Parallel Lists #

This lab introduces parallel lists.

Syllabus Topics [SL] #

• B2.2.2 Construct programs that apply arrays and Lists.
• B2.4.2 Construct and trace algorithms to implement a linear search and a binary search for data retrieval.

Key Vocabulary #

What are parallel lists? #

📖 Here is an example of parallel lists. Notice how information at the same index, across both lists, are associated.

cities = ['Beijing', 'Tokyo', 'Seoul', 'Busan']
country = ['China', 'Japan', 'South Korea', 'South Korea']

print(f"{cities[0]} is in {country[0]}") # Beijing is in China

[0] Set up #

💻 Go into your unit folder and clone your repo. Be sure to replace yourGithubUsername with your actual username.

cd ~/desktop/dpcs/unit02_data_structures
git clone https://github.com/isf-dp-cs/lab_parallel_lists_yourGithubUsername

cd lab_parallel_lists_yourGithubUsername

💻 Enter the Poetry Shell to start the lab. As a reminder, we will run this command at the start of each lab, but only when we are inside a lab folder.

poetry shell

👾 💬 Exiting the poetry shell

When you want to exit the shell, you can type exit or ^D

[1] Song Query #

👀 First, take a look at song_data.py and notice the parallel arrays with song metadata.

💻 Then, in query.py write 4 functions to easily query the titles_list and artists_list.

• format_song(title, artist)
• get_unique_artists(artists)
• get_artist_by_title(titles, artists, search_title)
• get_titles_by_artist(titles, artists, search_artist)

💻 Use the functions to answer the questions at the bottom of the file.

✅ Check your answers with a peer

[2] Deliverables #

⚡✨ Once you complete the lab, be sure to complete these two steps:

📋 Update Syllabus Tracker: Go to your Syllabus Content Checklist in your Google Drive and update it accordingly.

💻 Push your work to Github

• git status
• git add -A
• git status
• git commit -m “describe your code here”
• git push
• remote