Welcome back to our mini series on Turba.
Part I covered all the features and integrations provided by Turba.
Part II gives a dive into implementation, code structure etc.
Part III will consist of proposals for a changed architecture.
In the first chapter we looked at Turba’s features, APIs, Protocols. In the current installment, I want to present the concepts and structure of the code.
Turba is among the oldest horde applications. As such, it contains parts from various stages of Horde’s development.
Basically, it’s a layered architecture, but not fully fleshed-out or fully separated.
- Presentation layer
- Application Logic Layer
- Storage/Backend layer
This is plugged together with some framework-provided integration points
- with the sync services and inter-app API, RPC
- with the portal/blocks service
- with the Backup API
- with the Content Tagger
Presentation Layer.
Turba provides both a desktop UI and a mobile UI. The following is mostly about the desktop UI. Blog de culturismo total fitness de lee hayward: debes probar estos entrenamientos musculares híbridos primobolan depot inicio – culturismo femenino y control de la natalidad, entrenamientos de culturismo femenino youtube – la casa de juegos del kama sutra negro.
Turba’s UI is organized into client pages rather than using a controller/route approach. This means, user visible URLs include files with a .php suffix.
The client pages build the UI, but are also API endpoints in a very traditional sense, catch interaction from forms or buttons as get variables and trigger actions in the backend
A representative example:
https://github.com/horde/turba/blob/master/search.php#L155
try {
$share = Turba::createShare(strval(new Horde_Support_Randomid()), $params);
$vid = $share->getName();
} catch (Horde_Share_Exception $e) {
$notification->push(sprintf(_("There was a problem creating the virtual address book: %s"), $e->getMessage()), 'horde.error');
Horde::url('search.php', true)->redirect();
}
Typically the top part of each client page is initializing the application, catching request and environment/session variables, setting up the business objects.
The middle part usually orchestrates actions depending on present or missing parameter scenarios.
The lower part will actually output the Horde Topbar, utility javascript, and the actual page content.
A rather extreme example is the data import/export part: https://github.com/horde/turba/blob/master/data.php
It contains mappings, attribute filtering, a longer cascade of if’s and switch statements and after about 360 lines, the actual UI logic starts.
This might sound messier than it really is. Actual functionality is mostly factored out into separate classes and the UI uses both some View classes and a form library.
Turba’s UI is heavy in forms and tables for the very reason that editing and displaying a highly configurable addressbook with hundreds of fields of data is
very crud-like by nature.
The Turba UI uses three types of helpers to compose the UI:
- View classes
- The Forms library
- HTML templates with PHP snippets
View Classes
The View classes are very similar to the horde/view library and replicate some of its functionality, but are not using or inheriting from it.
Forms Library
Turba is a prominent user of the horde/forms library.
This utility allows to dynamically compose forms or multiple fields, check for internal/formal validity of entered values, missing mandatory values, etc.
It couples both a readonly and editable representation with a lot of processing logic.
Forms relies mostly on server-generated HTML with small parts of javascript injected for usability improvements.
The JavaScript snippets may utilize PrototypeJs and Scriptaculous, two formerly popular mainstream libraries.
Templates
The HTML templates provide most of the actual presentation apart from the forms – though they also provide some HTML forms to drive interaction.
Mobile View
Turba provides a read-only, touch friendly mobile phone presentation based on jQuery Mobile. This is completely separate from the rest of the turba UI.
Application Logic Layer and Backend Layer.
These two layers are closely tied together so it makes sense to discuss them as one.
From a problem domain perspective, it would make sense to expect these items:
- Multiple addressbook sources or backends. These are individual configurations using drivers. Multiple sources on the same ldap driver can represent different directories or different views on one.
- Addressbooks
- Addressbook entries or contacts
- Groups which are both entries and contain entries.
Turba’s logic layer consists of
- Representations of actual addressbook entries via the Object and Object_Group classes.
- A collection of reusable static functions in the Turba class.
- Parts of the base backend driver.
- Exporters/Importers for formats like LDIF and vCard.
- specialised forms which deal both with presentation and state transformations.
Turba Objects and Groups are the common ground here. The objects glue together the actual data from the driver, files from VFS, permissions managed by the driver, the object’s change history and tags in the tagger app.
Groups are the only subtypes of Objects or Entries. Other subtypes suggested by the vcard standard like organisations or locations get no special treatment. Groups act as virtual addressbooks or views on addressbook data.
Turba’s groups only work with turba-accessible contacts. They cannot reference external contacts from other sources.
The addressbooks don’t really show up as entity objects. They are arrays of passive data managed by different parties.
This makes part of the logic a little hard to reason about and to setup unit tests.
A lot of Turba’s logic is data transformation. Backends have a native representation of data as SQL columns, LDAP objects, etc… as well as possibly native key names.
A person’s name may be a column “object_lastname” in one backend, but an attribute “givenName” in another one.
This is complicated by a highly configurable list of fields each backend can hold.
A driver transforms these native formats into a uniform format, transform date strings into date objects, handle blobs etc…
Both the driver dependent format and the “turba” format are hashes. It is up to the driver to actually generate a list object containing individual addressbook entry objects.
Another functionality delegated to the driver is deriving TimeObjects from addressbook data. TimeObjects are really not objects but hashes, representing anniversaries or birthdays.
Permission management in turba is using three distinct approaches:
- The permission system allows restricting who can view or edit a certain addressbook
- One addressbook source, usually the SQL db, can be configured as using the Shares system. In this case, the user can delegate access to addressbooks to other users or groups or make them world readable
- The backing technology can restrict the user further. For example, the LDAP driver can be used to either bind using a service credential or using the user’s credential. Different users could have completely different data presented based on LDAP ACLs.
In the next article of this series, I am going to propose some modernisation approaches for Turba and discuss how they bring benefits in maintaining or extending the software vs being a tedious refactoring exercise.
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