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# The Two Threads

Release: | trunk
Date: | November 03, 2011

Most users of Camelot won’t need the information in this Chapter and can simply enjoy building applications that don’t freeze. However, if you start customizing your application beyond developing custom delegates, this information might be crucial to you.

## Introduction

A very important aspect of any GUI application is the speed with which it responds to the user’s request. While it is acceptable that some actions take some time to complete, an application freezing for even half a second makes the user feel uncomfortable.

From an application developer’s point of view, potential freezes are everywhere (open a file, access a database, do some calculations), so we need a structural approach to get rid of them.

Two different approaches are possible. The first approach is split all possibly blocking operations into small parts and hook everything together with events. This is the approach taken in some of the QT classes (eg.: the network classes) or in the Twisted framework. The second approach is to use multiple threads of execution and make sure the blocking operations run in another thread than the GUI.

Events :
  - No multi-threaded programming needed : no deadlocks etc.
  - Every single library you use must support this approach
Multiple threads :
  - Scary : potential race conditions and deadlocks
  - Can be used with existing libraries

The Camelot framework was developed using the multi-threaded approach. This allows to build on top of a large number of existing libraries (sqlalchemy, PIL, numpy,...) that don’t support the event based approach.

## Two Threads

To keep the problems associated with multi-threaded programming under control, Camelot runs only two threads for its basic operations. Those threads don’t share any data with each other and exchange information using a message queue (the way Erlang advocates). This ensures there are no deadlocks or race conditions.

The first thread, called the GUI Thread contains the QT widgets and runs the QT event loop. No blocking operations should take place in this thread. The second thread contains all the data, like objects mapped to the database by sqlalchemy, and is called the Model Thread.

This approach keeps the problem of application freezes under control, it won’t speed up your application when certain actions take a long time, but it will ensure the gui remains responsive during those actions.

## The Model Thread

Since every single operation on a data model is potentially blocking (eg : getting an attribute of a class mapped to the database by sqlalchemy might trigger a query to the database which might be overloaded at that time), the whole data model lives in a separate thread and every operation on the data model should take place within this thread.

To keep things simple and avoid the use of locks and data synchronization between threads, there is only one such thread, called the Model Thread.

Other threads that want to interact with the model can post operations to the model thread using its queue

    from camelot.view.model_thread import get_model_thread

    mt = get_model_thread()
    mt.post(my_operation)

where ‘my_operation’ is a function that will then be executed within the model thread.

## The GUI Thread

Now that all potentially blocking operations have been move to the model thread, we have a GUI Thread that never blocks. But the GUI thread will need some data from the model to present to the user.

The GUI thread gets its data by posting an operation to the Model Thread that strips some data from the model, this data will then be posted by the Model thread to the GUI thread.

Suppose we want to display the name of the first person in the database in a QLabel

    from camelot.view.model_thread import get_model_thread
    from PyQt4 import QtGui

    class PersonLabel(QtGui.QLabel):

      def __init__(self):
    QtGui.QLabel.__init__(self)
    mt = get_model_thread()
    mt.post(self.strip_data_from_model, self.put_data_on_label)

      def strip_data_from_model(self):
    from camelot.model.authentication import Person
    return Person.query.first().name

      def put_data_on_label(self, name):
        self.setText(name)

When the strip_data_from_model method is posted to the Model Thread, it will be executed within the Model Thread and its result (the name of the person) will be posted back to the GUI thread. Upon arrival of the name in the GUI thread the function put_data_on_label will be executed within the GUI thread with as its first argument the name.

In reality, the stripping of data from the model and presenting this data to the gui is taken care off by the proxy classes in camelot.view.proxy.

## Actions

## Proxy classes

## Application speedup

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