Coding Exercises For Powerful Python

Coding Exercises For Powerful Python

Thank you for your interest in Powerful Python Bootcamp. Set aside 45-60 minutes to watch the videos and complete the following coding exercises.

Step 1. Download Exercise Files

Download ZIP

Download the file (PowerfulPythonSample.zip), un-zip it, then go to the next step:

Step #2. Watch The "Labs" Video

These "labs" are coding exercises designed to QUICKLY teach you advanced Python concepts, and put them into action. Watch this video:

After this video, do helloworld.py in your courseware. You'll find it in the "labs" folder. If you need a hint, peek in the "solutions" folder.

When you finish, continue to the next step:

Step #3. OOP Exercise

After this video, do oop.py in your labs folder. Peek in the solutions folder if you need a hint.

NOTE: Because different applicants have different backgrounds and strengths, you do NOT need to complete the lab and make all tests pass. Time box this to 10-15 minutes, completing it if possible, but otherwise getting as far as you can.

When you finish, continue to the next step:

Step #4. Function Abstraction Exercise

Watch this Video:

After this video, do keyfunc.py in your labs folder. Peek in the solutions folder if you need a hint.

Again, time box this to 10-15 minutes, completing it if possible but otherwise just getting as far as you can in that time.

Step #5. Compare

Look at the provided solutions, and compare to the code you wrote. Is it different? If so, what lessons does this teach you about writing high-quality Python code?

Step #6. Evaluate

  • Were you able to follow along the sample videos?
  • Were you able to (mostly) complete the labs?
  • Do you feel like it was a good challenge level for you, and you are excited to learn more?
  • What did you learn when comparing your code to the official solutions?

If the answer is YES to all of these, then Powerful Python Bootcamp is for you.

(The labs on this page are simplified, shortened versions of the course material in Powerful Python Bootcamp. You can get more realistic, complex lab samples here.)

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