Day 25 - Transition to Python 2

Skills: None

Pre-reading: 9.1.6, 9.1.7

Intro (10 mins)

• Today we explore how to create and process lists in Python, and compare with Pyret.
• In Python, lists are created with square brackets, e.g.:

  fruits = ["apple", "banana", "cherry", "date"]
• Python has built-in functions like filter and map for processing lists, but you must wrap their results with list():

  fruits_with_a = list(filter(lambda f: "a" in f, fruits))
  # ["apple", "banana", "date"]
  fruits_upper = list(map(lambda f: f.upper(), fruits))
  # ["APPLE", "BANANA", "CHERRY", "DATE"]
• Anonymous functions use lambda in Python (single expression only).
• Dataclasses: Python's @dataclass decorator allows you to define structured data types, similar to structured data using Pyret's data definitions (conditional data is more complicated, and not covered here). Example:

  from dataclasses import dataclass
  
  @dataclass
  class Fruit:
      name: str
      color: str

Class Exercises (35 mins)

• Create a list of integers from 1 to 10.
• Write a expression using map that produces a list of their squares.
• Design a function all_even(nums: list) -> list that returns a list of all even numbers from the input list.
• Design a function capitalize_all(words: list) -> list that returns a list of all words capitalized.
• Use map and lambda to produce a list of the lengths of each word in ["hello", "world", "python"].
• What happens if you forget to wrap the result in list()? Try it and note the error.
• Define a @dataclass called Book with fields title (str), author (str), and pages (int).
• Design a function long_books(books: list) -> list that returns a list of titles of books with more than 300 pages. Remember to always include docstring, type signature, and pytest tests.
• Create a list of Book instances and use long_books to filter them.
• Design a function filter_by_author(books: list, author: str) -> list that returns a list of titles of books by the given author.

Wrap-up (5 mins)

• Python lists use square brackets and require wrapping map/filter results with list().
• Dataclasses provide a way to define structured data, similar to Pyret's data.