Questions and Answers
What does the factorial function return when the input is 0?
What operator is used to unpack an iterable in Python?
What is the result of the following code: 'a, b, *c = [1, 2, 3, 4]'?
How does the factorial function defined in the content handle recursive calls?
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What will the variable 'd' contain after running the code 'a, b, c, *d = [1, 2, 3, 4, 5, 6]'?
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What will happen if the number of variables in parallel assignment exceeds the number of elements in the iterable?
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When unpacking a dictionary, what is the primary outcome?
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Which of the following is NOT a method to unpack an iterable in Python?
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What will be the output of the following code: print(main(10, 5, 5))?
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What is the primary purpose of a default argument in a function?
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Which of the following statements correctly describes the use of mutable optional parameters?
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What will happen if a non-default argument is placed after a default argument in a function definition?
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In the example function list_appender, what will be the output of print(list_appender('hola')) after the previous calls?
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What is likely the output of the function call: print(main(10, 5)) if num3 is defined as a default argument with the value 0?
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Which of the following best describes the behavior of default arguments in the context of function calls?
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How should parameters be structured in a function if one of them is to have a default value?
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What will the following code print? my_dict = {'name': 'John', 'age': 30, 'city': 'New York'}; print_person(**my_dict)
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Which of the following is a correct use of the unpack operator (**)?
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How do you convert the iterator returned by map() to a list?
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What type of data can the map() function operate on?
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What does the filter() function return when provided with a function returning True for all elements?
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What will the following code print? temperatures = [0, 10, 20, 30, 40]; fahrenheit_temperatures = list(map(lambda x: (9/5) * x + 32, temperatures)); print(fahrenheit_temperatures)
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Which of the following statements is true about the filter() function?
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Using the unpack operator (**), what will be the result of combination = {**numbers, **letters} where numbers and letters are defined dictionaries?
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What will be the output when the first element of the array is modified to 0?
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What does the filter() function do in Python?
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What is the effect of using the pop() method on an array?
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What will the following code output: print(list(filter(lambda x: x >= 0, [-1, 0, 1, 2])))?
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Which of the following statements about Python arrays is true?
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What will the reduce() function return in this code: ans = reduce(lambda x, y: x + y, [1, 2, 3])?
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What happens if you try to delete an array using the del statement after removing all elements from it?
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What is a key characteristic of arrays in programming?
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What will be the output of the following code snippet: numbers = arr.array('i', [10, 11, 12, 12, 13]); numbers.remove(12); print(numbers)?
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Which statement is true about the implementation of arrays in Python?
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Which method can be used to reverse the elements of an array?
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What is the primary difference between Python lists and arrays?
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What will the output be when this code is executed: print(reduce(product, [2, 3, 4])) where product is defined as: def product(x,y): return x*y?
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In the context of an array, what does an index represent?
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What will be printed after executing my_array.reverse() on my_array = array.array('i', [1, 2, 3, 4, 5])?
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How does the reduce() function differ from the filter() function?
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Study Notes
Python Functions and Arguments
- Functions can have default arguments, allowing some parameters to be optional.
- Example of a function with default argument:
-
def main(num1, num2, num3=0): return num1 + num2 + num3
-
- Calling
main(10, 5)returns 15, whilemain(10, 5, 5)returns 20. - Default arguments must follow non-default ones in function definitions.
Mutable Optional Parameters
- Mutable types (e.g., lists, dictionaries) as optional parameters maintain state across function calls.
- Example of a function appending to a list:
-
def list_appender(item, items=[]): items.append(item); return items
-
- Consecutive calls modify the same list, not a new one.
Recursion in Python
- A recursive function can call itself, useful for problems like factorials.
- Example:
-
def factorial(x): return 1 if x == 1 else x * factorial(x-1)
-
-
factorial(3)computes 6.
Unpacking Iterables
- The unpacking operator (
*) extracts elements from an iterable into variables. - Use case involves dictionaries, allowing key-value pairs to be accessible in functions.
- Example with unpacking a dictionary:
-
fun(**d)wheredis a dictionary.
-
The map() Function
-
map(function, iterable)applies a function to each item in an iterable. - Returns a map object, which can be converted to a list.
- Example for squaring numbers:
-
list(map(square, numbers))returns squared values.
-
The filter() Function
-
filter(function, iterable)filters items based on a condition. - Returns an iterable with only elements that returned True from the function.
- Example filters to retain only non-negative numbers.
The reduce() Function
- Part of
functools,reduce(function, iterable)returns a single cumulative value. - Example sums a list of numbers:
-
reduce(lambda x, y: x + y, nums).
-
Arrays in Python
- Arrays store multiple values of the same type, enhancing code efficiency.
- Arrays can be created using the
arraymodule. - Access elements by index, starting at 0.
Array Operations
- Changing and adding elements can be done through direct assignment or slicing.
- Example:
- Change first element
numbers[0] = 0.
- Change first element
- Removing elements uses
del,remove(), orpop().
Differences Between Lists and Arrays
- Lists can contain mixed types; arrays require all elements to be of the same type.
- Error in arrays when mixed data types are attempted.
Reversing and Extending Arrays
- Reverse an array in place using
array.reverse(). - Extend an array with additional values via the
extend()method.
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Description
This quiz covers essential concepts related to Python functions, including default arguments, mutable optional parameters, recursion, and unpacking iterables. Test your understanding of these key programming principles and enhance your Python skills.
