Overview¶

In this reference guide you will learn what the project completeness refers to and how we manage it in Akeneo PIM. It will explain our technical and structure choices.

Goal¶

The Teamwork Assistant feature is about creating projects from a product selection that gives a vision on the enrichment progress to contributors (users in charge of the enrichment). Each project gives to the contributor their own completeness on the product selection, taking into account their permissions to edit or not product, attribute groups, locales and channels.

For example, if Bob can only edit the “Technical” attribute group of the “High-tech” category, he will see the project 100% complete if all attributes in the attribute group “Technical” of “High-tech” products in the project are filled in, even if other attribute groups are empty and required by the family. However, Julia, the owner of the project, will see that it is not complete if some attributes are not filled in in others attribute groups. The contributor sees the completeness of the project in terms of his own permissions, whereas the owner sees the completeness of all the project.

As every user will have his very own completeness depending on his permissions, we need to walk through every product to compute completeness for every user. As you can guess, it’s a really huge task that cannot be done synchronously.

One table to rule them all¶

From this introduction, let’s recap which data we need: - For each locale, - For each channel, - For each user, - Does the product - have at least an attribute filled in? - or is it complete?

Creating a table to gather all data we need to compute the completeness seems to be a good idea but we need some adjustments. It can’t be scalable if we do this for each user.

So let’s remove users from this table. And now, how can we retrieve the completeness for a user? In the project format, we have product filters. From those filters it’s easy to know which user is impacted by the product selection. To gain some time, we pre-calculate which user is impacted and we link them to project at its creation. But it’s not scalable either. If we add a user, its completeness could not be calculated because he is not linked to the project yet. The problem is resolved by linking user groups to project and not directly to users.

Some data are still missing. User groups permissions are not only about products but also about attribute groups.

Here is the final structure we needed (only data that are relevant for the demonstration are shown): - Pre-processing table:

• For each locale,

• For each channel,

• Does the attribute group,

• in the product,

• have at least an attribute filled in?

• or is it complete?

• Project model:

  • locale

  • channel

  • product filters

  • products (*)

  • user groups (*)

(*) As these fields are only used for the completeness calculation purpose and they have no sense from a business point of view, they are not mapped to doctrine. The products field from project model is a n - n table that helps to join project to pre-processing. The user groups field from project model is a n - n table that helps to know who is impacted by the product selection. These tables are filled thanks to the calculation step.

By cross-checking pre-processing table, project table, category accesses table, attribute group accesses table we are able to calculate those three little numbers that are the number of products not started to enrich, in progress and done in terms of a user and a products selection.

In ORM, the process of joining Project to Category access works as follows:

project -> project_products -> product_category -> category -> category_access

Project Completeness Format¶

One normalized, the completeness looks like this:

array:7 => [
  "isComplete" => (bool),
  "productsCountTodo" => (int),
  "productsCountInProgress" => (int),
  "productsCountDone" => (int),
  "ratioTodo" => (int),
  "ratioInProgress" => (int),
  "ratioDone" => (int),
]

This is the end¶

The drawback of this method is that the completeness is not really up-to-date. For the moment, the pre-processing data are computed once you save a project, when you save a product concerned by a project from the Product Edit Form and the sequential edit. Moreover, a command php bin/console pimee:project:recalculate is provided to help you to recalculate data according to your needs.

The advantage is that the regularity of the pre-processing data updating can be adjusted as required with this command. Before using this you should have a look to the scalability guide.

According to our benchmark on a catalog with 3.6 millions of product values, pre-processing those data is feasible during the night for many projects as we don’t pre-process all the catalog but only products concerned by projects and products that has been updated.