Regular Expressions (Regex) with Python - Easy and Fast!

• Pattern Detection - Look for occurrences of a pattern using a concise language
• Data Preparation - Locate and transform data of interest
• Data Validation - Validate Input and Improve Security by Preventing Injection Attacks
• Learn Techniques to Write High-Performance Patterns
• Hands-on projects
• Complements Machine Learning Skills

Hi, and welcome to the Regular Expressions (Regex) with Python - Easy and Fast!

Regular Expression (regex) is a pattern detection language – they are typically used to search patterns in text, extract matching values, and data validation.

Regex is supported in many programming languages, including Python, C#, JavaScript, Perl, SQL, and more.

This course is designed to provide hands-on experience with regular expressions through various exercises and projects

I am Chandra Lingam, and I am your instructor.

Here are some typical uses of regular expression

Pattern Detection

Look for occurrences of a pattern using a concise language

Data Preparation

Data clean-up and preparation is often one of the most time-consuming activities

You can define the structure of data as a regex pattern and parse data

One good application of this is AWS Glue and Athena.

You can use regex to define the structure of a record in a plain text file, Create a table and query the file using SQL

Input Validation

You can implement a client-side check for input validation

For example, your app can guide the user to provide data in the correct format using regex.

As part of the zero-trust architecture, you need to validate input to your microservice

With regex, you can verify and validate data payloads in your service

Cloud Services

Several cloud services use regex for advanced configuration.

With the AWS web application firewall, you can allow or deny traffic based on a regex pattern

In Google Workspace, you can use regex for content filtering, Gmail route configuration, and to search for content in google docs

In Google Analytics, you can use regex to locate and transform matching data in your data set

Regex is also supported by several products such as SAP, Oracle, and SQL Server

Curriculum

The source code for this course is distributed using Github – so, you always have access to up-to-date code

As part of resources, you will get this high-quality cheat-sheet for regex language

And an interactive regex tool to write patterns

In the Python Regex features section, you will get familiar with various regex methods, their purpose, and how to unit test your pattern

In the regex language section, you will learn how to write patterns – starting from the simplest of patterns

You will also learn to incorporate regex in your HTML input types for validation

Regex engine puts the onus on the developers, that is us, to write efficient patterns

In this section, you will gain knowledge of regular expression engine that will help you write optimal patterns

There are several exercises for you to apply your new skills

We then look at performance and how poorly written patterns can degrade exponentially

You will learn how to optimize the patterns and address performance issues

There are four hands-on projects in this course

You will learn how to apply the regex for distinctly different data sets – unstructured log data, IoT sensor data, and parsing medical test data in HTML format

You will get prompt support through the course Q&A forum and private messaging.

I am looking forward to meeting you

Thank You!

Chandra Lingam

Cloud Wave LLC