numeric(df['Column Name'])

# Convert Series datatype to numeric, changing non-numeric values to NaN
# h/t @makmanalp for the updated syntax!

liquidgenius

# Compiled source #
###################
*.com
*.class
*.dll
*.exe
*.o
*.so

# Packages #

liquidgenius

# uses the date_to_milliseconds and interval_to_milliseconds functions
# https://gist.github.com/sammchardy/3547cfab1faf78e385b3fcb83ad86395
# https://gist.github.com/sammchardy/fcbb2b836d1f694f39bddd569d1c16fe

from binance.client import Client
import time

def get_historical_klines(symbol, interval, start_str, end_str=None):
    """Get Historical Klines from Binance

liquidgenius

def interval_to_milliseconds(interval):
    """Convert a Binance interval string to milliseconds

    :param interval: Binance interval string 1m, 3m, 5m, 15m, 30m, 1h, 2h, 4h, 6h, 8h, 12h, 1d, 3d, 1w
    :type interval: str

    :return:
         None if unit not one of m, h, d or w
         None if string not in correct format
         int value of interval in milliseconds