OElesin

from bs4 import BeautifulSoup
import re
from urllib.parse import unquote
import time
import boto3, json, os

import requests
from bs4 import BeautifulSoup
s3 = boto3.client('s3')

OElesin

from time import sleep, time
from picamera import PiCamera
from datetime import datetime, timedelta
from boto3 import client
import json
import os

firehose = client('firehose')
lookout_vision = client('lookoutvision')

OElesin

import java.io.{File, FileOutputStream, IOException, InputStream}
import java.util

import scala.collection.JavaConverters._
import org.xml.sax.{ContentHandler, SAXException}
import org.apache.tika.metadata.Metadata
import org.apache.tika.metadata.HttpHeaders.CONTENT_TYPE
import org.apache.tika.mime.MediaType
import org.apache.tika.parser.{AbstractParser, ParseContext}
import org.apache.commons.io.IOUtils

OElesin

    def avgTime(message: String, f:  => Any) {
      var avg = 0L
      val c = 42
      1 to c foreach {
        _ =>
          val t0 = System.nanoTime()
          f
          val t1 = System.nanoTime()
          avg += t1 - t0
      }

OElesin

Squashing Git Commits

The easy and flexible way

This method avoids merge conflicts if you have periodically pulled master into your branch. It also gives you the opportunity to squash into more than 1 commit, or to re-arrange your code into completely different commits (e.g. if you ended up working on three different features but the commits were not consecutive).

Note: You cannot use this method if you intend to open a pull request to merge your feature branch. This method requires committing directly to master.

Switch to the master branch and make sure you are up to date:

OElesin

Sendy

Sendy is a self hosted email newsletter application that lets you send trackable emails via Amazon Simple Email Service (SES).

Heroku

You can deploy Sendy on Heroku using the following instructions (I assume you've already installed the heroku toolbelt).

1. On Heroku, create a new app.
2. Clone that app to your desktop

OElesin

/* Adapted from Tom Cunningham's 'Data Warehousing with MySql' (www.meansandends.com/mysql-data-warehouse) */

###### small-numbers table
DROP TABLE IF EXISTS numbers_small;
CREATE TABLE numbers_small (number INT);
INSERT INTO numbers_small VALUES (0),(1),(2),(3),(4),(5),(6),(7),(8),(9);

###### main numbers table
DROP TABLE IF EXISTS numbers;
CREATE TABLE numbers (number BIGINT);

OElesin

<?php
/* Caveat: I'm not a PHP programmer, so this may or may
 * not be the most idiomatic code...
 *
 * FPDF is a free PHP library for creating PDFs:
 * http://www.fpdf.org/
 */
require("fpdf.php");

class PDF extends FPDF {

OElesin

1. General Background and Overview

• Probabilistic Data Structures for Web Analytics and Data Mining : A great overview of the space of probabilistic data structures and how they are used in approximation algorithm implementation.
• Models and Issues in Data Stream Systems
• Philippe Flajolet’s contribution to streaming algorithms : A presentation by Jérémie Lumbroso that visits some of the hostorical perspectives and how it all began with Flajolet
• Approximate Frequency Counts over Data Streams by Gurmeet Singh Manku & Rajeev Motwani : One of the early papers on the subject.
• [Methods for Finding Frequent Items in Data Streams](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.187.9800&rep

OElesin

These links no longer work. Springer have pulled the free plug.

Graduate texts in mathematics

duplicates = multiple editions

A Classical Introduction to Modern Number Theory, Kenneth Ireland Michael Rosen

A Classical Introduction to Modern Number Theory, Kenneth Ireland Michael Rosen