Scaling Python With Generators
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Scaling Python With Generators

Write Python That Gracefully, Robustly, And Effortlessly Handles As Much Data As You Can Toss At It.

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Dear fellow Python programmer,

If you want your Python code to gracefully handle increasing amounts of data...

Make your programs robust, responsive, and highly performant...

While deeply understanding one of the most powerful, yet mis-understood features of Python today...

What you need is called generators.

Now, maybe you know about the "yield" keyword already.

But no one has ever told you the higher-level design patterns for working with Python generator functions.

Or the mental model that lets you quickly troubleshoot any bug or issue you may run into with generators.

Or the principles of Scalable Composability, allowing you to construct memory-efficient internal data pipelines within any Python program.

It is a fact that these keys for Python generators are not widely known, yet allow you to infuse robust scalability into all your Python code from now on.

That is why Powerful Python has developed a full course for Python professionals, called:

Scaling Python With Generators


"Taking "Scaling Python With Generators" was like driving in rush hour traffic and having a clear fastlane appear out of nowhere just for me. A lane that gets me past the slowdowns right to my destination."

Bryan Stutts, Colorado, USA

What You Will Learn

1. How To Write Python Code That Performs Great Even Under Massive Stressful Data Loads

2. ​Understand A Fundamental "Power Feature" Of Python At The "Wizard Level" (Especially Helpful When You Need To "Think Fast" During Interviews)

3. ​How To Infuse Every Line Of Python You Write With Robust, High-Performance Scalability

"This course does an excellent job of explaining this compelling and often confusing feature of Python. The leisurely pace of the course makes it easy to follow. I now feel confident in using generators to scale my code. Thanks!"

John Tekdek, Milton Keynes, England

What's Included

1. Over 2.5 hours of instructional video

2. Extensive hands-on coding exercises ("Labs")

3. Full solutions

4. Lifetime access...

5. With all future updates and additions.

"Always looking for advanced Python resources and yours are first quality... Congratulations for a great work! And thanks for a GREAT service to the community."

Javier Novoa Cataño, Mexico City, Mexico

The Requirements

1. Ability to write simple Python scripts using functions, dicts and lists.

2. A recent version of Python 3.

3. About 9 hours to watch and re-watch videos, and do the "labs" (coding exercises).

4. Willingness to apply what you learn to the Python code you write outside of class.

"I am completely amazed by the coroutine concept. I did not read ANYTHING like this about generators ANYWHERE ELSE!

This wonderful course... Greatly structured... Good for advanced programmers who want to level up their skills. Once again, Thank you for making me a seasoned Python developer :)"

Shankar Jha, Bangalore, India

Course Videos

1 Course Intro (19 minutes)

2 Foundations of Generators (30 minutes)

3 Generator Patterns (16 minutes)

4 Iteration(12 minutes)

5 List Comprehensions (15 minutes)

6 Generator Comprehensions (5 And Other Comprehensions) ( minutes)

7 Passing In Data (Coroutines) (28 minutes)

Bonus: Overview of AsyncIO(14 minutes)

"An EXCELLENT course... explaining a variety of concepts and techniques, including the concepts and uses of coroutines, iterators and comprehensions. Thoroughly recommended!"

Tony Holdroyd, Gravesend, UK

"Another excellent Python class from an excellent instructor. Clearly illustrates concepts in Python scalability... Clear lectures, meaningful lab exercises... students will gain invaluable insight into Python internals."

Mike Clapper, Oklahoma, USA

"The course went deep into Python GEMS... Every time I go over a course by this instructor, I learn a lot. Which very much helps me in my day to day Python development."

Kapil Gupta, Gurgaon, India

"The course is excellent value for money. Recommended."

Tony Holdroyd, Gravesend, UK

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