Swapnil Saurav

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Mar 6 2022
Free Python Webinar

Python expert Swapnil Saurav conducted one-hour long Python Webinar for those who want to learn Python programming. The session was conducted on March 5th 6-7pm India time. This was conducted as part of Swapnil’s mission to make India Python literate. The webinar was attended by over 30 participants.

Following topics were covered in the session:

  1. Why is gaining popular
  2. Top features of Python
  3. Brief history
  4. Download, Installation and Working of Python.exe, Pycharm and using Google Colab
  5. Print() function
  6. Variables
  7. Basic datatypes – Int, String

List of participants included:

  1. Borra John
  2. Shivakumar
  3. Ajan S
  4. Juhaira K
  5. Sankar K
  6. Velmurugan A
  7. Loga Varshini.P
  8. Bhuwan Kumar Sharma
  9. Aswini M
  10. Harini Sri A.R.
  11. K. Swetha
  12. Rohan S Lolage
  13. M. Jaya varshini
  14. Nathalie Joy D. Fronda
  15. S. Sanjay
  16. Inika.R.G.
  17. Kanividya G.P.
  18. Indu Bala
  19. Sivanarul Selvan S
  20. Shrasti Agrawal
  21. S. Srinivas
  22. Pandu Rangan C.R
  23. M. Hemapriya
  24. Muskan Mahato
  25. Debjit Biswas
  26. Noor Mohammed G
  27. Chauhan Mitul Kumar
  28. Souvik Chakraborty
  29. Navneet Singh
  30. Kapil RJ
  31. Gagan Manocha

Attached here is the presentation deck:

Presentation slides
admin 2 Comments
Jan 9 2022
Cloud Computing Basics – 1

Cloud computing is a computing term or metaphor that evolved in the late 2000s, based on utility and consumption of computer resources. Cloud computing is about moving computing from the single desktop PC/Data centers to Internet.

Figure 1.1: Cloud computing terms

Cloud: The “Cloud” is the default symbol of the internet in diagrams

Computing: The broader term of “Computing” encompasses- computation, coordination logic and storage.

Chapter 1.1: Fundamentals of cloud computing

Let’s take an example, you wish to play Ninja Fighters game with your friend on your smartphone. You go to the app store, download the app, log in, find your friend and within five minutes, you’re having fun. This ability to request services for yourself when you need them in cloud computing terms is known as on-demand self-service. You didn’t need to go to a physical store, you didn’t need to call someone to place an order and you didn’t need to sit on hold or wait for anyone else to do anything for you. Another example is of Gmail. You don’t need to install any software nor do you need hard disk space to save your emails -It’s all in the “cloud” managed by Google. In cloud computing, you don’t care what kind of software it is, all you care about is that the service offered is available and reliable. As more users join the game, the cloud is able to quickly grow or shrink to meet the change in demand—elasticity in techie terms. This is possible because a cloud provider, like IBM, has a massive number of servers pooled together that can be balanced between its various customers. But ultimately, you don’t care as long as it’s available for you.

1.1.1Features of Cloud Computing

Figure 2: NIST Visual Model of Cloud Computing Definition

Figure 2: NIST Visual Model of Cloud Computing Definition

The generally accepted definition of Cloud Computing comes from the National Institute of Standards and Technology (NIST). The NIST definition runs to several hundred words but essentially says that:

Cloud computing is a model for enabling convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction.

What this simply means is the ability for end users to utilize parts of bulk resources and that these resources can be acquired quickly and easily. NIST also offers up several characteristics that it sees as essential for a service to be considered “Cloud”. These characteristics include;

  • On-demand self-service: The ability for an end user to sign up and receive services without the long delays that have characterized traditional IT
  • Broad network access: Ability to access the service via standard platforms (desktop, laptop, mobile etc)
  • Resource pooling: Resources are pooled across multiple customers
  • Rapid elasticity: Capability can scale to cope with demand peaks
  • Measured Service: Billing is metered and delivered as a utility service

1.1.2Types of Cloud

With cloud computing technology, large pools of resources can be connected through private or public networks.

Figure 3: Types of Cloud (Deployment Model)

What are the differences between these types of cloud computing, and how can you determine the right cloud path for your organization? Here are some fundamentals of each to help with the decision-making process().

Public

Public clouds are made available to the general public by a service provider who hosts the cloud infrastructure. Generally, public cloud providers like Amazon AWS, Microsoft and Google own and operate the infrastructure and offer access over the Internet. With this model, customers have no visibility or control over where the infrastructure is located. It is important to note that all customers on public clouds share the same infrastructure pool with limited configuration, security protections and availability variances.

Public Cloud customers benefit from economies of scale, because infrastructure costs are spread across all users, allowing each individual client to operate on a low-cost, “pay-as-you-go” model. Another advantage of public cloud infrastructures is that they are typically larger in scale than an in-house enterprise cloud, which provides clients with seamless, on-demand scalability. These clouds offer the greatest level of efficiency in shared resources; however, they are also more vulnerable than private clouds.

A public cloud is the obvious choice when:

  • Your standardized workload for applications is used by lot of people, such as e-mail.
  • You need to test and develop an application code.
  • You need incremental capacity i.e. the ability to add resources for peak times.
  • You’re doing collaboration projects.

Private

Private cloud is cloud infrastructure dedicated to a particular organization. Private clouds allow businesses to host applications in the cloud, while addressing concerns regarding data security and control, which is often lacking in a public cloud environment.  It is not shared with other organizations, whether managed internally or by a third-party, and it can be hosted internally or externally.

There are two variations of private clouds:

On-Premise Private CloudExternally Hosted
This type of cloud is hosted within an organization’s own facility. A businesses IT department would incur the capital and operational costs for the physical resources with this model. On-Premise Private Clouds are best used for applications that require complete control and configurability of the infrastructure and security.Externally hosted private clouds are also exclusively used by one organization, but are hosted by a third party specializing in cloud infrastructure. The service provider facilitates an exclusive cloud environment with full guarantee of privacy. This format is recommended for organizations that prefer not to use a public cloud infrastructure due to the risks associated with the sharing of physical resources.

Undertaking a private cloud project requires a significant level and degree of engagement to virtualize the business environment, and it will require the organization to reevaluate decisions about existing resources. Private clouds are more expensive but also more secure when compared to public clouds. An Info-Tech survey shows that 76% of IT decision-makers will focus exclusively on the private cloud, as these clouds offer the greatest level of security and control.

When to opt for a Private Cloud?

  • You need data sovereignty but want cloud efficiencies
  • You want consistency across services
  • You have more server capacity than your organization can use
  • Your data center must become more efficient
  • You want to provide private cloud services

Hybrid

Hybrid Clouds are a composition of two or more clouds (private, community or public) that remain unique entities but are bound together offering the advantages of multiple deployment models. In a hybrid cloud, you can leverage third party cloud providers in either a full or partial manner; increasing the flexibility of computing. Augmenting a traditional private cloud with the resources of a public cloud can be used to manage any unexpected surges in workload.

Hybrid cloud architecture requires both on-premise resources and off-site server based cloud infrastructure. By spreading things out over a hybrid cloud, you keep each aspect of your business in the most efficient environment possible. The downside is that you have to keep track of multiple cloud security platforms and ensure that all aspects of your business can communicate with each other.

Here are a couple of situations where a hybrid environment is best:

  • Your company wants to use a SaaS application but is concerned about security.
  • Your company offers services that are tailored for different vertical markets. You can use a public cloud to interact with the clients but keep their data secured within a private cloud.
  • You can provide public cloud to your customers while using a private cloud for internal IT.

Community

A community cloud is a is a multi-tenant cloud service model that is shared among several or organizations and that is governed, managed and secured commonly by all the participating organizations or a third party managed service provider. Community clouds are a hybrid form of private clouds built and operated specifically for a targeted group. These communities have similar cloud requirements and their ultimate goal is to work together to achieve their business objectives.

The goal of community clouds is to have participating organizations realize the benefits of a public cloud with the added level of privacy, security, and policy compliance usually associated with a private cloud. Community clouds can be either on-premise or off-premise.

Here are a couple of situations where a community cloud environment is best:

  • Government organizations within a state that need to share resources
  • A private HIPAA compliant cloud for a group of hospitals or clinics
  • Telco community cloud for telco DR to meet specific FCC regulations

Cloud computing is about shared IT infrastructure or the outsourcing of a company’s technology.  It is essential to examine your current IT infrastructure, usage and needs to determine which type of cloud computing can help you best achieve your goals.  Simply, the cloud is not one concrete term, but rather a metaphor for a global network and how to best utilize its advantages depends on your individual cloud focus.

1.1.3Advantages & Disadvantages

Advantagesof Cloud Computing

Cloud computing presents a huge opportunity for businesses.Let’s look at some of them:

Cost Efficient

Cloud computing is probably the most cost efficient method to use, maintain and upgrade. Traditional desktop software costs companies a lot in terms of finance. Adding up the licensing fees for multiple users can prove to be very expensive for the establishment concerned. The cloud, is available at much cheaper rates and can significantly lower the company’s IT expenses. Besides, there are many one-time-payment, pay-as-you-go and other scalable options available, which makes it reasonable.

Almost Unlimited Storage

Storing information in the cloud gives you almost unlimited storage capacity. Hence, you no more need to worry about running out of storage space or increasing your current storage space availability. 

Backup and Recovery

Since all your data is stored in the cloud, backing it up and restoring the same is relatively much easier than storing the same on a physical device. Furthermore, most cloud service providers are usually competent enough to handle recovery of information. Hence, this makes the entire process of backup and recovery much simpler than other traditional methods of data storage.

Automatic Software Integration

In the cloud, software integration is usually something that occurs automatically. This means that you do not need to take additional efforts to customize and integrate your applications as per your preferences. This aspect usually takes care of itself. You can also handpick just those services and software applications that you think will best suit your particular enterprise.  

Easy Access to Information

Once you register yourself in the cloud, you can access the information from anywhere, where there is an Internet connection.

Quick Deployment

Cloud computing gives you the advantage of quick deployment. Once you opt for this method of functioning, your entire system can be fully functional in a matter of a few minutes, dependingupon the exact kind of technology that you need for your business.

Disadvantages of Cloud Computing

Cloud computing also has some challengessuch as:

Technical Issues

Though it is true that information and data on the cloud can be accessed anytime and from anywhere at all, there are times when this system can have some serious dysfunction. Technology is always prone to outages and other technical issues. Even the best cloud service providers run into this kind of trouble, in spite of keeping up high standards of maintenance. Besides, you will need a very good Internet connection to be logged onto the server at all times. You will invariably be stuck in case of network and connectivity problems. 

Security in the Cloud

The other major issue while in the cloud is that of security issues. Before adopting this technology, you should know that you will be surrendering all your company’s sensitive information to a third-party cloud service provider. This could potentially put your company to great risk. Hence, you need to make absolutely sure that you choose the most reliable service provider, who will keep your information totally secure.

Prone to Attack

Storing information in the cloud could make your company vulnerable to external hack attacks and threats. As you are well aware, nothing on the internet is completely secure and hence, there is always the lurking possibility of stealth of sensitive data.

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Nov 6 2021
Know Everything About Cloud Computing
Beginners guide to cloud computing

The origin of cloud computing can be traced back as far as 1961 when John McCarthy first conceived the idea. His vision was that computation should be arranged and organized as a public utility to lower the cost of computing, enhance reliability, and relieve users from owning and operating complicated computing infrastructure. And, since then, improvement in legacy technologies like virtualization, commodity and Grid computing has brought about the realization of the cloud computing paradigm. Cloud computing’s flexibility and scalability has continued to enhance the agility and effectiveness of huge organizations, meeting reliability, and the efficiency of large-scale applications. However, performance requirements remain a serious concern and studies and have shown that performance variability is a critical concern for cloud application providers. The reason for that is because it impacts a lot the end-user’s quality of experience. In this discussion, we are going to see in details what cloud computing is, clouds deployment models, delivery models, datacenters, and more.   

What Is Cloud Computing?

It can be defined as a paradigm change in how computation is delivered and utilized. It is based on the idea that the processing of information can take place more effectively on large computing farms and storage systems accessible via the Internet. It offers a set of technologies which enable provision of computational resources like compute and storage as a service via the Internet either on a pay-per-use or on-demand mode.

Two factors that contribute to the high adoption rate of the cloud are; – (1) its ability to offer smooth scalability and elasticity to consumers without huge initial capital expenses and (2) it provides resources that can be metered so that users are only billed for they have consumed. The two appeal factors have led to a drastic change in how IT (Information Technology) departments and application providers organize and manage IT services.

https://youtu.be/HegVrE0g6dIWatch the video of this content

Cloud Delivery Models

Depending on the abstraction level in which a service is provided, public clouds have three main delivery models. These are as below:

  • Infrastructure as a Service (IaaS)–  this involves fundamental computing resources like servers, network, and storage that are provided. Consumers are responsible for installing the operating system (OS) and can create arbitrary applications using application development tools of their choice. Various IaaS providers are available and they include Google Cloud Platform, Rackspace, Amazon EC2, and Microsoft Azure Infrastructure.
  • Platform as a Service (PaaS)– this model gives cloud users the capability to develop, deploy, and manage apps using app development tools, operating systems, APIs, and hardware supported by a provider. The cloud user controls only the application, its architecture, and hosting space configuration but not the network, storage, servers, or even the principal operating system. Among the most renowned PaaS offerings available today are Windows Azure, Google App Engine, and Amazon’s Elastic Beanstalk.
  • Software as a Service (SaaS)- this occurs when end-users start using finished applications accessible via various client devices over the Internet, together with the required software, OS, network, and hardware. The users can enjoy some measure of minimal customization, but they have limited control on the application, its platform, and underlying infrastructure. Some of SaaS applications are Web 2.0 applications (like WordPress & LinkedIn), accounting systems (e.g. NetSuite), and Customer Relationship Management (e.g. ServiceNow).

Clouds Deployment Models

How are cloud infrastructures categorized? The classification can be based on either ownership or how they are managed. Five deployment models are available for cloud infrastructure so far and they are as described below:

  1. Private clouds– they are managed and used by individual entities. Several organizations adopt these clouds to accrue the benefits of cloud computing like scalability and flexibility, and at the same time having complete control on its infrastructure and security.
  2. Public clouds– these are infrastructures managed by an organization which leases them to third-parties on a pay-per-use basis. Public clouds include Rackspace, Google Cloud Platform, and Microsoft Azure.
  3. Community clouds– they are used and share by a group (s) of people or organizations with a mutual interest e.g. the North Carolina Education Cloud (NCEdCloud).
  4. Hybrid clouds– these are called hybrid because it involves a merger between two or more clouds. For instance, if a large organization which hosts its core IT infrastructure on a private or community clouds wants to expand its capacity to meet a sudden surge in user demand, it can team up with at least a public cloud for that purpose. It will do so by leasing public cloud resources and hence the name, “hybrid clouds.” The mechanism through which that happens is called cloud bursting.
  5. Federated clouds– these are an emerging type of clouds consisting of only public clouds, only private clouds or both to provide end-users with seemingly unlimited computing utility service. These clouds enable high interoperability and compatibility between different cloud services through open APIs that allows cloud users to distribute services based on offerings from various vendors or transfer data easily across platforms. An example of federated clouds is one established among numerous datacenters owned by a single cloud provider.

Cloud Datacenters

What are cloud datacenters? They can be referred to as the power houses of cloud computing as they house several servers, communications, and storage systems needed for cloud computing. The servers, communications, and storage systems are co-located in the datacenters because of their similar physical security, environmental, and maintenance requirements. Hence, the consolidation of such resources help in ensuring their effective utilization. Multiple applications cloud providers can share server resources, thus, avoiding under-utilization and server stretch in datacenters.

The technology that makes consolidation and sharing better is called virtualization technology. It provides performance isolation among co-located applications. Consolidation is cost-efficient as it reduces capital and operational expenses, and lowers energy consumption. Two mainstream platforms are available for realizing virtualization today (hypervisor-based virtualization and container-based virtualization). Hypervisor-based virtualization e.g. Xen, KVM, and Hyper-V imitates a machine hardware and allows instances of the imitation (i.e. virtual machines, VMs) to run on a different physical machine managed by a specialized operating system called the hypervisor. The approach, however, is OS agnostic since the guest OS (OS installed in the VM) may be different from the host OS (OS running on the physical host of the VM).

Container-based visualization does not emulate hardware platform, but provides visualization at the OS-level to reduce performance and speed overhead of the hypervisor-based visualization. It allows multiple isolated Linux environments (containers) to share the base kernel of the host OS. Examples of container-based visualization platforms are LXC, Docker, and OpenVZ. Despite enjoying an increasing adoption, containers still cannot match VMs which remain to be the common unit of cloud deployments because of the technology’s maturity. VMs can be easily moved from one server to another to balance the load across the datacenter or merge workloads on fewer servers.

VMs are also easy-to-manage software-defined units and they facilitate the elasticity of the cloud. It is also possible to replicate them across servers (horizontal scaling) and their resource capacity (such as CPU cores) can be reduced or increased to address overload or underload situations (vertical scaling). Infrastructure as a Software (IaaS) datacenters face a challenge of resource allocation. The concern is how to optimally share or distribute computing, storage, and network resources among a set of VMs in a way that tries to equally meet service objectives of both service providers and cloud provider.

Software-Defined Infrastructures

There is a need for increased automation and programmability as the adoption of cloud computing for performing various roles grows. One such role is running mission-critical and performance-sensitive applications like analytics, mobile services, the Internet of Things (IoT), and machine-to-machine communications. It means that there is an increased demand for agility, performance, and energy efficiency. And, that is what has led to the recent trend towards Software-Defined Infrastructures (SDI).

To facilitate automation, several studies have applied autonomic computing techniques in different aspects of managing current clouds like resource allocation, rescheduling, and energy management. SDIs are anticipated to change the compute, storage, and network infrastructures to software-defined and vigorously programmable entities. But, what is a SDI? A simple definition could be; it is an infrastructure that is consistently transforming itself by properly exploiting heterogeneous capabilities and utilizing insights obtained from built-in deep monitoring to constantly honor consumer SLAs amid provider’s constraints such as cost and energy constraints. There are currently only a few SDI products or platforms available, but many of the technology’s aspects are still evolving. Even so, below are the key architectural components of SDIs:

  • Software-defined Compute (SDC)– it performs two roles; – (1) enhancing the programmability of existing virtualized compute resources like VMs, containers, and virtual CPUs and (2) leveraging specialized processing units e.g. GPUs (graphical processing units), FPGAs (field-programmable gate arrays), and other accelerators. It decouples the provision of heterogeneous compute resources from the existing hardware or OS so that it is based on identified or discovered workload needs.  
  • Software-defined Network (SDN)- its function is the separation of control and management functions of the network infrastructures away from the hardware to the server. It does so to improve performance isolation, security, programmability, and effectiveness. By means of virtualization, it allows network resources to be transformed to virtual devices (like links, end-points, & switches) that connect various virtual storage and compute instances.
  • Software-defined Storage- it functions to manage huge data volumes by separating the control and management functions from the data storage system. Such separation helps in reducing management complexity and lower the cost of infrastructure.

A SDI controller manages all SDI components by providing the control intelligence needed to meet workload requirements. It uses the classical MAPE loop to consistently monitor the current state of SDI entities.

Cloud Stakeholders and Their Roles

Cloud stakeholders are usually grouped into one of three roles depending on the service delivery models. The role of the cloud provider or IP (Infrastructure provider) ranges from infrastructure provision in IaaS, platforms and infrastructure provision in PaaS, to the provision of the whole cloud stack (infrastructure, platforms, and applications) in SaaS.

Cloud users or SP (Service Providers) are mostly found under the IaaS and PaaS model. They use the infrastructure and/or platform given by the cloud provider to host application services that are used the end-user. Interactions in terms of roles between the cloud stakeholders (cloud and service providers) are administered by an official document known as the Service Level Agreement (SLA). 

The SLA describes what quality of service is expected and the legal agreements. A characteristic SLA constitutes important elements like the service credits and service guarantees(outlines functional metrics e.g. response time, availability, and safety that a cloud provider needs to meet during the service guarantee period). A service credit is a sum credited to a customer or put in place towards a future payment when the IP cannot meet the service guarantees.

Conclusion

Cloud computing is here to stay with us. It’s what drives every IT operation. Most cloud providers know what their role in providing hosting platforms is and they will strive to maintain their offering. It’s my hope that this discussion has shed some light about cloud computing for you.

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Oct 4 2021
How to get date and time in Python

Python has a module called as datetime which gives the current date and time in Python. Datetime module comes with pre-built so we dont have to install it explicitly but we do need to import the module. datetime module provide some functions to get the current date as well as time. You can get complete information from the document website here. In this article, we will look at the some of the important functions and implement with examples. Let’s look at them.

date.today():
today() method of date class under datetime module returns a date object which contains the value of Today’s date.

Syntax: date.today()
Returns: Return the current local date.

Implementation of datetime

# Import the module datetime
import datetime as dt

# Returns the current local date using class date
today_date = dt.date.today()
print("Today's date: ", today_date)
# We can extract date, month and year separately too
print("Today's date: ", today_date.day,"-",today_date.month,"-",today_date.year)

To know what is inside datetime, we can use dir() function to get a list containing all attributes of a module.

import datetime
print(dir(datetime))

Output:

['MAXYEAR', 'MINYEAR', 'builtins', 'cached', 'doc', 'file', 'loader', 'name', 'package', 'spec', 'date', 'datetime', 'datetime_CAPI', 'sys', 'time', 'timedelta', 'timezone', 'tzinfo']

We have already seen the date class. Other commonly used classes are: time, datetime, timedelta

We can create object of Time class to represent time. example:

from datetime import time
import datetime as dt
from time import strftime

current_time = dt.datetime.now()
print("current_time =", current_time.time())
#change the format
print(dt.datetime.now().strftime('%Y-%m-%d %H:%M:%S'))

# time(hour, minute and second)
time1 = time(11, 34, 56)
print("Given time =", time1)

time2 = time(hour = 11, minute = 34, second = 56)
print("Given time  =", time2)

# time(hour, minute, second, microsecond)
time3 = time(11, 34, 56, 234566)
print("Given time  =", time3)
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Oct 2 2021
Speaker at ATAL online FDP on “The Internet of Things and Everything- IOT/IOE”

I am so pleased to share the news that I was one of the speakers at the ATAL Online Faculty Development Program, a 5-days course conducted by Chandigarh University and was Organized By Department of Electronics & Communication Engineering, Chandigarh University. The programme was accepted and approved by AICTE Training and Learning (ATAL) Academy cell.

The sessions were conducted by the team of eminent academicians and industry experts possessing in-depth knowledge in the area of Internet of Everything. Topis covered were:

  • Introduction to embedded systems, IOT and IOE
  • Internet of Everything v Internet of things
  • IOT Network and Protocols
  • IOT System architecture -Design and Development
  • IOT Programming and Simulator
  • Security and Privacies issues in IOT
  • Cloud deployment and its application in IOT
  • IOT/IOE in Healthcare applications
  • AI Powered IOT/IOE
  • Building a sample IOT application

I spoke on Day 5 Session 1. My topic was “IoT for Retail Management”.

  • I spoke about various ways Retail Industry is using the IoT to manage their store, customer experience, employee management and supply chain.
    Other speakers at the event were:


    In my next blog, I will write about the content I presented at the event. Stay tuned!

Other speakers at the event were:

In my next blog, I will write about the content I presented at the event. Stay tuned!

admin 0 Comments
Sep 22 2021
How classes and objects are used in Python

Python is said to be a pure object oriented programming language and almost everything you come across in Python is an object. A class can be defined as a user-defined type that, by having its own methods (functions) and property (variables), define what object will look like. An object is a single instance of a class. You can create many objects from the same class type.

Creating a class in Python
class keyword is used in Python to create a class, an example is shown below. We create a class named Books with a property named total_count:

class Books:
  total_count = 5

Creating an object
class is just a blueprint. In order to use the class, we need to create an object. In below example, lets create an object called learn_python and using this we will print the value of total_count:

class Books:
  total_count = 5
python_book = Books()
print(python_book.total_count)

The init() Function
Let’s look at an important member of the class. We are talking about init() function. Infact all classes have this function, which is always called an object of the class in being created. This function is called automatically so you dont have to specifically call this. We use the init() function to initialize values or properties that needs to be assigned to the object immediately when created. In the below example, we create a class Books and using the init() function, we have automatically assigning title and the cost to the object:

class Books:
  def __init__(self, title, cost):
    self.title = title
    self.cost = cost

python_book = Books("Learn and Practice Python Programming", 136)
print(python_book.title)
print(python_book.cost)

Object Functions
A class will also have object functions or methods. Functions that are defined in objects, belong to object (and not to the class). It means that the objects will use these functions and the result returned will be specific to the objects. These are characterised by self keyword as first parameter being passed. Let’s add a function to our class Books which will print the title of the book. This is called object function because it knows which objects are referencing and the title value is linked to that object only.
Example:

class Books:
  def __init__(self, title, cost):
    self.title = title
    self.cost = cost
  def gettitle(self):
      print("Title of the book is: "+self.title)

python_book = Books("Learn and Practice Python Programming", 136)
print(python_book.title)
print(python_book.cost)
python_book.gettitle()

The self parameter used in object functions is to show the reference to the current object associated to the class.
Please note, it does not have to be named self, we can use any name we like it but whatever name we choose, that has to be the first parameter of the object functions.

We will end our discussion here. We will develop a mini application using classes in next article.

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Sep 21 2021
Python 3.10 – what can we expect from it?

Image above shows how CASE statement can be implemented in Python, wait you cant make it work today but surely can after 4th October, that is after Python 3.10 is made available for all of us. In the 3.10 version, we will see some of the most fascinating features like structural pattern matching, parenthesized context managers, more typing, and improved error messages to make our life easier.

In 2020, Guido van Rossum, the creator of Python, committed the first documentation showing the new switch-statements, which have been named Structural Pattern Matching. Python is not using the switch keyword for its Structural Pattern Matching as other programming languages do, instead, it will be using match keywords. So it might be possible that we would refer to it as a Python match case statement instead of a Python switch case.

The new structural pattern matching will help us to match variables against one or even one of a set of possible values. This will no doubt be very powerful feature and will make it possible to write code for a variety of scenarios. One example is offcourse the code added as an image above. Lets look at another example:

Let’s try to use match case Statement and implement the weekday calculator as example:

def weekday(day):
    match day:
        case 1:
            return "Sunday"
        case 2:
            return "Monday"
        case 3:
            return "Tuesday"
        case 4:
            return "Wednesday"
        case 5:
            return "Thursday"
        case 6:
            return "Friday"
        case 7:
            return "Saturday"
        #wildcard case
         case _:
            return "Please Enter a Valid Day Number"

 print(weekday(1))   #Sunday
 print(weekday(4))  #Wednesday
 print(weekday(7))  #Saturday
 print(weekday(11)) #Please Enter a Valid Day Number

Impressed? There is more to come. Using, what is called as structural pattern matching, we can perform the same match-case logic even based on whether the structure of our comparison object matches a given pattern.

To demonstrate, lets take two dictionaries:

dict_a = {
    'id': 1,
    'meta': {
        'source': 'abc',
        'location': 'west'
    }
}

dict_b = {
    'id': 2,
    'source': 'def',
    'location': 'west'
}

 We could write a pattern to match dict_a like:

{
    'id': int,
    'meta': {'source': str,
             'location': str}
}

A pattern to match dict_b like:

 {    'id': int,
    'source': str,
    'location': str
}

We can now put both of these together in a match-case statement:

# loop through both dictionaries and a 'test'
for d in [dict_a, dict_b, 'test']:
   match d:
       case {'id': ident,
             'meta': {'source': source,
                      'location': loc}}:
           print(ident, source, loc)
       case {'id': ident,
             'source': source,
             'location': loc}:
           print(ident, source, loc)
       case _:
           print('no match')

Watch out for my next few articles in which I will cover:

  • Parenthesized context managers
  • More Python typing features
  • Display better error messages

Stay tuned. Do comment here if you liked this article.

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Sep 19 2021
Understanding the term Data Science?

Another article talking about the basic concept of machine learning and data science.

As the world has entered the time period of big data, so did the demand for data containers. Until 2010, it was the main threat and consideration for the corporate businesses. The primary focus was on developing a framework and data storage systems.
When is it going to happen? The secret sauce here is data science. Data Science can make all of the ideas that you see in Hollywood sci-fi movies a reality. The destiny of Artificial Intelligence is Data Science. As a result, it is essential to recognize what Data Science is and how it might benefit your company?


What is Data Science?
Data Science is a collection of tools, techniques, and deep learning fundamentals that aim to uncover hidden styles in original data. But how does this differ from what statistical methods have done for years? As shown in the preceding image, a Data Analyst typically explains what is happening on by tracing the data’s handling background.
A Data Analyst, on the other hand, not only performs exploratory analysis to glean insights from it, but also employs a variety of advanced machine learning techniques to predict the occurrence of a specific event in the future. A Data Scientist will examine the data from a variety of perspectives, including some that were previously unknown.


Do you need a data science certificate?
A certification on your resume is unlikely to help you land a job. Employers are interested in the skills you possess. A registration, by itself, tells an employer nothing about your abilities. It simply informs them that you researched a subject. Certifications, on the other hand, can be extremely valuable if they effectively teach you the skills you require.
Certification programmes and platforms can still be a great investment, but please remember that their value is in the skills they can instruct you. Employers will look at your skills, project portfolio, and transferable skills when they review your resume. A certificate is unlikely to sway their decision, so focus on developing the necessary skills and creating exciting projects.


Why is data science important?
Data science is essential in almost all aspects of business and techniques. For example, it offers data about consumers that enables businesses to create more effective marketing plans and targeted marketing in order to increase product sales. It aids in the management of financial risks, the detection of fraudulent purchases, and the prevention of equipment failure in production facilities and other industrial sites.
It aids in the prevention of cyber-attacks and other security threats in IT systems. Data science initiatives can improve operational management in the supply chains, product inventory levels, distribution channels, and customer service. On a more basic level, they point the way toward greater efficiency and lower costs.
Data science also allows enterprises to develop strategic initiatives based on an in-depth analysis of customer behavior, market trends, and competition. Without it, business owners risk missing out on possibilities and making bad choices.


Challenges in data science:
Due to the obvious advanced essence of the data analysis involved, data science is especially challenging. The massive amounts of data that are typically analyzed contribute to the complexity and lengthen the time it would take to execute tasks. Furthermore, data scientists regularly work with pools of big data that may encompass a mix of structured, unstructured, and semi-structured data, confounding the analytics platform even further.
Removing bias in data sets and advanced analytics is one of the most difficult challenges. This includes both problems with the original data and problems that data scientists unconsciously build into algorithms and prescriptive models. If such biases are not identified, they can skew analytics results, resulting in flawed findings and poor business decisions. Worse, they can have a negative impact on specific groups of people, as in the particular instance of ethnic partiality in AI technologies.


Why businesses need Data Science?
We’ve progressed from working in small frames of structured data to huge mining areas of unorganized and semi-structured info coming in from a variety of sources. When it tends to come to having to process this huge pool of unstructured information, conventional Business Intelligence tools fall short.
As a result, Data Science includes more sophisticated tools for working with large volumes of data from various sources such as economic logs, multimedia content, advertising forms, detectors and tools, and text files.


What does a data scientist really do?
Algorithms are created and used by data scientists to analyses data. In general, this process entails using and developing machine learning tools and personalized data goods to interest of business and clients in interpreting data in a useful manner.
They also aid in the breakdown of data-driven reports in order to gain a better understanding of the clients. Overall, data scientists are involved in every stage of data processing, from processing it to creating and maintaining facilities, testing, and analyzing it for real-world applications.

All these are more information are available in the book “Data Science and Machine Learning with Python” by Swapnil Saurav. Available on Amazon here

You can find more articles by the author on the topic here.

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Sep 19 2021
What is artificial intelligence?

In continuation to our earlier discussions, and talking about basic terms first before we get into higher level of discussions, in this article I talk about what is AI from my perspective.

Artificial intelligence (AI) is a subfield of computer science concerned with the simulated world of human intelligence in machines. Another way to think about AI is as a quest to create machines that can perform specific tasks that require human intelligence. AI has the potential to free us from monotonous tasks, make quick and accurate decisions, act as a catalyst for accelerating discoveries and inventions, and even complete dangerous processes in extreme environments. There is no magic in this place.
It’s a group of intelligent algorithms attempting to mimic human intellect. AI employs techniques such as machine learning and deep learning to learn from data and improve on a regular basis. And AI is more than just a subfield of computer science. Rather, it incorporates elements of statistics, mathematics, intelligent systems, neuroscience, cybernetics, psychology, philology, philosophy, economy, and other disciplines.


Different types of AI:
At a very high level, artificial intelligence can be split into two broad types:

Narrow AI:
Narrow AI is what we see everywhere us in computing systems. It refers to expert machines that have been taught and learned how to perform specific tasks without being pattern recognition to do so. This class of machine intellect is visible in the Siri digital assistant on the Apple iPhone’s communication – language acknowledgment, visual acuity systems on ego cars, and recommendation engines that accurate recommendations you might like predicated on what you’ve purchased in the history. These processes, unlike humans, can only learn or be taught how to perform specific tasks, which is why they are referred to as narrow AI.

General AI:
General AI is very unique and is the a kind of flexible intellectual ability found in people, a flexible form of intelligence smart enough to learn how to hold out massively various tasks, such as hairdressing, building spreadsheet applications, or reasoning about a wide range of topics based on its collective experience. This is the type of AI seen in films, such as HAL in 2001 or Skynet in The Terminator, but it does not exist today – and AI specialists are divided on the how shortly it would become a actuality.

How Artificial Intelligence (AI) Works?
Constructing an AI system is a meticulous process that involves reverse-engineering human characteristics and abilities in a machine and then using its supercomputing prowess to outperform what we are competent of. To comprehend How Artificial Intelligence Works, one must first delve into the various subsites of Ai Technology and comprehend how those domains can be applied to various areas of business. You can also enroll in an artificial intelligence course to develop a full understanding.

What is the Purpose of Artificial Intelligence?
The goal of Artificial Intelligence is to augment human ability and assist us in making complex decisions with far-reaching consequences. From a technical standpoint, that is the answer. From a philosophical standpoint, Artificial Intelligence is the ability to help human’s live more good lives free of hard labor, as well as to assist in managing the complex web of interconnected individual people, businesses, states, and nations to function in a way that benefits all of civilization.
Currently, the objective of Artificial Intelligence is communicated by all the various techniques that we’ve created over the last long time – to optimize human effort and assist us in making important choices. Artificial intelligence has also been dubbed our “Final Discovery,” a conception that would create ground-breaking tools that would tremendously change how we live our lives, ideally eradicating conflict, unfairness, and human misery.

Where is Artificial Intelligence (AI) Used?
AI is used in a variety of domains to provide insights into user behavior and make suggestions based on data. Google’s forecasting search algorithm, for example, used previous user data to determine what a user would type next in the search field. Netflix uses past user data to suggest what movie a user should watch next, keeping the user on the forum and increasing watch time. Facebook uses past user data to instantly suggest tags for your friends predicated on their facial characteristics in their images. AI is being used by large organizations all over the world to make the lives of end users easier.
AI could be used to rapidly and conveniently complete tasks that humans find tedious, such as trying to sort through huge amounts of data and recognizing styles. It also enables machines to become cleverer in ways that would make them more convenient, easier to use, and competent of accomplishing more than ever before. This applies to our personal devices and larger industry technologies, as well as virtually everything between.

All these are more information are available in the book “Data Science and Machine Learning with Python” by Swapnil Saurav. Available on Amazon here

You can find more articles by the author on the topic here.

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Sep 18 2021
Terms and Conditions

TERMS OF SERVICES

PLEASE READ THIS TERMS OF SERVICE AGREEMENT CAREFULLY, AS IT CONTAINS IMPORTANT INFORMATION REGARDING YOUR LEGAL RIGHTS AND REMEDIES.Last Revised: 2021-09-18 04:37:26

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This Site and the Services are available only to Users who can form legally binding contracts under applicable law. By using this Site or the Services, you represent and warrant that you are (i) at least eighteen (18) years of age, (ii) otherwise recognized as being able to form legally binding contracts under applicable law, and (iii) are not a person barred from purchasing or receiving the Services found under the laws of the India or other applicable jurisdiction.If you are entering into this Agreement on behalf of a company or any corporate entity, you represent and warrant that you have the legal authority to bind such corporate entity to the terms and conditions contained in this Agreement, in which case the terms “you”, “your”, “User” or “customer” shall refer to such corporate entity. If, after your electronic acceptance of this Agreement, Company finds that you do not have the legal authority to bind such corporate entity, you will be personally responsible for the obligations contained in this Agreement.

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You will not:

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  • copy or duplicate this Terms of Services agreement, which was created with the help of the TermsHub Terms and Conditions Generator,
  • modify or alter any part of this Site or any of its related technologies,
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In addition to the general rules above, the provisions in this Section apply specifically to your use of Companies Content posted to Site. Companies Content on this Site, including without limitation the text, software, scripts, source code, API, graphics, photos, sounds, music, videos and interactive features and the trademarks, service marks and logos contained therein (“Companies Content”), are owned by or licensed to swapnil.pw in perpetuity, and are subject to copyright, trademark, and/or patent protection.Companies Content is provided to you “as is”, “as available” and “with all faults” for your information and personal, non-commercial use only and may not be downloaded, copied, reproduced, distributed, transmitted, broadcast, displayed, sold, licensed, or otherwise exploited for any purposes whatsoever without the express prior written consent of Company. No right or license under any copyright, trademark, patent, or other proprietary right or license is granted by this Agreement.

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Some of the features of this Site may allow Users to view, post, publish, share, or manage (a) ideas, opinions, recommendations, or advice (“User Submissions”), or (b) literary, artistic, musical, or other content, including but not limited to photos and videos (together with User Submissions, “User Content”). By posting or publishing User Content to this Site, you represent and warrant to Company that (i) you have all necessary rights to distribute User Content via this Site or via the Services, either because you are the author of the User Content and have the right to distribute the same, or because you have the appropriate distribution rights, licenses, consents, and/or permissions to use, in writing, from the copyright or other owner of the User Content, and (ii) the User Content does not violate the rights of any third party.You agree not to circumvent, disable or otherwise interfere with the security-related features of this Site (including without limitation those features that prevent or restrict use or copying of any Companies Content or User Content) or enforce limitations on the use of this Site, the Companies Content or the User Content therein.

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The provisions in this Section apply specifically to Companies use of User Content posted to Site.You shall be solely responsible for any and all of your User Content or User Content that is submitted by you, and the consequences of, and requirements for, distributing it.With Respect to User Submissions, you acknowledge and agree that:

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Company shall own exclusive rights (including all intellectual property and other proprietary rights) to any User Submissions posted to this Site, and shall be entitled to the unrestricted use and dissemination of any User Submissions posted to this Site for any purpose, commercial or otherwise, without acknowledgment or compensation to you or to anyone else.With Respect to User Content, by posting or publishing User Content to this Site, you authorize Company to use the intellectual property and other proprietary rights in and to your User Content to enable inclusion and use of the User Content in the manner contemplated by this Site and this Agreement.You hereby grant Company a worldwide, non-exclusive, royalty-free, sublicensable, and transferable license to use, reproduce, distribute, prepare derivative works of, combine with other works, display, and perform your User Content in connection with this Site, including without limitation for promoting and redistributing all or part of this Site in any media formats and through any media channels without restrictions of any kind and without payment or other consideration of any kind, or permission or notification, to you or any third party. You also hereby grant each User of this Site a non-exclusive license to access your User Content through this Site, and to use, reproduce, distribute, prepare derivative works of, combine with other works, display, and perform your User Content as permitted through the functionality of this Site and under this Agreement.The above licenses granted by you in your User Content terminate within a commercially reasonable time after you remove or delete your User Content from this Site. You understand and agree, however, that Company may retain (but not distribute, display, or perform) server copies of your User Content that have been removed or deleted. The above licenses granted by you in your User Content are perpetual and irrevocable.Company generally does not pre-screen User Content but reserves the right (but undertakes no duty) to do so and decide whether any item of User Content is appropriate and/or complies with this Agreement. Company may remove any item of User Content if it violating this Agreement, at any time and without prior notice.

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This Site may contain links to third-party websites that are not owned or controlled by Company. Company assumes no responsibility for the content, terms and conditions, privacy policies, or practices of any third-party websites. In addition, Company does not censor or edit the content of any third-party websites. By using this Site you expressly release Company from any and all liability arising from your use of any third-party website. Accordingly, Company encourages you to be aware when you leave this Site and to review the terms and conditions, privacy policies, and other governing documents of each other website that you may visit.

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Nothing in this Agreement shall be deemed to confer any third-party rights or benefits.

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Any controversy or claim arising out of or relating to these Terms of Services will be settled by binding arbitration. Any such controversy or claim must be arbitrated on an individual basis, and must not be consolidated in any arbitration with any claim or controversy of any other party. The arbitration must be conducted in India, Telangana, and judgment on the arbitration award may be entered into any court having jurisdiction thereof.

19. TITLES AND HEADINGS

The titles and headings of this Agreement are for convenience and ease of reference only and shall not be utilized in any way to construe or interpret the agreement of the parties as otherwise set forth herein.

20. SEVERABILITY

Each covenant and agreement in this Agreement shall be construed for all purposes to be a separate and independent covenant or agreement. If a court of competent jurisdiction holds any provision (or portion of a provision) of this Agreement to be illegal, invalid, or otherwise unenforceable, the remaining provisions (or portions of provisions) of this Agreement shall not be affected thereby and shall be found to be valid and enforceable to the fullest extent permitted by law.

21. CONTACT INFORMATION

If you have any questions about this Agreement, please contact us by email or regular mail at the following address:swapnil.pw

Hyderabad

India

callswapnil@gmail.com

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