IS 210 Assignment 10

Warmup Tasks

College:	CUNY School of Professional Studies
Course-Name:	Software Application Programming I
Course-Code:	IS 210

Overview

The Python dict class is Python's core mapping-type. With it, data may be stuctured and related with meaningful keys which opens a huge realm of program capabilities.

Instructions

The following tasks will either have you interacting with existing files in the assignment repository or creating new ones on the fly. Don't forget to add your interpreter directive, utf-8 encoding, and a short docstring with any new files that you create!

Important

In these exercises, you may, on occasion, come across a task that requres you to research or use a function or method not directly covered by the course text. Since Python is such a large language it would be impossible for the author to have included descriptions of each and every available function which would largely duplicate the offical Python documentation.

A vital skill to successful programming is being comfortable searching for and using official language documentation sources like the Python String Documentation page. Throughout our coursework we will be practicing both the use of the language in practice and the search skills necessary to become functional programmers.

Warmup Tasks

Task 01

Dictionaries can often be thought of as tabular data which is why they're so commonly used to represent database data. For this task, we'll be creating a dictionary from a table of data.

Specifications

1. Create a file, task_01.py.

# In task_01.py, create a constant called GRADE_DATA that stores the

following table, Grades, as a nested dictionary.

1. The first level key of the dictionary is student which represents the student's name.
2. Second level keys of this dictionary should map to the subjects.
3. Do not use functions that convert data of other types to instantiate the dictionary. You should use some form of the {} syntax to construct the dictionary.
4. Your dictionary construction should be clean and well-indented to make it easy to read.

Data

Grades

student	subject	grade
Luke Skywalker	math	B
Luke Skywalker	etiquette	B+
Luke Skywalker	grammar	B
Luke Skywalker	gym	A
Han Solo	math	A-
Han Solo	etiquette	C-
Han Solo	grammar	B
Han Solo	gym	B
C-3PO	math	C
C-3PO	etiquette	A+
C-3PO	grammar	A
C-3PO	gym	F

Task 02

There are a number of ways to access data from dictionaries. Here we'll practice a few of the most common ones.

Specifications

1. Start off by opening data.py and just taking a look at the structure of the BANDS dictionary.
2. Create a file named task_02.py.
3. In task_02.py, import the data module.
4. In one line, create a new constant named NIGEL and use dictionary keys to assign its value value from the 'Nigel Tufnel' entry of the data.BANDS dictionary.
5. Create a new constant named BANDS_NAMES and use a built-in dictionary function to fill it with a list of band-names from data.BANDS.

Examples

>>> import task_02
>>> task_02.NIGEL
['guitar', 'vocals', 'bass', 'violin', 'harmonica', 'clarinet',
 'keyboards', 'piano']
>>> task_02.BAND_NAMES
['The Rolling Stones', 'Van Halen', 'Spinal Tap', 'Queen', 'The Beatles',
 'The Who', 'Fleetwood Mac']

Task 03

There are a number of ways to add or remove keys to Python dictionaries. Here, we'll cover the most common types.

Specifications

1. Create a new file named, task_03.py

2. Import the data module.

3. With task_03.py, copy data.BANDS into a new constant named CORRECTED.

   Tip

   Keep in mind that the assignment operator (=), doesn't create a new dictionary, it just creates a new reference to it. There is a built-in dictionary function that creates a new copy of a dictionary.

4. Using the assignment syntax ([]) add a new entry to CORRECTED with a key value of Dylan and the following value:

   {'Bob Dylan': ['vocals', 'guitar', 'harmonica']}

5. Remove the 'David Lee Roth' entry from the 'Van Halen' entry of CORRECTED with the del statement.

6. Using the assignment syntax ([]), add a new entry to CORRECTED['Van Halen'] with key 'Sammy Hagar' and value ['vocals'].

Examples

>>> CORRECTED['Van Halen'].keys()
['Eddie Van Halen', 'Sammy Hagar', 'Michael Anthony', 'Alex Van Halen']

Task 04

The .update() method is a powerful tool for merging dictionary data as you'll see below.

Specifications

1. Create a file named task_04.py.

2. With task_04.py, create a new top-level band entry in data.BANDS with the key, 'Buckingham Nicks. The key:values of Buckingham Nicks are:

   'Lindsey Buckingham': ['guitar', 'vocals'],
   'Stevie Nicks': ['vocals', 'tambourine']

3. Use a built-in dictionary function to merge data.BANDS['Buckingham Nicks'] into data.BANDS['Fleewood Mac'] so that there are now five keys in data.BANDS['Fleetwood Mac'].

Task 05

Changing dictionary values is nearly identical to assigning them.

Specifications

1. Create a file named task_05.py.
2. With task_05.py, import the data module.
3. Change the value of data.SUPERHEROES['Logan']['alias'] to 'Wolverine' without altering data.py and without creating a new dictionary or variable.

Task 06

The .get() function has surprising utility when traversing data that could be incomplete.

Specifications

1. Start by taking a peek inside data.SUPERHEROES to get a sense of its structure.
2. Open task_06.py
3. Complete line 10 of task_06.py so that the 'pet' key of the HERO_DATA dictionary is added to the new SUPER_SIDEKICKS dictionary.
4. If no pet data exists, the returned value should be None
5. Use a built-in dictionary function to achieve this objective.
6. Restrict your edits to just line 10.

Task 07

It is often very useful to iterate through a dictionary object separating the iteration into key and value pairs. In this task you will need to use your new knowledge of dictionary iteration using the iteritems() method.

Specifications

1. Create a file named task_07.py
2. Declare a variable named DATA as a dictionary object. Assign it a set of key/value pairs. This is example data for you to work with but you may create any dictionary of data provided it is at least 10 items long and both keys and values are integers.
3. Create a function named iter_dict_funky_sum() that takes one dictionary argument.
   1. Declare a running total integer variable.
   2. Extract the key/value pairs from DATA simultaneously in a loop. Do this with just one for loop and no additional forms of looping.
   3. Assign and append the product of the value minus the key to the running total variable.
   4. Return the funky total.

Example Data

DATA = {
    2: 7493945,
    76: 4654320,
    3: 4091979,
    90: 1824881,
    82: 714422,
    45: 1137701,
    10: 374362,
    0: 326226,
    -15: 417203,
    -56: 333525,
    67: 323451,
    99: 321696,
    21: 336753,
    -100: 361237,
    55: 1209714,
    5150: 1771800,
    42: 4714011,
    888: 14817667,
    3500: 13760234,
    712: 10903322,
    7: 10443792,
    842: 11716264,
    18584: 10559923,
    666: 9275602,
    70: 11901200,
    153: 12074784,
    8: 4337229
}

Examples

>>> import task_07
>>> task_07.iter_dict_funky_sum(task_07.DATA)
140166242

Executing Tests

Code must be functional and pass tests before it will be eligible for credit.

Linting

Lint tests check your code for syntactic or stylistic errors To execute lint tests against a specific file, simply open a terminal in the same directory as your code repository and type:

$ pylint filename.py

Where filename.py is the name of the file you wish to lint test.

Unit Tests

Unit tests check that your code performs the tested objectives. Unit tests may be executed individually by opening a terminal in the same directory as your code repository and typing:

$ nosetests tests/name_of_test.py

Where name_of_test.py is the name of the testfile found in the tests directory of your source code.

Running All Tests

All tests may be run simultaneously by executing the runtests.sh script from the root of your assignment repository. To execute all tests, open a terminal in the same directory as your code repository and type:

$ ./runtests.sh

Submission

Code should be submitted to GitHub by means of opening a pull request.

As-of Lesson 02, each student will have a branch named after his or her GitHub username. Pull requests should be made against the branch that matches your GitHub username. Pull requests made against other branches will be closed. This work flow mimics the steps you took to open a pull request against the pull branch in Week Two.

For a refresher on how to open a pull request, please see homework instructions in Lesson 01. It is recommended that you run PyLint locally after each file is edited in order to reduce the number of errors found in testing.

In order to receive full credit you must complete the assignment as-instructed and without any violations (reported in the build status). There will be automated tests for this assignment to provide early feedback on program code.

When you have completed this assignment, please post the link to your pull request in the body of the assignment on Blackboard in order to receive credit.