Module 1: Assorted Advanced Topics

1.6 Exercise: Type up the above in my_fruits.py and use the data file fruits.txt to confirm. Next, in my_fruits2.py, change the program to accommodate the additional fruits in fruits2.txt.

Aside from being tedious, this approach has other issues:

• One would like to be able to write a general program that does not need to know which fruits are in a file.

• What if there were a thousand different kinds of items (not fruits, say, but department-store items)?

• A single mistake in a variable can cause the counts to be wrong.

Fortunately, the use of dictionaries will make it easy:

# Make an empty dictionary
counters = dict()

with open('fruits.txt','r') as data_file:
    line = data_file.readline()
    while line != '':
        fruit = line.strip()
        if fruit in counters.keys():
            # If we've seen the fruit before, increment.
            counters[fruit] += 1
        else:
            # If this is the first time, set the counter to 1
            counters[fruit] = 1
        line = data_file.readline()

print(counters)
    

1.7 Exercise: Type up the above in my_fruits3.py and first apply it to fruits.txt and then to fruits2.txt. (Submit your program with the latter file as the input file.) In your module pdf, describe what you had to change in the code to make it work for the second file.

Now let's explain:

• A dictionary is a technical term that is only somewhat related to an actual English dictionary.

• Think of an English dictionary as something where you look up a word and receive its meaning.

• They operations here are look up and receive an associated value (the word's meaning, in this case).

• In Python, a dictionary is a structure that lets you associate one kind of data with another.

• The technical equivalent of a word is called a key and the equivalent of the meaning is called the value.

• So, a dictionary is a collection of key-value pairs.

• Here's an example:

  d = {'apple': 3, 'banana': 3, 'pear': 1, 'kiwi': 2, 'orange': 4}
    

  In this case, we're associating
  • The value 3 with the key 'apple'
  • The value 3 with the key 'banana'
  • The value 1 with the key 'pear'
  • The value 2 with the key 'kiwi'
  • The value 4 with the key 'orange'

• Conveniently, Python allows array indexing using the key:

  d = {'apple': 3, 'banana': 3, 'pear': 1, 'kiwi': 2, 'orange': 4}
  
  print(d['apple'])  # Prints 3
  
  d['banana'] = 0    
  # Which changes the value associated with 'banana' to 3
    

• The above is an example of a dictionary that's already built (after we've processed the data).

• To process data on-the-fly, we need an additional operation that an English dictionary does not really have: we need to be able to add something that's not already there.

• To add a new key, we simply use it as an index:

  d = {'apple': 3, 'banana': 3, 'pear': 1, 'kiwi': 2, 'orange': 4}
  
  d['plum'] = 0
    

With this understanding we can now revisit the code in the fruit example:

• We've seen how to read a file line-by-line before

  with open('fruits.txt','r') as data_file:
      line = data_file.readline()
      while line != '':
          fruit = line.strip()           # Remove whitespace on either side
  
          # This is where we'd do something with the datda
  
          line = data_file.readline()    # Get the next line
    

• The rest is merely the dictionary part:

  with open('fruits.txt','r') as data_file:
      line = data_file.readline()
      while line != '':
          fruit = line.strip()           # Remove whitespace on either side
  
          if fruit in counters.keys():
              # If we've seen the fruit before, increment.
              counters[fruit] += 1
          else:
              # If this is the first time, set the counter to 1
              counters[fruit] = 1
  
          line = data_file.readline()    # Get the next line
    

1.8 Exercise: In my_stopwords2.py, write code that uses a dictionary to compare the relative occurrence of stopwords in alice.txt and darwin.txt. In particular, we'd like to know: what percentage of the stopword occurence can be attributed to 'the', what percentage to 'and', and so on. For alice.txt the output should look like this (not necessarily in the same order) using the string formatting from the previous section. In your module pdf, compare the outputs for the two texts: do the stopwords occur with similar relative frequencies across the two texts?

1.9 Audio:

1.3    Advanced topic: global variables

Enter circle parameters: 3 4 3
Enter circle parameters: 4 3 1
Enter circle parameters: 5 7 2
Enter circle parameters: 
  

25
27
2.23606797749979
  

x = 0
for i in range(5):
    print('i=', i, 'x=', x)
    x += 0.1
    

i= 0 x= 0
i= 1 x= 0.1
i= 2 x= 0.2
i= 3 x= 0.30000000000000004
i= 4 x= 0.4
  

x = 0
for i in range(5):
    format_string = 'i = {0:2d}  x = {1:.2f}'
    string_to_print = format_string.format(i, x)
    print(string_to_print)
    x += 0.1
  

import random

#random.seed(123)

for i in range(5):
    x = random.uniform(1.0, 10.0)
    print(x)
    

#random.seed(123)