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Dec 02: Review Chapters 9–12

Learning Objectives

After today's class, you should be able to:

  • Write programs that use topics from the last 4 chapters.
  • Identify what you have left to do on Parts C and D of PA3.

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Review Activity

Setup

Instructions

  • Work together to complete the review exercises below
  • After each exercise, run the corresponding test function
    • In VS Code, click the "" button
    • In Thonny, run the shell command: 
      !pytest -q -k test_ch09

Chapter 9: Sequences

  • String and list methods
  • The slice operator ([:])
  • Splitting/joining strings

Exercise 9 (ch09.py)

Function 1: indent_stars(text)

Write a function that processes a multi-line string representing notes. For each line in the string, if the line starts with "* ", add four spaces to the beginning of that line. Return the updated string with the appropriate indentation applied.

For example, given the string: 

Quiz 5
* Chapter 9: Sequences
* Chapter 10: File I/O
Quiz 6
* Chapter 11: Nested Data
* Chapter 12: Recursion
Return the string: 
Quiz 5
    * Chapter 9: Sequences
    * Chapter 10: File I/O
Quiz 6
    * Chapter 11: Nested Data
    * Chapter 12: Recursion

Function 2: unindent_stars(text)

Write a function that does the opposite as before: for each line that starts with "    * ", remove the four leading spaces.

Chapter 10: File I/O

  • Reading/writing files
  • Command-line arguments
  • The csv module

Exercise 10 (ch10.py)

Function 1: search_file(path, term)

Write a function that searches a file for a specified term (a word or short phrase). The function should return the line number and column number of the first occurrence.

For example, given the file contents: 

Practice makes progress.
Time and tide wait for none.
The word tide is on line 2, column 10.

Function 2: strip_file(path)

Also write a function that reads a text file, removes trailing whitespace (spaces and tabs) from the end of each line, and overwrites the file with the updated content.

Chapter 11: Nested Data

  • Lists of lists
  • Dicts of dicts
  • The json module

Exercise 11 (ch11.py)

Function 1: print_stats(label, strings)

Write a function that prints statistics about the lengths of strings in a set. The statistics include the minimum, median, mean, and maximum string lengths. Also print a label before the statistics to identify the output.

For example, print_stats("Letters:", {"A", "BB", "CCC", "DDD"}) would print: 

Letters: min = 1.0, median = 2.5, mean = 2.2, min = 3.0

Function 2: def track_stats(tracks)

Write a function that processes the fulltracks.json data from Last.fm and creates three sets: one containing all track names, another with all artist names, and a third with all album titles. After building the sets, call the print_stats() function for each set, using the labels "Track names:", "Artist names:", and "Album titles:" to identify the output.

Chapter 12: Recursion

  • Base case(s)
  • Recursive call
  • Keeping track

Exercise 12 (ch12.py)

Function: search_json(data, term, expr="data")

Write a function that searches for a given term in a JSON-like object (a dict, list, or string). The function should return a Python expression (as a string) that leads to the term if found, or None if not found.

Some of the code is already provided. The function uses isinstance() to check if data is a string, dict, or list. If data is a string, the function searches the string for the term. If data is a dict, the function recursively searches each key-value pair of the dict. If data is a list, the function recursively searches each index-value pair of the list.

For example, given the data: 

{
    "name": "Alice",
    "address": {
        "city": "Wonderland",
        "zipcode": "12345"
    },
    "hobbies": ["reading", "gardening", "coding"]
}
Searching for the term "Wonderland" would return: 
'data["address"]["city"]'