#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Felix Muzny
10/85/2022
DS 2000
Lecture 15 - dictionaries, part 2 (the asynchronous lecture)

Logistics:
    - Homework 6 is due Friday @ 9pm
        - Dictionaries are not required. We don't think that using
        them will make your lives easier.
    
    - NO Quiz this week
    
        
    - *IMPORTANT* On Friday, I will be holding office hours during 
    from 9:50 - 10:55am and 1:35 - 2:40pm in RI 236.
    
    No class or office hours during Section 4's regular meeting time.
    (I will be on a train.)
    
"""

"""
Warm-up 1: dictionaries
    
Given the following code, what will the output be?
"""
print("warm up 1")
d = {}
d["Oscar"] = "apple" # new key-value pair
d["Kermit"] = "banana" # new key-value pair
d["Kermit"] = "orange" # re-seting the value associated with Kermit
d["Miss Piggy"] = d["Kermit"] # add the key Miss Piggy to the dic
                                # with the same value as what Kermit is 
                                # associated with
print(len(d))
print(d)        
print()

"""
A. 1
B. 2
C. 3 <---
D. 4
E. Error
"""



"""
Warm-up 2: dictionaries
    
If I have the following code, what is the effect of the designated
code block?
"""
print("warm up 2")
old_dict = {}
# iterate 5 times, i will go from 0 to 4
for i in range(5):
    old_dict[i] = 0
print(old_dict)  # {0:0, 1:0, 2:0, ...}
print()
    
# this code block from start to stop
# start
new_dict = {}
for k in old_dict:
    new_dict[k] = old_dict[k]
  
# stop

print(new_dict)
print(new_dict.copy())
print()

"""
A. This will create an empty dictionary
B. This will remove all values from d2
C. This will set all values in d3 (new_dict) to 0
D. This will put the same keys in d3 that d2 has <---
E. This will create a copy of d2 (old_dict) <---- most correct
"""


"""
Translating code into a function
---

(Using warm-up 2)
"""

def dict_copy(old_dict):
    """
    Copies a dictionary.

    Parameters
    ----------
    old_dict : dict
        mapping of keys to values.

    Returns
    -------
    new_dict : dict
        contain all key/value pairs in old_dict.
    """
    new_dict = {}
    for k in old_dict:
        new_dict[k] = old_dict[k]
    return new_dict

d4 = {1: 10, 2:10}
d5 = {"Felix": 97, "John": 43}
d4_copy = dict_copy(d4)
print(d4_copy)
d5_copy = dict_copy(d5)
print(d5_copy)
print(d5_copy.items())
print()


"""
Dictionaries 
---
Essential patterns:
    
1) testing for a key in/not a dictionary
    key in dict
    "Felix" in d5_copy -> True or False

2) iterating through a dictionary
    for key in dict:
        # code to be repeated
        
    for key, value in dict.items():
        # code to be repeated

3) adding keys/values to dictionaries
    (especially in the context of loops)
    dict[key] = value

"""


"""
Review: writing a larger program
---

Using the movie review data (blackadam.txt and tickettoparadise.txt), write
a larger program that will read in each review for the given movie, 
line-by-line and does three things:
    1) Lets the user ask how many times a word exists in the reviews
    2) Reports the combined word counts for all reviews for that movie
    
https://www.rottentomatoes.com/m/black_adam
https://www.rottentomatoes.com/m/ticket_to_paradise_2022
"""





"""
Example data for the rest of lecture: 
    
    
title,MPAA,rotten_tomato,IMDB
Black Adam,PG-13,39,7.1
Ticket to Paradise,PG-13,56,6.3
Smile,R,79,6.9
Halloween Ends,R,41,5.0
The Woman Kind,PG-13,94,6.8
"""


"""
Revisiting data utils
---

To-do: update the read_data function so that you can specify
types for each column.


Suggestion: you may find it helpful to write a function that will 
get a subset of rows for you based on the value in a specific column :)
"""

import data_utils

# read in the data as a list of lists
types = [str, str, int, float]
data_ls = data_utils.read_data("movies.csv", skip_header=True, type_casts = types)
print(data_ls)
print()

"""
Dictionaries + csv files
---
So far, we've read in data as lists of lists.

We can also read in data as lists of dictionaries!
"""

# write a function to read in data from a csv file as a list of dicts


types = {"rotten_tomato": int, "IMDB": float}
data_dicts = data_utils.read_data_dict("movies.csv", type_cast_dict=types)
print(data_dicts)
print()
data_dicts = data_utils.read_data_dict("movies.csv")
print(data_dicts)

# How can you use the data utils get_column function with your list of dicts?






"""
Next time
    - string processing & string manipulation
    - data and data sources
"""