Latest Posts

I stopped working on the Osm Admin project, for financial reasons. Did it hurt? A lot. Was it necessary? Unfortunately, yes. This post is a short retrospection on this matter.

After 3 days of intensive work, I've got dot syntax working!

Along the way, I refactored the query internals once again, which reminds me a heuristics saying that you've got to implement something three times to get it right :)

New query implementation uses the concept of formulas - SQL-like expressions used for selecting, filtering and sorting data. Currently, formulas are quite limited, but with time, they should be a really powerful feature.

I decided to support selecting, filtering and ordering by properties of a related object using dot syntax: product.price, parent.level. This syntax will automatically join the table that stored related objects.

I realized that implementing joins requires a better query model than my current naive wrapper around Laravel query. This article describes the new query model.

This article is about running SELECT and INSERT queries on data objects stored in the database.

In short, use the query() function. It runs on top of Laravel Query\Builder. It handles the mapping of data class properties onto table columns, and initiates the computation of indexed properties.

Currently, you can only SELECT and INSERT, other operations are coming soon.

Today, I implemented computation of indexed properties during insert. The implementation dictated some changes in indexed property definitions compare to the initial design, and how indexers are reflected into the data schema.

Also, I implemented a table query class working on the top of Laravel Query\Builder. More about it next time, for now I'll review how indexed properties are computed during INSERT operation.

It's often needed to compute, or index, data in database tables based on data in other tables.

This article is the first sketch of a consistent indexing solution.

I've finished refactoring how Osm Admin stores data objects in the database. Also, in order to support multi-website, multi-vendor, multi-language applications, I've introduced the concept of scopes.

Most reasoning from the first version is still valid, so let's take a fresh look of what's changed.

I developed dehydrate()/hydrate() functions for a very practical need - storing the data class schema:

• in cache - to reduce processing time spent on reflection;
• and in database - to compare current and new database schema, and only add new tables and columns.

This article describes the information stored in the schema, and unit tests that I prepared in order to be sure that schema classes are property hydrated.

As described in Migrations, most data objects of the same class will be stored in a database table.

But what about subclasses? In an e-commerce application, bags, dresses, and digital products, collectively known as subclasses, are all products stored in products table, and they may have bad-specific, dress-specific or digital product specific properties that should also be stored there.

This article describes how subclasses are defined and stored in Osm Admin.

Different data classes have repeating structural patterns. For example, most data classes stored in database tables have the auto-incremented id property. Use PHP traits to effectively introduce the same properties to different data classes over and over again.

I partly implemented data schema migration. It takes data class definitions, and incrementally creates or alters underlying database tables.

The article below describes how schema migration works, and what's not implemented yet, but most probably will be.

Note. This topic is continued in the new article.