Multiple Signals And Slots Python

PyQt5 has a unique signal and slot mechanism to deal with events. Signals and slots are used for communication between objects. A signal is emitted when a particular event occurs. A slot can be any Python callable. The signals are created with the signature of the slot to which they will be connected. The same signal can be emitted in multiple places. Now, let's define some slots that can be connected to the Circle's signals. Remember last time, when we said we'd see more about the @Slot decorator? We now have signals that carry data, so we'll see how to.

In Python every class can have instance attributes. By default Pythonuses a dict to store an object’s instance attributes. This is reallyhelpful as it allows setting arbitrary new attributes at runtime.

The signal and slot operation are used to handle events and signals of the objects or widgets at the python app development level. It will also enable communication between some designed objects. The following steps are needed for creating a Python signal and slot operations. QtCore.SIGNAL and QtCore.SLOT macros allow Python to interface with Qt signal and slot delivery mechanisms. This is the old way of using signals and slots. The example below uses the well known clicked signal from a QPushButton. The connect method has a non python-friendly syntax. 'Signals and slots are used for communication between objects. The signals and slots mechanism is a central feature of Qt and probably the part that differs most from the features provided by other frameworks'. I literally copied that off from the QT Signals and Slots documentation. Until recently I didn't really use signal and slots much in my python code. I knew about them but did not really.

However, for small classes with known attributes it might be abottleneck. The dict wastes a lot of RAM. Python can’t just allocatea static amount of memory at object creation to store all theattributes. Therefore it sucks a lot of RAM if you create a lot ofobjects (I am talking in thousands and millions). Still there is a wayto circumvent this issue. It involves the usage of __slots__ totell Python not to use a dict, and only allocate space for a fixed setof attributes. Here is an example with and without __slots__:

Without__slots__:

With__slots__:

Multiple Signals And Slots Python Compiler

The second piece of code will reduce the burden on your RAM. Some peoplehave seen almost 40 to 50% reduction in RAM usage by using thistechnique.

Multiple Signals And Slots Python Ide

On a sidenote, you might want to give PyPy a try. It does all of theseoptimizations by default.

Multiple Signals And Slots Python Cheat

Below you can see an example showing exact memory usage with and without __slots__ done in IPython thanks to https://github.com/ianozsvald/ipython_memory_usage