DEV Community: Tahuruzzoha Tuhin

The Smart Home Revolution: IoT's Influence on Modern Living

Tahuruzzoha Tuhin — Fri, 15 Sep 2023 05:50:52 +0000

The idea of the "smart home" has moved beyond science fiction to become an essential component of modern living in an era of rapid technological growth. How we engage with our living places is changing as a result of the Internet of Things (IoT) and home automation's convergence. Our houses' once-static walls have evolved into dynamic ecosystems where electronics easily interact, work together, and adapt to our preferences. We explore the revolutionary potential of IoT technology, its influence on daily life, the advantages and disadvantages, and the future of linked living in this article as we delve deeply into the smart home revolution.

The Rise of Smart Homes: A Glimpse into the Future

Connecting the Dots; Smart homes are now a significant part of both the present and the future, moving beyond the realm of theory.

Thanks to the IoT ecosystem, a variety of devices and gadgets can readily link, resulting in a complicated network that functions well. The intelligent metamorphosis of thermostats, lights, refrigerators, and even doorbells has altered how we interact with our homes.

Understanding the Internet of Things: The Basis for Smart Homes

The smart home revolution is supported by the Internet of Things (IoT). It alludes to the system of linked devices that utilizes the internet to communicate and exchange data. These gadgets, which range from appliances to sensors, have connections, actuators, and sensors that allow them to gather, send, and act on data.

Key Components of IoT:

Sensors/Devices: Sensors gather information from their surroundings, ranging from straightforward temperature readings to intricate video feeds. A phone with cameras, accelerometers, and GPS is an example of a device with numerous sensors integrated into it. Data gathering from the environment by something is required for this first phase.

Connectivity: The cloud can be accessed by sensors and devices via a variety of connections, including cellular, satellite, WiFi, Bluetooth, LPWAN, gateway/router, and ethernet. The ideal option will depend on the IoT application. Each option has trade-offs in terms of battery consumption, range, and bandwidth.

Data Processing: Cloud computing is used to handle data for both straightforward jobs like checking temperature ranges and more complicated ones like recognizing intruders. The user is in charge of dealing with extreme temperatures or intrusions into their property.

User Interface: Through warnings, proactive system checks, and remote actions, the IoT system gives important information to end users. Users have the ability to change the temperature, carry out specified actions, and alert security personnel or law enforcement to intruders. A secure environment is ensured and some activities are carried out automatically to allow the system to adjust to user preferences.

Benefits of Smart Homes: Transforming Daily Life

Numerous advantages that improve our daily lives result from the adoption of IoT technology in our homes:

Easy Inter connectivity: By providing remote control of thermostats, security cameras, and lighting schedules, smart home integration improves productivity, monitors in-home devices remotely, and reduces utility costs.

Check-Ins & Remote Monitoring: Remote monitoring makes smart homes manageable from any mobile device. This makes it possible to check in on numerous components of your house and property in real-time. It is priceless to know that your home and loved ones are secure from dangers like burglars, vandals, fire, and carbon monoxide.

Health & Wellness Tracking: Integrate smart wellness technology, real-time communication, smart contact sensors, and Alarm.com Wellness Personal Emergency Response Pendants and wristbands for increased security to support senior loved ones' safe, independent lifestyles.

Energy & Utilities Management: Control utilities like lighting, heating, and cooling to save energy and lower consumption. Utilize smart LED lamps for security, smart outlets for automatic shut-off, and pre-programmed thermostats. Solar panels lower bills and produce credits for green energy.

Appliance Safety & Automatic Shutoffs: Install contact sensors on refrigerators and freezers and smart stove and grill guards for automatic appliance shutoffs, monitoring fires, gas leaks, propane loss, and carbon monoxide poisoning.

Leak Detection & Flood Sensors: Another smart feature is one that guards your house from leaks and flooding. Utilize the leak detection and flood sensors in your system to send out real-time mobile warnings so you can stop costly damages in their tracks. Including Alarm.com The Smart Water Valve + Meter provides daily use insights as well as instant leak and moisture identification to ensure automatic shutoff.

Challenges and Considerations

Although the smart home revolution has great potential, there are a number of issues that need to be resolved:

1. Technical Difficulty: For some consumers, setting up and customizing a smart home ecosystem can be difficult and overwhelming.

2. Data Privacy: As gadgets gather and send data, worries about data privacy, security lapses, and potential surveillance start to surface.

3. Data Security: Concerns about data privacy, security flaws, and potential spying start to appear as devices collect and communicate data.

1. Cost: While smart infrastructure and devices can initially be expensive, over time, energy savings and convenience could outweigh this cost.

The Potential of Smart Homes in the Future

Continuous innovation and research define the smart home revolution's course. There are several rising trends and directions:

Integration of AI and machine learning: With the incorporation of AI and machine learning, smart homes will become even smarter since gadgets will be able to learn from human behavior and adjust accordingly.

Energy Sustainability: Energy efficiency will continue to be a top priority in smart homes, which will also incorporate load control, renewable energy sources, and energy storage.

Privacy and Data Ethics: Addressing data privacy and setting moral standards for data utilization will be critical.

Integration of Smart Cities: Smart houses will be incorporated into larger smart city programs, aiding in effective resource management and urban planning.

The smart home revolution signifies a fundamental shift in how we interact with our living surroundings and goes beyond a simple technological change.

Home automation and IoT technology have merged to create a linked ecosystem that enables people to customize their surroundings to suit their preferences and needs.The smart home revolution promises to improve comfort, convenience, efficiency, and security in ways that were once thought to be impossible as the frontiers of what is conceivable continue to blur.

Despite difficulties, the dedication to innovation, security, and ethical concerns will pave the way for a day when smart homes redefine contemporary living and make it possible for a more connected and peaceful way of life.

Blockchain Beyond Cryptocurrencies: Unveiling the True Potential

Tahuruzzoha Tuhin — Sat, 02 Sep 2023 09:04:21 +0000

Few ideas in the realm of technology have so thoroughly captivated the public's imagination as blockchain. Blockchain was first presented as the underlying technology for cryptocurrencies, but it has since expanded and is now set to transform a wide range of sectors. While digital currencies like Bitcoin and Ethereum have drawn a lot of attention, blockchain technology's greater potential offers the possibility of fundamentally altering how we interact with data, conduct commerce, and maintain security. In this essay, we explore the many facets of blockchain technology beyond cryptocurrencies, delving into its fundamental concepts, practical uses, and untold future potential.

Blockchain: An Overview of a Decentralized Ledger

Blockchain is a decentralized, immutable database that makes it easier to track assets and record transactions in a corporate network. An asset might be physical (a house, car, money, or piece of land) or intangible (patents, copyrights, branding, and intellectual property). On a blockchain network, practically anything of value may be recorded and traded, lowering risk and increasing efficiency for all parties.

Important components of a blockchain

Distributed ledger technology: The distributed ledger and its immutable record of transactions are available to all network users. Transactions are only recorded once with this shared ledger, preventing the duplication of effort present in conventional corporate networks.
Immutable records: Once a transaction has been counted to the shared ledger, no participant is permitted to alter or interfere with it. A fresh transaction must be added to undo an error in a transaction record before both transactions are displayed.
Smart contracts: A set of instructions known as a smart contract is saved on the blockchain and automatically carried out to speed up transactions. A smart contract can specify parameters for corporate bond payments, stipulate how much must be paid for travel insurance, and much more.

Beyond Cryptocurrencies: Blockchain Use Cases Across the Board

Blockchain was popularized by cryptocurrencies, but its actual potential resides in the applications it finds in a wide range of fields:

Healthcare: Blockchain technology is revolutionizing the industry, and various use cases illustrate its potential for disruption. It prevents breaches and hackers thanks to its immutable architecture. The creation of innovative medicines and individualized therapies is being done by blockchain app developers.
Supply Chain: Businesses may trace their supply chain from raw materials to delivery using blockchain technology, and employees can scan items in the store app to track them from harvest to the sales floor.
Encrypted Messaging: End-to-end encryption is revolutionized by blockchain technology thanks to decentralization. Companies like Crypviser develop blockchain-based messaging systems that offer customers secure encrypted messages with no chance of hacking. Enterprise systems especially profit from this.
Banking and Finance: Blockchain has the potential to transform settlements, remittances, and cross-border payments in addition to cryptocurrencies. It improves security while speeding up transaction times and prices.
Gaming and entertainment: Blockchain can provide verifiable ownership and scarcity of digital assets, opening up new business models in these sectors.

Challenges and Roadblocks

Despite the enormous promise of blockchain, several issues need to be resolved:

Energy Consumption: Blockchains powered by Proof of Work, like Bitcoin, need a significant amount of energy, which raises environmental concerns. It is crucial to switch to consensus procedures that use less energy.
Regulation & Legal Frameworks: As blockchain technology upends established industries, regulatory frameworks must be modified to take into account its special characteristics.
Scalability: Due to their high processing demands and constrained throughput, blockchain networks, particularly public ones, experience scalability problems.
User Experience: The absence of user-friendly interfaces in many blockchain apps can prevent their wider adoption.

Blockchain's Future: A Changing Landscape

Blockchain technology is constantly evolving as a result of continuing research and development. Its future is being shaped by several trends and initiatives:

Interoperability Solutions: Initiatives and protocols are being created to enable communication and collaboration among various blockchain networks.
Integration with Emerging Technologies: As blockchain interacts with emerging technologies like 5G, the Internet of Things, and artificial intelligence, new applications and use cases are made possible.
Government Adoption: A few countries are looking at implementing blockchain technology for public services like identity verification and property registration.
Asset Tokenization: The idea of tokenizing physical assets, such as art or real estate, is gaining popularity since it allows for fractional ownership and liquidity.
Sustainability: Transitioning to more energy-efficient consensus processes is being worked on to lessen the environmental impact of blockchain networks.
Regarding confidentiality and privacy: Blockchain transactions are becoming more private because of developments in zero-knowledge proofs and other encryption methods.

Blockchain's transformation impact on businesses is becoming more and more obvious as it moves beyond its roots in cryptocurrency. Blockchain technology has the ability to completely reshape how we interact with data, conduct commerce, and maintain security in our increasingly digital environment because of its decentralized and transparent nature. Despite the obstacles in our way to complete adoption, the blockchain ecosystem's ongoing innovation, research, and collaboration keep us moving forward. Blockchain has the potential to completely transform supply chains, healthcare, finance, and other industries. This will have a profound impact on how we live, work, and interact.

AWS Route Table, Regions, and Multiple Availability Zones

Tahuruzzoha Tuhin — Thu, 11 May 2023 12:30:51 +0000

In this article, we will discuss the AWS Route Table, AWS regions, and multiple availability zones and give an introduction to how they work and how to use them.

Route Table

The route table contains the networking rules for the subnets in a VPC. A route table contains the target and destination for each network call. So the user can define who can reach whom. When a subnet is created, it’s automatically and implicitly attached to the main route table. Each subnet must be connected to the Route table. The best practice for the user is to categorize public and private subnets and create routing groups to use for each purpose. Each subnet can only be associated with one route table. But one route table can be attached to multiple subnets.

Each VPC comes with a main route table that can not be deleted. But users can create and associate new route tables according to their preferences. Also in each Route table, there is a local route for communication inside the VPC. The Route Table connects various entities in a VPC. It can be associated with subnets, internet gateways, and virtual private gateways. Route tables for IPv4 and IPv6 traffic are created separately.

There is a limit on how many Route tables you can create per VPC. Also, there is an upper limit to the number of routes in Route table.

Destination

It’s where the traffic will go. It’s the CIDR address of end nodes that can call the target. Example: 172.15.0.1/16 (some custom IP address), 0.0.0.0/0 (for allowing all IPv4 traffic), or simply a single IP address that can call the target. IPv4 and IPv6 are treated separately by the Route table.

The destination can’t be arbitrary. The destination IP addresses must be available to the VPC.

Target

through which the traffic will go. It can be a local connection, an internet gateway, or virtual private gateway. If the target is some gateway, then the Route table is called the gateway route table.

There are fixed types of targets available. For example, internet gateway.

Table: An example of destination & target Route

Destination	Target
0.0.0.0/0	igw-9821231012912321

Overwriting Routes

One subnet can be assigned to multiple Routes. But the most specified routes are given preference. For example, all IPv4 internet traffic is 0.0.0.0/0. If it’s connected to an internet gateway, but if you use a route for 172.1.0.0/16 IPv4 to a different target, then this one will be applied rather than the 0.0.0.0/0 one.

Managing Security Risk

Route table helps to identify and prevent various attacks with a few simple clicks. This creates an abstraction layer over all traffic in the VPC and helps the user to minimize risk.

The Gateway Route table is the Route table that has the gateway as the target. This kind our Route table can save a lot of hassle in emergency cases. For hacking and resource misusage, you can easily turn on/off the target connection in the Route table and test out any kind of failure.

Regions and Multiple Availability Zones

Amazon EC2 is hosted over multiple regions over the globe. Here regions mean geographically separated areas. The regions are isolated from each other, This achieves the greatest possible fault tolerance and stability. The User has to choose a region before launching VPCs and instances. In case of rare failures, just a single area will be affected. Deploying to a specific region helps the people of that region to get to the server fast and provide a lightning-fast service.

Each region is subdivided into multiple Availability Zones. Each availability zone has its own power, cooling, and network system. So, it’s an isolated failure domain within the isolated regions, which provides safer data storage. Users are encouraged by AWS to launch instances into multiple AZs in case of rare failures. The subnets of each AZs are closer to each other, so they can communicate with low latency.

If necessary users can migrate from one availability zone to another zone using the AWS-provided backup facilities.

Local Zones

Local zones are extensions of the AWS region. To deploy resources to the proximity of end users, sometimes local zones are preferred. Local zones have low latency for local users.

Wavelength Zones

To use cutting-edge 5G communication technology, AWS provides Wavelength zones. Storage and computing are similar to standard resources, but communication is much faster for instances deployed in wavelength zones. But it’s not available in all Regions.

Wavelength zones are tied to a Region; it’s a logical extension of a Region. Application deployed to wavelength zones has ultra-low latency response. To use a Wavelength zone, the user must opt into that zone and deploy subnet and other resources in that zone.

In this article, we discussed Route tables to manage your inbound and outbound traffic in AWS. We also discussed AWS’s regions and multiple availability zones, and how to use them to get low latency. The more you learn about these, the more you can customize your AWS platform to manage security and serve the end users with minimal delay.

Amazon Web Service VPS vs VPC

Tahuruzzoha Tuhin — Fri, 14 Apr 2023 16:08:20 +0000

AWS VPS vs VPC

Amazon provides two types of cloud computing services: VPS (Virtual Private Server) and VPC (Virtual Private Cloud). Both give the user the ability to distribute resources and applications with different types of scaling capabilities. Both have their perks. VPS is preferred for better management for steady usage applications. If the demand for server resource usage fluctuates and you need better and more secure control over your cloud resources, VPC is preferred.

In this article, we will discuss what are VPS and VPC, and how they vary in their usage and resources.

VPS

A VPS or Virtual Private Server is a virtual machine that is hosted on a physical server. VPS is also known as Virtual Dedicated Server. VPS uses a virtualization technique that can launch multiple virtual machines that shares resources on a single physical machine. As VPS is shared on the machine, the resources for it are reserved. It gives the users more control than shared servers. Users can increase dedicated resources such as processing power, memory, and storage.

VPSs are ideal for applications that require more control and customization than shared hosting but still want the benefits of cloud computing, such as scalability and reliability. VPSs on the same physical devices aren’t essentially connected.
AWS provides the Lightsail VPS instance, which is easy to configure. The managing UI for Lightsail is very intuitive. You can launch Lightsail in just 2-3 minutes. AWS provides both Windows and Linux OS for Lightsail at moderately low prices starting with $3.5 for Linux OS and $8 for Windows OS.

VPC

A VPC is a virtual network in the cloud, where users can get isolated and secure computing environments. VPC is a logical division in the cloud environment that is run by various security protocols (Encryption, Private IP, Virtual LAN, etc). VPCs allow you to launch AWS resources into a virtual network with Subnet Routing (Understanding AWS Subnet).

Users can connect to the network with preferred protocols (SSH (SSH to AWS EC2 from Windows), TCP). To understand the main difference between VPC with VPS is: VPC allows applications to be deployed into a private network and requires a higher level of security and control.

AWS’s cloud console lets you easily launch a VPC. You can set up security groups (what traffic is allowed), Route tables (what devices can use your instances). This type of management helps to have better control over your system. You can also select which region to launch your application depending on your end user. If the VPC is closer to your end user the application will have low latency. All the instances launched in your VPC will share the same regionality as your VPC.

You can also select inbound and outbound rules for your private instances. This makes some of your instances only accessible through your specified instances. For backend and databases, this type of private connection helps to make your application more secure.

Performance

The performance of VPS and VPC can vary depending on the number of resources allocated. For the same type of workload, they should give the same performance. VPS is best for applications that require easier management with steady resource usage and easy customization, while VPC is best for applications that require a higher level of security and need to be deployed in a private network. VPC is more flexible to fluctuating demands compared to VPS.

Resource scaling (AWS Vertical Scaling vs Horizontal Scaling) is different for VPS and VPC. For VPS only vertical scaling is available. One can scale horizontally for VPS but it can become complicated due to the VPSs not being internally connected like VPCs. For VPC both horizontal and vertical scaling is possible considering the architecture of the application.

In the VPC, all the internal connections, designs, and network configurations can be specifically created by the user. This can result in better performance for applications running in a VPC compared to those running in a VPS. On the other hand, VPS is typically easier to set up and manage compared to VPC, and users can consider using VPS for smaller applications that do not require a high level of security and customization.

Adaptation Period

Beginners can easily adapt to VPS with basic OS and deployment-related knowledge. Learning about managing all the resources, firewalls and other security issues might require some time. Compared to VPS, VPC is much harder to learn. AWS provides 12 certificates for different types of professionals with varying degrees of difficulty. But for most cases, entry-level simple deployment can be easy to learn due to AWS’s intuitive interface.

However, There is no correct answer to which is better. If an application needs better securing and resource management, then VPC is preferred. But if this is not an issue, VPS can be cheap and easily maintainable with the added benefit of cloud management.

Programming Fundamentals using Python

Tahuruzzoha Tuhin — Wed, 12 Apr 2023 04:53:46 +0000

Programming fundamentals are the basic concepts and building blocks of programming. These concepts are essential for understanding how to write and execute code in any programming language.

Variables: Variables are used to store and manipulate data in a program. They have a name and a value, and the value can be changed during the execution of the program.

Example:

x = 5
y = 10
result = x + y
print(result)  # Output: 15

Data types: Different programming languages have different data types, such as integers, floating-point numbers, strings, and boolean values. Understanding the different data types and how to use them is essential for writing code that is efficient and correct.

Example:


age = 25
price = 19.99
name = "John"
is_student = True

print(type(age))    # Output: <class 'int'>
print(type(price))  # Output: <class 'float'>
print(type(name))   # Output: <class 'str'>
print(type(is_student)) # Output: <class 'bool'>

Operators: Operators are used to performing operations on variables and values. Common operators include arithmetic operators (+, -, *, /), comparison operators (>, <, >=, <=, ==, !=), and logical operators (and, or, not).

Example:


x = 5
y = 2

print(x + y)   # Output: 7
print(x - y)   # Output: 3
print(x * y)   # Output: 10
print(x / y)   # Output: 2.5

is_true = (x > 3) and (y < 5)
print(is_true) # Output: True

Control structures: Control structures are used to control the flow of execution in a program. They include if-else statements, loops (such as for and while), and functions.

Example:


x = 5

if x > 0:
    print("x is positive")
else:
    print("x is non-positive")

for i in range(5):
    print(i)
    # Output: 0, 1, 2, 3, 4

i = 0
while i < 5:
    print(i)
    i += 1
    # Output: 0, 1, 2, 3, 4

Functions: Functions are blocks of code that can be reused throughout a program. They take input in the form of parameters and return output.

Example:


def greet(name):
    """This function greets the person passed in as a parameter"""
    print("Hello, " + name + ". How are you today?")

greet("John") # Output: Hello, John. How are you today?

Arrays and collections: Arrays and collections are used to store multiple values in a single variable. They are used to organize and manipulate data in a program.

Example:


numbers = [1, 2, 3, 4, 5]

print(numbers[0]) # Output: 1
numbers.append(6)
print(numbers) # Output: [1, 2, 3, 4, 5, 6]

fruits = {"apple", "banana", "orange"}
print("banana" in fruits) # Output: True

info = {"name": "John", "age": 25}
print(info["name"]) # Output: John

Object-oriented programming: Object-oriented programming (OOP) is a programming paradigm that uses objects to represent and manipulate data in a program. OOP concepts include classes, objects, inheritance, and polymorphism.

Example:

class Dog:
    def __init__(self, name, age):
        self.name = name
        self.age = age

    def bark(self):
        print("Woof, woof!")

dog1 = Dog("Fido", 3)
print(dog1.name) # Output: Fido
dog1.bark() # Output: Woof, woof!

Algorithm: An algorithm is a step-by-step procedure for solving a problem. It is a set of instructions that a computer can execute to accomplish a specific task.

Example:


def find_largest(numbers):
    """This function finds the largest number in a list of numbers"""
    largest = numbers[0]
    for num in numbers:
        if num > largest:
            largest = num
    return largest

print(find_largest([1, 5, 2, 8, 3])) # Output: 8

Data structure: A data structure is a way of organizing and storing data in a computer's memory so that it can be accessed and modified efficiently. There are several common data structures in computer science, each with its own strengths and weaknesses.

such as, Linked Lists: Linked lists can be implemented in Python using a class to represent the nodes and another class to represent the linked list. Here's an example of a singly linked list:


class Node:
    def __init__(self, data):
        self.data = data
        self.next = None

class LinkedList:
    def __init__(self):
        self.head = None

    def append(self, data):
        new_node = Node(data)
        if self.head is None:
            self.head = new_node
            return
        current = self.head
        while current.next:
            current = current.next
        current.next = new_node

Debugging: Debugging is the process of identifying and fixing errors in a program. It is an essential part of the programming process and can be done using tools such as print statements, debuggers, and testing frameworks.

Example:


def find_largest(numbers):
    """This function finds the largest number in a list of numbers"""
    largest = numbers[0]
    for num in numbers:
        print(num, largest)
        if num > largest:
            largest = num
    return largest

print(find_largest([1, 5, 2, 8, 3]))

In the above example, I added a print statement to check the value of the num and largest variable for each iteration. This way we can check the values in each step and debug the code accordingly.

Also, most IDE has built-in debugging tools that can be used to inspect the variables, set breakpoints, and step through the code, which can make the debugging process more efficient.

Commenting: Commenting is the practice of adding explanations and notes to the code. It helps to understand the code and also it helps other developers to understand the code.

Example:


"""This is a doc-string or multi-line comment"""
# This is a single line comment

These concepts form the foundation of programming, and understanding them is essential for becoming a proficient programmer. However, every programming languages have its own syntax and libraries, so it's important to learn the specific details of the language you're working with.

To become a good programmer, it's important to have a solid understanding of the programming fundamentals concepts that I mentioned in my previous response, such as variables, data types, operators, control structures, functions, arrays and collections, object-oriented programming, algorithms, debugging, and commenting. Here are some ways to gain knowledge and improve your skills in these areas:

Practice: The more you practice writing code and solving problems, the more comfortable and proficient you will become with the language and concepts.

Learn by doing: Try to work on real projects as much as possible, it will help you to apply the concepts you learn and to get a better understanding of how they can be used in the industry.

Read the documentation: The official documentation is a great resource for learning about the different features and capabilities of a programming language.

Learn from others: Join online communities, attend meetups, read blogs, and follow programming experts on social media.

Learn multiple languages: Learning multiple languages, it will help you to understand how different languages tackle the same problem and how the concepts are implemented differently in different languages.

Read code: Read other people's code to understand how they solve problems and to get new ideas for your own projects.

Keep learning: The field of programming is constantly changing, so it's important to stay up to date with new technologies and trends.

Learn the best practices: Learn the best practices of the programming languages, such as commenting, variable naming, coding style, and formatting.

Test your code: Test your code thoroughly to ensure that it works as expected and to catch any bugs early on.

Don't be afraid to ask for help: It's okay to ask for help when you get stuck or don't understand something.

By following these tips and continuously practicing and learning, you will be able to improve your skills and become a better programmer.

Here are some resources that can help you to improve your understanding of programming fundamentals:

Codecademy: Python 3: Codecademy offers interactive coding lessons for a variety of programming languages, including Python.
Coursera: Python: Coursera provides online courses on a wide range of programming topics, from beginner to advanced levels.
edX: CS50-Python: edX is another online learning platform that offers a variety of programming courses, including those that focus on specific languages and concepts.
SoloLearn: Python: SoloLearn is a mobile app that offers interactive coding lessons and quizzes on a variety of programming languages.
EnableGeek: Interactive Python: Enablegeek provides various kinds of text-based programming tutorials. Which is provided absolutely free for everyone to enroll. They have beginner to intermediate or intermediate to advanced level tutorials of various technologies on this platform. You can enrich your programming fundamentals with these free resources.
Tutorialspoint: Python Tutorial: This Python tutorial has been written for beginners to help them understand the basic to advanced concepts of Python Programming Language. After completing this tutorial, you will find yourself at a great level of expertise in Python, from where you can take yourself to the next level to become a world-class Software Engineer.
Project Euler: Archive: Project Euler is a website that offers mathematical and computer programming problems that can be solved with code.
HackerRank: Python: HackerRank is a website that offers coding challenges and competitions to help you improve your coding skills.
GitHub: GitHub is a platform where you can find open-source projects to contribute to and learn from.
Books: There are many books available on programming fundamentals and specific languages such as "Python Crash Course" by Eric Matthes, "Eloquent JavaScript" by Marijn Haverbeke, "Think Python" by Allen B Downey.

You can find lots of python books in PDF Drive Python Catalogue.

These resources can help you to learn and practice programming concepts, keep up with the industry trends and get insights from experienced programmers. Remember, the key to becoming a good programmer is practice and experience, so try to work on projects, solve problems and make the most of these resources.

Benefits of Python and its Use Cases

Tahuruzzoha Tuhin — Mon, 06 Mar 2023 11:48:33 +0000

What is Python?
-Python is a high-level scripting language that can be used for a wide variety of text processing, system administration, and internet-related tasks. Unlike many similar languages, its core language is very small and easy to master, while allowing the addition of modules to perform a virtually limitless variety of tasks. Python is a true object-oriented language, and is available on a wide variety of platforms such as It is used for a wide range of applications, from web development to machine learning and data analysis.

Benefits of Python:

Simple to learn and implement: The difficult effort of learning a new language that doesn't look anything like what they're used to reading and writing is one of the largest obstacles for prospective programmers. However, unlike many other languages, Python has English syntax and was made to be short and simple to comprehend. As a result, it is easier for beginners to learn than many other programming languages. It is one of the most used languages by highly productive professional programmers. The code is highly readable and requires fewer lines of code compared to other programming languages. This makes it easy to maintain and debug.
Versatility: Python programming is powering the global job market because the benefits of Python are clear. Python can be used for a wide range of applications, including:

Finance and trading
Data Science
Scientific and mathematical computing
Basic game development
Web development
System automation and administration
Computer graphics
Security and penetration testing
General and application-specific scripting
Mapping and geography (GIS software)

Open Source: Python is recognized as one of the most popular programming languages for use in data science and artificial intelligence applications, and it is still one of the most important members of the development community. Several helpful third-party packages are included with this open-source programming language. This has caused a sizable community of developers to contribute to its growth and improve it over time. It is a very well-liked option among data scientists, but because of its extensive libraries, it can also be used for web development and machine learning.
Platform Independent: Platform-independent technology is that which can be developed on one machine and used without modification on another. Platform-independent binary languages are those that run on virtual computers and may be moved from one device to another in their built, binary version. Python is a binary programming language that works on every platform. Almost any platform or operating system can run the same Python code. Windows, Linux, and macOS are just a few of the platforms on which Python code can be executed.
Significant Community and Support: Tens of thousands of Python developers assist and guide the community through local, regional, and international events as well as an active developer community that offers support, shares information, and contributes to its growth. This guarantees that any problems are dealt with right away and that a solution is always available. You can check Stackoverflow Python Community.
Libraries and Frameworks: One of the most well thought and efficient programming languages, Python has a substantial library and framework for practically every technological area. Libraries aid in the reduction of coding errors, increase the productivity of programmers and minimize the size of software (and lines of code). Coders can use libraries to execute simple tasks, frequently with just a single line of code, rather than writing several lines of code to do so. These libraries include Django, Flask, Pandas, Matplotlib, NumPy, and many others.

The use cases of Python:

Machine Learning: The requirement for intelligent answers to practical issues needs the further development of AI in order to automate laborious processes that would be difficult to program without AI. The Python programming language is thought to be the ideal technique for automating these processes since it is more straightforward and consistent than other programming languages. For creating and refining machine learning models, sophisticated tools are available thanks to libraries like TensorFlow, Keras, and PyTorch.
Data Analysis and Visualization: Python performs admirably during each level of data analysis. The Python packages created specifically for data science are what makes the language so useful. Data mining, data processing, and modeling together with data visualization are the 3 most prevalent techniques of how Python is being utilized for data analysis. Python is widely used for data analysis and visualization, with the most well-known packages being NumPy, Pandas, and Matplotlib. These libraries offer effective and potent tools for data analysis, visualization, and manipulation.
Web Development: Python is a free software program. In the sense that it can be altered by the concerned developer to match his own demands and requirements. Python makes it simple to create blocks and libraries, and more crucially, it can be scaled up and modified as a language to keep up with evolving technologies. These frameworks offer a high level of abstraction, which facilitates the speedy development of complex web applications.
Game Development: As the gaming industry has expanded, Python game programming has shown to be the ideal answer for developers seeking quick prototyping and game execution. The most well-known Python libraries for game development are Pygame and PyOpenGL. It is a fantastic option for game development because of the concise syntax that helps with the smooth execution of an idea or logic, the ease of adding features, and the reduced difficulty of debugging.
Finance: The financial services industry needs to be more flexible and responsive to customer needs, providing unique experiences and value-adding supplementary services. Because of this, financial institutions and fintech require a system that is adaptable and versatile, and Python provides just that. Python is frequently used in finance for modeling and data analysis.

In conclusion, Python is in high demand, and a career in Python can be the perfect path to achieve your career goals. From NASA to Facebook, and from Google to Instagram – leading technology giants all over the world use Python as a programming language for a wide variety of applications. Naturally, there’s a high demand for skilled Python professionals. Here are some websites that can help you to improve your understanding of programming fundamentals:
Tutorialspoint, W3Schools, EnableGeek, HackerRank(Problem-solving), Python, and so on.

Python Intermediate: How to use Python Decorators.

Tahuruzzoha Tuhin — Tue, 27 Sep 2022 04:01:14 +0000

Python decorators

Python has an intriguing feature called decorators that allows you to add functionality to existing programs. This is also known as metaprogramming since a portion of the program attempts to alter another portion of the program during the compilation process. Learning requirements for decorators: To comprehend decorators, we must first grasp a few fundamental Python concepts.

We must be comfortable with the reality that everything in Python is an object (yes, including classes). The names we provide to these things are merely identifiers. Functions are not exceptions; they are also objects (with attributes). Different names can be assigned to the same function object.

Example:

def function(value):
   print(value)

function("Enablegeek")

second = function
second("Enablegeek")

Output:

Enablegeek
Enablegeek

The output from the first and second functions is the same when the code is executed. The first and second names in this case correspond to a similar function object. Things are starting to become strange now. Functions can be provided to another function as parameters. If you’ve used Python functions like map, filter, or reduce, you’re already aware of this. Higher-order functions are functions that accept other functions as parameters. Here’s an example of a function like this.

Example:

def Additive(item):
   return item + 10


def Substructive(item):
   return item - 10


def Operator(func, x):
   result = func(x)
   return result

print(Operator(Additive, 100))
print(Operator(Substructive, 100))

Output:

110
90

Returning to Decorators, Callable functions and methods are those that can be called. Callable refers to any object that implements the special call() function. A decorator, in the most basic sense, is a callable that returns another callable. A decorator basically takes a function, adds some functionality to it, and returns it.

Example:

def Decorated_Function(func):
   def Internal():
       print("Decorated methods here!")
       func()
   return Internal


def Simple_Function():
   print("Ordinary methods here!")


Simple_Function()

Well_Decorated = Decorated_Function(Simple_Function)
Well_Decorated()

Output:

Ordinary methods here!
Decorated methods here!
Ordinary methods here!

The function Simple_Fuction() was decorated, and the resulting function was named Well_Decorated().

The decorator function, as we can see, provided some extra functionality to the original function. This is analogous to wrapping a present. The decorator serves as a container. The nature of the adorned object (the real present within) remains unchanged. However, it now appears to be attractive (since it got decorated).

In general, we decorate a function and rename it,

Example:

def Decorated_Function(func):
   def Internal():
       print("Decorated methods here!")
       func()
   return Internal


@Decorated_Function
def Simple_Function():
   print("Ordinary methods here!")

Simple_Function()

Output:

Decorated methods here!
Ordinary methods here!

Python Decorator Chaining

Python allows for the chaining of several decorators. This means that a function can be decorated several times with various (or the same) decorators. The decorators are simply placed above the required function.

Example:

def initialize(func):
   def internal(*args, **kwargs):
       print("$" * 30)
       func(*args, **kwargs)
       print("$" * 30)
   return internal


def hash_wise(func):
   def internal(*args, **kwargs):
       print("#" * 30)
       func(*args, **kwargs)
       print("#" * 30)
   return internal


@initialize
@hash_wise
def printer(msg):
   print(msg)


printer("Enablegeek is Awesome!")

Output:

$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$
##############################
Enablegeek is Awesome!
##############################
$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$

This has been a long road! You began this session by learning more about functions, specifically how they may be defined inside other functions and handed around like any other Python object. Then you discovered decorators and how to write them.

You can also find the tutorial Python Decorators.