A class is a code template for creating objects. Objects have member variables and have behaviour associated with them. In python a class is created by the keyword class.
An object is created using the constructor of the class. This object will then be called the instance of the class.
OOPS concepts are one of the most important concepts in high level languages. Here in this PPT we will learn more about Object oriented approach in python programming which includes details related to classes and objects, inheritance, dat abstraction, polymorphism and many more with examples and code.
OOPS concepts are one of the most important concepts in high level languages. Here in this PPT we will learn more about Object oriented approach in python programming which includes details related to classes and objects, inheritance, dat abstraction, polymorphism and many more with examples and code.
Command-line arguments are given after the name of the program in command-line shell of Operating Systems.
To pass command line arguments, we typically define main() with two arguments : first argument is the number of command line arguments and second is list of command-line arguments.
All data values in Python are encapsulated in relevant object classes. Everything in Python is an object and every object has an identity, a type, and a value. Like another object-oriented language such as Java or C++, there are several data types which are built into Python. Extension modules which are written in C, Java, or other languages can define additional types.
To determine a variable's type in Python you can use the type() function. The value of some objects can be changed. Objects whose value can be changed are called mutable and objects whose value is unchangeable (once they are created) are called immutable.
What is Multithreading In Python | Python Multithreading Tutorial | EdurekaEdureka!
YouTube Link: https://youtu.be/JnFfp81VbOs
** Python Certification Training: https://www.edureka.co/python **
This Edureka PPT on 'Multithreading in Python'' will help you understand the concept of threading in python. Below are the topics covered in this live PPT:
What is multitasking in Python?
Types of multitasking
What is a thread?
How to achieve multithreading in Python?
When to use multithreading?
How to create threads in Python?
Advantages of multithreading
Python Tutorial Playlist: https://goo.gl/WsBpKe
Blog Series: http://bit.ly/2sqmP4s
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PYTHON-Chapter 3-Classes and Object-oriented Programming: MAULIK BORSANIYAMaulik Borsaniya
Classes and Object-oriented Programming:
Classes: Creating a Class, The Self Variable, Constructor, Types of Variables, Namespaces, Types of Methods (Instance Methods, Class Methods, Static Methods), Passing Members of One Class to Another Class, Inner Classes
Inheritance and Polymorphism: Constructors in Inheritance, Overriding Super Class Constructors and Methods, The super() Method, Types of Inheritance, Single Inheritance, Multiple Inheritance, Method Resolution Order (MRO), Polymorphism, Duck Typing Philosophy of Python, Operator Overloading, Method Overloading, Method Overriding
Abstract Classes and Interfaces: Abstract Method and Abstract Class, Interfaces in Python, Abstract Classes vs. Interfaces,
Inheritance and Polymorphism in Python. Inheritance is a mechanism which allows us to create a new class – known as child class – that is based upon an existing class – the parent class, by adding new attributes and methods on top of the existing class.
Command-line arguments are given after the name of the program in command-line shell of Operating Systems.
To pass command line arguments, we typically define main() with two arguments : first argument is the number of command line arguments and second is list of command-line arguments.
All data values in Python are encapsulated in relevant object classes. Everything in Python is an object and every object has an identity, a type, and a value. Like another object-oriented language such as Java or C++, there are several data types which are built into Python. Extension modules which are written in C, Java, or other languages can define additional types.
To determine a variable's type in Python you can use the type() function. The value of some objects can be changed. Objects whose value can be changed are called mutable and objects whose value is unchangeable (once they are created) are called immutable.
What is Multithreading In Python | Python Multithreading Tutorial | EdurekaEdureka!
YouTube Link: https://youtu.be/JnFfp81VbOs
** Python Certification Training: https://www.edureka.co/python **
This Edureka PPT on 'Multithreading in Python'' will help you understand the concept of threading in python. Below are the topics covered in this live PPT:
What is multitasking in Python?
Types of multitasking
What is a thread?
How to achieve multithreading in Python?
When to use multithreading?
How to create threads in Python?
Advantages of multithreading
Python Tutorial Playlist: https://goo.gl/WsBpKe
Blog Series: http://bit.ly/2sqmP4s
Follow us to never miss an update in the future.
YouTube: https://www.youtube.com/user/edurekaIN
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PYTHON-Chapter 3-Classes and Object-oriented Programming: MAULIK BORSANIYAMaulik Borsaniya
Classes and Object-oriented Programming:
Classes: Creating a Class, The Self Variable, Constructor, Types of Variables, Namespaces, Types of Methods (Instance Methods, Class Methods, Static Methods), Passing Members of One Class to Another Class, Inner Classes
Inheritance and Polymorphism: Constructors in Inheritance, Overriding Super Class Constructors and Methods, The super() Method, Types of Inheritance, Single Inheritance, Multiple Inheritance, Method Resolution Order (MRO), Polymorphism, Duck Typing Philosophy of Python, Operator Overloading, Method Overloading, Method Overriding
Abstract Classes and Interfaces: Abstract Method and Abstract Class, Interfaces in Python, Abstract Classes vs. Interfaces,
Inheritance and Polymorphism in Python. Inheritance is a mechanism which allows us to create a new class – known as child class – that is based upon an existing class – the parent class, by adding new attributes and methods on top of the existing class.
در این جلسه به بررسی بحث برنامه نویسی شی گرا و کلاس ها در پایتون پرداختیم
PySec101 Fall 2013 J7E1 By Mohammad Reza Kamalifard
Talk About:
Object oriented programming and Classes in Python
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Search and Society: Reimagining Information Access for Radical FuturesBhaskar Mitra
The field of Information retrieval (IR) is currently undergoing a transformative shift, at least partly due to the emerging applications of generative AI to information access. In this talk, we will deliberate on the sociotechnical implications of generative AI for information access. We will argue that there is both a critical necessity and an exciting opportunity for the IR community to re-center our research agendas on societal needs while dismantling the artificial separation between the work on fairness, accountability, transparency, and ethics in IR and the rest of IR research. Instead of adopting a reactionary strategy of trying to mitigate potential social harms from emerging technologies, the community should aim to proactively set the research agenda for the kinds of systems we should build inspired by diverse explicitly stated sociotechnical imaginaries. The sociotechnical imaginaries that underpin the design and development of information access technologies needs to be explicitly articulated, and we need to develop theories of change in context of these diverse perspectives. Our guiding future imaginaries must be informed by other academic fields, such as democratic theory and critical theory, and should be co-developed with social science scholars, legal scholars, civil rights and social justice activists, and artists, among others.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Let's dive deeper into the world of ODC! Ricardo Alves (OutSystems) will join us to tell all about the new Data Fabric. After that, Sezen de Bruijn (OutSystems) will get into the details on how to best design a sturdy architecture within ODC.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
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Gopinath Rebala
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Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
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3. Creation of Class
General Format
Class is a model or plan to create the objects
Class contains,
Attributes: Represented by variables
Actions : Performed on methods
Syntax of defining the class,
Syntax Example
class Classname(object):
"""docstrings"""
Attributes
def __init__(self):
def method1():
def method2():
class Student:
"""The below block defines attributes"""
def __init__(self):
self.name = "Ram"
self.age = 21
self.marks = 89.75
"""The below block defines a method"""
def putdata(self):
print("Name: ", self.name)
print("Age: ", self.age)
print("Marks: ", self.marks)
4. Creation of Class
Program
#To define the Student calss and create an Object to it.
#Class Definition
class Student:
#Special method called constructor
def __init__(self):
self.name = "Ram"
self.age = 21
self.marks = 75.90
#This is an instance method
def putdata(self):
print("Name: ", self.name)
print("Age: ", self.age)
print("Marks: ", self.marks)
#Create an instance to the student class
s = Student()
#Call the method using an Object
s.putdata()
6. The Self Variable
‘Self’ is the default variable that contains the memory address of the instance of the
current class
s1 = Student() s1 contains the memory address of the instance
This memory address is internally and by default passed to
‘self’ variable
Usage-1:
def __init__(self):
The ‘self’ variable is used as first parameter in the
constructor
Usage-2:
def putdata(self):
The ‘self’ variable is used as first parameter in the
instance methods
8. Constructor
Constructor with NO parameter
Constructors are used to create and initialize the 'Instance Variables'
Constructor will be called only once i.e at the time of creating the objects
s = Student()
Example def __init__(self):
self.name = "Ram"
self.marks = 99
9. Constructor
Constructor with parameter
Example def __init__(self, n = "", m = 0):
self.name = n
self.marks = m
Instance-1 s = Student()
Will initialize the instance variables with default parameters
Instance-2 s = Student("Ram", 99)
Will initialize the instance variables with parameters passed
10. Constructor
Program
#To create Student class with a constructor having more than one parameter
class Student:
#Constructor definition
def __init__(self, n = "", m = 0):
self.name = n
self.marks = m
#Instance method
def putdata(self):
print("Name: ", self.name)
print("Marks: ", self.marks)
#Constructor called without any parameters
s = Student()
s.putdata()
#Constructor called with parameters
s = Student("Ram", 99)
s.putdata()
13. Types Of Variables
Instance Variables
Variables whose separate copy is created for every instance/object
These are defined and init using the constructor with 'self' parameter
Accessing the instance variables from outside the class,
instancename.variable
class Sample:
def __init__(self):
self.x = 10
def modify(self):
self.x += 1
#Create an objects
s1 = Sample()
s2 = Sample()
print("s1.x: ", s1.x)
print("s2.x: ", s2.x)
s1.modify()
print("s1.x: ", s1.x)
print("s2.x: ", s2.x)
14. Types Of Variables
Class Variables
Single copy is created for all instances
Accessing class vars are possible only by 'class methods'
Accessing class vars from outside the class,
classname.variable
class Sample:
#Define class var here
x = 10
@classmethod
def modify(cls):
cls.x += 1
#Create an objects
s1 = Sample()
s2 = Sample()
print("s1.x: ", s1.x)
print("s2.x: ", s2.x)
s1.modify()
print("s1.x: ", s1.x)
print("s2.x: ", s2.x)
16. Namespaces
Introduction
Namespace represents the memory block where names are mapped/linked to objects
Types:
Class namespace
- The names are mapped to class variables
Instance namespace
- The names are mapped to instance variables
17. Namespaces
Class Namespace
#To understand class namespace
#Create the class
class Student:
#Create class var
n = 10
#Access class var in class namespace
print(Student.n)
#Modify in class namespace
Student.n += 1
#Access class var in class namespace
print(Student.n)
#Access class var in all instances
s1 = Student()
s2 = Student()
#Access class var in instance namespace
print("s1.n: ", s1.n)
print("s2.n: ", s2.n)
10n
Class Namespace
10n 10n
Instance NamespaceInstance Namespace
11n
Class Namespace
11n 11n
Instance NamespaceInstance Namespace
Before modifyng class variable ‘n’
After modifyng class variable ‘n’
If class vars are modified in class namespace, then it reflects to all instances
18. Namespaces
Instance Namespace
#To understand class namespace
#Create the class
class Student:
#Create class var
n = 10
s1 = Student()
s2 = Student()
#Modify the class var in instance namespace
s1.n += 1
#Access class var in instance namespace
print("s1.n: ", s1.n)
print("s2.n: ", s2.n)
10n
Class Namespace
10n 10n
Instance NamespaceInstance Namespace
10n
Class Namespace
11n 10n
Instance NamespaceInstance Namespace
Before modifyng class variable ‘n’
After modifyng class variable ‘n’
If class vars are modified in instance namespace, then it reflects only to
that instance
21. Types of Methods
Instance Methods
●
Acts upon the instance variables of that class
●
Invoked by instance_name.method_name()
#To understanf the instance methods
class Student:
#Constructor definition
def __init__(self, n = "", m = 0):
self.name = n
self.marks = m
#Instance method
def putdata(self):
print("Name: ", self.name)
print("Marks: ", self.marks)
#Constructor called without any parameters
s = Student()
s.putdata()
#Constructor called with parameters
s = Student("Ram", 99)
s.putdata()
22. Types of Methods
Instance Methods: Accessor + Mutator
#To understand accessor and mutator
#Create the class
class Student:
#Define mutator
def setName(self, name):
self.name = name
#Define accessor
def getName(self):
return self.name
#Create an objects
s = Student()
#Set the name
s.setName("Ram")
#Print the name
print("Name: ", s.getName())
Accessor Mutator
● Methods just reads the instance variables,
will not modify it
● Generally written in the form: getXXXX()
● Also called getter methods
● Not only reads the data but also modifies
it
● Generally wriiten in the form: setXXXX()
● Also called setter methods
23. Types of Methods
Class Methods
#To understand the class methods
class Bird:
#Define the class var here
wings = 2
#Define the class method
@classmethod
def fly(cls, name):
print("{} flies with {} wings" . format(name, cls.wings))
#Call
Bird.fly("Sparrow")
Bird.fly("Pigeon")
● This methods acts on class level
● Acts on class variables only
● Written using @classmethod decorator
● First param is 'cls', followed by any params
● Accessed by classname.method()
24. Types of Methods
Static Methods
#To Understand static method
class Sample:
#Define class vars
n = 0
#Define the constructor
def __init__(self):
Sample.n = Sample.n + 1
#Define the static method
@staticmethod
def putdata():
print("No. of instances created: ", Sample.n)
#Create 3 objects
s1 = Sample()
s2 = Sample()
s3 = Sample()
#Class static method
Sample.putdata()
● Needed, when the processing is at the class level but we need not involve the class or
instances
● Examples:
- Setting the environmental variables
- Counting the number of instances of the class
● Static methods are written using the decorator @staticmethod
● Static methods are called in the form classname.method()
26. Passing Members
● It is possible to pass the members(attributes / methods) of one class to another
● Example:
e = Emp()
● After creating the instance, pass this to another class 'Myclass'
● Myclass.mymethod(e)
- mymethod is static
27. Passing Members
Example
#To understand how members of one class can be passed to another
#Define the class
class Emp:
def __init__(self, name, salary):
self.name = name
self.salary = salary
def putdata(self):
print("Name: ", self.name)
print("Salary: ", self.salary)
#Create Object
e = Emp("Ram", 20000)
#Call static method of Myclass and pass e
Myclass.mymethod(e)
#Define another class
class Myclass:
@staticmethod
def mymethod(e):
e.salary += 1000
e.putdata()
30. Inner Class
Introduction
● Creating class B inside Class A is called nested class or Inner class
● Example:
Person's Data like,
- Name: Single value
- Age: Single Value
- DoB: Multiple values, hence separate class is needed
31. Inner Class
Program: Version-1
#To understand inner class
class Person:
def __init__(self):
self.name = "Ram"
self.db = self.Dob()
def display(self):
print("Name: ", self.name)
#Define an inner class
class Dob:
def __init__(self):
self.dd = 10
self.mm = 2
self.yy = 2002
def display(self):
print("DoB: {}/{}/{}" . format(self.dd,
self.mm, self.yy))
#Creating Object
p = Person()
p.display()
#Create inner class object
i = p.db
i.display()
32. Inner Class
Program: Version-2
#To understand inner class
class Person:
def __init__(self):
self.name = "Ram"
self.db = self.Dob()
def display(self):
print("Name: ", self.name)
#Define an inner class
class Dob:
def __init__(self):
self.dd = 10
self.mm = 2
self.yy = 2002
def display(self):
print("DoB: {}/{}/{}" . format(self.dd,
self.mm, self.yy))
#Creating Object
p = Person()
p.display()
#Create inner class object
i = Person().Dob()
i.display()