Introduction

The purpose of this exercise is to learn some basics of Python by manipulating RNA sequences.

Contents

• Getting set up
• Exercise
  • The goal
  • The script
    • Input
    • Output
    • Examples
    • Some hints to get you coding
• Acknowledgments
• License

Getting set up

At this point, you should have (1) an account on Github and (2) been introduced to the very basics of Git.

1. Login to your Github account.

2. Fork this repository, by clicking the 'Fork' button on the upper right of the page.

   After a few seconds, you should be looking at your copy of the repo in your own Github account.

3. Click the 'Clone or download' button, and copy the URL of the repo via the 'copy to clipboard' button.

4. In your terminal, navigate to where you want to keep this repo (you can always move it later, so just your home directory is fine). Then type:

   $ git clone the-url-you-just-copied
   

   and hit enter to clone the repository. Make sure you are cloning your fork of this repo.

5. Next, cd into the directory:

   $ cd the-name-of-directory-you-just-cloned
   

6. At this point, you should be in your own local copy of the repository.

   As you work on the exercise below, be sure to frequently commit your work and push changes to the remote copy of the repo hosted on Github.

Exercise

The goal

The goal of this exercise is for you to practice Python coding by editing a script (or module) for manipulating RNA sequences until it runs and passes a suite of tests.

Type ls in the directory of the repo you just cloned. You should see something like:

$ ls
LICENSE.txt
README.md
test_translate.py
translate.py

The file translate.py is where you will write your Python code. Go ahead and open it with your preferred text editor. You will see that the file is mostly filled with functions and their docstrings. Currently these functions don't do anything; they only call the pass statement, which does nothing and causes them to return None.

The file test_translate.py is a Python script that runs a series of tests on the translate.py script. Since that code doesn't exist yet, all of these tests currently fail. Try it:

$ python3 test_translate.py

Your goal is to add Python code to translate.py until these tests pass. Based on the functions' docstrings and the messages reported by failing tests, it should be clear what the functions in translate.py should be doing to pass the tests.

NOTE: You do NOT need to know how the tests work! You only need to add code to translate.py. The tests only care about what each function returns, not how the functions work.

NOTE: You do NOT need to change the code below the if __name__ == '__main__': line. Only the functions themselves need work.

Suggestions

• Make sure you are using Git to commit and push your work often as you work on this exercise.
• print statements are your friend while you are debugging.
• assert statements are also your friend.
• If a function is getting long, define your own new functions to keep the code as modular as possible.
• Once you get the script working and all the tests passing, think about how you might improve the script. For example:
  • What happens if a DNA sequence is passed to your functions? How would you want to handle this?
  • Should your functions only accommodate strings for the sequence argument? What if someone passes a list? a tuple? How do you want your functions to behave?
  • Should you have a default genetic code, so the caller doesn't always have to create and pass a big dictionary to your functions? How would you do this in a way that does not rely on global variables? How could you avoid globals and avoid creating multiple instances of the genetic code? This is a bit advanced, but a good solution might involve creating a class that manages genetic codes.

Good luck!

Acknowledgments

Material

This exercise was inspired by, and borrowed heavily from, the class notes and Python scripts written by Mark Holder, which can be found at https://github.com/mtholder/eebprogramming.

Support

This work was made possible by funding provided to Jamie Oaks from the National Science Foundation (DEB 1656004).

License

This work is licensed under a Creative Commons Attribution 4.0 International License.