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python interview questions :171

Dictionary of types?

  • Since type names don't have to be unique across modules, you must use the type (classObject) itself.
  • Luckily, types will automatically have a non-trivial hash value:
>>> class A(object): pass
>>> class B(object): pass
>>> hash(A)
2579460
>>> hash(B)
2579600
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python interview questions :172

What is the purpose of the `//` operator in python?

x=10
y=2
print x/y
print x//y
Both output 5 as the value.

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Integer division vs. float division:

>>> 5.0/3
3: 1.6666666666666667
>>> 5.0//3
4: 1.0
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python interview questions :173

What Is The Command To Debug A Python Program?

  • The following command helps run a Python program in debug mode.
$ python -m pdb python-script.py
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python interview questions :174

How Do You Monitor The Code Flow Of A Program In Python?

  • In Python, we can use <sys> module’s <settrace()> method to setup trace hooks and monitor the functions inside a program.
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  • You need to define a trace callback method and pass it to the <settrace()> method. The callback should specify three arguments as shown below.
import sys

def trace_calls(frame, event, arg):
    # The 'call' event occurs before a function gets executed.
    if event != 'call':
        return
    # Next, inspect the frame data and print information.
    print 'Function name=%s, line num=%s' % (frame.f_code.co_name, frame.f_lineno)
    return

def demo2():
    print 'in demo2()'

def demo1():
    print 'in demo1()'
    demo2()

sys.settrace(trace_calls)
demo1()
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python interview questions :175

Why And When Do You Use Generators In Python?

  • A generator in Python is a function which returns an iterable object. We can iterate on the generator object using the <yield> keyword. But we can only do that once because their values don’t persist in memory, they get the values on the fly.
  • Generators give us the ability to hold the execution of a function or a step as long as we want to keep it. However, here are a few examples where it is beneficial to use generators.
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  • We can replace loops with generators for efficiently calculating results involving large data sets.
  • Generators are useful when we don’t want all the results and wish to hold back for some time.
  • Instead of using a callback function, we can replace it with a generator. We can write a loop inside the function doing the same thing as the callback and turns it into a generator.

python interview questions :176

What Does The <Yield> Keyword Do In Python?

  • The <yield> keyword can turn any function into a generator. It works like a standard return keyword. But it’ll always return a generator object. Also, a function can have multiple calls to the <yield> keyword.
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Example :

def testgen(index):
  weekdays = ['sun','mon','tue','wed','thu','fri','sat']
  yield weekdays[index]
  yield weekdays[index+1]

day = testgen(0)
print next(day), next(day)
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output:

sun mon

python interview questions :177

How To Convert A List Into Other Data Types?

  • Sometimes, we don’t use lists as is. Instead, we have to convert them to other types.
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Turn A List Into A String.

  • We can use the <”.join()> method which combines all elements into one and returns as a string.
weekdays = ['sun','mon','tue','wed','thu','fri','sat']
listAsString = ' '.join(weekdays)
print(listAsString)
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output:

 sun mon tue wed thu fri sat

Turn A List Into A Tuple.

  • Call Python’s <tuple()> function for converting a list into a tuple. This function takes the list as its argument. But remember, we can’t change the list after turning it into a tuple because it becomes immutable.
weekdays = ['sun','mon','tue','wed','thu','fri','sat']
listAsTuple = tuple(weekdays)
print(listAsTuple)
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output:

('sun', 'mon', 'tue', 'wed', 'thu', 'fri', 'sat')

Turn A List Into A Set.

  • Converting a list to a set poses two side-effects.
  • Set doesn’t allow duplicate entries, so the conversion will remove any such item if found.
  • A set is an ordered collection, so the order of list items would also change.
  • However, we can use the <set()> function to convert a list to a set.
weekdays = ['sun','mon','tue','wed','thu','fri','sat','sun','tue']
listAsSet = set(weekdays)
print(listAsSet)
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output:

 set(['wed', 'sun', 'thu', 'tue', 'mon', 'fri', 'sat'])

Turn A List Into A Dictionary.

  • In a dictionary, each item represents a key-value pair. So converting a list isn’t as straight forward as it were for other data types.
  • However, we can achieve the conversion by breaking the list into a set of pairs and then call the <zip()> function to return them as tuples.
  • Passing the tuples into the <dict()> function would finally turn them into a dictionary.
weekdays = ['sun','mon','tue','wed','thu','fri']
listAsDict = dict(zip(weekdays[0::2], weekdays[1::2]))
print(listAsDict)

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output:

{'sun': 'mon', 'thu': 'fri', 'tue': 'wed'}

python interview questions :178

How Do You Count The Occurrences Of Each Item Present In The List Without Explicitly Mentioning Them?

  • Unlike sets, lists can have items with same values. In Python, the list has a <count()> function which returns the occurrences of a particular item.
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  • Count The Occurrences Of An Individual Item.
weekdays = ['sun','mon','tue','wed','thu','fri','sun','mon','mon']
print(weekdays.count('mon'))
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output:

3
  • Count The Occurrences Of Each Item In The List.
  1. We’ll use the list comprehension along with the <count()> method. It’ll print the frequency of each of the items.
weekdays = ['sun','mon','tue','wed','thu','fri','sun','mon','mon']
print([[x,weekdays.count(x)] for x in set(weekdays)])
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output:

 [['wed', 1], ['sun', 2], ['thu', 1], ['tue', 1], ['mon', 3], ['fri', 1]]

python interview questions :179

What Is NumPy And How Is It Better Than A List In Python?

  • NumPy is a Python package for scientific computing which can deal with large data sizes. It includes a powerful N-dimensional array object and a set of advanced functions.
  • Also, the NumPy arrays are superior to the built-in lists. There are a no. of reasons for this.
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  • NumPy arrays are more compact than lists.
  • Reading and writing items is faster with NumPy.
  • Using NumPy is more convenient than to the standard list.
  • NumPy arrays are more efficient as they augment the functionality of lists in Python.

python interview questions :180

What Are Different Ways To Create An Empty NumPy Array In Python?

  • There are two methods which we can apply to create empty NumPy arrays.
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  • The First Method To Create An Empty Array.
import numpy
numpy.array([])
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  • The Second Method To Create An Empty Array.
# Make an empty NumPy array
numpy.empty(shape=(0,0))

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