Regular Expressions Regex with C NET Easy and Fast

Regular Expressions Regex with C NET Easy and Fast

What you’ll learn

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

Requirements

Familiarity with C# and .NET

Description

Hi, and welcome to the Regular Expressions (Regex) with C# .NET – 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 projectsI am Chandra Lingam, and I am your instructor.Here are some typical uses of regular expressionPattern DetectionLook for occurrences of a pattern using a concise languageData PreparationData clean-up and preparation is often one of the most time-consuming activitiesYou can define the structure of data as a regex pattern and parse dataOne good application of this is AWS Glue and Athena.You can use regex to define the structure of a record in a text file, and query the file using SQLInput ValidationYou can implement a client-side check for input validationFor example, your app can guide the user to provide data in the correct format.As part of the zero-trust architecture, you need to validate input to your microserviceWith regex, you can verify and validate data payloads in your serviceCloud ServicesSeveral cloud services use regex for advanced configuration.With the AWS web application firewall, you can allow or deny traffic based on a regex patternIn Google Workspace, you can use regex for content filtering, Gmail route configuration, and to search for content in google docsIn Google Analytics, you can use regex to locate and transform matching data in your data setRegex is also supported by several products such as SAP, Oracle, and SQL ServerCurriculumHere is a brief course outline:In the Regex features section, you will get familiar with various regex methods, their purpose, and how-to unit test your patternIn the regex language section, you will learn how to write patterns – starting from the simplest of patternsYou will also learn to incorporate regex in your HTML input types for validationRegex engine puts the onus on the developers, that is us, to write efficient patternsYou will gain knowledge of regular expression engine that will help you write optimal patternsThere are several exercises for you to apply your new skillsWe then look at performance and how poorly written patterns can degrade exponentiallyHow to optimize the patterns and address performance issuesIn .NET, there are a few different ways to interact with the regular expression classYou will gain insight into what method is appropriate for a given performance requirementThere are four hands-on projects in this courseYou 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 formatYou will get prompt support through the course Q&A forum and private messaging.I am looking forward to meeting you

Overview

Section 1: Introduction

Lecture 1 Introduction

Lecture 2 Increase the speed of learning

Lecture 3 Source Code Setup

Lecture 4 Join us for the Live Q&A – Every Month!

Section 2: .NET Regex Features

Lecture 5 Introduction to Regex Features

Lecture 6 Development Environment Setup and Pattern Representation

Lecture 7 Regex IsMatch and Unit Testing

Lecture 8 Match, Matches, and Groups

Lecture 9 Find-Replace, Split

Lecture 10 Learn Regex Interactive Tool

Section 3: .NET Regex Language

Lecture 11 Downloadable Resources

Lecture 12 Single Character Patterns

Lecture 13 Anchors

Lecture 14 Character Classes

Lecture 15 Quantifiers

Lecture 16 HTML input validation example

Lecture 17 Input Validation Example (Browser)

Lecture 18 Instructions for Quiz and Exercise

Section 4: .NET Regex Engine – Behind the scenes

Lecture 19 Downloadable Resources

Lecture 20 One character at a time

Lecture 21 Left to Right

Lecture 22 Lab – Left to Right

Lecture 23 Greedy, Lazy and Backtracking Analogy

Lecture 24 Greedy, Lazy and Backtracking Examples

Lecture 25 Lab – Greedy, Lazy and Backtracking

Lecture 26 Groups, Backreference, Replacement

Lecture 27 Lab – Groups, Backreference, Replacement

Lecture 28 Look Ahead

Lecture 29 Look Behind

Lecture 30 Exercise – Currency Symbol

Lecture 31 Solution – Currency Symbol

Lecture 32 Exercise – Match a number

Lecture 33 Solution – Match a number

Lecture 34 Exercise – List all cars not made by Honda

Lecture 35 Solution – List all cars not made by Honda

Lecture 36 Exercise – Webserver Log Parser

Lecture 37 Solution – Webserver Log Parser

Lecture 38 Exercise – Filter by price

Lecture 39 Solution – Filter by price

Lecture 40 Exercise – List cars that meet specified criteria

Lecture 41 Solution – List cars that meet specified criteria

Lecture 42 Exercise – Password Validation

Lecture 43 Solution – Password Validation

Section 5: .NET Regex Performance

Lecture 44 Downloadable Resources

Lecture 45 Exponential degradation – example of bad patterns and performance implication

Lecture 46 How to correct performance issues and optimize pattern

Lecture 47 Static, Instance, and Compiled Directive

Lecture 48 Lab – Performance Test with Static, Instance and Compiled Directive

Section 6: Project 1 – Log Parser

Lecture 49 Log Data Parser Objective

Lecture 50 Exercise 1 – Write a pattern to capture header information

Lecture 51 Exercise 2 – Write a pattern to capture error message

Lecture 52 Exercise 3 – Write a pattern to capture metrics

Lecture 53 Solution – How to write log parser regex patterns

Lecture 54 Solution – Log Data to JSON

Section 7: Project 2 – IoT Sensor Data

Lecture 55 Sensor Data Parser Objective

Lecture 56 Exercise 1 – Capture Date Value

Lecture 57 Exercise 2 – Capture Temperature and Humidity Value

Lecture 58 Solution – How to write sensor data patterns

Lecture 59 Solution – Sensor Data to JSON

Section 8: Project 3 – Health Care Data

Lecture 60 Health care Data Parser Objective

Lecture 61 Exercise 1- Cleanup pattern

Lecture 62 Exercise 2 – Write a pattern to capture a row

Lecture 63 Exercise 3 – Write a pattern to capture a cell

Lecture 64 Solution – How to write health care data patterns

Lecture 65 Solution – Health care data to CSV

Section 9: Project 4 – Network Configuration Parser

Lecture 66 Network Configuration Parser

Lecture 67 Solution – Network Configuration Parser

Section 10: Interesting Question and Answers from the Discussion Forum

Lecture 68 How to Remove Embedded Comma Inside Double Quotes

Lecture 69 How to Extract Unit Number from Postal Address

Lecture 70 How to split text that uses comma and/or newline as separators

Section 11: Conclusion

Lecture 71 Congratulations!

System Administrators,Developers,Architects,Database Administrators

Course Information:

Udemy | English | 3h 39m | 1.39 GB
Created by: Chandra Lingam

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