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How Do I Write Tests Using Pytest and Hypothesis?

Thu, Aug 31
10:30am-12pm ET

Unlock the Power of Python Testing

Overview

Join Cameron Riddell in this 90-minute seminar as he unravels the art of writing comprehensive tests using Pytest and Hypothesis. Discover how to go beyond mechanical testing and gain a deeper understanding of your Python code to ensure its correctness. Explore defensive programming techniques and learn how to use Hypothesis for reliable rapid prototyping.

Details

Effective testing is a critical aspect of writing reliable and maintainable Python code. In this 90-minute seminar, Cameron Riddell will guide you through the process of writing meaningful tests using Pytest and Hypothesis. You'll learn how to craft effective test cases, create test fixtures, and leverage the powerful features of Pytest and Hypothesis to ensure robust code testing. The session will include real-world examples and practical tips to improve the quality of your Python code through testing. By the end of the seminar, you'll have the knowledge and skills to take your testing game to the next level and produce more reliable and error-resistant Python applications.

Goals

  • Understanding the significance of meaningful tests in Python
  • Learning how to apply defensive programming techniques for rapid prototyping
  • Exploring the benefits of using Hypothesis for reliable testing

Audience

This seminar is targeted toward Python developers with prior experience and an intermediate skill level. If you want to improve your testing skills and gain confidence in writing reliable Python code, this session is for you.

How Do I Write “Constructively” Correct Code with Metaclasses & Decorators?

Thu, Sep 7
10:30am-12pm ET

Empower Your Code with Python's Object Construction Mechanism

Overview

Join James Powell in this 90-minute seminar as he delves into the powerful concept of leveraging Python's object construction mechanism to enforce code correctness. Discover how metaclasses, decorators, and other language features can be used to validate and coerce input data, define selective object hierarchies, and implement abstract base classes. Gain valuable insights into designing code that anticipates and prevents errors before they occur.

Details

Writing Python code that is correct, robust, and flexible is crucial for software development. In this 90-minute seminar, James Powell will guide you through advanced techniques using metaclasses, decorators, and other powerful language features. Learn how to utilize Python's object construction mechanism to apply transparent constraints to your programs. Explore input validation and coercion techniques to ensure data integrity. Dive into defining selective object hierarchies to model complex relationships efficiently. Uncover how to create your own abstract base classes (better than the abc module!) to establish contracts and improve code maintainability.

By the end of the session, you'll have the knowledge and skills to harness Python's object construction capabilities for code that is reliable and maintainable.

Goals

  • Understanding the applications of metaclasses, decorators, and other object construction mechanisms in Python
  • Leveraging transparent constraints for input validation and data integrity
  • Techniques for defining selective object hierarchies and improving code maintainability

Audience

This seminar is targeted toward Python developers with prior experience and an intermediate skill level. If you want to improve your testing skills and gain confidence in writing reliable Python code, this session is for you.

How, When, and Why Should I Use PEP-484 Type Hinting?

Wed, Sep 13
10:30-11:30am ET

Mastering PEP-484 Type Hinting in Python

Overview

Join Cameron Riddell in this 60-minute seminar as he explores the relatively new addition of type hinting to Python. Discover when and how to use type hints effectively to improve code clarity, debugging, and early error detection. Explore the benefits of using type hint information to catch possible errors before they even occur.

Details

PEP-484 introduced type hinting to Python, making it easier to write more reliable and maintainable code. In this 60-minute seminar, Cameron Riddell will guide you through the practical applications of type hinting in Python. Learn how to use type hints to improve code readability and debugging, and catch potential errors during development. Gain valuable insights into the benefits of type hint information for enhancing code quality and preventing bugs.

Goals

  • Understanding the importance and benefits of PEP-484 type hinting in Python
  • Learning how to effectively use type hints for code clarity and debugging
  • Techniques for using type hint information to catch errors early

Audience

This seminar is targeted toward Python developers with prior experience and an intermediate skill level. If you want to improve your testing skills and gain confidence in writing reliable Python code, this session is for you.

How do I Check that my Data and Analyses are Correct?

Wed, Sep 30
10:30-11:30am ET

Ensure Accurate Data Analyses in Python

Overview

Join James Powell in this 60-minute seminar as he unravels the art of performing data analysis with confidence in Python. Explore the challenges of data analysis pipelines and learn how to write robust analyses that have observable hooks. Discover methods for data cleaning and validation to avoid silent errors that can pollute your results.

Details

Data analysis in Python presents unique challenges, as silent errors in data pipelines can lead to misleading results. In this 60-minute seminar, James Powell will guide you through essential techniques for writing reliable data analyses in Python. Learn how to structure your analyses with observable hooks to peek at data at various steps. Dive into data cleaning methods to ensure data integrity and accuracy. By the end of the session, you'll be equipped to perform data analyses with confidence and produce accurate results.

By the end of the session, you'll be equipped to perform data analyses with confidence and produce accurate results.

Goals

  • Understanding the challenges of data analysis in Python
  • Learning data cleaning methods for data integrity
  • Techniques for structuring analyses with observable hooks

Audience

This seminar is targeted toward Python developers with prior experience and an intermediate skill level. If you want to improve your testing skills and gain confidence in writing reliable Python code, this session is for you.

Past seminars and classes:

Matplotlib's Backend API for Customized Plotting

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Training: How Do I Know If My pandas Will Be Slow?

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Training: How do I Measure
(and Debug) the Performance of my Code?

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Training: How Do I Know If My Python Will Be Slow?

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Training: How Do I Tighten My Iteration Loop?

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Everything About Python Concurrency

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Everything you ever wanted to know about Asyncio

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On the Spot, Live-Coded Data Visualizations

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You Need to Try Bokeh

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Animations with Matplotlib & ipyvizzu

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You Should Know Polars

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Write a Telegram Bot in Python

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Bot-Writing Strategies:

Generator Coroutines

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Build a Discord Bot in Python

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Bot-Control Strategies:

Dashboards

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Spaces in Filenames?
Come on!

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Let's Rewrite itertools

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About Us:
Don't Use This Code is a professional training, coaching, and consulting company. We are deeply invested in the open source scientific computing community, and we are dedicated to bringing better processes, better tools, and better understanding to the world.