Checklist 02

Here is a general outline of the key concepts (arranged by topic) that you should know for Exam 02.

The exam will have the following format:

1. Python Scripting (multiple-choice, fill-in-the-blank)

2. Data Processing (multiple-choice)

3. Functional Programming (multiple-choice)

4. List Comprehensions (multiple-choice)

5. Generators (multiple-choice)

6. Concurrency and Parallelism (multiple-choice)

7. Translations: Convert Unix pipelines to Python code (coding on the computer)

All portions of the exam will take place online. Parts 1 through 6 will be an online quiz while Part 7 will require submitting code to your assignments repository.

Python Scripting / Data Processing¶

Concepts¶

1. How is Python different from the Bourne shell? How is it similar?

2. How do we manage control flow in Python? How do we utilize these constructs?

   • Conditionals

   • Loops

   • Exceptions

   • Functions

3. What data structures do we have in Python? What are their basic operations? When would we want to use each type of data structure?

   • Lists / Tuples

   • Dictionaries / Sets

4. How do we do the following in Python?

   • Process command-line arguments

   • Read standard input

   • Read files

   • Access environment variables

   • Change the case of a string

   • Split a string, combine a list of strings

   • Slice a list

   • Execute an external command

   • Process JSON data from the web

   • Sort lists and dictionaries

   • Count with dictionaries

Sample Questions¶

Code Snippets¶

Write Python code snippets to perform the following tasks (don't worry about she-bangs or imports):

1. Print out each element of a list (one element per line).

2. Print the contents of stdin (line-by-line).

3. Print the first 10 items of a list.

4. Print the length of a list.

5. Print the largest and smallest elements of a list.

6. Print the first and last words in the string "Let this promise in me start, Like an anthem in my heart".

7. Print the results of the ps aux command.

8. Print the contents of a specific webpage.

Code Evaluation¶

Given the following data:

comics = {
    "marvel": ["deadpool", "spider-man", "wolverine"],
    "dc"    : ["batman", "superman"]
}

For each of the following expressions, state the output value:

1. len(comics)

2. list(comics.keys())[0]

3. list(comics.values())[-1]

4. comics['marvel'][1]

5. comics['dc'][-1][-3:]

Translation¶

Given the following Unix pipelines, write Python code that accomplishes the same task.

1. cat /etc/passwd | cut -d : -f 1 | grep d$ | wc -l

2. cat /etc/passwd | cut -d : -f 3 | grep -E '^[0-9]{2}$' | sort | uniq

3. curl -sL http://yld.me/raw/lmz | cut -d , -f 1 | grep -Eo '^[^jfs].*'

4. curl -sL http://yld.me/raw/lmz | cut -d , -f 2 | grep -Eo '^B.*' | sort

5. who | sed -rn 's|.*\((.*)\).*|\1|p' | sort | uniq

6. ls -l /etc | awk '{print $2}' | sort | uniq -c

Functional Programming¶

Concepts¶

1. What is the difference between imperative and functional programming?

   • What are some benefits of functional programming?

   • How is functional programming related to the Unix Philosophy?

2. How do we use map, filter, and lambda to do functional programming in Python?

List Comprehensions¶

Concepts¶

1. How do we use list comprehensions in Python?

Generators¶

Concepts¶

1. What is an iterator and how is it different from a list?

2. What is a generator and how it is different from a list?

   • What does the yield command do?

   • Why would we use a generator over a list (and vice versa)?

   • How do we convert a list comprehension to a generator expression?

3. How do we use common iterators and generators such as:

   • sorted
   • reversed
   • range
   • enumerate

Sample Questions¶

Translation¶

Translate the following imperative code:

def find_squares(start, end):
    squares = []
    for number in range(start, end):
        if math.sqrt(number) == int(math.sqrt(number)):
            squares.append(number)
    return squares

1. To using map, filter, and lambda.
2. To using a list comprehension.
3. To using a generator with yield.
4. To using a generator expression.

Concurrency and Parallelism¶

Concepts¶

1. What is the difference between concurrency and parallelism?

   • What are some problems with concurrency?

   • How does functional programming help enable concurrency and avoid these problems?

   • What does it mean for a problem to be task parallel, data parallel, or embarrassingly parallel? Examples?

Sample Questions¶

True / False¶

Identify whether the statements below are True or False and explain why.

1. The slurp.py class example exhibits data parallelism.
2. The slurp.py class example exhibits task parallelism.
3. The slurp.py class example is embarrassingly parallel.