Tutorials

Sign Up For Tutorials

The tutorials at PyCon Canada have a limited capacity of up to 60 people. If you're interested in attending one of the PyCon Canada tutorials, please sign-up in advance below. You can sign up by clicking the "edit" button in the top right of this page, and adding your name to the lists. If you do not have access to edit this page, please send us an email at speakers@pycon.ca Note that you must already have a ticket to PyCon Canada 2017 to attend.

We will also be using this list to send out any tutorial requirements (things that you should have installed on your laptop before arriving at the tutorial).

---

Writing tests that write themselves

David Kua

Saturday, November 18th, 2017 at 11:10 a.m.

Property-based testing is a powerful method of generating test cases from properties of your code. With a few lines of code you can have tests that create and test hundreds of examples and can catch edge cases in your code that you weren't even aware of. Originally only available for Haskell developers via the QuickCheck library, property-based tests can now be written in a variety of languages including Python. In this tutorial you will learn about the basics of property-based testing and how to get started writing property-based tests using the Python library Hypothesis. You will also learn how to add and use property-based tests alongside other tests in your existing codebases.

Software requirements:

To follow along, attendees will need working knowledge of Python and a laptop with Python 2.7+, pytest, and Hypothesis.

Add your name here:

1. Danial Gagne
2. Ke Sun
3. Steven Seguin
4. François Leblanc
5. Renaud Grandjean-Joyeux
6. Ankit Mittal
7. Hoa Du
8. Keefer Rourke
9. Dan Gale
10. David Ward
11. Ihtisham Mazhar
12. Nadia Tahiri
13. Cam Guinemer
14. Paul Gamble
15. Victoria Powell
16. Nik Sieber
17. Darrell Aucoin
18. Abbas Taher
19. Diana Gil
20. Emeric Vigier
21. Erik Hauner
22. Jason Bernhardt
23. Ludovic Demers
24. Nathan Blok
25. Tim Fenwick
26. Christine Gibson
27. Roberta Voulon
28. Steve Jackson
29. Emmanuel Thompson
30. Wajdi Al-Hawari
31. Nitesh Arora
32. Trish Gillett
33. Phil Isaac
34. Obiamaka Agbaneje
35. Annaelle Duff
36. Mohamed Konate
37. khaled kachkorian
38. Yann Parizeau
39. David Côté
40. Deept Ijoshi
41. Ahmad Akkaoui
42. Alexandre Tremblay
43. Seak Pek Chhan
44. Ghislain Bourgeois
45. Joshua Butler
46. Mark Iantorno
47. Dhia Ayachi
48. Saida Khazri
49. Michael Mulley
50. Olesya Baranova
51. François Lefebvre
52. Oleksandr Huziy
53. Ricardo Lima
54. Douglas Soares de Andrade
55. Ai O
56. Timothée Faucon
57. Paul Morelle
58. Javier Ramirez Martinez
59. Gary Graham
60. Amy Wooding
61. Mohamed Kerbachi
62. Ahmed Belgana

---

Python can do that? Building cross-platform graphical tools for Android and iOS with Kivy

Stephen Astels

Saturday, November 18th, 2017 at 2:20 p.m.

As developers at Learn Leap Fly, we have been using Python and Kivy to make innovative educational apps that run on Android and iOS devices. Along the way we have had to create tools to help us, for example, manage our library of sound and graphics assets. The Kivy library let us quickly create graphical tools for whatever task we needed to solve. We could then deploy them on Android and iOS for our team members for whom the instruction “You’ll need to pip install ...” would seem like gibberish.

In this tutorial we will describe our experiences with Kivy, with a focus on rapid tool development, and guide the audience through the creation of a simple multi-platform graphical tool.

Software requirements

• The tutorial will be using python 2.7. Alternatively, Kivy mostly works with Python 3. Mostly.
• You will need Jupyter Notebook and Kivy, as well as the notebooks and example data here.
• Easiest way to install Jupyter Notebook is by installing Anaconda
• NOTE that there is a bug in the current release of Kivy that might crash the install. Luckily the bug has already been fixed in the development (master) branch. I would recommend:
  • install Anaconda
  • create a conda environment (conda create --name myenv)
  • activate the environment ("source activate myenv" on macOS/Linux, Windows is a bit different)
  • install Kivy's dependancies as described on the Kivy Homepage but DON'T do the final "pip install kivy"
  • install the development branch of Kivy (pip install http://github.com/kivy/kivy/archive/master.zip)
• (Optional) We will show how to build Kivy apps for iOS. To do this yourself requires a Mac and the kivy-ios package.

Add your name here:

1. Danial Gagne
2. Radu Raicea
3. Shawn Elbaz
4. Keefer Rourke
5. Ihtisham Mazhar
6. Nadia Tahiri
7. Talha Mirza
8. Paul Gamble
9. Victoria Powell
10. Franco Saliola
11. Susie Saliola
12. Paul Pype
13. Erik Hauner
14. Jason Bernhardt
15. Christopher Palazzolo
16. John Palazzolo
17. Andrew Francis
18. Max Humber
19. Yinyi Hu
20. Steve Jackson
21. Emeric Vigier
22. Alejandra Cabrera
23. Sean Casey
24. Vincent Lizotte
25. Oleksandr Huziy
26. Timothée Faucon
27. Pierre Paul Lefebvre
28. Joel Babcock
29. Derrick Yang
30. Jen Garner
31. Félix Antoine Goudreault
32. Cody Antunez
33. Jonathan Dundas
34. Patricia Campbell

---

Simple made easy 2: a new infrastructure for microservices

Steve Jackson

Sunday, November 19th, 2017 at 11:50 a.m.

This tutorial illustrates how self-trained “citizen programmers” can employ Python to create exactly the Microservices they need and want. This empowers the stakeholders, and eases many of the cultural problems that so often bring conflict in software development work. The DSI methodology is inherently Agile, because it naturally supports the 12 Principles (without scrums, kanbans, standups, or micro-managing) DSI systems can be built so as to expose just a tiny attack surface. Disaster recovery based on immutable data storage can be engineered into each design. DSI is ideal for IoT data sources. Development of the microservices can proceed in parallel, in remote shops. Late-arriving change orders are not disruptive.

Software requirements

None. Just bring your curiosity.

Add your name here:

1. Mafinar Khan
2. Renaud Grandjean-Joyeux
3. Danial Gagne
4. Keefer Rourke
5. Nadia Tahiri
6. Cam Guinemer
7. Serge Basso
8. Paul Gamble
9. Victoria Powell
10. Nik Sieber
11. Abbas Taher
12. Erik Hauner
13. Jason Bernhardt
14. Jim Matchett
15. Nathan Blok
16. Tim Fenwick
17. Yinyi Hu
18. Roberta Voulon
19. Josh Baker
20. Philippe Casgrain
21. Marc-Antoine Parent
22. Nitesh Arora
23. Phil Isaac
24. Gary Graham
25. Dhia Ayachi
26. Dan Gale
27. Saida Khazri
28. Douglas Soares de Andrade
29. köusu
30. Mohamed Kerbachi
31. Ahmed Belgana
32. JPLemelin
33. Francis Bolduc
34. Joshua Butler
35. Andrew Jenssen
36. Jean-Philippe Mallette
37. Yanis Medjkoune
38. Jean-Paul Fiorini
39. Ryan Sampana
40. Kojo Idrissa
41. Zachary Bergeron
42. Gabriel Provencher
43. Shaun Hamelin-Owens
44. Timothée Faucon
45. Tristan Lescut

---

Matplotlib custom tools universe

Federico Ariza

Sunday, November 19th, 2017 at 1:55 p.m.

The tool API

• Discover the new ToolManager capabilities and how does it handle tools.
• Explore tool classes and see how easy is to create new tools to handle your specific needs

The work

We will not go to the moon (only 60 minutes), but you will do the basics so you can go on your own.

• Remove the clutter from the plot Toolbar and customize it to fit your needs (or my needs since I'm the one teaching).
• Create a tool to toggle legend visibility
• Add a tool for line color changing
• What about a tool for hiding/showing different lines?
• Get you started with your own tools

Software requirements

• Upstream version of matplotlib (master from github) installed and running
• GTK3 or Tk backends working (prefereably GTK3)
• Make sure the example matplotlib/examples/user_interfaces/toolmanager_sgskip.py works

Add your name here:

1. François Leblanc
2. Andry Randriamoeliarivony
3. Ankit Mittal
4. Hoa Du
5. Dan Gale
6. Jonathan Deng
7. Cam Guinemer
8. Allen P. Doss
9. Darrell Aucoin
10. Usama Mostafa
11. Dilhan Tanir
12. John Harrigan
13. Nassim Tabet
14. Miti Modi
15. Asieh Harati
16. Erik Hauner
17. Elvin Cordero
18. Ian Flores
19. Karim Yacout
20. Sepideh Ghafouri
21. Martin Denault
22. Emmanuel Thompson
23. Mohamed Kerbachi
24. Ahmed Belgana
25. Félix Antoine Goudreault
26. Jean-Philippe Mallette
27. Felix Archambault

---

Thinking in GraphQL with Python

Mafinar Khan

Sunday, November 19th, 2017 at 3:40 p.m.

GraphQL is a query language that facilitates data centric communication between clients and servers. It is designed to be language agnostic, and there is one or more implementations of it in almost all major languages. In this tutorial, I will focus on API designining with GraphQL through Python.

I would start off with introducing the concept of GraphQL, why was it made and what are the more natural type of problems it tries to solve. It will be followed by presentation of some minor use cases and how an API designer would go on thinking about the design. How Python and GraphQL come together and an introduction to the Graphene work-flow will precede the longest part of the tutorial, developing a real life Asset Tracking API with Django and Graphene. I had created RESTful asset tracking systems with Django few years back. I intend to create a similar and simplified version through GraphQL and explain every step along the way, with relevant and neutral experience comparisons when needed. My main focus will be on three "How to"-s in descending order of emphasis: i) How to Think, ii) How to Create, iii) How to Test.

Anyone with the knowledge of Python and web development with it would feel comfortable with the contents covered.

Software requirements

• A system with Python 2.7+ and pip
• We will be installing the following libraries during the tutorial
  • Django
  • graphene-django
• During the tutorial, please go to this live link on your computer so that you can see the live slides while I can focus on writing on the board.
• This repository will be used for the demo app.

Add your name here:

1. Ke Sun
2. Myles Braithwaite
3. Cam Guinemer
4. Serge Basso
5. Paul Gamble
6. Victoria Powell
7. Nik Sieber
8. Darrell Aucoin
9. Abbas Taher
10. Iruoma Nwabuzor
11. Kyle Connolly
12. Miti Modi
13. Erik Hauner
14. Jason Bernhardt
15. Tim Fenwick
16. Jens Nistler
17. Elvin Cordero
18. Cedric Jolly
19. Ian Flores
20. Yinyi Hu
21. Brad Dillon
22. Christine Gibson
23. Michael Mulley
24. Andre Prado
25. Roberta Voulon
26. Anarosa Paredes
27. Emmanuel Thompson
28. Andres Roget
29. Marc-Antoine Parent
30. Obiamaka Agbaneje
31. Mohamed Konate
32. Alejandra Cabrera
33. Sean Casey
34. Joshua Butler
35. Vincent Lizotte
36. Ricardo Lima
37. Saida Khazri
38. Douglas Soares de Andrade
39. Ai Onda
40. Timothée Faucon
41. Paul Morelle
42. Gary Graham
43. Mohamed Kerbachi
44. Ghislain Bourgeois
45. Éric Saulnier
46. Benoit Paquet
47. JPLemelin
48. Francis Bolduc
49. Yanis Medjkoune
50. Ryan Sampana
51. Jean-Paul Fiorini
52. Gabriel Provencher
53. Shaun Hamelin-Owens
54. Pascal de Ladurantaye
55. Thomas Kearvell
56. Alexandre Tremblay
57. Ankur Taxali
58. Nicolas Leblanc
59. Mounir Messelmeni
60. Jens Nistler
61. Steffen Zieger

---