🔰 Python Developer 🔰
Last Updated: 2023-09-23- What is monkey patching in Python?
- Does python support multiple inheritance?
- What is Polymorphism in Python?
- Define encapsulation in Python?
- How do you do data abstraction in Python?
- Does python make use of access specifiers?
- How to create an empty class in Python?
- What is a control flow statement?
- Create a new list to convert the following list of number strings to a list of numbers.
- Given the first and last names of all employees in your firm, what data type will you use to store it?
- How would you work with numbers other than those in the decimal number system?
- What does the following code output?
- How many arguments can the range() function take?
- What is PEP 8?
- How is Python different from Java?
- What is the best code you can write to swap two numbers?
- How can you declare multiple assignments in one statement?
- If you are ever stuck in an infinite loop, how will you break out of it?
- What does an object() do?
- Write a program in Python to execute the Bubble sort algorithm.
- Write a program in Python to produce Star triangle.
- Write a program to produce Fibonacci series in Python.
- Write a program in Python to check if a number is prime.
- Write a program in Python to check if a sequence is a Palindrome.
- Write a one-liner that will count the number of capital letters in a file. Your code should work even if the file is too big to fit in memory.
- How do we execute Python?
- Explain Python’s parameter-passing mechanism.
- What is the with statement in Python?
- How is a .pyc file different from a .py file?
- What makes Python object-oriented?
- How many types of objects does Python support?
- Write a sorting algorithm for a numerical dataset in Python.
- Looking at the below code, write down the final values of A0, A1, …An.
- Explain what Flask is and its benefits?
- Is Django better than Flask?
- Mention the differences between Django, Pyramid and Flask.
- Discuss Django architecture.
- Explain how you can set up the Database in Django.
- Give an example how you can write a VIEW in Django?
- Mention what the Django templates consist of.
- Explain the use of session in Django framework?
- List out the inheritance styles in Django.
- How To Save An Image Locally Using Python Whose URL Address I Already Know?
- How can you Get the Google cache age of any URL or web page?
- You are required to scrap data from IMDb top 250 movies page. It should only have fields movie name, year, and rating.
- What is map function in Python?
- Is python numpy better than lists?
- How to get indices of N maximum values in a NumPy array?
- How do you calculate percentiles with Python/ NumPy?
- What is the difference between NumPy and SciPy?
- How do you make 3D plots/visualizations using NumPy/SciPy?
- Which of the following statements create a dictionary? (Multiple Correct Answers Possible)
- Which one of these is floor division?
- What is the maximum possible length of an identifier?
- Why are local variable names beginning with an underscore discouraged?
- Which of the following is an invalid statement?
- What is the output of the following?
- Suppose list1 is [2, 33, 222, 14, 25], What is list1[-1] ?
- To open a file c:scores.txt for writing, we use
- What is the output of the following?
- When will the else part of try-except-else be executed?
- What is the difference between list and tuples in Python?
- What are the key features of Python?
- What type of language is python? Programming or scripting?
- Python an interpreted language. Explain.
- What is pep 8?
- How is memory managed in Python?
- What is namespace in Python?
- What is PYTHONPATH?
- What are python modules? Name some commonly used built-in modules in Python?
- What are local variables and global variables in Python?
- Is python case sensitive?
- What is type conversion in Python?
- What are the key features of Python?
- Differentiate between lists and tuples.
- Explain the ternary operator in Python.
- What are negative indices?
- Is Python case-sensitive?
- How long can an identifier be in Python?
- How would you convert a string into lowercase?
- What is the pass statement in Python?
- Explain help() and dir() functions in Python.
- How do you get a list of all the keys in a dictionary?
- What is slicing?
- How would you declare a comment in Python?
- How will you check if all characters in a string are alphanumeric?
- How will you capitalize the first letter of a string?
- We know Python is all the rage these days. But to be truly accepting of a great technology, you must know its pitfalls as well. Would you like to talk about this?
- With Python, how do you find out which directory you are currently in?
- How do you insert an object at a given index in Python?
- And how do you reverse a list?
- What is the Python interpreter prompt?
- How does a function return values?
- How would you define a block in Python?
- Why do we need break and continue in Python?
- Will the do-while loop work if you don’t end it with a semicolon?
- In one line, show us how you’ll get the max alphabetical character from a string.
- What is Python good for?
- Can you name ten built-in functions in Python and explain each in brief?
- What will the following code output?
- How will you convert a list into a string?
- How will you remove a duplicate element from a list?
- Can you explain the life cycle of a thread?
- What is a dictionary in Python?
- Explain the //, %, and ** operators in Python.
- What do you know about relational operators in Python.
- What are assignment operators in Python?
- Explain logical operators in Python.
- What are membership operators?
- Explain identity operators in Python.
- Finally, tell us about bitwise operators in Python.
- What data types does Python support?
- What is a docstring?
- How would you convert a string into an int in Python?
- How do you take input in Python?
- What is a function?
- What is recursion?
- What does the function zip() do?
- How do you calculate the length of a string?
- Explain Python List Comprehension.
- How do you get all values from a Python dictionary?
- What if you want to toggle case for a Python string?
- Write code to print only upto the letter t.
- Write code to print everything in the string except the spaces.
- Now, print this string five times in a row.
- What is the purpose of bytes() in Python?
- How to install Python on Windows and set path variable?
- Is indentation required in python?
- What is the difference between Python Arrays and lists?
- What are functions in Python?
- What is __init__?
- What is a lambda function?
- What is self in Python?
- How does break, continue and pass work?
- What does [::-1} do?
- How can you randomize the items of a list in place in Python?
- What are python iterators?
- How can you generate random numbers in Python?
- What is the difference between range & xrange?
- How do you write comments in python?
- What is pickling and unpickling?
- What are the generators in python?
- How will you capitalize the first letter of string?
- How will you convert a string to all lowercase?
- How to comment multiple lines in python?
- What are docstrings in Python?
- What is the purpose of is, not and in operators?
- What is the usage of help() and dir() function in Python?
- Whenever Python exits, why isn’t all the memory de-allocated?
- What is a dictionary in Python?
- How can the ternary operators be used in python?
- What does this mean: *args, **kwargs? And why would we use it?
- What does len() do?
- Explain split(), sub(), subn() methods of “re” module in Python.
- What are negative indexes and why are they used?
- What are Python packages?
- How can files be deleted in Python?
- What are the built-in types of python?
- What advantages do NumPy arrays offer over (nested) Python lists?
- How to add values to a python array?
- How to remove values to a python array?
- Does Python have OOps concepts?
- What is the difference between deep and shallow copy?
- How is Multithreading achieved in Python?
- What is the process of compilation and linking in python?
- What are Python libraries? Name a few of them.
- What is split used for?
- How to import modules in python?
- Explain Inheritance in Python with an example.
- How are classes created in Python?
Ans: In Python, the term monkey patch only refers to dynamic modifications of a class or module at run-time.
Consider the below example:
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# m.py
class MyClass:
def f(self):
print "f()"
We can then run the monkey-patch testing like this:
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import m
def monkey_f(self):
print "monkey_f()"
m.MyClass.f = monkey_f
obj = m.MyClass()
obj.f()
The output will be as below:
monkey_f()
As we can see, we did make some changes in the behavior of f() in MyClass using the function we defined, monkey_f(), outside of the module m.
Ans: Multiple inheritance means that a class can be derived from more than one parent classes. Python does support multiple inheritance, unlike Java.
Ans: Polymorphism means the ability to take multiple forms. So, for instance, if the parent class has a method named ABC then the child class also can have a method with the same name ABC having its own parameters and variables. Python allows polymorphism.
Ans: Encapsulation means binding the code and the data together. A Python class in an example of encapsulation.
Ans: Data Abstraction is providing only the required details and hiding the implementation from the world. It can be achieved in Python by using interfaces and abstract classes.
Ans: Python does not deprive access to an instance variable or function. Python lays down the concept of prefixing the name of the variable, function or method with a single or double underscore to imitate the behavior of protected and private access specifiers.
Ans: An empty class is a class that does not have any code defined within its block. It can be created using the pass keyword. However, you can create objects of this class outside the class itself. IN PYTHON THE PASS command does nothing when its executed. it’s a null statement.
For example-
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class a:
  pass
obj=a()
obj.name="xyz"
print("Name = ",obj.name)
Output:
Name = xyz
A Python program usually starts to execute from the first line. From there, it moves through each statement just once and as soon as it’s done with the last statement, it transactions the program. However, sometimes, we may want to take a more twisted path through the code. Control flow statements let us disturb the normal execution flow of a program and bend it to our will.
nums=[‘22’,’68’,’110’,’89’,’31’,’12’]
We will use the int() function with a list comprehension to convert these strings into integers and put them in a list.
>>> [int(i) for i in nums]
[22, 68, 110, 89, 31, 12]
I can use a dictionary to store that. It would be something like this-
{‘first_name’:’Ayushi’,’second_name’:’Sharma’
With Python, it is possible to type numbers in binary, octal, and hexadecimal.
Binary numbers are made of 0 and 1. To type in binary, we use the prefix 0b or 0B.
>>> int(0b1010)
10
To convert a number into its binary form, we use bin().
>>> bin(0xf)
‘0b1111’
Octal numbers may have digits from 0 to 7. We use the prefix 0o or 0O.
>>> oct(8)
‘0o10’
Hexadecimal numbers may have digits from 0 to 15. We use the prefix 0x or 0X.
>>> hex(16)
‘0x10’
>>> hex(15)
‘0xf’
DataFlair’s latest article on Python Numbers with Examples
>>> def extendList(val, list=[]):
list.append(val)
return list
>>> list1 = extendList(10)
>>> list2 = extendList(123,[])
>>> list3 = extendList('a')
>>> list1,list2,list3
([10, ‘a’], [123], [10, ‘a’])
You’d expect the output to be something like this:
([10],[123],[‘a’])
Well, this is because the list argument does not initialize to its default value ([]) every time we make a call to the function. Once we define the function, it creates a new list. Then, whenever we call it again without a list argument, it uses the same list. This is because it calculates the expressions in the default arguments when we define the function, not when we call it.
The range() function in Python can take up to 3 arguments. Let’s see this one by one.
a. One argument
When we pass only one argument, it takes it as the stop value. Here, the start value is 0, and the step value is +1.
>>> list(range(5))
[0, 1, 2, 3, 4]
>>> list(range(-5))
[]
>>> list(range(0))
[]
b. Two arguments
When we pass two arguments, the first one is the start value, and the second is the stop value.
>>> list(range(2,7))
[2, 3, 4, 5, 6]
>>> list(range(7,2))
[]
>>> list(range(-3,4))
[-3, -2, -1, 0, 1, 2, 3]
c. Three arguments
Here, the first argument is the start value, the second is the stop value, and the third is the step value.
>>> list(range(2,9,2))
[2, 4, 6, 8]
>>> list(range(9,2,-1))
[9, 8, 7, 6, 5, 4, 3]
PEP 8 is a coding convention that lets us write more readable code. In other words, it is a set of recommendations.
Python vs Java - Which is best for Beginners
Following is the comparison of Python vs Java –
Java is faster than Python
Python mandates indentation. Java needs braces.
Python is dynamically-typed; Java is statically typed.
Python is simple and concise; Java is verbose
Python is interpreted
Java is platform-independent
Java has stronger database-access with JDBC
I can perform the swapping in one statement.
>>> a,b=b,a
Here’s the entire code, though-
>>> a,b=2,3
>>> a,b=b,a
>>> a,b
(3, 2)
This is one of the most asked interview questions for Python freshers –
There are two ways to do this:
First –
>>> a,b,c=3,4,5 #This assigns 3, 4, and 5 to a, b, and c respectively
Second –
>>> a=b=c=3 #This assigns 3 to a, b, and c
For this, we press Ctrl+C. This interrupts the execution. Let’s create an infinite loop to demonstrate this.
>>> def counterfunc(n):
while(n==7):print(n)
>>> counterfunc(7)
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7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
Traceback (most recent call last):
File “
counterfunc(7)
File “
while(n==7):print(n)
KeyboardInterrupt
Ans: It returns a featureless object that is a base for all classes. Also, it does not take any parameters.
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def bs(a):             # a = name of list
  b=len(a)-1         # minus 1 because we always compare 2 adjacent values
                           
  for x in range(b):
      for y in range(b-x):
          if a[y]>a[y+1]:
              a[y],a[y+1]=a[y+1],a[y]
  return a
a=[32,5,3,6,7,54,87]
bs(a)
Output: [3, 5, 6, 7, 32, 54, 87]
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def pyfunc(r):
for x in range(r):
print(' '*(r-x-1)+'*'*(2*x+1))
pyfunc(9)
Output:
*
***
*****
*******
*********
***********
*************
***************
*****************
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# Enter number of terms needed                   #0,1,1,2,3,5....
a=int(input("Enter the terms"))
f=0                                         #first element of series
s=1                                         #second element of series
if a<=0:
  print("The requested series is
",f)
else:
  print(f,s,end=" ")
  for x in range(2,a):
      next=f+s                         
      print(next,end=" ")
      f=s
      s=next</pre>
Output: Enter the terms 5 0 1 1 2 3
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a=int(input("enter number"))     
if a>1:
  for x in range(2,a):
      if(a%x)==0:
          print("not prime")
          break
  else:
      print("Prime")
else:
  print("not prime")
Output:
enter number 3
Prime
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a=input("enter sequence")
b=a[::-1]
if a==b:
  print("palindrome")
else:
  print("Not a Palindrome")
Output:
enter sequence 323 palindrome
Ans: Let us first write a multiple line solution and then convert it to one-liner code.
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with open(SOME_LARGE_FILE) as fh:
count = 0
text = fh.read()
for character in text:
if character.isupper():
count += 1
We will now try to transform this into a single line.
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count sum(1 for line in fh for character in line if character.isupper())
Python files first compile to bytecode. Then, the host executes them.
Revise the concept of Python Compiler
To pass its parameters to a function, Python uses pass-by-reference. If you change a parameter within a function, the change reflects in the calling function. This is its default behavior. However, when we pass literal arguments like strings, numbers, or tuples, they pass by value. This is because they are immutable.
The with statement in Python ensures that cleanup code is executed when working with unmanaged resources by encapsulating common preparation and cleanup tasks. It may be used to open a file, do something, and then automatically close the file at the end. It may be used to open a database connection, do some processing, then automatically close the connection to ensure resources are closed and available for others. with will cleanup the resources even if an exception is thrown. This statement is like the using statement in C#.
Consider you put some code in a try block, then in the finally block, you close any resources used. The with statement is like syntactic sugar for that.
The syntax of this control-flow structure is:
with expression [as variable]:
….with-block
>>> with open('data.txt') as data:
#processing statements
While both files hold bytecode, .pyc is the compiled version of a Python file. It has platform-independent bytecode. Hence, we can execute it on any platform that supports the .pyc format. Python automatically generates it to improve performance(in terms of load time, not speed).
Python OOPS Interview Questions and Answers
Python is object-oriented because it follows the Object-Oriented programming paradigm. This is a paradigm that revolves around classes and their instances (objects). With this kind of programming, we have the following features:
Encapsulation
Abstraction
Inheritance
Polymorphism
Data hiding
Objects in Python are mutable and immutable. Let’s talk about these.
Immutable objects- Those which do not let us modify their contents. Examples of these will be tuples, booleans, strings, integers, floats, and complexes. Iterations on such objects are faster.
>>> tuple=(1,2,4)
>>> tuple
(1, 2, 4)
>>> 2+4j
(2+4j)
Mutable objects – Those that let you modify their contents. Examples of these are lists, sets, and dicts. Iterations on such objects are slower.
>>> [2,4,9]
[2, 4, 9]
>>> dict1={1:1,2:2}
>>> dict1
{1: 1, 2: 2}
While two equal immutable objects’ reference variables share the same address, it is possible to create two mutable objects with the same content.
Ans: The following code can be used to sort a list in Python:
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list = ["1", "4", "0", "6", "9"]
list = [int(i) for i in list]
list.sort()
print (list)
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A0 = dict(zip(('a','b','c','d','e'),(1,2,3,4,5)))
A1 = range(10)A2 = sorted([i for i in A1 if i in A0])
A3 = sorted([A0[s] for s in A0])
A4 = [i for i in A1 if i in A3]
A5 = {i:i*i for i in A1}
A6 = [[i,i*i] for i in A1]
print(A0,A1,A2,A3,A4,A5,A6)
Ans: The following will be the final outputs of A0, A1, … A6
A0 = {'a': 1, 'c': 3, 'b': 2, 'e': 5, 'd': 4} # the order may vary
A1 = range(0, 10)
A2 = []
A3 = [1, 2, 3, 4, 5]
A4 = [1, 2, 3, 4, 5]
A5 = {0: 0, 1: 1, 2: 4, 3: 9, 4: 16, 5: 25, 6: 36, 7: 49, 8: 64, 9: 81}
A6 = [[0, 0], [1, 1], [2, 4], [3, 9], [4, 16], [5, 25], [6, 36], [7, 49], [8, 64], [9, 81]]
Ans: Flask is a web microframework for Python based on “Werkzeug, Jinja2 and good intentions” BSD license. Werkzeug and Jinja2 are two of its dependencies. This means it will have little to no dependencies on external libraries. It makes the framework light while there is a little dependency to update and fewer security bugs.
A session basically allows you to remember information from one request to another. In a flask, a session uses a signed cookie so the user can look at the session contents and modify. The user can modify the session if only it has the secret key Flask.secret_key.
Ans: Django and Flask map the URL’s or addresses typed in the web browsers to functions in Python.
Flask is much simpler compared to Django but, Flask does not do a lot for you meaning you will need to specify the details, whereas Django does a lot for you wherein you would not need to do much work. Django consists of prewritten code, which the user will need to analyze whereas Flask gives the users to create their own code, therefore, making it simpler to understand the code. Technically both are equally good and both contain their own pros and cons.
Ans:
Flask is a “microframework” primarily build for a small application with simpler requirements. In flask, you have to use external libraries. Flask is ready to use.
Pyramid is built for larger applications. It provides flexibility and lets the developer use the right tools for their project. The developer can choose the database, URL structure, templating style and more. Pyramid is heavy configurable.
Django can also be used for larger applications just like Pyramid. It includes an ORM.
Ans: Django MVT Pattern:
Ans: You can use the command edit mysite/setting.py, it is a normal python module with module level representing Django settings.
Django uses SQLite by default; it is easy for Django users as such it won’t require any other type of installation. In the case your database choice is different that you have to the following keys in the DATABASE ‘default’ item to match your database connection settings.
Engines: you can change the database by using ‘django.db.backends.sqlite3’ , ‘django.db.backeneds.mysql’, ‘django.db.backends.postgresql_psycopg2’, ‘django.db.backends.oracle’ and so on
Name: The name of your database. In the case if you are using SQLite as your database, in that case, database will be a file on your computer, Name should be a full absolute path, including the file name of that file.
If you are not choosing SQLite as your database then settings like Password, Host, User, etc. must be added.
Django uses SQLite as a default database, it stores data as a single file in the filesystem. If you do have a database server—PostgreSQL, MySQL, Oracle, MSSQL—and want to use it rather than SQLite, then use your database’s administration tools to create a new database for your Django project. Either way, with your (empty) database in place, all that remains is to tell Django how to use it. This is where your project’s settings.py file comes in.
We will add the following lines of code to the setting.py file:
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DATABASES = {
'default': {
'ENGINE' : 'django.db.backends.sqlite3',
'NAME' : os.path.join(BASE_DIR, 'db.sqlite3'),
}
}
Ans: This is how we can use write a view in Django:
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from django.http import HttpResponse
import datetime
def Current_datetime(request):
now = datetime.datetime.now()
html = "<html><body>It is now %s</body></html> % now
return HttpResponse(html)
Returns the current date and time, as an HTML document
Ans: The template is a simple text file. It can create any text-based format like XML, CSV, HTML, etc. A template contains variables that get replaced with values when the template is evaluated and tags (% tag %) that control the logic of the template.
Ans: Django provides a session that lets you store and retrieve data on a per-site-visitor basis. Django abstracts the process of sending and receiving cookies, by placing a session ID cookie on the client side, and storing all the related data on the server side.
Ans: In Django, there are three possible inheritance styles:
Abstract Base Classes: This style is used when you only want parent’s class to hold information that you don’t want to type out for each child model.
Multi-table Inheritance: This style is used If you are sub-classing an existing model and need each model to have its own database table.
Proxy models: You can use this model, If you only want to modify the Python level behavior of the model, without changing the model’s fields.
Ans: We will use the following code to save an image locally from an URL address
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import urllib.request
urllib.request.urlretrieve("URL", "local-filename.jpg")
Ans: Use the following URL format:
http://webcache.googleusercontent.com/search?q=cache:URLGOESHERE
Be sure to replace “URLGOESHERE” with the proper web address of the page or site whose cache you want to retrieve and see the time for. For example, to check the Google Webcache age of edureka.co you’d use the following URL:
http://webcache.googleusercontent.com/search?q=cache:edureka.co
Ans: We will use the following lines of code:
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from bs4 import BeautifulSoup
import requests
import sys
url = 'http://www.imdb.com/chart/top'
response = requests.get(url)
soup = BeautifulSoup(response.text)
tr = soup.findChildren("tr")
tr = iter(tr)
next(tr)
for movie in tr:
title = movie.find('td', {'class': 'titleColumn'} ).find('a').contents[0]
year = movie.find('td', {'class': 'titleColumn'} ).find('span', {'class': 'secondaryInfo'}).contents[0]
rating = movie.find('td', {'class': 'ratingColumn imdbRating'} ).find('strong').contents[0]
row = title + ' - ' + year + ' ' + ' ' + rating
print(row)
The above code will help scrap data from IMDb’s top 250 list
Ans: map function executes the function given as the first argument on all the elements of the iterable given as the second argument. If the function given takes in more than 1 arguments, then many iterables are given. #Follow the link to know more similar functions.
Ans: We use python numpy array instead of a list because of the below three reasons:
Less Memory
Fast
Convenient
For more information on these parameters, you can refer to this section – Numpy Vs List.
Ans: We can get the indices of N maximum values in a NumPy array using the below code:
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import numpy as np
arr = np.array([1, 3, 2, 4, 5])
print(arr.argsort()[-3:][::-1])
Output
[ 4 3 1 ]
Ans: We can calculate percentiles with the following code
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import numpy as np
a = np.array([1,2,3,4,5])
p = np.percentile(a, 50) #Returns 50th percentile, e.g. median
print(p)
Output
3
Ans:
In an ideal world, NumPy would contain nothing but the array data type and the most basic operations: indexing, sorting, reshaping, basic elementwise functions, et cetera.
All numerical code would reside in SciPy. However, one of NumPy’s important goals is compatibility, so NumPy tries to retain all features supported by either of its predecessors.
Thus NumPy contains some linear algebra functions, even though these more properly belong in SciPy. In any case, SciPy contains more fully-featured versions of the linear algebra modules, as well as many other numerical algorithms.
If you are doing scientific computing with python, you should probably install both NumPy and SciPy. Most new features belong in SciPy rather than NumPy.
Ans: Like 2D plotting, 3D graphics is beyond the scope of NumPy and SciPy, but just as in the 2D case, packages exist that integrate with NumPy. Matplotlib provides basic 3D plotting in the mplot3d subpackage, whereas Mayavi provides a wide range of high-quality 3D visualization features, utilizing the powerful VTK engine.
a) d = {}
b) d = {“john”:40, “peter”:45}
c) d = {40:”john”, 45:”peter”}
d) d = (40:”john”, 45:”50”)
Answer: b, c & d.
Course Curriculum
Data Science Certification Training with Python
Weekday / Weekend Batches
Dictionaries are created by specifying keys and values.
a) /
b) //
c) %
d) None of the mentioned
Answer: b) //
When both of the operands are integer then python chops out the fraction part and gives you the round off value, to get the accurate answer use floor division. For ex, 5/2 = 2.5 but both of the operands are integer so answer of this expression in python is 2. To get the 2.5 as the answer, use floor division using //. So, 5//2 = 2.5
a) 31 characters
b) 63 characters
c) 79 characters
d) None of the above
Answer: d) None of the above
Identifiers can be of any length.
a) they are used to indicate a private variables of a class
b) they confuse the interpreter
c) they are used to indicate global variables
d) they slow down execution
Answer: a) they are used to indicate a private variable of a class
As Python has no concept of private variables, leading underscores are used to indicate variables that must not be accessed from outside the class.
a) abc = 1,000,000
b) a b c = 1000 2000 3000
c) a,b,c = 1000, 2000, 3000
d) a_b_c = 1,000,000
Answer: b) a b c = 1000 2000 3000
Spaces are not allowed in variable names.
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5
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7
try:
if '1' != 1:
raise "someError"
else:
print("someError has not occured")
except "someError":
print ("someError has occured")
a) someError has occured
b) someError has not occured
c) invalid code
d) none of the above
Answer: c) invalid code
A new exception class must inherit from a BaseException. There is no such inheritance here.
a) Error
b) None
c) 25
d) 2
Answer: c) 25
The index -1 corresponds to the last index in the list.
a) outfile = open(“c:scores.txt”, “r”)
b) outfile = open(“c:scores.txt”, “w”)
c) outfile = open(file = “c:scores.txt”, “r”)
d) outfile = open(file = “c:scores.txt”, “o”)
Answer: b) The location contains double slashes ( ) and w is used to indicate that file is being written to.
1
2
3
4
5
6
7
8
f = None
for i in range (5):
with open("data.txt", "w") as f:
if i > 2:
break
print f.closed
a) True
b) False
c) None
d) Error
Answer: a) True
The WITH statement when used with open file guarantees that the file object is closed when the with block exits.
a) always
b) when an exception occurs
c) when no exception occurs
d) when an exception occurs into except block
Answer: c) when no exception occurs
The else part is executed when no exception occurs.
Answer:- LIST vs 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)
Answer:- Python is an interpreted language. That means that, unlike languages like C and its variants, Python does not need to be compiled before it is run. Other interpreted languages include PHP and Ruby.
Python is dynamically typed, this means that you don’t need to state the types of variables when you declare them or anything like that. You can do things like x=111 and then x="I'm a string" without error
Python is well suited to object orientated programming in that it allows the definition of classes along with composition and inheritance. Python does not have access specifiers (like C++’s public, private).
In Python, functions are first-class objects. This means that they can be assigned to variables, returned from other functions and passed into functions. Classes are also first class objects
Writing Python code is quick but running it is often slower than compiled languages. Fortunately,Python allows the inclusion of C-based extensions so bottlenecks can be optimized away and often are. The numpy package is a good example of this, it’s really quite quick because a lot of the number-crunching it does isn’t actually done by Python
Python finds use in many spheres – web applications, automation, scientific modeling, big data applications and many more. It’s also often used as “glue” code to get other languages and components to play nice.
Answer:- Python is capable of scripting, but in general sense, it is considered as a general-purpose programming language. To know more about Scripting, you can refer to the Python Scripting Tutorial.
Answer:- An interpreted language is any programming language which is not in machine-level code before runtime. Therefore, Python is an interpreted language.
Answer:- PEP stands for Python Enhancement Proposal. It is a set of rules that specify how to format Python code for maximum readability.
Answer:- Memory is managed in Python in the following ways:
Memory management in python is managed by Python private heap space. All Python objects and data structures are located in a private heap. The programmer does not have access to this private heap. The python interpreter takes care of this instead.
The allocation of heap space for Python objects is done by Python’s memory manager. The core API gives access to some tools for the programmer to code.
Python also has an inbuilt garbage collector, which recycles all the unused memory and so that it can be made available to the heap space.
Answer:- A namespace is a naming system used to make sure that names are unique to avoid naming conflicts.
Answer:- It is an environment variable which is used when a module is imported. Whenever a module is imported, PYTHONPATH is also looked up to check for the presence of the imported modules in various directories. The interpreter uses it to determine which module to load.
Answer:- Python modules are files containing Python code. This code can either be functions classes or variables. A Python module is a .py file containing executable code.
Some of the commonly used built-in modules are:
os
sys
math
random
data time
JSON
Answer:- Global Variables:
Variables declared outside a function or in global space are called global variables. These variables can be accessed by any function in the program.
Local Variables:
Any variable declared inside a function is known as a local variable. This variable is present in the local space and not in the global space.
Example:
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6
a=2
def add():
b=3
c=a+b
print(c)
add()
Output: 5
When you try to access the local variable outside the function add(), it will throw an error.
Answer:- Yes. Python is a case sensitive language.
Answer:- Type conversion refers to the conversion of one data type iinto another.
int() – converts any data type into integer type
float() – converts any data type into float type
ord() – converts characters into integer
hex() – converts integers to hexadecimal
oct() – converts integer to octal
tuple() – This function is used to convert to a tuple.
set() – This function returns the type after converting to set.
list() – This function is used to convert any data type to a list type.
dict() – This function is used to convert a tuple of order (key,value) into a dictionary.
str() – Used to convert integer into a string.
complex(real,imag) – This functionconverts real numbers to complex(real,imag) number.
If it makes for an introductory language to programming, Python must mean something. These are its qualities:
Interpreted
Dynamically-typed
Object-oriented
Concise and simple
Free
Has a large community
The major difference is that a list is mutable, but a tuple is immutable. Examples:
>>> mylist=[1,3,3]
>>> mylist[1]=2
>>> mytuple=(1,3,3)
>>> mytuple[1]=2
Traceback (most recent call last):
File “
mytuple[1]=2
TypeError: ‘tuple’ object does not support item assignment
Python Tuples vs Lists – A Detailed Comparison
Unlike C++, we don’t have ?: in Python, but we have this:
[on true] if [expression] else [on false]
If the expression is True, the statement under [on true] is executed. Else, that under [on false] is executed.
Below is how you would use it:
>>> a,b=2,3
>>> min=a if a< b else b
>>> min
2
>>> print("Hi") if a< b else print("Bye")
Hi
Let’s take a list for this.
>>> mylist=[0,1,2,3,4,5,6,7,8]
A negative index, unlike a positive one, begins searching from the right.
>>> mylist[-3]
6
This also helps with slicing from the back:
>>> mylist[-6:-1]
[3, 4, 5, 6, 7]
A language is case-sensitive if it distinguishes between identifiers like myname and Myname. In other words, it cares about case- lowercase or uppercase. Let’s try this with Python.
>>> myname='Ayushi'
>>> Myname
Traceback (most recent call last):
File “
Myname
NameError: name ‘Myname’ is not defined
As you can see, this raised a NameError. This means that Python is indeed case-sensitive.
According to the official Python documentation, an identifier can be of any length. However, PEP 8 suggests that you should limit all lines to a maximum of 79 characters. Also, PEP 20 says ‘readability counts’. So, a very long identifier will violate PEP-8 and PEP-20.
Apart from that, there are certain rules we must follow to name one:
It can only begin with an underscore or a character from A-Z or a-z.
The rest of it can contain anything from the following: A-Z/a-z/_/0-9.
Python is case-sensitive, as we discussed in the previous question.
Keywords cannot be used as identifiers. Python has the following keywords:
and def False import not True
as del finally in or try
assert elif for is pass while
break else from lambda print with
class except global None raise yield
continue exec if nonlocal return
We use the lower() method for this.
>>> 'AyuShi'.lower()
‘ayushi’
To convert it into uppercase, then, we use upper().
>>> 'AyuShi'.upper()
‘AYUSHI’
Also, to check if a string is in all uppercase or all lowercase, we use the methods isupper() and islower().
>>> 'AyuShi'.isupper()
False
>>> 'AYUSHI'.isupper()
True
>>> 'ayushi'.islower()
True
>>> '@yu$hi'.islower()
True
>>> '@YU$HI'.isupper()
True
So, characters like @ and $ will suffice for both cases
Also, istitle() will tell us if a string is in title case.
>>> 'The Corpse Bride'.istitle()
True
There may be times in our code when we haven’t decided what to do yet, but we must type something for it to be syntactically correct. In such a case, we use the pass statement.
>>> def func(*args):
pass
>>>
Similarly, the break statement breaks out of a loop.
>>> for i in range(7):
if i==3: break
print(i)
1
2
Finally, the continue statement skips to the next iteration.
>>> for i in range(7):
if i==3: continue
print(i)
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2
4
5
6
The help() function displays the documentation string and help for its argument.
>>> import copy
>>> help(copy.copy)
Help on function copy in module copy:
copy(x)
Shallow copy operation on arbitrary Python objects.
See the module’s __doc__ string for more info.
The dir() function displays all the members of an object(any kind).
>>> dir(copy.copy)
[‘__annotations__’, ‘__call__’, ‘__class__’, ‘__closure__’, ‘__code__’, ‘__defaults__’, ‘__delattr__’, ‘__dict__’, ‘__dir__’, ‘__doc__’, ‘__eq__’, ‘__format__’, ‘__ge__’, ‘__get__’, ‘__getattribute__’, ‘__globals__’, ‘__gt__’, ‘__hash__’, ‘__init__’, ‘__init_subclass__’, ‘__kwdefaults__’, ‘__le__’, ‘__lt__’, ‘__module__’, ‘__name__’, ‘__ne__’, ‘__new__’, ‘__qualname__’, ‘__reduce__’, ‘__reduce_ex__’, ‘__repr__’, ‘__setattr__’, ‘__sizeof__’, ‘__str__’, ‘__subclasshook__’]
For this, we use the function keys().
>>> mydict={'a':1,'b':2,'c':3,'e':5}
>>> mydict.keys()
dict_keys([‘a’, ‘b’, ‘c’, ‘e’])
Wait!! Have you developed any Python Project yet?
Practice with Top Python Projects with source code and become job-ready
Slicing is a technique that allows us to retrieve only a part of a list, tuple, or string. For this, we use the slicing operator [].
>>> (1,2,3,4,5)[2:4]
(3, 4)
>>> [7,6,8,5,9][2:]
[8, 5, 9]
>>> 'Hello'[:-1]
‘Hell’
Unlike languages like C++, Python does not have multiline comments. All it has is octothorpe (#). Anything following a hash is considered a comment, and the interpreter ignores it.
>>> #line 1 of comment
>>> #line 2 of comment
In fact, you can place a comment anywhere in your code. You can use it to explain your code.
For this, we use the method isalnum().
Simply using the method capitalize().
>>> 'ayushi'.capitalize()
‘Ayushi’
>>> type(str.capitalize)
However, it will let other characters be.
>>> '@yushi'.capitalize()
‘@yushi’
>>> 'Ayushi123'.isalnum()
True
>>> 'Ayushi123!'.isalnum()
False
Other methods that we have include:
>>> '123.3'.isdigit()
False
>>> '123'.isnumeric()
True
>>> 'ayushi'.islower()
True
>>> 'Ayushi'.isupper()
False
>>> 'Ayushi'.istitle()
True
>>> ' '.isspace()
True
>>> '123F'.isdecimal()
False
Of course. To be truly yourself, you must be accepting of your flaws. Only then can you move forward to work on them. Python has its flaws too:
Python’s interpreted nature imposes a speed penalty on it.
While Python is great for a lot of things, it is weak in mobile computing, and in browsers.
Being dynamically-typed, Python uses duck-typing (If it looks like a duck, it must be a duck). This can raise runtime errors.
Python has underdeveloped database access layers. This renders it a less-than-perfect choice for huge database applications.
And then, well, of course. Being easy makes it addictive. Once a Python-coder, always a Python coder.
To find this, we use the function/method getcwd(). We import it from the module os.
>>> import os
>>> os.getcwd()
‘C:\\Users\\lifei\\AppData\\Local\\Programs\\Python\\Python36-32’
>>> type(os.getcwd)
We can also change the current working directory with chdir().
>>> os.chdir('C:\\Users\\lifei\\Desktop')
>>> os.getcwd()
‘C:\\Users\\lifei\\Desktop’
Let’s build a list first.
>>> a=[1,2,4]
Now, we use the method insert. The first argument is the index at which to insert, the second is the value to insert.
>>> a.insert(2,3)
>>> a
[1, 2, 3, 4]
Using the reverse() method.
>>> a.reverse()
>>> a
[4, 3, 2, 1]
You can also do it via slicing from right to left:
>>> a[::-1]
>>> a
[1, 2, 3, 4]
This gives us the original list because we already reversed it once. However, this does not modify the original list to reverse it.
This is the following sign for Python Interpreter:
>>>
If you have worked with the IDLE, you will see this prompt.
A function uses the ‘return’ keyword to return a value. Take a look:
>>> def add(a,b):
return a+b
For any kind of statements, we possibly need to define a block of code under them. However, Python does not support curly braces. This means we must end such statements with colons and then indent the blocks under those with the same amount.
>>> if 3>1:
print("Hello")
print("Goodbye")
Hello
Goodbye
Both break and continue are statements that control flow in Python loops. break stops the current loop from executing further and transfers the control to the next block. continue jumps to the next iteration of the loop without exhausting it.
Trick question! Python does not support an intrinsic do-while loop. Secondly, to terminate do-while loops is a necessity for languages like C++.
For this, we’ll simply use the max function.
>>> max('flyiNg')
‘y’
The following are the ASCII values for all the letters of this string-
f- 102
l- 108
y- 121
i- 105
N- 78
g- 103
By this logic, try to explain the following line of code-
>>> max('fly{}iNg')
‘}’
(Bonus: } – 125)
Python is a jack of many trades, check out Applications of Python to find out more.
Meanwhile, we’ll say we can use it for:
Web and Internet Development
Desktop GUI
Scientific and Numeric Applications
Software Development Applications
Applications in Education
Applications in Business
Database Access
Network Programming
Games, 3D Graphics
Other Python Applications
Ten Built-in Functions, you say? Okay, here you go.
complex()- Creates a complex number.
>>> complex(3.5,4)
(3.5+4j)
eval()- Parses a string as an expression.
>>> eval('print(max(22,22.0)-min(2,3))')
20
filter()- Filters in items for which the condition is true.
>>> list(filter(lambda x:x%2==0,[1,2,0,False]))
[2, 0, False]
format()- Lets us format a string.
>>> print("a={0} but b={1}".format(a,b))
a=2 but b=3
hash()- Returns the hash value of an object.
>>> hash(3.7)
644245917
hex()- Converts an integer to a hexadecimal.
>>> hex(14)
‘0xe’
input()- Reads and returns a line of string.
>>> input('Enter a number')
Enter a number7
‘7’
len()- Returns the length of an object.
>>> len('Ayushi')
6
locals()- Returns a dictionary of the current local symbol table.
>>> locals()
{‘__name__’: ‘__main__’, ‘__doc__’: None, ‘__package__’: None, ‘__loader__’:
open()- Opens a file.
>>> file=open('tabs.txt')
>>> word=’abcdefghij’
>>> word[:3]+word[3:]
The output is ‘abcdefghij’. The first slice gives us ‘abc’, the next gives us ‘defghij’.
We will use the join() method for this.
>>> nums=['one','two','three','four','five','six','seven']
>>> s=' '.join(nums)
>>> s
‘one two three four five six seven’
We can turn it into a set to do that.
>>> list=[1,2,1,3,4,2]
>>> set(list)
{1, 2, 3, 4}
python scripting interview questions
To create a thread, we create a class that we make override the run method of the thread class. Then, we instantiate it.
A thread that we just created is in the new state. When we make a call to start() on it, it forwards the threads for scheduling. These are in the ready state.
When execution begins, the thread is in the running state.
Calls to methods like sleep() and join() make a thread wait. Such a thread is in the waiting/blocked state.
When a thread is done waiting or executing, other waiting threads are sent for scheduling.
A running thread that is done executing terminates and is in the dead state.
Basic Python Program Interview Questions and Answers
A python dictionary is something I have never seen in other languages like C++ or Java programming. It holds key-value pairs.
>>> roots={25:5,16:4,9:3,4:2,1:1}
>>> type(roots)
>>> roots[9]
3
A dictionary is mutable, and we can also use a comprehension to create it.
>>> roots={x**2😡 for x in range(5,0,-1)}
>>> roots
{25: 5, 16: 4, 9: 3, 4: 2, 1: 1}
The // operator performs floor division. It will return the integer part of the result on division.
>>> 7//2
3
Normal division would return 3.5 here.
Similarly, ** performs exponentiation. a**b returns the value of a raised to the power b.
>>> 2**10
1024
Finally, % is for modulus. This gives us the value left after the highest achievable division.
>>> 13%7
6
>>> 3.5%1.5
0.5
Relational operators compare values.
Less than (<) If the value on the left is lesser, it returns True.
>>> 'hi'<'Hi'
False
Greater than (>) If the value on the left is greater, it returns True.
>>> 1.1+2.2>3.3
True
This is because of the flawed floating-point arithmetic in Python, due to hardware dependencies.
Less than or equal to (<=) If the value on the left is lesser than or equal to, it returns True.
>>> 3.0<=3
True
Greater than or equal to (>=) If the value on the left is greater than or equal to, it returns True.
>>> True>=False
True
Equal to (==) If the two values are equal, it returns True.
>>> {1,3,2,2}=={1,2,3}
True
Not equal to (!=) If the two values are unequal, it returns True.
>>> True!=0.1
True
>>> False!=0.1
True
You will surely face a question from Python Operators. There are chances that question may be in an indirect way. Prepare yourself for it with the best guide – Python Operators
python coding interview questions
We can combine all arithmetic operators with the assignment symbol.
>>> a=7
>>> a+=1
>>> a
8
>>> a-=1
>>> a
7
>>> a*=2
>>> a
14
>>> a/=2
>>> a
7.0
>>> a**=2
>>> a
49.0
>>> a//=3
>>> a
16.0
>>> a%=4
>>> a
0.0
We have three logical operators- and, or, not.
>>> False and True
False
>>> 7<7 or True
True
>>> not 2==2
False
With the operators ‘in’ and ‘not in’, we can confirm if a value is a member in another.
>>> 'me' in 'disappointment'
True
>>> 'us' not in 'disappointment'
True
The operators ‘is’ and ‘is not’ tell us if two values have the same identity.
>>> 10 is '10'
False
>>> True is not False
True
These operate on values bit by bit.
AND (&) This performs & on each bit pair.
>>> 0b110 & 0b010
2
OR (|) This performs | on each bit pair.
>>> 3|2
3
XOR (^) This performs an exclusive-OR operation on each bit pair.
>>> 3^2
1
Binary One’s Complement (~) This returns the one’s complement of a value.
>>> ~2
-3
Binary Left-Shift (<<) This shifts the bits to the left by the specified amount.
>>> 1<<2
4
Here, 001 was shifted to the left by two places to get 100, which is binary for 4.
Binary Right-Shift (>>)
>>> 4>>2
1
Python provides us with five kinds of data types:
Numbers – Numbers use to hold numerical values.
>>> a=7.0
>>>
Strings – A string is a sequence of characters. We declare it using single or double quotes.
>>> title="Ayushi's Book"
Lists – A list is an ordered collection of values, and we declare it using square brackets.
>>> colors=['red','green','blue']
>>> type(colors)
Tuples – A tuple, like a list, is an ordered collection of values. The difference. However, is that a tuple is immutable. This means that we cannot change a value in it.
>>> name=('Ayushi','Sharma')
>>> name[0]='Avery'
Traceback (most recent call last):
File “
name[0]=’Avery’
TypeError: ‘tuple’ object does not support item assignment
Dictionary – A dictionary is a data structure that holds key-value pairs. We declare it using curly braces.
>>> squares={1:1,2:4,3:9,4:16,5:25}
>>> type(squares)
>>> type({})
We can also use a dictionary comprehension:
>>> squares={x:x**2 for x in range(1,6)}
>>> squares
{1: 1, 2: 4, 3: 9, 4: 16, 5: 25}
Don’t miss the complete guide for Python Data Types and Variables
A docstring is a documentation string that we use to explain what a construct does. We place it as the first thing under a function, class, or a method, to describe what it does. We declare a docstring using three sets of single or double-quotes.
>>> def sayhi():
"""
The function prints Hi
"""
print("Hi")
>>> sayhi()
Hi
To get a function’s docstring, we use its __doc__ attribute.
>>> sayhi.__doc__
‘\n\tThis function prints Hi\n\t’
A docstring, unlike a comment, is retained at runtime.
If a string contains only numerical characters, you can convert it into an integer using the int() function.
>>> int('227')
227
Let’s check the types:
>>> type('227')
>>> type(int('227'))
For taking input from the user, we have the function input(). In Python 2, we had another function raw_input().
The input() function takes, as an argument, the text to be displayed for the task:
>>> a=input('Enter a number')
Enter a number7
But if you have paid attention, you know that it takes input in the form of a string.
>>> type(a)
Multiplying this by 2 gives us this:
>>> a*=2
>>> a
’77’
So, what if we need to work on an integer instead?
We use the int() function for this.
>>> a=int(input('Enter a number'))
Enter a number7
Now when we multiply it by 2, we get this:
>>> a*=2
>>> a
14
When we want to execute a sequence of statements, we can give it a name. Let’s define a function to take two numbers and return the greater number.
>>> def greater(a,b):
return a is a>b else b
>>> greater(3,3.5)
3.5
When a function makes a call to itself, it is termed recursion. But then, in order for it to avoid forming an infinite loop, we must have a base condition.
Let’s take an example.
>>> def facto(n):
if n==1: return 1
return n*facto(n-1)
>>> facto(4)
24
One of the less common functions with beginners, zip() returns an iterator of tuples.
>>> list(zip(['a','b','c'],[1,2,3]))
[(‘a’, 1), (‘b’, 2), (‘c’, 3)]
Here, it pairs items from the two lists and creates tuples with those. But it doesn’t have to be lists.
>>> list(zip(('a','b','c'),(1,2,3)))
[(‘a’, 1), (‘b’, 2), (‘c’, 3)]
This is simple. We call the function len() on the string we want to calculate the length of.
>>> len('Ayushi Sharma')
13
The list comprehension in python is a way to declare a list in one line of code. Let’s take a look at one such example.
>>> [i for i in range(1,11,2)]
[1, 3, 5, 7, 9]
>>> [i*2 for i in range(1,11,2)]
[2, 6, 10, 14, 18]
We saw previously, to get all keys from a dictionary, we make a call to the keys() method. Similarly, for values, we use the method values().
>>> 'd' in {'a':1,'b':2,'c':3,'d':4}.values()
False
>>> 4 in {'a':1,'b':2,'c':3,'d':4}.values()
True
We have the swapcase() method from the str class to do just that.
>>> 'AyuShi'.swapcase()
‘aYUsHI’
Let’s apply some concepts now, shall we? Questions 50 through 52 assume the string ‘I love Python’. You need to do the needful.
>>> i=0
>>> while s[i]!='t':
print(s[i],end=’’)
i+=1
I love Py
>>> for i in s:
if i==' ': continue
print(i,end='')
IlovePython
>>> for i in range(6):
print(s)
I love Python
I love Python
I love Python
I love Python
I love Python
I love Python
Okay, moving on to more domains to conquer.
bytes() is a built-in function in Python that returns an immutable bytes object. Let’s take an example.
>>> bytes([2,4,8])
b’\x02\x04\x08′
>>> bytes(5)
b’\x00\x00\x00\x00\x00′
>>> bytes('world','utf-8')
b’world’
Answer:- To install Python on Windows, follow the below steps:
Install python from this link: https://www.python.org/downloads/
After this, install it on your PC. Look for the location where PYTHON has been installed on your PC using the following command on your command prompt: cmd python.
Then go to advanced system settings and add a new variable and name it as PYTHON_NAME and paste the copied path.
Look for the path variable, select its value and select ‘edit’.
Add a semicolon towards the end of the value if it’s not present and then type %PYTHON_HOME%
Answer:- Indentation is necessary for Python. It specifies a block of code. All code within loops, classes, functions, etc is specified within an indented block. It is usually done using four space characters. If your code is not indented necessarily, it will not execute accurately and will throw errors as well.
Answer:- Arrays and lists, in Python, have the same way of storing data. But, arrays can hold only a single data type elements whereas lists can hold any data type elements.
Example:
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import array as arr
My_Array=arr.array('i',[1,2,3,4])
My_list=[1,'abc',1.20]
print(My_Array)
print(My_list)
Output:
array(‘i’, [1, 2, 3, 4]) [1, ‘abc’, 1.2]
Answer:- A function is a block of code which is executed only when it is called. To define a Python function, the def keyword is used.
Example:
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def Newfunc():
print("Hi, Welcome to Edureka")
Newfunc(); #calling the function
Output: Hi, Welcome to Edureka
Answer:- __init__ is a method or constructor in Python. This method is automatically called to allocate memory when a new object/ instance of a class is created. All classes have the __init__ method.
Here is an example of how to use it.
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class Employee:
def __init__(self, name, age,salary):
self.name = name
self.age = age
self.salary = 20000
E1 = Employee("XYZ", 23, 20000)
# E1 is the instance of class Employee.
#__init__ allocates memory for E1.
print(E1.name)
print(E1.age)
print(E1.salary)
Output:
XYZ
23
20000
Answer:- An anonymous function is known as a lambda function. This function can have any number of parameters but, can have just one statement.
Example:
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a = lambda x,y : x+y
print(a(5, 6))
Output: 11
Answer:- Self is an instance or an object of a class. In Python, this is explicitly included as the first parameter. However, this is not the case in Java where it’s optional. It helps to differentiate between the methods and attributes of a class with local variables.
The self variable in the init method refers to the newly created object while in other methods, it refers to the object whose method was called.
Answer:- Break Allows loop termination when some condition is met and the control is transferred to the next statement.
Continue Allows skipping some part of a loop when some specific condition is met and the control is transferred to the beginning of the loop
Pass Used when you need some block of code syntactically, but you want to skip its execution. This is basically a null operation. Nothing happens when this is executed.
Answer:- [::-1] is used to reverse the order of an array or a sequence.
For example:
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import array as arr
My_Array=arr.array('i',[1,2,3,4,5])
My_Array[::-1]
Output: array(‘i’, [5, 4, 3, 2, 1])
[::-1] reprints a reversed copy of ordered data structures such as an array or a list. the original array or list remains unchanged.
Answer:- Consider the example shown below:
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from random import shuffle
x = ['Keep', 'The', 'Blue', 'Flag', 'Flying', 'High']
shuffle(x)
print(x)
The output of the following code is as below.
['Flying', 'Keep', 'Blue', 'High', 'The', 'Flag']
Answer:- Iterators are objects which can be traversed though or iterated upon.
Answer:- Random module is the standard module that is used to generate a random number. The method is defined as:
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import random
random.random
The statement random.random() method return the floating point number that is in the range of [0, 1). The function generates random float numbers. The methods that are used with the random class are the bound methods of the hidden instances. The instances of the Random can be done to show the multi-threading programs that creates a different instance of individual threads. The other random generators that are used in this are:
randrange(a, b): it chooses an integer and define the range in-between [a, b). It returns the elements by selecting it randomly from the range that is specified. It doesn’t build a range object.
uniform(a, b): it chooses a floating point number that is defined in the range of [a,b).Iyt returns the floating point number
normalvariate(mean, sdev): it is used for the normal distribution where the mu is a mean and the sdev is a sigma that is used for standard deviation.
The Random class that is used and instantiated creates independent multiple random number generators.
Answer:- For the most part, xrange and range are the exact same in terms of functionality. They both provide a way to generate a list of integers for you to use, however you please. The only difference is that range returns a Python list object and x range returns an xrange object.
This means that xrange doesn’t actually generate a static list at run-time like range does. It creates the values as you need them with a special technique called yielding. This technique is used with a type of object known as generators. That means that if you have a really gigantic range you’d like to generate a list for, say one billion, xrange is the function to use.
This is especially true if you have a really memory sensitive system such as a cell phone that you are working with, as range will use as much memory as it can to create your array of integers, which can result in a Memory Error and crash your program. It’s a memory hungry beast.
Answer:- Comments in Python start with a # character. However, alternatively at times, commenting is done using docstrings(strings enclosed within triple quotes).
Example:
#Comments in Python start like this
print("Comments in Python start with a #")
Output: Comments in Python start with a #
Answer:- Pickle module accepts any Python object and converts it into a string representation and dumps it into a file by using dump function, this process is called pickling. While the process of retrieving original Python objects from the stored string representation is called unpickling.
Answer:- Functions that return an iterable set of items are called generators.
Course Curriculum
Data Science Certification Training with Python
Answer:- In Python, the capitalize() method capitalizes the first letter of a string. If the string already consists of a capital letter at the beginning, then, it returns the original string.
Answer:- To convert a string to lowercase, lower() function can be used.
Example:
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stg='ABCD'
print(stg.lower())
Output: abcd
Answer:- Multi-line comments appear in more than one line. All the lines to be commented are to be prefixed by a #. You can also a very good shortcut method to comment multiple lines. All you need to do is hold the ctrl key and left click in every place wherever you want to include a # character and type a # just once. This will comment all the lines where you introduced your cursor.
Answer:- Docstrings are not actually comments, but, they are documentation strings. These docstrings are within triple quotes. They are not assigned to any variable and therefore, at times, serve the purpose of comments as well.
Example:
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"""
Using docstring as a comment.
This code divides 2 numbers
"""
x=8
y=4
z=x/y
print(z)
Output: 2.0
Answer:- Operators are special functions. They take one or more values and produce a corresponding result.
is: returns true when 2 operands are true (Example: “a” is ‘a’)
not: returns the inverse of the boolean value
in: checks if some element is present in some sequence
Answer:- Help() and dir() both functions are accessible from the Python interpreter and used for viewing a consolidated dump of built-in functions.
Help() function: The help() function is used to display the documentation string and also facilitates you to see the help related to modules, keywords, attributes, etc.
Dir() function: The dir() function is used to display the defined symbols.
Answer:-
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.
Answer:- 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.
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dict={'Country':'India','Capital':'Delhi','PM':'Modi'}
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print dict[Country]
India
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print dict[Capital]
Delhi
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print dict[PM]
Modi
Answer:- The Ternary operator is the operator that is used to show the conditional statements. This consists of the true or false values with a statement that has to be evaluated for it.
Syntax:
The Ternary operator will be given as:
[on_true] if [expression] else [on_false]x, y = 25, 50big = x if x < y else y
Example:
The expression gets evaluated like if x Answer:- We use *args when we aren’t sure how many arguments are going to be passed to a function, or if we want to pass a stored list or tuple of arguments to a function. **kwargs is used when we don’t know how many keyword arguments will be passed to a function, or it can be used to pass the values of a dictionary as keyword arguments. The identifiers args and kwargs are a convention, you could also use *bob and **billy but that would not be wise. Answer:- It is used to determine the length of a string, a list, an array, etc. Example: 1 2 stg='ABCD' len(stg) Answer:- To modify the strings, Python’s “re” module is providing 3 methods. They are: split() – uses a regex pattern to “split” a given string into a list. sub() – finds all substrings where the regex pattern matches and then replace them with a different string subn() – it is similar to sub() and also returns the new string along with the no. of replacements. Answer:- The sequences in Python are indexed and it consists of the positive as well as negative numbers. The numbers that are positive uses ‘0’ that is uses as first index and ‘1’ as the second index and the process goes on like that. The index for the negative number starts from ‘-1’ that represents the last index in the sequence and ‘-2’ as the penultimate index and the sequence carries forward like the positive number. The negative index is used to remove any new-line spaces from the string and allow the string to except the last character that is given as S[:-1]. The negative index is also used to show the index to represent the string in correct order. Answer:- Python packages are namespaces containing multiple modules. Answer:- To delete a file in Python, you need to import the OS Module. After that, you need to use the os.remove() function. Example: 1 2 import os os.remove("xyz.txt") Answer:- Built-in types in Python are as follows – Integers Floating-point Complex numbers Strings Boolean Built-in functions Answer:- Python’s lists are efficient general-purpose containers. They support (fairly) efficient insertion, deletion, appending, and concatenation, and Python’s list comprehensions make them easy to construct and manipulate. They have certain limitations: they don’t support “vectorized” operations like elementwise addition and multiplication, and the fact that they can contain objects of differing types mean that Python must store type information for every element, and must execute type dispatching code when operating on each element. NumPy is not just more efficient; it is also more convenient. You get a lot of vector and matrix operations for free, which sometimes allow one to avoid unnecessary work. And they are also efficiently implemented. NumPy array is faster and You get a lot built in with NumPy, FFTs, convolutions, fast searching, basic statistics, linear algebra, histograms, etc. Answer:- Elements can be added to an array using the append(), extend() and the insert (i,x) functions. Example: 1 2 3 4 5 6 7 a=arr.array('d', [1.1 , 2.1 ,3.1] ) a.append(3.4) print(a) a.extend([4.5,6.3,6.8]) print(a) a.insert(2,3.8) print(a) Output: array(‘d’, [1.1, 2.1, 3.1, 3.4]) array(‘d’, [1.1, 2.1, 3.1, 3.4, 4.5, 6.3, 6.8]) array(‘d’, [1.1, 2.1, 3.8, 3.1, 3.4, 4.5, 6.3, 6.8]) Answer:- Array elements can be removed using pop() or remove() method. The difference between these two functions is that the former returns the deleted value whereas the latter does not. Example: 1 2 3 4 5 a=arr.array('d', [1.1, 2.2, 3.8, 3.1, 3.7, 1.2, 4.6]) print(a.pop()) print(a.pop(3)) a.remove(1.1) print(a) Output: 4.6 3.1 array(‘d’, [2.2, 3.8, 3.7, 1.2]) Answer:- Python is an object-oriented programming language. This means that any program can be solved in python by creating an object model. However, Python can be treated as procedural as well as structural language. Answer:- Shallow copy is used when a new instance type gets created and it keeps the values that are copied in the new instance. Shallow copy is used to copy the reference pointers just like it copies the values. These references point to the original objects and the changes made in any member of the class will also affect the original copy of it. Shallow copy allows faster execution of the program and it depends on the size of the data that is used. Deep copy is used to store the values that are already copied. Deep copy doesn’t copy the reference pointers to the objects. It makes the reference to an object and the new object that is pointed by some other object gets stored. The changes made in the original copy won’t affect any other copy that uses the object. Deep copy makes execution of the program slower due to making certain copies for each object that is been called. Answer:- Python has a multi-threading package but if you want to multi-thread to speed your code up, then it’s usually not a good idea to use it. Python has a construct called the Global Interpreter Lock (GIL). The GIL makes sure that only one of your ‘threads’ can execute at any one time. A thread acquires the GIL, does a little work, then passes the GIL onto the next thread. This happens very quickly so to the human eye it may seem like your threads are executing in parallel, but they are really just taking turns using the same CPU core. All this GIL passing adds overhead to execution. This means that if you want to make your code run faster then using the threading package often isn’t a good idea. Answer:- The compiling and linking allows the new extensions to be compiled properly without any error and the linking can be done only when it passes the compiled procedure. If the dynamic loading is used then it depends on the style that is being provided with the system. The python interpreter can be used to provide the dynamic loading of the configuration setup files and will rebuild the interpreter. The steps that are required in this as: Create a file with any name and in any language that is supported by the compiler of your system. For example file.c or file.cpp Place this file in the Modules/ directory of the distribution which is getting used. Add a line in the file Setup.local that is present in the Modules/ directory. Run the file using spam file.o After a successful run of this rebuild the interpreter by using the make command on the top-level directory. If the file is changed then run rebuildMakefile by using the command as ‘make Makefile’. Python libraries are a collection of Python packages. Some of the majorly used python libraries are – Numpy, Pandas, Matplotlib, Scikit-learn and many more. The split() method is used to separate a given string in Python. Example: 1 2 a="edureka python" print(a.split()) Output: [‘edureka’, ‘python’] Modules can be imported using the import keyword. You can import modules in three ways- Example: 1 2 3 import array #importing using the original module name import array as arr # importing using an alias name from array import * #imports everything present in the array module Answer:- 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 are 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. Answer:- Class in Python is created using the class keyword. Example: 1 2 3 4 5 class Employee: def __init__(self, name): self.name = name E1=Employee("abc") print(E1.name) Output: abc
Last Updated: 2023-09-23