Recursion, Callbacks and Generators
What will be the output of this code?
def func(n):
if n == 0:
return 0
return n + func(n-1)
print(func(3))
6 (Explanation: 3+2+1+0 = 6)
def outer(x):
def inner():
return x * 2
return inner
f = outer(5)
print(f())
10
import numpy as np
arr = np.array([1, 2, 3, 4, 5])
print(arr[1:4])
[2 3 4]
What is the difference between re.match() and re.search()?
A: re.match() checks for a match only at the beginning of the string, while re.search() searches the entire string for a match.
def add(a,b):
return a+b
assert add(2,2) == 4
print("OK")
OK
What is the base case in recursion and why is it essential?
A base case is the condition that stops the recursion. It is essential to prevent infinite recursion and stack overflow errors.
Explain any 2 conditions out of 3 for a function to be considered as closure function
nested function
free variable
outer should return inner function
In scikit-learn's KNN algorithm, what does the 'K' represent and what happens if K=1?
'K' represents the number of nearest neighbors to consider. If K=1, the algorithm classifies a point based only on its single closest neighbor, which can lead to overfitting.
What will re.match(r'\d+', '123abc') return when you call .group() on it?
A: '123'
def divide(a, b):
return a / b
def test_divide():
assert divide(10, 2) == 5
assert divide(9, 3) == 3
assert divide(1, 0) == 0
2 tests pass, 1 test fails with ZeroDivisionError (Explanation: The third assertion causes division by zero which raises an exception)
def outer(x):
def inner(y):
if y == 0:
return x
return outer(x + y)(y - 1)
return inner
print(outer(5)(3))
11 (Explanation: 5+3+2+1 = 11, recursive calls with decreasing y)
When the user RESIZES the window horizontally:
Which button grows the MOST?
Which button does NOT grow at all?
What role do the flags (wx.EXPAND, wx.ALIGN_CENTER_VERTICAL, wx.ALL) play for each?
import wx
app = wx.App()
frame = wx.Frame(None, title="Sizer Test", size=(400, 200))
panel = wx.Panel(frame)
sizer = wx.BoxSizer(wx.HORIZONTAL)
btn1 = wx.Button(panel, label="Save")
btn2 = wx.ToggleButton(panel, label="Play")
btn3 = wx.BitmapButton(panel, bitmap=wx.Bitmap("play_20x20.png"))
sizer.Add(btn1, 1, wx.ALL | wx.EXPAND, 10)
sizer.Add(btn2, 0, wx.ALIGN_CENTER_VERTICAL, 5)
sizer.Add(btn3, 3, wx.EXPAND | wx.ALL, 0)
panel.SetSizer(sizer)
frame.Show()
app.MainLoop()
btn3
btn2
sizer.Add(btn1, 1, wx.ALL | wx.EXPAND, 10)
wx.EXPAND → expands in both directions
wx.ALL + 10 → 10-pixel padding around it
Takes 1 unit of expandable space
sizer.Add(btn2, 0, wx.ALIGN_CENTER_VERTICAL, 5)
No wx.EXPAND → width remains fixed
wx.ALIGN_CENTER_VERTICAL → button stays vertically centered
proportion = 0 → no stretch at all
sizer.Add(btn3, 3, wx.EXPAND | wx.ALL, 0)
wx.EXPAND → grows fully
proportion = 3 → gets largest share of horizontal space
wx.ALL + 0 → no padding
import numpy as np
arr = np.array([[1, 2, 3], [4, 5, 6]])
print(arr.shape)
print(arr.reshape(3, 2))
(2, 3) [[1 2] [3 4] [5 6]]
import re
text = "Contact: john@email.com and jane@email.com"
pattern = r'\b[a-z]+@[a-z]+\.com'
matches = re.findall(pattern, text)
print(len(matches))
print(matches[0])
2
john@email.com
def factorial(n):
"""
Calculate factorial.
>>> factorial(5)
120
>>> factorial(0)
1
>>> factorial(3)
6
"""
if n == 0:
return 1
return n * factorial(n-1)
if __name__ == "__main__":
import doctest
result = doctest.testmod()
print(f"Failed: {result.failed}, Attempted:{result.attempted}")
Failed: 0, Attempted: 3 (Explanation: All three doctests pass)
def mystery(lst, callback):
result = []
for item in lst:
result.append(callback(item))
return result
nums = [1, 2, 3,4,5]
output = mystery(nums, lambda x: x**2 if x % 2 != 0 else x)
print(output)
[1, 2, 9,4,25] (Explanation: Odd numbers are squared, even numbers remain same
def dec(fn):
def wrap():
return fn()+2
return wrap
@dec
def num():
return 7**2
print(num())
51
import numpy as np
a = np.array([1, 2, 3])
b = np.array([4, 5, 6])
result1 = a * b
result2 = np.dot(a, b)
print(result1)
print(result2)
print(result1.sum() == result2)
[ 4 10 18]
32
True
(Explanation: Element-wise multiplication vs dot product; sum of element-wise equals dot product)
import re
print(re.findall(r'\d+', 'a12b003c9'))
['12', '003', '9']
Predict which doctest will fail or pass and why:
def divide_numbers(a, b):
"""
Divide two numbers.
>>> divide_numbers(10, 2)
5.0
>>> divide_numbers(7, 2)
3.5
>>> divide_numbers(9, 3)
3
>>> divide_numbers(0, 5)
0.0
"""
return a / b
if __name__ == "__main__":
import doctest
doctest.testmod()
The third test divide_numbers(9, 3) expects 3 but gets 3.0. Division in Python 3 always returns a float. Failed: 1, Attempted: 4
def generator_chain():
yield 1
yield from [2, 3, 4]
yield 5
yield from range(6, 8)
result = [x**2 for x in generator_chain() if x % 2 == 0]
print(result)
print(result)
[4, 16, 36]
[]
(Explanation: Even numbers are 2, 4, 6; their squares are 4, 16, 36)
def make():
val = 10
def f():
nonlocal val
val += 5
return val
return f
x = make()
print(x(), x(), x())
15 20 25
from sklearn.neighbors import KNeighborsClassifier
import numpy as np
X_train = np.array([[1, 1], [2, 2], [3, 3], [6, 6], [7, 7], [8, 8]])
y_train = np.array([0, 0, 0, 1, 1, 1])
X_test = np.array([[4, 4], [5, 5]])
knn = KNeighborsClassifier(n_neighbors=3)
knn.fit(X_train, y_train)
predictions = knn.predict(X_test)
print(predictions)
print(predictions[0] == predictions[1])
[0 1]
False
(Explanation: [4,4] is closer to class 0 points, [5,5] is closer to class 1 points based on 3 nearest neighbors)
import re
text = "aa aba aaaa abba"
print(re.findall(r'a.b', text))
s = "cat scatter cater cutoff"
print(re.findall(r'ca[t|r]+', s))
print(re.findall(r'a.b', text))
['aab', 'aba']
['cat', 'catter']
import pytest
def process_data(numbers):
if not numbers:
return []
return [x ** 2 for x in numbers if x > 0]
def test_process_data():
# Test 1
result1 = process_data([1, 2, 3])
assert result1 == [1, 4, 9], f"Expected [1, 4, 9], got {result1}"
# Test 2
result2 = process_data([-1, 0, 2, -3, 4])
assert len(result2) == 2
assert result2[0] == 4
assert result2[1] == 16
# Test 3
result3 = process_data([])
assert result3 == []
# Test 4
result4 = process_data([-5, -10])
assert result4 == [], f"Expected empty list for all negatives"
# How many total assertions are in this test?
# Will all assertions pass?
Total assertions: 6 All assertions pass: Yes
Breakdown:
(Explanation: Multiple assertions in one test function still count as one test. All pass because the function correctly filters positive numbers and squares them.)
Claude can make mistakes.
Please double-check responses.