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Python GUI Programming with Tkinter, 2nd edition

You're reading from   Python GUI Programming with Tkinter, 2nd edition Design and build functional and user-friendly GUI applications

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Product type Paperback
Published in Oct 2021
Publisher Packt
ISBN-13 9781801815925
Length 664 pages
Edition 2nd Edition
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Author (1):
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Alan D. Moore Alan D. Moore
Author Profile Icon Alan D. Moore
Alan D. Moore
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Toc

Table of Contents (22) Chapters Close

Preface 1. Introduction to Tkinter 2. Designing GUI Applications FREE CHAPTER 3. Creating Basic Forms with Tkinter and Ttk Widgets 4. Organizing Our Code with Classes 5. Reducing User Error with Validation and Automation 6. Planning for the Expansion of Our Application 7. Creating Menus with Menu and Tkinter Dialogs 8. Navigating Records with Treeview and Notebook 9. Improving the Look with Styles and Themes 10. Maintaining Cross-Platform Compatibility 11. Creating Automated Tests with unittest 12. Improving Data Storage with SQL 13. Connecting to the Cloud 14. Asynchronous Programming with Thread and Queue 15. Visualizing Data Using the Canvas Widget 16. Packaging with setuptools and cxFreeze 17. A: A Quick Primer on reStructuredText 18. B: A Quick SQL Tutorial 19. Other Books You May Enjoy
20. Index
Appendices

Creating simple graphs using 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

Working with another data analyst at ABQ, you develop 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. The query looks like this:

SELECT
  date - (SELECT...
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