Interview Questions Flashcards
What is Python? What are the benefits of using Python
Python is a high-level, interpreted, general-purpose programming language. Being a general-purpose language, it can be used to build almost any type of application with the right tools/libraries. Additionally, python supports objects, modules, threads, exception-handling, and automatic memory management which help in modelling real-world problems and building applications to solve these problems.
What is a dynamically typed language?
Static - Data Types are checked before execution.
Dynamic - Data Types are checked during execution.
What is PEP 8 and why is it important?
PEP stands for Python Enhancement Proposal. A PEP is an official design document providing information to the Python community, or describing a new feature for Python or its processes. PEP 8 is especially important since it documents the style guidelines for Python Code. Apparently contributing to the Python open-source community requires you to follow these style guidelines sincerely and strictly
What is an interpreter language
An Interpreted language executes its statements line by line. Languages such as Python, Javascript, R, PHP, and Ruby are prime examples of Interpreted languages. Programs written in an interpreted language runs directly from the source code, with no intermediary compilation step.
is not in machine-level code before runtime.
What is Scope in Python
Every object in Python functions within a scope. A scope is a block of code where an object in Python remains relevant. Namespaces uniquely identify all the objects inside a program. However, these namespaces also have a scope defined for them where you could use their objects without any prefix. A few examples of scope created during code execution in Python are as follows:
A local scope refers to the local objects available in the current function.
A global scope refers to the objects available throughout the code execution since their inception.
A module-level scope refers to the global objects of the current module accessible in the program.
An outermost scope refers to all the built-in names callable in the program. The objects in this scope are searched last to find the name referenced.
What are lists and tuples? What is the key difference between the two?
Lists and Tuples are both sequence data types that can store a collection of objects in Python. The objects stored in both sequences can have different data types. Lists are represented with square brackets [‘sara’, 6, 0.19], while tuples are represented with parantheses (‘ansh’, 5, 0.97). The key difference between the two is that while lists are mutable, tuples on the other hand are immutable objects
What is pass in Python?
The pass keyword represents a null operation in Python. It is generally used for the purpose of filling up empty blocks of code which may execute during runtime but has yet to be written. Without the pass statement in the following code, we may run into some errors during code execution.
What are modules and packages in Python?
Python packages and Python modules are two mechanisms that allow for modular programming in Python. Modularizing has several advantages -
Simplicity: Working on a single module helps you focus on a relatively small portion of the problem at hand. This makes development easier and less error-prone.
Maintainability: Modules are designed to enforce logical boundaries between different problem domains. If they are written in a manner that reduces interdependency, it is less likely that modifications in a module might impact other parts of the program.
Reusability: Functions defined in a module can be easily reused by other parts of the application.
Scoping: Modules typically define a separate namespace, which helps avoid confusion between identifiers from other parts of the program.
Modules, in general, are simply Python files with a .py extension and can have a set of functions, classes, or variables defined and implemented. They can be imported and initialized once using the import statement. If partial functionality is needed, import the requisite classes or functions using from foo import bar.
Packages allow for hierarchial structuring of the module namespace using dot notation. As, modules help avoid clashes between global variable names, in a similar manner, packages help avoid clashes between module names.
Creating a package is easy since it makes use of the system’s inherent file structure. So just stuff the modules into a folder and there you have it, the folder name as the package name. Importing a module or its contents from this package requires the package name as prefix to the module name joined by a dot.
What are global, protected and private attributes in Python?
Global variables are public variables that are defined in the global scope. To use the variable in the global scope inside a function, we use the global keyword.
Protected attributes are attributes defined with an underscore prefixed to their identifier eg. _sara. They can still be accessed and modified from outside the class they are defined in but a responsible developer should refrain from doing so.
Private attributes are attributes with double underscore prefixed to their identifier eg. __ansh. They cannot be accessed or modified from the outside directly and will result in an AttributeError if such an attempt is made.
What is the use of self in Python?
Self is used to represent the instance of the class. With this keyword, you can access the attributes and methods of the class in python. It binds the attributes with the given arguments. self is used in different places and often thought to be a keyword. But unlike in C++, self is not a keyword in Python
What is __init__?
__init__ is a contructor method in Python and is automatically called to allocate memory when a new object/instance is created. All classes have a __init__ method associated with them. It helps in distinguishing methods and attributes of a class from local variables.
What is break, continue and pass in Python?
Break The break statement terminates the loop immediately and the control flows to the statement after the body of the loop.
Continue The continue statement terminates the current iteration of the statement, skips the rest of the code in the current iteration and the control flows to the next iteration of the loop.
Pass As explained above, the pass keyword in Python is generally used to fill up empty blocks and is similar to an empty statement represented by a semi-colon in languages such as Java, C++, Javascript, etc.
What are unit tests in Python?
Unit test is a unit testing framework of Python.
Unit testing means testing different components of software separately.
Can you think about why unit testing is important? Imagine a scenario, you are building software that uses three components namely A, B, and C. Now, suppose your software breaks at a point time. How will you find which component was responsible for breaking the software? Maybe it was component A that failed, which in turn failed component B, and this actually failed the software. There can be many such combinations.
This is why it is necessary to test each and every component properly so that we know which component might be highly responsible for the failure of the software.
What is docstring in Python?
Documentation string or docstring is a multiline string used to document a specific code segment.
The docstring should describe what the function or method does.
What is slicing in Python?
As the name suggests, ‘slicing’ is taking parts of.
Syntax for slicing is [start : stop : step]
start is the starting index from where to slice a list or tuple
stop is the ending index or where to sop.
step is the number of steps to jump.
Default value for start is 0, stop is number of items, step is 1.
Slicing can be done on strings, arrays, lists, and tuples.
What is the difference between Python Arrays and lists?
- Arrays in python can only contain elements of same data types i.e., data type of array should be homogeneous.
- It is a thin wrapper around C language arrays
consumes far less memory than lists. - Lists in python can contain elements of different data types i.e., data type of lists can be heterogeneous. It has the disadvantage of consuming large memory.
How is memory managed in Python?
Memory management in Python is handled by the Python Memory Manager. The memory allocated by the manager is in form of a private heap space dedicated to Python. All Python objects are stored in this heap and being private, it is inaccessible to the programmer. Though, python does provide some core API functions to work upon the private heap space.
Additionally, Python has an in-built garbage collection to recycle the unused memory for the private heap space.
What are Python namespaces? Why are they used?
namespace in Python ensures that object names in a program are unique and can be used without any conflict. Python implements these namespaces as dictionaries with ‘name as key’ mapped to a corresponding ‘object as value’. This allows for multiple namespaces to use the same name and map it to a separate object. A few examples of namespaces are as follows:
Local Namespace includes local names inside a function. the namespace is temporarily created for a function call and gets cleared when the function returns.
Global Namespace includes names from various imported packages/ modules that are being used in the current project. This namespace is created when the package is imported in the script and lasts until the execution of the script.
Built-in Namespace includes built-in functions of core Python and built-in names for various types of exceptions.
The lifecycle of a namespace depends upon the scope of objects they are mapped to. If the scope of an object ends, the lifecycle of that namespace comes to an end. Hence, it isn’t possible to access inner namespace objects from an outer namespace.
What is Scope Resolution in Python
What is Scope Resolution in Python?
Sometimes objects within the same scope have the same name but function differently. In such cases, scope resolution comes into play in Python automatically. A few examples of such behavior are:
Python modules namely ‘math’ and ‘cmath’ have a lot of functions that are common to both of them - log10(), acos(), exp() etc. To resolve this ambiguity, it is necessary to prefix them with their respective module, like math.exp() and cmath.exp().
Consider the code below, an object temp has been initialized to 10 globally and then to 20 on function call. However, the function call didn’t change the value of the temp globally. Here, we can observe that Python draws a clear line between global and local variables, treating their namespaces as separate identities.
What are decorators in Python?
decorator function to convert to lowercase
functionality to an existing function in Python without changing the structure of the function itself. They are represented the @decorator_name in Python and are called in a bottom-up fashion. For example:
def lowercase_decorator(function):
def wrapper():
func = function()
string_lowercase = func.lower()
return string_lowercase
return wrapper
# decorator function to split words
def splitter_decorator(function):
def wrapper():
func = function()
string_split = func.split()
return string_split
return wrapper
@splitter_decorator # this is executed next
@lowercase_decorator # this is executed first
def hello():
return ‘Hello World’
hello() # output => [ ‘hello’ , ‘world’ ]
The beauty of the decorators lies in the fact that besides adding functionality to the output of the method, they can even accept arguments for functions and can further modify those arguments before passing it to the function itself. The inner nested function, i.e. ‘wrapper’ function, plays a significant role here. It is implemented to enforce encapsulation and thus, keep itself hidden from the global scope.
What is lambda in Python? Why is it used?
Lambda is an anonymous function in Python, that can accept any number of arguments, but can only have a single expression. It is generally used in situations requiring an anonymous function for a short time period. Lambda functions can be used in either of the two ways:
Assigning lambda functions to a variable:
mul = lambda a, b : a * b
print(mul(2, 5)) # output => 10
Wrapping lambda functions inside another function:
What are generators in Python?
Generators are functions that return an iterable collection of items, one at a time, in a set manner.
Generators, in general, are used to create iterators with a different approach. They employ the use of yield keyword rather than return to return a generator object.
What is PYTHONPATH in Python?
PYTHONPATH is an environment variable which you can set to add additional directories where Python will look for modules and packages. This is especially useful in maintaining Python libraries that you do not wish to install in the global default location.
What is the use of help() and dir() functions?
help() function in Python is used to display the documentation of modules, classes, functions, keywords, etc. If no parameter is passed to the help() function, then an interactive help utility is launched on the console.
dir() function tries to return a valid list of attributes and methods of the object it is called upon. It behaves differently with different objects, as it aims to produce the most relevant data, rather than the complete information.
For Modules/Library objects, it returns a list of all attributes, contained in that module.
For Class Objects, it returns a list of all valid attributes and base attributes.
With no arguments passed, it returns a list of attributes in the current scope.
How Python is interpreted?
Python as a language is not interpreted or compiled. Interpreted or compiled is the property of the implementation. Python is a bytecode(set of interpreter readable instructions) interpreted generally.
Source code is a file with .py extension.
Python compiles the source code to a set of instructions for a virtual machine. The Python interpreter is an implementation of that virtual machine. This intermediate format is called “bytecode”.
.py source code is first compiled to give .pyc which is bytecode. This bytecode can be then interpreted by the official CPython or JIT(Just in Time compiler) compiled by PyPy.
