Assignment 7

Problems

  1. Every letter counts

    First up a problem to give you a little practice working with the collection types (lists and dictionaries). Write the following implementations of the function letter_frequency that takes a string and returns a collection type showing how often each letter of the alphabet occurs in the string.

    1. The first version (letter_frequencyA) should return a list with 26 integer elements representing the frequency of occurrence of each letter of the alphabet in order from a to z.

    2. The second version (letter_frequencyB) should return a list of 26 lists, each of which contains a letter and its associated count.

    3. The third version (letter_frequencyC) should return a dictionary that uses the letters as keys and whose values are the letters' counts.

    The program that will call these functions is letter_frequency.py. Your job is to replace the pass statements with function bodies that implement the functionality specified above. Studying the embedded tests should answer any other questions you have about the functions' operations.

  2. Anagrams

    An anagram is produced by rearranging the letters of one word or phrase to produce another word or phrase, e.g. "cat" and "act" are anagrams, as are "scare", "races", "acres" and "cares". Write two functions called anagramsA and anagramsB each of which returns True if the two strings it is passed are anagrams of each other and False otherwise. anagramsA should be based on the observation that if two strings are anagrams they each have the same numbers of each letter in them. This means that their letter frequency counts will be identical. anagramsB should be based on the observation that anagrams are strings that could be rearranged to be the same. One easy way to rearrange things is to use Python's built-in sort methods, so you could test to see if two strings are anagrams by sorting them and comparing the sorted versions.

  3. Win 32 Network Resource Anlayzer

    Many of the Win32 Network Resource enumeration tools return a list of dictionaries:

    [ {'name':'YVB127','comment':'Rm A2507','type':WKSTATION},
  {'name':'YVB143','comment':'Rm T1010','type':SERVER},
  ...
]

    Write the following functions to work with the import'ed file net_res.py:

    1. count_summary() should return a dictionary where the machine type is the key and the count of machines of that type is the value.
    2. list_by_type(type) should be passed a type, e.g. SERVER and return a list of the rooms containing machines of that type.
    3. max_count() should return the name of the room, e.g. 'Rm A2507', that contains the most computers.

    Embed your functions in a module with an if __name__... block that runs them and displays their output. It should import the filenet_res.py.

  4. Topography

    No dictionaries required for this one. It just gives you some more practice working with lists of lists. Suppose you are given some map elevation data stored as a list of lists, e.g. 

    data = [ [20, 54, 50, 64, 60, 63, 60, 48, 20, 20],
         [20, 56, 72, 76, 72, 20, 52, 62, 53, 20],
         [20, 52, 62, 81, 67, 23, 48, 67, 52, 20],
         [20, 54, 54, 82, 72, 22, 42, 64, 50, 20],
         [20, 53, 49, 87, 69, 47, 48, 49, 21, 20],
         [20, 20, 62, 71, 61, 36, 28, 31, 22, 20],
         [20, 20, 20, 20, 20, 22, 21, 28, 24, 20],
         [20, 20, 20, 20, 20, 20, 20, 20, 20, 20],
         [20, 20, 20, 20, 20, 20, 20, 20, 20, 20],
         [20, 20, 20, 20, 20, 20, 20, 20, 20, 20]
       ]

    Write a function called peaks that is passed a list of lists like this one and returns a list of the coordinates (row, col) of all the peaks in the dataset. A peak is a point that is higher than its eight surrounding neighbours (the red values at (2,7) and (4,3) above are the peaks and the orange values aroung them are their eight neighbours). For the data set above the function should return,

    [(2, 6), (4, 3)]

Logistics