John David

John David


A guide to Python Dictionaries

Dictionary in Python is an unordered collection of data values, used to store data values like a map, which unlike other Data Types that hold only single value as an element, Dictionary holds key:value pair. Key value is provided in the dictionary to make it more optimized. Each key-value pair in a Dictionary is separated by a colon :, whereas each key is separated by a ‘comma’.

A Dictionary in Python works similar to the Dictionary in a real world. Keys of a Dictionary must be unique and of immutable data type such as Strings, Integers and tuples, but the key-values can be repeated and be of any type.

Note – Keys in a dictionary doesn’t allows Polymorphism.

Creating a Dictionary

In Python, a Dictionary can be created by placing sequence of elements within curly {} braces, separated by ‘comma’. Dictionary holds a pair of values, one being the Key and the other corresponding pair element being its Key:value. Values in a dictionary can be of any datatype and can be duplicated, whereas keys can’t be repeated and must be immutable.

Dictionary can also be created by the built-in function dict(). An empty dictionary can be created by just placing to curly braces{}.

Note – Dictionary keys are case sensitive, same name but different cases of Key will be treated distinctly.

# Creating an empty Dictionary 
Dict = {} 
print("Empty Dictionary: ") 

# Creating a Dictionary 
# with Integer Keys 
Dict = {1: 'Geeks', 2: 'For', 3: 'Geeks'} 
print("\nDictionary with the use of Integer Keys: ") 

# Creating a Dictionary 
# with Mixed keys 
Dict = {'Name': 'Geeks', 1: [1, 2, 3, 4]} 
print("\nDictionary with the use of Mixed Keys: ") 

# Creating a Dictionary 
# with dict() method 
Dict = dict({1: 'Geeks', 2: 'For', 3:'Geeks'}) 
print("\nDictionary with the use of dict(): ") 

# Creating a Dictionary 
# with each item as a Pair 
Dict = dict([(1, 'Geeks'), (2, 'For')]) 
print("\nDictionary with each item as a pair: ") 


Empty Dictionary: 

Dictionary with the use of Integer Keys: 
{1: 'Geeks', 2: 'For', 3: 'Geeks'}

Dictionary with the use of Mixed Keys: 
{1: [1, 2, 3, 4], 'Name': 'Geeks'}

Dictionary with the use of dict(): 
{1: 'Geeks', 2: 'For', 3: 'Geeks'}

Dictionary with each item as a pair: 
{1: 'Geeks', 2: 'For'}

Nested Dictionary:

# Creating a Nested Dictionary 
# as shown in the below image 
Dict = {1: 'Geeks', 2: 'For', 
		3:{'A' : 'Welcome', 'B' : 'To', 'C' : 'Geeks'}} 



{1: 'Geeks', 2: 'For', 3: {'A': 'Welcome', 'B': 'To', 'C': 'Geeks'}}

Adding elements to a Dictionary

In Python Dictionary, Addition of elements can be done in multiple ways. One value at a time can be added to a Dictionary by defining value along with the key e.g. Dict[Key] = ‘Value’. Updating an existing value in a Dictionary can be done by using the built-in update() method. Nested key values can also be added to an existing Dictionary.
Note- While adding a value, if the key value already exists, the value gets updated otherwise a new Key with the value is added to the Dictionary.

# Creating an empty Dictionary 
Dict = {} 
print("Empty Dictionary: ") 

# Adding elements one at a time 
Dict[0] = 'Geeks'
Dict[2] = 'For'
Dict[3] = 1
print("\nDictionary after adding 3 elements: ") 

# Adding set of values 
# to a single Key 
Dict['Value_set'] = 2, 3, 4
print("\nDictionary after adding 3 elements: ") 

# Updating existing Key's Value 
Dict[2] = 'Welcome'
print("\nUpdated key value: ") 

# Adding Nested Key value to Dictionary 
Dict[5] = {'Nested' :{'1' : 'Life', '2' : 'Geeks'}} 
print("\nAdding a Nested Key: ") 


Empty Dictionary: 

Dictionary after adding 3 elements: 
{0: 'Geeks', 2: 'For', 3: 1}

Dictionary after adding 3 elements: 
{0: 'Geeks', 2: 'For', 3: 1, 'Value_set': (2, 3, 4)}

Updated key value: 
{0: 'Geeks', 2: 'Welcome', 3: 1, 'Value_set': (2, 3, 4)}

Adding a Nested Key: 
{0: 'Geeks', 2: 'Welcome', 3: 1, 5: {'Nested': {'1': 'Life', '2': 'Geeks'}}, 'Value_set': (2, 3, 4)}

Accessing elements from a Dictionary

In order to access the items of a dictionary refer to its key name.Key can be used inside square brackets.There is also a method called get() that will also help in acessing the element from a dictionary.

# Python program to demonstrate 
# accesing a element from a Dictionary 

# Creating a Dictionary 
Dict = {1: 'Geeks', 'name': 'For', 3: 'Geeks'} 

# accessing a element using key 
print("Acessing a element using key:") 

# accessing a element using key 
print("Acessing a element using key:") 

# accessing a element using get() 
# method 
print("Acessing a element using get:") 


Acessing a element using key:

Acessing a element using key:

Acessing a element using get:

Removing Elements from Dictionary

In Python Dictionary, deletion of keys can be done by using the del keyword. Using del keyword, specific values from a dictionary as well as whole dictionary can be deleted. Other functions like pop() and popitem() can also be used for deleting specific values and arbitrary values from a Dictionary. All the items from a dictionary can be deleted at once by using clear() method. Items in a Nested dictionary can also be deleted by using del keyword and providing specific nested key and particular key to be deleted from that nested Dictionary.
Note- del Dict will delete the entire dictionary and hence printing it after deletion will raise an Error.

# Initial Dictionary 
Dict = { 5 : 'Welcome', 6 : 'To', 7 : 'Geeks', 
		'A' : {1 : 'Geeks', 2 : 'For', 3 : 'Geeks'}, 
		'B' : {1 : 'Geeks', 2 : 'Life'}} 
print("Initial Dictionary: ") 

# Deleting a Key value 
del Dict[6] 
print("\nDeleting a specific key: ") 

# Deleting a Key from 
# Nested Dictionary 
del Dict['A'][2] 
print("\nDeleting a key from Nested Dictionary: ") 

# Deleting a Key 
# using pop() 
print("\nPopping specific element: ") 

# Deleting an arbitrary Key-value pair 
# using popitem() 
print("\nPops an arbitrary key-value pair: ") 

# Deleting entire Dictionary 
print("\nDeleting Entire Dictionary: ") 


Initial Dictionary: 
{'A': {1: 'Geeks', 2: 'For', 3: 'Geeks'}, 'B': {1: 'Geeks', 2: 'Life'}, 5: 'Welcome', 6: 'To', 7: 'Geeks'}

Deleting a specific key: 
{'A': {1: 'Geeks', 2: 'For', 3: 'Geeks'}, 'B': {1: 'Geeks', 2: 'Life'}, 5: 'Welcome', 7: 'Geeks'}

Deleting a key from Nested Dictionary: 
{'A': {1: 'Geeks', 3: 'Geeks'}, 'B': {1: 'Geeks', 2: 'Life'}, 5: 'Welcome', 7: 'Geeks'}

Popping specific element: 
{'A': {1: 'Geeks', 3: 'Geeks'}, 'B': {1: 'Geeks', 2: 'Life'}, 7: 'Geeks'}

Pops an arbitrary key-value pair: 
{'B': {1: 'Geeks', 2: 'Life'}, 7: 'Geeks'}

Deleting Entire Dictionary: 


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A guide to Python Dictionaries
Ray  Patel

Ray Patel


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


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.


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

Ray  Patel

Ray Patel


Working with Python dictionaries: a cheat sheet

Accessing, editing and looping through dictionary items

Dictionaries in Python are a collection of key-value pairs — meaning every item in the dictionary has a key and an associated value.

If we want to write down prices of some items in a grocery store, normally we will note them on a piece of paper like this:

eggs - 4.99
banana - 1.49
cheese- 4.5
eggplant - 2.5
bread - 3.99

In Python dictionary lingo, the name of each item is “key” and the associated price is “value” and they appear in pairs. We can represent the same in a Python dictionary data structure as follows:

{"eggs": 4.99,
"banana": 1.49,
"cheese": 4.5,
"eggplant": 2.5,
"bread": 3.99}

Notice the differences. In the dictionary

  • each key is within quotation marks because they are strings
  • the associated values are not quoted because they are numeric
  • keys and values are separated by a colon (:)
  • the items are comma-separated

#dictionary #python #artificial-intelligence #dictionaries #python dictionary #working with python dictionaries

Art  Lind

Art Lind


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


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.


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