Michael Bryan

Michael Bryan

1556035932

5 Python Exercises

Best Way To Strengthen And Practice Your Python Skills

Here are 5 Python exercises.

For each exercise, I will also mention the topics it is intending to test. By the end of the exercise, you will feel that you have gained a much superior end-to-end understanding of the language.

Remember, there are multiple ways to peel an orange so solve the questions how you understand them. I will post the answers in an upcoming blog soon.### 1. Logging Using Python Decorator

  1. Implement a calculator class with following functions:

Sum(a,b), Multiply(a,b), Divide(a,b) and Subtract(a,b)

  1. Import logging library

  2. Decorate each method of the calculator class with a custom method that logs the values of a and b. Implement the logger custom method too.

  3. Execute calculator.Sum(a,b) and it should print out the values of a and b. For example:

The Input Values Of A and B Are '123' and '234' # if a =123 and b=234

What Will It Test?

  • It will test whether you understood Pip commands that are required to import the libraries
  • How to create class and functions with arguments in Python
  • How to use decorators

2. Tree Traversal Using Python Recursion

  1. Implement a class: **Node **which will be used to represent a tree. For example:
class Node(object):
    def __init__(self, name):
        self.name= name
        self.children = []
 def add_child(self, obj):
        self.children.append(obj)

Each node has a name and children e.g.

a = Node('A')
a_goal = Node('Goal')
a.add_child(a_goal)

  1. Print out all of the paths of the tree which can lead you to the node named “Goal”.

  2. The tree can have N number of levels (1>N>100). Goal node can have children too.

For example, for tree below, your code should print out following paths:

A->Goal

A->B->Goal

A->D->Goal

A->F->H->L->Goal

All other paths do not lead you to the Goal node.

Write your code in a way that it can be unit tested.

What Will It Test?

  • It should test your understanding of recursion
  • It should also test how you prevent from going into infinite loops — it will test your loops, expression and conditional logic
  • It will also test your data structures understanding and variables scope

3. Flatten A List Of Nested Dictionaries Into A List Of Multiple Flattened Dictionaries

  1. Create an object which contains a list of dictionaries.
  2. Each item in the list is a dictionary which contains a number of keys.
  3. Each key of the dictionary will contain a value. The value can be of type string, or it can be a of type dictionary. When the value is of type dictionary then it implies that it is a nested dictionary within a dictionary.
  4. Each dictionary can contain a variable number of keys.
  5. Loop over the items and create a single dictionary to store keys at the same level. For example, if you loop over the items and if each item contains a dictionary with two keys e.g.“Name” and “Surname” and both of the keys contain values of type string then simply return the collection of dictionaries (as it’s already flat).
  6. However if it contains “Name”, “Surname” and “PlacesVisited” keys, where PlacesVisited is itself a list of dictionaries such that each item of the dictionary contains two keys “Name of place” and “date when it was visited” then I expect to see two lists as the result. First list should contain a collection of dictionaries with keys Name and Surname. The second list should contain the keys “Name Of place”, “date when it was visited” and ParentId where ParentId will contain the key “Name” of the first dictionary.
  7. Take the value of the ParentId as the value of the first key of the parent dictionary e.g. for the example above, “Name” is chosen as the ParentId.

For each nested dictionary, create a new dictionary.

Final result should be a number of flatten dictionaries to represent a nested dictionary

For example, if this is your input:

sample_object = [
{'Name':'Farhad', 'Surname:'Malik', 'Blogs':{'BlogName:'Python1','Date1':'20180901'}},
{'Name':'Farhad2', 'Surname:'Malik2', 'Blogs':{'BlogName:'Python3','Date1':'20180101'}}
]
The result should be:

dictionary_1 = [
{'Name':'Farhad', 'Surname:'Malik'}, 
{'Name':'Farhad2', 'Surname:'Malik2'}
]
dictionary_2 = [
{'ParentId':'Farhad', 'BlogName:'Python1','Date1':'20180901'},
{'ParentId':'Farhad2','BlogName:'Python3','Date1':'20180101'}
]

The key is to ensure that the items at the same level belong to the same dictionary.

What Will It Test?

  • It should test your understanding of dictionaries, arrays and sets.
  • It should also help you understand how to check for keys and values
  • Lastly, it will help you see how you can pass in optional parameters.
  • This is how you can flatten out a JSON object.

4. Multi-Process And Error Handling Code

  • Take the three exercises above, make the code run on multiple processes
  • Use try/catch and catch exceptions where appropriate
  • Profile and log performance of the code
  • Write unit tests for each of the exercises that perform positive and negative tests

What Will It Test?

  • This will really help you see how to run your code on multiple processes
  • How to catch exceptions and how to enable logging in your code to an extent that it is useful.

5. Package And Modules

  • Create the classes and code that you have implemented above into a package with multiple modules
  • Understand how the files should be placed and imported.
  • Create a main class that drives everything
  • Write out a console application that runs your unit tests via command line and informs you the tests that have passed or failed.

What Will It Test?

  • It should help you really understand and see how packages and modules work
  • You will get a solid understanding of Python programming language

Summary

This article presented you with 5 Python exercises.

Please post your answers in the comments section. I will post the answers in my upcoming Python blogs.

If you want more exercises, please do let me know.

#python

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5 Python Exercises
Ray  Patel

Ray Patel

1619510796

Lambda, Map, Filter functions in python

Welcome to my Blog, In this article, we will learn python lambda function, Map function, and filter function.

Lambda function in python: Lambda is a one line anonymous function and lambda takes any number of arguments but can only have one expression and python lambda syntax is

Syntax: x = lambda arguments : expression

Now i will show you some python lambda function examples:

#python #anonymous function python #filter function in python #lambda #lambda python 3 #map python #python filter #python filter lambda #python lambda #python lambda examples #python map

Shardul Bhatt

Shardul Bhatt

1626775355

Why use Python for Software Development

No programming language is pretty much as diverse as Python. It enables building cutting edge applications effortlessly. Developers are as yet investigating the full capability of end-to-end Python development services in various areas. 

By areas, we mean FinTech, HealthTech, InsureTech, Cybersecurity, and that's just the beginning. These are New Economy areas, and Python has the ability to serve every one of them. The vast majority of them require massive computational abilities. Python's code is dynamic and powerful - equipped for taking care of the heavy traffic and substantial algorithmic capacities. 

Programming advancement is multidimensional today. Endeavor programming requires an intelligent application with AI and ML capacities. Shopper based applications require information examination to convey a superior client experience. Netflix, Trello, and Amazon are genuine instances of such applications. Python assists with building them effortlessly. 

5 Reasons to Utilize Python for Programming Web Apps 

Python can do such numerous things that developers can't discover enough reasons to admire it. Python application development isn't restricted to web and enterprise applications. It is exceptionally adaptable and superb for a wide range of uses.

Robust frameworks 

Python is known for its tools and frameworks. There's a structure for everything. Django is helpful for building web applications, venture applications, logical applications, and mathematical processing. Flask is another web improvement framework with no conditions. 

Web2Py, CherryPy, and Falcon offer incredible capabilities to customize Python development services. A large portion of them are open-source frameworks that allow quick turn of events. 

Simple to read and compose 

Python has an improved sentence structure - one that is like the English language. New engineers for Python can undoubtedly understand where they stand in the development process. The simplicity of composing allows quick application building. 

The motivation behind building Python, as said by its maker Guido Van Rossum, was to empower even beginner engineers to comprehend the programming language. The simple coding likewise permits developers to roll out speedy improvements without getting confused by pointless subtleties. 

Utilized by the best 

Alright - Python isn't simply one more programming language. It should have something, which is the reason the business giants use it. Furthermore, that too for different purposes. Developers at Google use Python to assemble framework organization systems, parallel information pusher, code audit, testing and QA, and substantially more. Netflix utilizes Python web development services for its recommendation algorithm and media player. 

Massive community support 

Python has a steadily developing community that offers enormous help. From amateurs to specialists, there's everybody. There are a lot of instructional exercises, documentation, and guides accessible for Python web development solutions. 

Today, numerous universities start with Python, adding to the quantity of individuals in the community. Frequently, Python designers team up on various tasks and help each other with algorithmic, utilitarian, and application critical thinking. 

Progressive applications 

Python is the greatest supporter of data science, Machine Learning, and Artificial Intelligence at any enterprise software development company. Its utilization cases in cutting edge applications are the most compelling motivation for its prosperity. Python is the second most well known tool after R for data analytics.

The simplicity of getting sorted out, overseeing, and visualizing information through unique libraries makes it ideal for data based applications. TensorFlow for neural networks and OpenCV for computer vision are two of Python's most well known use cases for Machine learning applications.

Summary

Thinking about the advances in programming and innovation, Python is a YES for an assorted scope of utilizations. Game development, web application development services, GUI advancement, ML and AI improvement, Enterprise and customer applications - every one of them uses Python to its full potential. 

The disadvantages of Python web improvement arrangements are regularly disregarded by developers and organizations because of the advantages it gives. They focus on quality over speed and performance over blunders. That is the reason it's a good idea to utilize Python for building the applications of the future.

#python development services #python development company #python app development #python development #python in web development #python software development

Art  Lind

Art Lind

1602968400

Python Tricks Every Developer Should Know

Python is awesome, it’s one of the easiest languages with simple and intuitive syntax but wait, have you ever thought that there might ways to write your python code simpler?

In this tutorial, you’re going to learn a variety of Python tricks that you can use to write your Python code in a more readable and efficient way like a pro.

Let’s get started

Swapping value in Python

Instead of creating a temporary variable to hold the value of the one while swapping, you can do this instead

>>> FirstName = "kalebu"
>>> LastName = "Jordan"
>>> FirstName, LastName = LastName, FirstName 
>>> print(FirstName, LastName)
('Jordan', 'kalebu')

#python #python-programming #python3 #python-tutorials #learn-python #python-tips #python-skills #python-development

Art  Lind

Art Lind

1602666000

How to Remove all Duplicate Files on your Drive via Python

Today you’re going to learn how to use Python programming in a way that can ultimately save a lot of space on your drive by removing all the duplicates.

Intro

In many situations you may find yourself having duplicates files on your disk and but when it comes to tracking and checking them manually it can tedious.

Heres a solution

Instead of tracking throughout your disk to see if there is a duplicate, you can automate the process using coding, by writing a program to recursively track through the disk and remove all the found duplicates and that’s what this article is about.

But How do we do it?

If we were to read the whole file and then compare it to the rest of the files recursively through the given directory it will take a very long time, then how do we do it?

The answer is hashing, with hashing can generate a given string of letters and numbers which act as the identity of a given file and if we find any other file with the same identity we gonna delete it.

There’s a variety of hashing algorithms out there such as

  • md5
  • sha1
  • sha224, sha256, sha384 and sha512

#python-programming #python-tutorials #learn-python #python-project #python3 #python #python-skills #python-tips

How To Compare Tesla and Ford Company By Using Magic Methods in Python

Magic Methods are the special methods which gives us the ability to access built in syntactical features such as ‘<’, ‘>’, ‘==’, ‘+’ etc…

You must have worked with such methods without knowing them to be as magic methods. Magic methods can be identified with their names which start with __ and ends with __ like init, call, str etc. These methods are also called Dunder Methods, because of their name starting and ending with Double Underscore (Dunder).

Now there are a number of such special methods, which you might have come across too, in Python. We will just be taking an example of a few of them to understand how they work and how we can use them.

1. init

class AnyClass:
    def __init__():
        print("Init called on its own")
obj = AnyClass()

The first example is _init, _and as the name suggests, it is used for initializing objects. Init method is called on its own, ie. whenever an object is created for the class, the init method is called on its own.

The output of the above code will be given below. Note how we did not call the init method and it got invoked as we created an object for class AnyClass.

Init called on its own

2. add

Let’s move to some other example, add gives us the ability to access the built in syntax feature of the character +. Let’s see how,

class AnyClass:
    def __init__(self, var):
        self.some_var = var
    def __add__(self, other_obj):
        print("Calling the add method")
        return self.some_var + other_obj.some_var
obj1 = AnyClass(5)
obj2 = AnyClass(6)
obj1 + obj2

#python3 #python #python-programming #python-web-development #python-tutorials #python-top-story #python-tips #learn-python