Python Interview Question & Answers

1. Compare Java & Python

Criteria	Java	Python
Ease of use	Good	Very Good
Speed of coding	Average	Excellent
Data types	Static typed	Dynamically typed
Data Science & machine learning applications	Average	Very Good

2. What is Python?

Python is a high-level, interpreted, interactive and object-oriented scripting language. Python is designed to be highly readable. It uses English keywords frequently where as other languages use punctuation, and it has fewer syntactical constructions than other languages

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3. What is the purpose of PYTHONPATH environment variable?

PYTHONPATH − It has a role similar to PATH. This variable tells the Python interpreter where to locate the module files imported into a program. It should include the Python source library directory and the directories containing Python source code. PYTHONPATH is sometimes preset by the Python installer.

4. What is the purpose of Pythonstartup, Pythoncaseok, Pythonhome, Pythonstartup environment variables?

Pythonstartup − It contains the path of an initialization file containing Python source code. It is executed everytime you start the interpreter. It is named as .pythonrc.py in Unix and it contains commands that load utilities or modify Pythonpath

Pythoncaseok − It is used in Windows to instruct Python to find the first case-insensitive match in an import statement. Set this variable to any value to activate it.

Pythonhome − It is an alternative module search path. It is usually embedded in the Pythonstartup or Pythonpath directories to make switching module libraries easy.

5. What are the supported data types in Python?

Python has five standard data types −

• Numbers
• String
• List
• Tuple
• Dictionary

6. What is the difference between list and tuples?

LIST	TUPLES
Lists are mutable i.e they can be edited.	Tuples are immutable (tuples are lists which can’t be edited).
Lists are slower than tuples.	Tuples are faster than list.
Syntax: list_1 = [10, ‘Chelsea’, 20]	Syntax: tup_1 = (10, ‘Chelsea’ , 20)

7. How is memory managed in Python?

1. Python memory is managed by Python private heap space. All Python objects and data structures are located in a private heap. The programmer does not have an access to this private heap and interpreter takes care of this Python private heap.
2. The allocation of Python heap space for Python objects is done by Python memory manager. The core API gives access to some tools for the programmer to code.
3. Python also have an inbuilt garbage collector, which recycle all the unused memory and frees the memory and makes it available to the heap space.

8. Explain Inheritance in Python with an example.

Inheritance allows One class to gain all the members(say attributes and methods) of another class. Inheritance provides code reusability, makes it easier to create and maintain an application. The class from which we are inheriting is called super-class and the class that is inherited is called a derived / child class.

They are different types of inheritance supported by Python:

·         Single Inheritance – where a derived class acquires the members of a single super class.

·         Multi-level inheritance – a derived class d1 in inherited from base class base1, and d2 is inherited from base2.

·         Hierarchical inheritance – from one base class you can inherit any number of child classes

·         Multiple inheritance – a derived class is inherited from more than one base class.

9. Whenever Python exits, why isn’t all the memory de-allocated?

·         Whenever Python exits, especially those Python modules which are having circular references to other objects or the objects that are referenced from the global namespaces are not always de-allocated or freed.

·         It is impossible to de-allocate those portions of memory that are reserved by the C library.

·         On exit, because of having its own efficient clean up mechanism, Python would try to de-allocate/destroy every other object.

10. What is dictionary in Python?

The built-in datatypes in Python is called dictionary. It defines one-to-one relationship between keys and values. Dictionaries contain pair of keys and their corresponding values. Dictionaries are indexed by keys.

Let’s take an example:

The following example contains some keys. Country, Capital & PM. Their corresponding values are India, Delhi and Modi respectively.

dict={‘Country’:’India’,’Capital’:’Delhi’,’PM’:’Modi’}

print dict[Country]

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