Python subjective question for competitive exam (4)

Q1.How will you improve the performance of a program in Python?

There are many ways to improve the performance of a Python
program. Some of these are as follows:
i. Data Structure: We have to select the right data structure
for our purpose in a Python program.
ii. Standard Library: Wherever possible, we should use
methods from standard library. Methods implemented in
standard library have much better performance than user
implementation.
iii. Abstraction: At times, a lot of abstraction and
indirection can cause slow performance of a program.
We should remove the redundant abstraction in code.
iv. Algorithm: Use of right algorithm can make a big
difference in a program. We have to find and select the
suitable algorithm to solve our problem with high
performance.

Q2. What is the difference between a Tuple and List in Python?

In Python, Tuple and List are built-in data structures.
Some of the differences between Tuple and List are as follows:
I. Syntax: A Tuple is enclosed in parentheses:
E.g. myTuple = (10, 20, “apple”);
A List is enclosed in brackets:
E.g. myList = [10, 20, 30];
II. Mutable: Tuple is an immutable data structure. Whereas, a List is
a mutable data structure.
III. Size: A Tuple takes much lesser space than a List in Python.
IV. Performance: Tuple is faster than a List in Python. So it gives us
good performance.

Q3. What are the benefits of using Python?

Python is strong that even Google uses it. Some of the benefits of using
Python are as follows:
i. Efficient: Python is very efficient in memory
management. For a large data set like Big Data, it is much
easier to program in Python.
ii. Faster: Though Python code is interpreted, still Python
has very fast performance.
iii. Wide usage: Python is widely used among different
organizations for different projects. Due to this wide
usage, there are thousands of add-ons available for use
with Python.
iv. Easy to learn: Python is quite easy to learn. This is the
biggest benefit of using Python. Complex tasks can be
very easily implemented in Python.

Q4.What is the difference between List and Dictionary data types in Python?

Main differences between List and Dictionary data types in Python are as
follows:
I. Syntax: In a List we store objects in a sequence. In a Dictionary
we store objects in key-value pairs.
II. Reference: In List we access objects by index number. It starts
from 0 index. In a Dictionary we access objects by key specified at
the time of Dictionary creation.
III. Ordering: In a List objects are stored in an ordered sequence. In a
Dictionary objects are not stored in an ordered sequence.
IV. Hashing: In a Dictionary, keys have to be hashable. In a List there
is no need for hashing.

Q5.What are the different built-in data types available in Python?

Some of the built-in data types available in Python are as follows:
Numeric types: These are the data types used to represent numbers in
Python.
int: It is used for Integers
long: It is used for very large integers of non-limited length.
float: It is used for decimal numbers.
complex: This one is for representing complex numbers
Sequence types: These data types are used to represent sequence of
characters or objects.
str: This is similar to String in Java. It can represent a sequence of
characters.
bytes: This is a sequence of integers in the range of 0-255.
byte array: like bytes, but mutable (see below); only available in Python 3.x
list: This is a sequence of objects.
tuple: This is a sequence of immutable objects.
Sets: These are unordered collections.
set: This is a collection of unique objects.
frozen set: This is a collection of unique immutable objects.
Mappings: This is similar to a Map in Java.
dict: This is also called hashmap. It has key value pair to store information
by using hashing