Introduction to PyQt4. Home > Python and PyQt4 > Introduction to PyQt4 Creating an application in PyQT4 may be done in a few ways.
The most common one is to use QTDesigner, which we get with QT. QTDesigner let us draw the GUI which is very handy for complicated interfaces. We can place widgets on the window, add names etc. To create an application in PyQT4 you have to: Create the GUI in QTDesignerSet names in the Property Editor to ease coding of the application (QTDesigner)Using pyuic4 create the python GUI classCall the application using that GUI classExtend it with our own slotsWhen you use a widget you go to PyQt's Classes and check methods of each used widgets. Nathan Horne – Technical Artist » PyQt and Maya 2011. Re-posting some information here that I had posted on TD club: Here’s a quick little bit of code showing how to create a custom GUI class using pyqt (Almost all the pyqt examples use this over using some form of .ui file, because it allows for much more control).
You can also use it in combination with ui files thanks to pyqt’s uic module. QT does not require objects to have “names”, but if you ever want to find your pyqt objects using MQtUil.findControl then you need to assign it a name using OBJECT.setObjectName(“AwesomeWindow”). First programs in PyQt4 toolkit. HomeContents In this part of the PyQt4 tutorial we will learn some basic functionality.
This page explains our final version (219 bytes). We initially worked alone but then exchanged ideas and tricks, so erling & mathewsb deserve most of the credits! Our code was originally 226 bytes, but "Cosmologicon" pointed out a way to save three whole bytes, bringing us to 223 bytes. 9.8. functools — Higher-order functions and operations on callable objects — Python v2.7.2 documentation. New in version 2.5.
Source code: Lib/functools.py The functools module is for higher-order functions: functions that act on or return other functions. In general, any callable object can be treated as a function for the purposes of this module. Mediawiki-parser/parsers.rst at master · erikrose/mediawiki-parser. Essential Python Reading List. Here’s my essential Python reading list.
I’ve tried to order the items so you can pause or stop reading at any point: at every stage you’ll have learned about as much possible about Python for the effort you’ve put in. The Zen of Python The Zen of Python is so short I can include it here in its entirety. Typing import this in an interpreted session gives a pythonic spin on “Hello, world”. >>> import this The Zen of Python, by Tim Peters Beautiful is better than ugly. Python functional programming for mathematicians « mvngu. This tutorial discusses some techniques of functional programming that might be of interest to mathematicians or people who use Python for scientific computation.
We first start off with a brief overview of procedural and object-oriented programming, and then discuss functional programming techniques. Along the way, we briefly review Python’s built-in support for functional programming, including filter(), lambda, map() and reduce(). The igraph library for complex network research. NodeBox. NodeBox is a Mac OS X open-source application for creating 2D visual output (static or animated) using Python programming language.
The application targets an audience of designers, with an easy set of state commands that is both intuitive and creative. It is essentially a learning environment and an automation tool. NodeBox also allows PDF and Quicktime export, as well as importing vector files from Adobe Illustrator. Thumbnail gallery. Computational Legal Studies™ | Computational Legal Studies™ Programming Dynamic Models in Python. In this series of tutorials, we are going to focus on the theory and implementation of transmission models in some kind of population.
In epidemiology, it is common to model the transmission of a pathogen from one person to another. In the social sciences and law, we may be interested in thinking about the way in which individuals influence each other’s opinions, ideology and actions. These two examples are different, but in many ways analogous: it is not difficult to imagine the influence that one individual has on another as being similar to the infectivity of a virus in the sense that both have the ability to change the state of an individual. One may go from being susceptible to being infected, or from unconvinced to convinced. Additionally, social networks have become an important area of study for epidemiological modelers.