µTraining: Become a Python Expert!

Don't Use This Code

Elevate your Python expertise in an intensive two-day, interactive micro-training!

Join us for a hands-on, interactive µtraining (“micro-training”) for programmers, data scientists, and researchers looking to improve their scripting, code-design, and use of advanced Python features! <h3>Details:</h3>This dynamic learning experience will focus on mastering advanced Python features such as generators, coroutines, and API design for remote communication. Led by seasoned instructors, this training will have you engaging in lively discussions and hands-on problem-solving sessions, where you’ll delve into the intricacies of state machines, create working prototypes, and craft robust interfaces. Uncover the power of Python’s iteration concepts, navigate through the world of generators and coroutines, and harness the capabilities of the itertools module.This unique training format ensures direct interaction with instructors and your peers, providing practical insights and immediate problem-solving guidance.Ready to reshape your Python journey? Join us for two days of immersive learning, where expertise meets real-world application! <h3>Goals and Outcomes:</h3>This µtraining is comprised of live discussion, hands-on problem solving, and code review with our instructors. By the end of this training, you will gain…<ul><li>Mastery over Python Generators and Coroutines: Gain a deeper understanding of Python generators and coroutines and how to apply them to common problems in your work.</li><li>Understanding of Advanced API Design: Create resilient interfaces that are readible, extensible, testable, and robust in the fast of ad hoc errors.</li></ul><ul><li>Practical Mastery of Python’s Iteration, Generators, and Coroutines: Develop hands-on expertise in writing fluent, high-quality, high-performance, correct Python code using all of the advanced features and tooling that the language has to offer.</li></ul>

<h2>Agenda</h2>In this two-day course, we will use the “Maze Runner” problem as our primary motivating example. You will write code that directs a robot to navigate simple mazes, while learning how to make the most of the core and advanced Python features, specific and generalized solutions to the problem at hand, and API design considerations when interfacing with remote devices. See below for more details and a sample exercise! <h3>Day 1: Navigating Simple Mazes with Generators</h3><h4>Tue. Dec 19, 10:30–12:00 and 13:30–15:00 US/Eastern</h4><ul><li>Introduces the maze navigation problem.</li><li>Discusses core and advanced Python features.</li><li>Explores specific and generalized solutions to the maze navigation problem.</li><li>Covers API design considerations when working with remote devices.</li></ul> <h3>Day 2: Coroutines &amp; State Machines</h3><h4>Thu. Dec 21, 10:30–12:00 and 13:30–15:00 US/Eastern</h4><ul><li>Dives into coroutines and state machines in Python.</li><li>Addresses the maze navigation problem using coroutines.</li><li>Discusses the use of generators, yield, and yield from.</li><li>Explores the differences between traditional states/transition models and generator coroutine modelings.</li><li>Touches on immediate vs retained modes of operation.</li><li>Covers the itertools module and iteration helpers.</li><li>Discusses the concept of pumping or priming and first vs last modalities.</li></ul>

<h2>Training Preview</h2> <h3>Problem Details</h3>You have a robot that needs to navigate a (small, square) maze (with 90° walls and rigid, unit spacing). There is no global information about the layout of the maze.Goal: navigate the robot to the exit.The robot can move forward but cannot move backward. The robot can turn in precise 90° increments clockwise or anticlockwise. You can communicate with the robot via the following request messages:<ul><li>start or stop moving (forward-only; snapped to single spaces)</li><li>start or stop turning clockwise or anticlockwise (snapped to 90° angles)</li><li>read front/left/right bumper sensor (i.e., has it hit a wall)</li><li>read overhead sensor (i.e., has it found the exit)</li></ul>For each of the above request messages, the robot will send a response to indicate its state:<ul><li>start moving → robot has started moving</li><li>stop moving → robot has stopped moving &amp; how far it has moved since it was last instructed (snapped to single spaces)</li><li>start turning → robot has started turning</li><li>stop turning → robot has stopped turning &amp; how far it has turned since it was last instructed (snapped to 90° angles)</li><li>read bumper → whether the robot is up against a wall</li><li>read overhead → whether the robot has exited the maze</li></ul>The robot is guaranteed to move in exact single spaces and turn at exact 90° angles; however, the robot’s motors will have arbitrary delays before starting an action, and movement or turning will sometimes be slower or faster. Therefore, you must confirm the action via the response. <h3>Sample Tasks and Questions</h3>Here is a small sample of the tasks we will work on using our "Maze Runner" example, answering the below questions (and more!) along the way.Tasks:<ol><li>Navigate the robot through a linear maze (one single corridor)</li><li>Navigate the robot through a T-junction where one side is a dead-end &amp; the other is the exit</li><li>Navigate the robot through an arbitrary maze (with left-wall hugging)</li><li>(Optional) Accommodate messaging faults (arbitrarily delayed or lost messages)</li></ol>and more...Questions:<ul><li>What is the difference between yield and return?</li><li>What is PEP-380 delegation to a subgenerator and yield from?</li><li>What is a generator coroutine in Python?</li><li>How do generator coroutine modelings of state machines differ from traditional states/transition modelings?</li><li>What are iteration helpers? How and why do I want to write my own? How do I write these properly?</li><li>What is pumping or priming? What are first vs last modalities?</li></ul>and much, MUCH more...<h3> </h3>

<h2>Presenter: James Powell</h2>James Powell is the founder and lead instructor at Don't Use This Code. A professional Python programmer and enthusiast, James got his start with the language by building reporting and analysis systems for proprietary trading offices; now, he uses his experience as a consultant for those building data engineering and scientific computing platforms for a wide range of clients using cutting-edge open source tools like Python, pandas, and React.He also currently serves as a Board Director of NumFOCUS, the 501(c)3 non-profit that supports all the major tools in the Python data analysis ecosystem (i.e., pandas, numpy, jupyter, matplotlib). At NumFOCUS, he helps build global open source communities for data scientists, data engineers, and business analysts. He helps NumFOCUS run the PyData conference series and has sat on speaker selection and organizing committees for 18 conferences. James is also a prolific speaker: since 2013, he has given over seventy conference talks at over fifty Python events worldwide.

<h2>Presenter: Cameron Riddell</h2>Cameron Riddell joined Don’t Use This Code in 2021. Prior to joining our team, he worked in academia studying various aspects of psychology, including the neural activity underlying social interaction, perception of taste, and human memory. His studies naturally led him to learn Python, which he has been writing for over 8 years with a strong emphasis on data analytics and scientific communication.As our resident pandas &amp; Matplotlib expert, Cameron takes a uniquely data-driven, analytical approach to his work and research. He enjoys sharing his knowledge both in and out of the classroom; in fact, he is ranked in the top 4% of all answerers on Stack Overflow. Thanks to his efforts, people overcome their coding challenges! His academic background and focus on programmatic thinking bring a great perspective to the training team at Don’t Use This Code.

<h2>Presented by: Don't Use This Code</h2>Don't Use This Code is a professional training, coaching, and consulting company deeply invested in open source technologies, centered around the PyData stack for scientific and numeric computing. We are dedicated to bringing better processes and a better understanding of these powerful tools.We are continually seeking new partners, clients, and engagements for our services. Organizations looking to better employ these tools would benefit from our wide range of training courses on offer (<a href="https://learning.dutc.io" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">learning.dutc.io</a>), ranging from an intensive introduction to Python fundamentals to advanced applications of Python for building large-scale production systems. Working with your team, we can craft targeted curricula to meet your training goals. We are also available for consulting services, such as building scientific computing and numerical analysis systems using technologies like Python and React.We pride ourselves on delivering top-notch training uniquely valuable to each individual attendee, and we do so by investing in three key areas: our content, our processes, and our contributors.

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µTraining: Become a Python Expert!

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