In previous posts, I talked about how we can use MySQL Shell to dump and load data using a multithreaded process and also how to export table data in different formats that can then be imported to a new MySQL instance. This post will discuss how we can copy data directly to another MySQL instance without performing separate dump and load operations.

Regular expressions are powerful but often misunderstood tools for developers. In recent posts, we have discussed subexpressions and back references (which are special types of subexpressions). This post will show examples of two other special subexpressions: look ahead and look behind.

We already discussed how we can use MySQL Shell to dump and load data using a multithreaded process. In this post, we will discuss ways we can export data from a table into different formats.

In my last regular expressions post, we discussed subexpressions and how to isolate specific parts of our pattern match. We can then use those subexpressions to replace parts of our pattern with other text. This post will discuss backreferences and how we can use them as part of our pattern match.

As I have discussed, regular expressions can be a powerful tool for developers. When we use regular expressions to match a pattern and need to replace part of that pattern, subexpressions make it much easier. Subexpressions are specific parts of a pattern that we can reference elsewhere in the process.

In my last post about regular expressions (regex), I offered up a solution to requirements to extract text a substring from a larger blob of text. Over the weekend, I was thinking about this solution and wanted to know if it was possible to meet the requirements using a solution based solely on a regular expression. It turns out it is.

In my last post, I demonstrated how we can use LucidORM to track and manage database changes. Today, I will discuss using seeders to populate our database.

I am rewriting an old web application to use AdonisJS. In my last post, I discussed some features of AdonisJS and initialized a new application. In today’s post, I will discuss my first foray into using database migrations with Lucid ORM.

Regular expressions are used to match patterns in a given block of text. In a previous post, I discussed some regular expression features of MySQL. The examples I provided allowed us to return rows based on a pattern match and replace instances of our pattern with another substring. In this post, I will discuss some other regular expression functions.

For those who do not know me very well, I am an avid golfer. I have managed a local golf league for the last 15 years. During that time, the league has become so popular that we had to split the league in two and have half of the golfers play on Tuesday night and the other half on Thursday. Quite a few years ago, I wrote a web application to help me manage the league. The web app started showing its age, and I decided it was time to rewrite it from scratch. I also decided to bring you all along for the ride.