Python Regular Expressions - Real World Applied Python
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Python Regular Expressions - Real World Applied Python

Learn Cutting Edge Pattern Matching Skills for Log Mining, Big Data Parsing, Cleanup and Preparation with Regex
Best Seller
4.4 (148 ratings)
Instead of using a simple lifetime average, Udemy calculates a course's star rating by considering a number of different factors such as the number of ratings, the age of ratings, and the likelihood of fraudulent ratings.
1,647 students enrolled
Created by Chandra Lingam
Last updated 4/2017
Current price: $10 Original price: $100 Discount: 90% off
5 hours left at this price!
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  • 3.5 hours on-demand video
  • 3 Articles
  • 8 Supplemental Resources
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
What Will I Learn?
  • Confidently use regular expression as a powerful text processing tool for data parsing, cleanup and preparation
  • Minimize effort spent on custom development for data cleanup
  • Gain practical tips to let Regular Expression do bulk of the work for data preparation
  • Understand potential performance issues and techniques to address them
View Curriculum
  • All material and software instructions are covered in house keeping lecture.
  • Familiarity with a Programming Language

*** NEW PREVIEW VIDEOS: All lectures in Section 2 and Section 3 enabled for preview!  Check it out! 

     NEW: Project 4 Network Configuration Parser added to the course***

Python Regular Expressions is a hands-on course that teaches you everything you need to know about Regular Expression using Python Language. Master cutting edge pattern matching, data extraction and data cleanup skills in this course.

Regular Expression is a powerful text processing tool for log mining, data parsing, cleanup and preparation.  Power and elegance of regular expression allows you to do complex data extraction and cleanup with very few lines of code.

Over 60% of the effort in big data projects is spent on data cleanup and preparation. Data can come from variety of sources including internal databases, log files, sensor generated data, Twitter, Facebook and so forth.  Having access to powerful regular expression tool will open up lot of opportunities for you on how you look at your data and what can you do with it.

This course contains over 25+ hands-on exercises, practical tips, quizzes and four projects to apply the new skills you learned in this class.  In the first project, we will be extracting useful information from unstructured text data from Robocopy tool, in the second project we will be on working on large data set generated by Sensors and in the third project we will look in to Health Care Systems that deal with Electronic Medical Records. ***NEW***Fourth project added on parsing Network Interface Configuration.

These exercises will demonstrate that with regular expression you can implement complex parsing with only a few lines of code

As a bonus, you will receive an Python Interactive Tool with Source Code for learning regular expression faster.

This course uses free Anaconda Python distribution tool for development and exercise.  This is an all video lecture with quizzes, full source code, downloadable list of data and patterns used.

Who is the target audience?
  • Data Scientists, Software Engineers and Developers
Compare to Other Python Courses
Curriculum For This Course
53 Lectures
4 Lectures 14:54

Where can you use regular expressions?  Class structure overview and teaching methodology

Preview 03:25

**UPDATE: Please Read Lecture 3 article for how to run interactive tool on newer Anaconda distributions with PyQt5**

Setup development environment from scratch:

Anaconda Python Environment, Course Notebook files and Learn Regex GUI Tool setup, Data Setup and Overview of Python Regular Expression Quick Reference Guide

Setup Python Development Environment and Solution

Learn Regex Interactive Tool - Additional Details

iPython Notebook Overview and run course notebook files

Preview 03:24
Regular Expression Usage and Demo
7 Lectures 25:01

Regular Expression Terminology used in this course

Coding tips to correctly handle patterns using raw strings

Preview 03:08

Shows different ways in which you can find a match for pattern in text

Preview 04:48

How do get all matches for a pattern.  Different ways of retrieving the matches

Preview 03:31

How to break a pattern into sub-patterns using Groups.  How are groups beneficial

Preview 03:59

Shows different ways of doing a find-replace capability using patterns and custom replacement logic

Preview 05:37

Shows how to split a text using patterns

Preview 01:34

Shows differences between python string and raw string.  Why raw strings are better for patterns

Preview 02:24

Regular Expression Usage Quiz
6 questions
Regular Expression Interactive Tool
2 Lectures 09:55

Shows how to open, launch and use interactive regular expression tool that comes with this course.  This tool is written in Python and uses Qt.

Preview 09:32

Setup Help - Interactive Tool
Regular Expression Language Overview
9 Lectures 36:44

Let's start with simplest building block: Single Character Patterns and how to use Set based match

Preview 04:44

Singe Character Pattern Quiz
3 questions

How to find matches using NOT operation

How to specify a range of characters using shortcut available in regular expression language

Set Negation, Range Characters

How to specify different ranges of characters, use of wildcard, escape special characters and use of control characters

Multi-Range, Wildcards, Escape, Controls Characters

How to provide instructions to regular expression engine to fine tune criteria for matching


Anchor Quiz
2 questions

How to write concise patterns using ready-made shortcuts known as character classes

Character Classes

How to specify repetition, upper and lower bounds, optional experssions

Quantifiers - Optional, Frequency of Occurence

Quantifiers Quiz
1 question

How to insert comments inside a regular expression pattern


If..Then...else style branching in regular expression

Conditional Expression

Summary of what we learned so far

Summary and Wrapup
Regular Expression Engine - Five Key Points
16 Lectures 01:04:19

Regular Expression Engine Overview

Regular Expression Engine Introduction

How Engine works internally to find a match

1. One Character at time

What order does Engine use to find a match

2. Left to Right

Left to Right Quiz
2 questions

What order does Engine use to find a match

2.1 Left to Right - One more example


Demo - Left to Right

How does engine handle quantifiers?  What does Greedy, Lazy and Back Tracking mean?

Greedy Example

3. Greedy, Lazy and Backtracking

Greedy Quiz
1 question

Lazy concept, example and demo

3.1 Lazy

How does engine perform exhaustive search to find the right match?

3.2 Exhaustive

Greedy hands-on demo

Demo - Greedy

Groups - What is it? How can you use it? Different types of groups

4. Groups - Indexed, Named, Non Capturing

Group Quiz
3 questions

Non capture groups to turn-off specific capability

Demo - Non Capture

How to refer back to a match inside the same pattern?  How to replace a matching text?

4.1 Groups - Back-reference, Substitution

What are look ahead and look behind? Where are they used and what capability does it provide

5. Look-Ahead and Look-Behind

Go forward only if certain pre-condition is met

5.1 Positive and Negative Look-Ahead

Go forward only if certain pre-condition is met before the current character

5.2 Positive and Negative Look-Behind

Demo - Negative Look-Ahead
Project 1 - Robocopy Log File Parsing with Regular Expression
2 Lectures 18:03

Overview of the project, how robocopy log is structured, what information is the solution going to extract

Overview and Scope

Strategy for solving the problem with regular expression, review of the solution and demo

Solution and Demo
Regular Expression Performance
7 Lectures 24:42

What can cause performance issues in patterns?


What type of patterns to watch for performance issues

Patterns Exhibiting Exponential Run Time - Under Partial Match Scenarios

Why is the performance degrading?  What is happening behind the scenes?

Root Cause

Various options for addressing the performance issue

How to fix performance issues?

Hands-on overview of all the concepts, solution with demo

Demo - Performance issue and fix

What is the difference between compiled regular expression objects and module methods?  When to use compiled objects?

Compiled Versus Module Regular Expression Methods

Demo of comparison between module and compiled object methods

Demo - Module Methods and Compiled Methods Performance
Project 2 - Intelligent Sensor Data Handling with Regular Expression
3 Lectures 16:29

Introduction to sensors and how they collect and store data


How to use regular expression to extract the data and convert to JSON. Solution walk-through and demo

Solution and Demo

Summary of how we use regular expressions

Summary and Wrapup
Project 3 - Health Care Electronic Medical Record
1 Lecture 07:30

In this project, we will use regular expression to extract information from hospital medical report files sent as HTML payload

Introduction, Solution and Demo
Project 4 - Network Configuration Parser
1 Lecture 00:03
Network Configuration Parser Problem
1 More Section
About the Instructor
Chandra Lingam
4.4 Average rating
1,144 Reviews
19,570 Students
6 Courses
Data Scientist and Solutions Architect

Chandra Lingam spent 15 years at Intel, developing and managing systems that handled hundreds of terabytes of worldwide factory data.  

Chandra is an expert on Amazon Web Services, mission critical systems and machine learning.  He has a rich background in systems development in both traditional IT data center and Cloud based infrastructure. For those new to AWS, he is uniquely positioned to guide you to become an expert in AWS Cloud Platform.

He has a Master's degree in Computer Science from ASU and Bachelor's degree in Computer Science from Thiagarajar College of Engineering, Madurai