#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Felix Muzny
10/18/2022
DS 2000
Lecture 12 - functions and optional parameters,
             functions and functions as parameters,
             if __name__ == __main__,
             dictionaries

Logistics:
    - Homework 5 is due this Friday 10/21 @ 9pm
    
    - Quiz 6 is available
    
    - remote attendance (https://bit.ly/remote-ds2000-muzny)
    
    
 Three ways to participate (please do one of these!)
 1) via the PollEverywhere website: https://pollev.com/muzny
 2) via text: text "muzny" to the number 22333 to join the session
 3) via Poll Everywhere app (available for iOS or Android)
    

Warm-up 1 - 
---
Write two different good, working function calls for the given 
generate_list function.

"""

import random

# this example has no positinal parameters
def generate_list(lower = 1, upper = 9):
    """
    Generate a list of length 10 filled with random ints from 
    a lower bound to an upper bound (1 - 9 by default).

    Parameters
    ----------
    lower : int, optional
        Inclusive lower bound of integers to generate. The default is 1.
    upper : int, optional
        Inclusive upper bound of integers to generate. The default is 9.

    Returns
    -------
    new_ls : list
        Generated list of ints.
    """
    
    new_ls = []
    for i in range(10):
        new_ls.append(random.randint(lower, upper))
    return new_ls


"""
Warm-up 2 - passing functions as parameters
---

Write down two good, working function calls for the given list_info
function and one bad, non-working function call
"""

def list_info(ls, func):
    print(func(ls))

numbers = [1, 2, 5, 6, 17]
data = [[1, 12], [23, 24], [35, 36]]




"""
Optional parameters
---
Examples with python built-in functions. We always list positional
(non-optional) parameters first.

print("Here", "are", "words", sep="what to put in between")
 
plt.plot(xs, ys, "o", color="red")
 

Writing our own functions with an optional parameter
---

General syntax:
def function_name(positional, parameters, first, then = optional):
    # code
    
Call the function as normal, but specify the values of any
optional parameters that you send to the function.

If a function takes both positional and optional parameters, 
they will be assigned in order if no optional names are specified.
    
"""
def person_info(name, likes_mushrooms = False, age = 10):
    print("Name", name)
    print("Likes mushrooms?", likes_mushrooms)
    print("Age", age)
    
# example function calls
                   

"""
Passing functions as parameters
---

Using our function that we wrote from before (convert_int),
write a new version that will convert everything from a 
list into a string.
"""

def convert_mutate(ls, cast = int):
    """
    Converts all values in given list according to the given function.
    Changes to ints by default.
    Mutates the given list.

    Parameters
    ----------
    ls : list
        list of values to be converted.
    cast : function, optional
        Function to be applied to every element in the list. The default is int.

    Returns
    -------
    None.
    """
    for i in range(len(ls)):
        ls[i] = cast(ls[i])
        
        
print("convert_mutate examples")
my_floats = [43.2, 35.4, 1123.123]
words = "This is a sentence".split()
numbers = "1 12  12 3 12 57".split()

"""
Writing our own modules & if __name__ == "__main__":
---

We've written a number of quite useful functions that 
are rather general purpose.

For instance:
    in earnings_lec10.py, we had:
    (https://course.ccs.neu.edu/ds2000/felix_lectures/earnings_lec10.py)
    
    - read_data
    - get_column
    
From lecture on Friday, we had a convert list function. These are all
highly useful, very general data processing functions that I might not
want to re-write every time I want to use them.
        
Solution: write our own module!
"""


"""
Dictionaries
---
A dictionary is a *data structure*, similarly to lists.

A dictionary links a *key* to a *value*.

Examples:
    student emails -> graduation year
    words -> definitions
    words -> counts of how often they occur
    
    
Keys: any immutable data type
    keys are *unique*
    
Values: any data type
    values are not unique

"""
# Dictionary examples

# Creating a dictionary


# adding a key/value pair to a dictionary


# updating a key/value pair in a dictionary


# iterating through all values in a dictionary


"""
How is a list similar to a dictionary?
---
"""

# if time: create a dictionary of counts

def count_words(text):
    """
    Count each word in a given string

    Parameters
    ----------
    text : str
        words separated by whitespace.

    Returns
    -------
    dict of word counts.
    """
    print("ro be implemented")
    
test1 = "This is a sentence"
test2 = "This is a longer test that has a second clause"




"""
Next time:
    - writing a larger program with dictionaries
"""