Book Image

Python GUI programming with Tkinter

By : Alan D. Moore
Book Image

Python GUI programming with Tkinter

By: Alan D. Moore

Overview of this book

Tkinter is a lightweight, portable, and easy-to-use graphical toolkit available in the Python Standard Library, widely used to build Python GUIs due to its simplicity and availability. This book teaches you to design and build graphical user interfaces that are functional, appealing, and user-friendly using the powerful combination of Python and Tkinter. After being introduced to Tkinter, you will be guided step-by-step through the application development process. Over the course of the book, your application will evolve from a simple data-entry form to a complex data management and visualization tool while maintaining a clean and robust design. In addition to building the GUI, you'll learn how to connect to external databases and network resources, test your code to avoid errors, and maximize performance using asynchronous programming. You'll make the most of Tkinter's cross-platform availability by learning how to maintain compatibility, mimic platform-native look and feel, and build executables for deployment across popular computing platforms. By the end of this book, you will have the skills and confidence to design and build powerful high-end GUI applications to solve real-world problems.
Table of Contents (23 chapters)
Title Page
Copyright and Credits
Packt Upsell

Creating simple graphs on the canvas

The first graph we want to produce is a simple line graph that shows the growth of our plants over time. Each lab has varying climate conditions, and we want to see how those conditions are affecting the growth of all plants, so the chart will have one line per lab showing the average of the median height measurements for all plots in the lab over the days of the experiment.

We'll start by creating a model method to return the raw data, then create a Canvas-based line-chart view, and finally create an application callback to pull the data and send it to the chart view.

Creating the model method

Suppose we have a SQL query that determines the day number of a plot check by subtracting its date from the oldest date in the plot_checks table, then pulls lab_id and the average of median_height for all plants in the given lab on the given day.

We'll run this query in a new SQLModel method called get_growth_by_lab():

    def get_growth_by_lab(self):