# debugging

def find_max(scores):
    max = scores[0]
    for s in scores:
        if s > max:
            max = s
    return max

scores = [90, 83, 85, 96, 82,71]
max = find_max(scores)
print("the highest score is: ", max)

the highest score is:  96

# approximating average

import numpy as np

def f(x):
    return x**2 + 2*x + 1

a = 0
b = 5

xs = np.linspace(0,5,100)
vectorized = np.vectorize(f)
ys = vectorized(xs)

deltax = xs[1] - xs[0]
average = np.sum(ys*deltax) / (b-a)

print(f"approximate average is: {average}")

approximate average is: 14.52062714688977

# Extra practice problems

#Write a function that takes a dictionary of type dict[str, int] 
#and creates a new dictionary sorted by the keys in alphabetical 
#order.

def sort_dict(d: dict[str, int]) -> dict[str, int]:
    new_d = {}
    sorted_keys = sorted(d)
    for key in sorted_keys:
        new_d[key] = d[key]
    return new_d

sort_dict({"a": 1, "c": 3, "b": 2})

{'a': 1, 'b': 2, 'c': 3}

#Write a function that sorts a list of numbers from highest to 
#lowest with mutation. Write annotations, a docstring, and tests 
#for this function. 

def sort_list(lst: list[float]) -> list[float]:
    """Return the list lst sorted from highest to lowest
    and mutate lst"""
    lst.sort(reverse = True)
    return lst

sort_list([1.6, -2.0, 9.0])

[9.0, 1.6, -2.0]

#Write a function that prints the first word from each line of 
#a text file.

def first_word(filename: str) -> None:
    with open(filename) as ifh:
        for line in ifh:
            print(line.split()[0])
            
# create your own text file to test this
first_word("myText.txt")

Hello
print
only
thanks!

#Write a function that opens the CSV file as a dictionary and 
#add all the values under a given key.

import csv

def add_column(filename: str, myKey: str) -> float:
    with open(filename) as ifh:
        fileCSV = csv.DictReader(ifh)
        fieldnames = list(fileCSV.fieldnames or [])
        assert myKey in fieldnames, "key must be valid"
        
        sum = 0.0
        for line in fileCSV:
            sum += float(line[myKey])
    return sum

# use the tutorial 6 students.csv file to test this

assert abs(add_column("Students.csv", "Age") - 158.0) < 0.001

annotateMe: tuple[dict[int, str], float] = ({1: "hi"}, 7.0)

Indexing = (["four", "me", ["you"]], {3: "see", 9: "hello", 10: "hi"}, "same")
Indexing[1][10]

'hi'