The document defines and provides examples of polymorphism in object-oriented programming. It discusses two types of polymorphism: static and dynamic. Static polymorphism is resolved at compile-time through function overloading and operator overloading, while dynamic polymorphism uses virtual functions and is resolved at run-time. Virtual functions, pure virtual functions, and abstract classes are also explained as key aspects of implementing dynamic polymorphism.
This document provides an overview of object-oriented programming (OOP) concepts like objects, classes, abstraction, encapsulation, inheritance, and polymorphism. It also discusses OOP principles and how they are implemented in C++. Key points include: OOP aims to model real-world entities and their relationships via objects and classes; classes act as blueprints that define objects; abstraction hides unnecessary details; encapsulation bundles related data and functions; inheritance allows code reusability; and polymorphism allows one interface to work with multiple forms. The document also contrasts compile-time vs. runtime polymorphism.
This document summarizes Week 3 of a Python programming course. It discusses introspection, which allows code to examine and manipulate other code as objects. It covers optional and named function arguments, built-in functions like type and str, and filtering lists with comprehensions. It also explains lambda functions and how and and or work in Python.
This document provides an overview of pointers, polymorphism, inheritance, and other object-oriented programming concepts in C++. It defines pointers and describes how they store memory addresses. It explains runtime and compile-time polymorphism using method overriding and overloading. Inheritance hierarchies like single, multiple, and multilevel inheritance are covered. Virtual functions and base classes are defined as ways to implement polymorphism. Abstract classes with pure virtual functions are introduced.
This document discusses polymorphism in C++. It defines polymorphism as objects being able to take on multiple forms. It discusses two types of polymorphism in C++ - compile-time polymorphism achieved through function overloading and operator overloading, and run-time polymorphism achieved through virtual functions and function overriding. It provides examples of each type of polymorphism, demonstrating how functions are called based on the object type at compile-time vs. run-time. It also discusses rules and syntax for operator overloading, virtual functions, and runtime polymorphism using references and data members.
Functions in Python are defined using the 'def' keyword followed by the function name and arguments. Functions return values using the 'return' statement and do not declare argument or return types. Python allows functions to be passed as arguments to other functions or used anonymously without naming. Python is popular for scientific programming due to its easy syntax, built-in data types, ability to run on many systems, large library of scientific packages, large user community, and use in universities.
Python supports object-oriented programming through classes, objects, and related concepts like inheritance, polymorphism, and encapsulation. A class acts as a blueprint to create object instances. Objects contain data fields and methods. Inheritance allows classes to inherit attributes and behaviors from parent classes. Polymorphism enables the same interface to work with objects of different types. Encapsulation helps protect data by restricting access.
This document provides an overview of polymorphism in Java, including the two types: compile-time polymorphism and run-time polymorphism. Compile-time polymorphism is demonstrated through method overloading, where a method can behave differently based on the parameters passed. Run-time polymorphism is shown via method overriding, where a child class can provide its own implementation of a method defined in the parent class, and the JVM determines which version to call based on the object. The document also lists some advantages of polymorphism such as cleaner code, ease of implementation, alignment with real-world concepts, reusability, and extensibility.
Python presentation of Government Engineering College Aurangabad, BiharUttamKumar617567
This document provides an overview of Python programming for an internship project. It covers the history and origins of Python, its key features like being open source, easy to code in, and object oriented. It also discusses Python concepts like variables, data types, operators, decision making, loops, functions, lists, tuples, object oriented programming, and taking screenshots. The document serves to introduce the Python language and common elements to someone new to programming in Python.
This document provides an introduction and overview of the Python programming language. It discusses what Python is, how it can be used for tasks like web development, data analysis, and scientific computing. It also covers how to get started with Python, including installing it and using basic features like variables, functions, modules, and packages. Examples are provided for common Python concepts like lists, dictionaries, and working with CSV files. MongoDB and the PyMongo module for interacting with MongoDB databases from Python are also briefly introduced.
This document covers polymorphism and operator overloading in C++. It discusses static and dynamic polymorphism, including function overloading, overriding, and virtual functions. It explains operator overloading concepts like overloading unary and binary operators. It also covers type conversion, both implicit and explicit, and keywords like explicit and mutable. The document provides examples of operator overloading, function overloading and overriding, and using virtual functions.
This document defines polymorphism and describes its two types - compile-time and run-time polymorphism. Compile-time polymorphism is demonstrated through method overloading examples, while run-time polymorphism is demonstrated through method overriding examples. The key advantages of polymorphism are listed as code cleanliness, ease of implementation, alignment with real world scenarios, overloaded constructors, and reusability/extensibility.
This document discusses polymorphism in C++. Polymorphism means an operator or function can take on multiple forms. C++ supports two types of polymorphism: compile-time and runtime. Compile-time polymorphism, also called static binding, includes function overloading and operator overloading where the version to call is determined at compile time based on arguments. Runtime polymorphism, also called dynamic binding, uses virtual functions where the target object and method are not known until runtime.
This document discusses the different types of polymorphism in C++, including compile-time and run-time polymorphism. Compile-time polymorphism is achieved through function overloading and operator overloading, while run-time polymorphism uses virtual functions and function overriding. Virtual functions allow for late binding at runtime and can be overridden in derived classes to change the behavior of base class functions depending on the object type.
Java and Python are compared on various aspects such as verbosity, object orientation, and execution model.
Python is found to be more concise and readable than Java for many common tasks like file I/O and logical expressions. However, Java's static typing enables safer refactoring. Both support inheritance but Python allows multiple inheritance and "duck typing".
The execution model differs as well - in Python, code is executed as it is loaded while Java separates loading, initialization and execution. This makes features like monkey patching possible in Python.
In the end, the developer is more important than the language. While each has strengths, the presenter currently prefers Python for its pragmatism and conciseness.
This document provides an introduction to object-oriented programming (OOP) concepts. It defines OOP as a design philosophy that groups everything as self-sustainable objects. The key OOP concepts discussed are objects, classes, encapsulation, abstraction, inheritance, polymorphism, method overloading, method overriding, and access modifiers. Objects are instances of classes that can perform related activities, while classes are blueprints that describe objects. Encapsulation hides implementation details within classes, and abstraction focuses on what objects are rather than how they are implemented.
The document discusses various topics in Objective-C including variables, data types, categories, protocols, and composite objects. It provides code examples to illustrate initializing objects, variable scope, enumerated data types, typedefs, data type conversion, categories, class extensions, protocols, delegates, and composite objects in Objective-C and compares some of these concepts to Java.
Python is an interpreted, object-oriented programming language that uses indentation to identify blocks of code. It is dynamically typed and strongly typed, with objects determining types at runtime rather than requiring explicit type declaration. Common data types include mutable types like lists and dictionaries as well as immutable types like strings and tuples.
Polymorphism.Difference between Inheritance & Polymorphismhuzaifaakram12
Polymorphism in Object-Oriented Programming (OOP) allows objects of different classes to be treated as objects of a common superclass. It enables a single interface to represent different underlying forms (data types). There are two main types of polymorphism:
Compile-time polymorphism (static binding): Achieved through method overloading and operator overloading.
Runtime polymorphism (dynamic binding): Achieved through method overriding, where a subclass provides a specific implementation of a method already defined in its superclass.
Polymorphism topic power point presentation li.pptxMalligaarjunanN
Polymorphism exists widely in Python. Operators like addition can work with different data types like integers, strings, lists, tuples, and dictionaries by supporting polymorphic "add" operations for each type. Methods like repr() also demonstrate polymorphism by converting data to strings in type-appropriate ways, such as converting an integer to its string representation. While Python supports advanced OOP features like operator overloading and multiple inheritance, it does not enforce strict encapsulation with private and public access modifiers, preferring simple syntax instead.
Friend functions allow non-member functions to access private and protected members of a class. Inline functions avoid function call overhead by copying the code into the calling function. The this pointer is an implicit parameter that provides access to the object from within member functions. Static members exist only once per class rather than for each object. Inheritance allows classes to inherit attributes and behaviors from other classes in a hierarchy. Polymorphism allows functions to take different implementations based on the runtime type of an object. Encapsulation binds data and functions that operate on that data together within a class to hide implementation details.
The document discusses Python interview questions and answers related to Python fundamentals like data types, variables, functions, objects and classes. Some key points include:
- Python is an interpreted, interactive and object-oriented programming language. It uses indentation to identify code blocks rather than brackets.
- Python supports dynamic typing where the type is determined at runtime. It is strongly typed meaning operations inappropriate for a type will fail with an exception.
- Common data types include lists (mutable), tuples (immutable), dictionaries, strings and numbers.
- Functions use def, parameters are passed by reference, and variables can be local or global scope.
- Classes use inheritance, polymorphism and encapsulation to create
This document provides an overview of polymorphism in Java, including the two types: compile-time polymorphism and run-time polymorphism. Compile-time polymorphism is demonstrated through method overloading, where a method can behave differently based on the parameters passed. Run-time polymorphism is shown via method overriding, where a child class can provide its own implementation of a method defined in the parent class, and the JVM determines which version to call based on the object. The document also lists some advantages of polymorphism such as cleaner code, ease of implementation, alignment with real-world concepts, reusability, and extensibility.
Python presentation of Government Engineering College Aurangabad, BiharUttamKumar617567
This document provides an overview of Python programming for an internship project. It covers the history and origins of Python, its key features like being open source, easy to code in, and object oriented. It also discusses Python concepts like variables, data types, operators, decision making, loops, functions, lists, tuples, object oriented programming, and taking screenshots. The document serves to introduce the Python language and common elements to someone new to programming in Python.
This document provides an introduction and overview of the Python programming language. It discusses what Python is, how it can be used for tasks like web development, data analysis, and scientific computing. It also covers how to get started with Python, including installing it and using basic features like variables, functions, modules, and packages. Examples are provided for common Python concepts like lists, dictionaries, and working with CSV files. MongoDB and the PyMongo module for interacting with MongoDB databases from Python are also briefly introduced.
This document covers polymorphism and operator overloading in C++. It discusses static and dynamic polymorphism, including function overloading, overriding, and virtual functions. It explains operator overloading concepts like overloading unary and binary operators. It also covers type conversion, both implicit and explicit, and keywords like explicit and mutable. The document provides examples of operator overloading, function overloading and overriding, and using virtual functions.
This document defines polymorphism and describes its two types - compile-time and run-time polymorphism. Compile-time polymorphism is demonstrated through method overloading examples, while run-time polymorphism is demonstrated through method overriding examples. The key advantages of polymorphism are listed as code cleanliness, ease of implementation, alignment with real world scenarios, overloaded constructors, and reusability/extensibility.
This document discusses polymorphism in C++. Polymorphism means an operator or function can take on multiple forms. C++ supports two types of polymorphism: compile-time and runtime. Compile-time polymorphism, also called static binding, includes function overloading and operator overloading where the version to call is determined at compile time based on arguments. Runtime polymorphism, also called dynamic binding, uses virtual functions where the target object and method are not known until runtime.
This document discusses the different types of polymorphism in C++, including compile-time and run-time polymorphism. Compile-time polymorphism is achieved through function overloading and operator overloading, while run-time polymorphism uses virtual functions and function overriding. Virtual functions allow for late binding at runtime and can be overridden in derived classes to change the behavior of base class functions depending on the object type.
Java and Python are compared on various aspects such as verbosity, object orientation, and execution model.
Python is found to be more concise and readable than Java for many common tasks like file I/O and logical expressions. However, Java's static typing enables safer refactoring. Both support inheritance but Python allows multiple inheritance and "duck typing".
The execution model differs as well - in Python, code is executed as it is loaded while Java separates loading, initialization and execution. This makes features like monkey patching possible in Python.
In the end, the developer is more important than the language. While each has strengths, the presenter currently prefers Python for its pragmatism and conciseness.
This document provides an introduction to object-oriented programming (OOP) concepts. It defines OOP as a design philosophy that groups everything as self-sustainable objects. The key OOP concepts discussed are objects, classes, encapsulation, abstraction, inheritance, polymorphism, method overloading, method overriding, and access modifiers. Objects are instances of classes that can perform related activities, while classes are blueprints that describe objects. Encapsulation hides implementation details within classes, and abstraction focuses on what objects are rather than how they are implemented.
The document discusses various topics in Objective-C including variables, data types, categories, protocols, and composite objects. It provides code examples to illustrate initializing objects, variable scope, enumerated data types, typedefs, data type conversion, categories, class extensions, protocols, delegates, and composite objects in Objective-C and compares some of these concepts to Java.
Python is an interpreted, object-oriented programming language that uses indentation to identify blocks of code. It is dynamically typed and strongly typed, with objects determining types at runtime rather than requiring explicit type declaration. Common data types include mutable types like lists and dictionaries as well as immutable types like strings and tuples.
Polymorphism.Difference between Inheritance & Polymorphismhuzaifaakram12
Polymorphism in Object-Oriented Programming (OOP) allows objects of different classes to be treated as objects of a common superclass. It enables a single interface to represent different underlying forms (data types). There are two main types of polymorphism:
Compile-time polymorphism (static binding): Achieved through method overloading and operator overloading.
Runtime polymorphism (dynamic binding): Achieved through method overriding, where a subclass provides a specific implementation of a method already defined in its superclass.
Polymorphism topic power point presentation li.pptxMalligaarjunanN
Polymorphism exists widely in Python. Operators like addition can work with different data types like integers, strings, lists, tuples, and dictionaries by supporting polymorphic "add" operations for each type. Methods like repr() also demonstrate polymorphism by converting data to strings in type-appropriate ways, such as converting an integer to its string representation. While Python supports advanced OOP features like operator overloading and multiple inheritance, it does not enforce strict encapsulation with private and public access modifiers, preferring simple syntax instead.
Friend functions allow non-member functions to access private and protected members of a class. Inline functions avoid function call overhead by copying the code into the calling function. The this pointer is an implicit parameter that provides access to the object from within member functions. Static members exist only once per class rather than for each object. Inheritance allows classes to inherit attributes and behaviors from other classes in a hierarchy. Polymorphism allows functions to take different implementations based on the runtime type of an object. Encapsulation binds data and functions that operate on that data together within a class to hide implementation details.
The document discusses Python interview questions and answers related to Python fundamentals like data types, variables, functions, objects and classes. Some key points include:
- Python is an interpreted, interactive and object-oriented programming language. It uses indentation to identify code blocks rather than brackets.
- Python supports dynamic typing where the type is determined at runtime. It is strongly typed meaning operations inappropriate for a type will fail with an exception.
- Common data types include lists (mutable), tuples (immutable), dictionaries, strings and numbers.
- Functions use def, parameters are passed by reference, and variables can be local or global scope.
- Classes use inheritance, polymorphism and encapsulation to create
SVM introduction for machine learning engineersabigailjudith8
In essence, the AWS Machine Learning Foundations program serves as a starting point for those looking to build a solid understanding of machine learning principles and gain practical experience using AWS’s powerful machine learning services. It emphasizes scalable model development, deployment, and management within the cloud infrastructure provided by AWS.
Quantum Computing Quick Research Guide by Arthur MorganArthur Morgan
This is a Quick Research Guide (QRG).
QRGs include the following:
- A brief, high-level overview of the QRG topic.
- A milestone timeline for the QRG topic.
- Links to various free online resource materials to provide a deeper dive into the QRG topic.
- Conclusion and a recommendation for at least two books available in the SJPL system on the QRG topic.
QRGs planned for the series:
- Artificial Intelligence QRG
- Quantum Computing QRG
- Big Data Analytics QRG
- Spacecraft Guidance, Navigation & Control QRG (coming 2026)
- UK Home Computing & The Birth of ARM QRG (coming 2027)
Any questions or comments?
- Please contact Arthur Morgan at [email protected].
100% human made.
Procurement Insights Cost To Value Guide.pptxJon Hansen
Procurement Insights integrated Historic Procurement Industry Archives, serves as a powerful complement — not a competitor — to other procurement industry firms. It fills critical gaps in depth, agility, and contextual insight that most traditional analyst and association models overlook.
Learn more about this value- driven proprietary service offering here.
Train Smarter, Not Harder – Let 3D Animation Lead the Way!
Discover how 3D animation makes inductions more engaging, effective, and cost-efficient.
Check out the slides to see how you can transform your safety training process!
Slide 1: Why 3D animation changes the game
Slide 2: Site-specific induction isn’t optional—it’s essential
Slide 3: Visitors are most at risk. Keep them safe
Slide 4: Videos beat text—especially when safety is on the line
Slide 5: TechEHS makes safety engaging and consistent
Slide 6: Better retention, lower costs, safer sites
Slide 7: Ready to elevate your induction process?
Can an animated video make a difference to your site's safety? Let's talk.
#StandardsGoals for 2025: Standards & certification roundup - Tech Forum 2025BookNet Canada
Book industry standards are evolving rapidly. In the first part of this session, we’ll share an overview of key developments from 2024 and the early months of 2025. Then, BookNet’s resident standards expert, Tom Richardson, and CEO, Lauren Stewart, have a forward-looking conversation about what’s next.
Link to recording, transcript, and accompanying resource: https://bnctechforum.ca/sessions/standardsgoals-for-2025-standards-certification-roundup/
Presented by BookNet Canada on May 6, 2025 with support from the Department of Canadian Heritage.
Book industry standards are evolving rapidly. In the first part of this session, we’ll share an overview of key developments from 2024 and the early months of 2025. Then, BookNet’s resident standards expert, Tom Richardson, and CEO, Lauren Stewart, have a forward-looking conversation about what’s next.
Link to recording, presentation slides, and accompanying resource: https://bnctechforum.ca/sessions/standardsgoals-for-2025-standards-certification-roundup/
Presented by BookNet Canada on May 6, 2025 with support from the Department of Canadian Heritage.
AI Changes Everything – Talk at Cardiff Metropolitan University, 29th April 2...Alan Dix
Talk at the final event of Data Fusion Dynamics: A Collaborative UK-Saudi Initiative in Cybersecurity and Artificial Intelligence funded by the British Council UK-Saudi Challenge Fund 2024, Cardiff Metropolitan University, 29th April 2025
https://alandix.com/academic/talks/CMet2025-AI-Changes-Everything/
Is AI just another technology, or does it fundamentally change the way we live and think?
Every technology has a direct impact with micro-ethical consequences, some good, some bad. However more profound are the ways in which some technologies reshape the very fabric of society with macro-ethical impacts. The invention of the stirrup revolutionised mounted combat, but as a side effect gave rise to the feudal system, which still shapes politics today. The internal combustion engine offers personal freedom and creates pollution, but has also transformed the nature of urban planning and international trade. When we look at AI the micro-ethical issues, such as bias, are most obvious, but the macro-ethical challenges may be greater.
At a micro-ethical level AI has the potential to deepen social, ethnic and gender bias, issues I have warned about since the early 1990s! It is also being used increasingly on the battlefield. However, it also offers amazing opportunities in health and educations, as the recent Nobel prizes for the developers of AlphaFold illustrate. More radically, the need to encode ethics acts as a mirror to surface essential ethical problems and conflicts.
At the macro-ethical level, by the early 2000s digital technology had already begun to undermine sovereignty (e.g. gambling), market economics (through network effects and emergent monopolies), and the very meaning of money. Modern AI is the child of big data, big computation and ultimately big business, intensifying the inherent tendency of digital technology to concentrate power. AI is already unravelling the fundamentals of the social, political and economic world around us, but this is a world that needs radical reimagining to overcome the global environmental and human challenges that confront us. Our challenge is whether to let the threads fall as they may, or to use them to weave a better future.
Semantic Cultivators : The Critical Future Role to Enable AIartmondano
By 2026, AI agents will consume 10x more enterprise data than humans, but with none of the contextual understanding that prevents catastrophic misinterpretations.
Dev Dives: Automate and orchestrate your processes with UiPath MaestroUiPathCommunity
This session is designed to equip developers with the skills needed to build mission-critical, end-to-end processes that seamlessly orchestrate agents, people, and robots.
📕 Here's what you can expect:
- Modeling: Build end-to-end processes using BPMN.
- Implementing: Integrate agentic tasks, RPA, APIs, and advanced decisioning into processes.
- Operating: Control process instances with rewind, replay, pause, and stop functions.
- Monitoring: Use dashboards and embedded analytics for real-time insights into process instances.
This webinar is a must-attend for developers looking to enhance their agentic automation skills and orchestrate robust, mission-critical processes.
👨🏫 Speaker:
Andrei Vintila, Principal Product Manager @UiPath
This session streamed live on April 29, 2025, 16:00 CET.
Check out all our upcoming Dev Dives sessions at https://community.uipath.com/dev-dives-automation-developer-2025/.
Technology Trends in 2025: AI and Big Data AnalyticsInData Labs
At InData Labs, we have been keeping an ear to the ground, looking out for AI-enabled digital transformation trends coming our way in 2025. Our report will provide a look into the technology landscape of the future, including:
-Artificial Intelligence Market Overview
-Strategies for AI Adoption in 2025
-Anticipated drivers of AI adoption and transformative technologies
-Benefits of AI and Big data for your business
-Tips on how to prepare your business for innovation
-AI and data privacy: Strategies for securing data privacy in AI models, etc.
Download your free copy nowand implement the key findings to improve your business.
AI and Data Privacy in 2025: Global TrendsInData Labs
In this infographic, we explore how businesses can implement effective governance frameworks to address AI data privacy. Understanding it is crucial for developing effective strategies that ensure compliance, safeguard customer trust, and leverage AI responsibly. Equip yourself with insights that can drive informed decision-making and position your organization for success in the future of data privacy.
This infographic contains:
-AI and data privacy: Key findings
-Statistics on AI data privacy in the today’s world
-Tips on how to overcome data privacy challenges
-Benefits of AI data security investments.
Keep up-to-date on how AI is reshaping privacy standards and what this entails for both individuals and organizations.
HCL Nomad Web – Best Practices and Managing Multiuser Environmentspanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-nomad-web-best-practices-and-managing-multiuser-environments/
HCL Nomad Web is heralded as the next generation of the HCL Notes client, offering numerous advantages such as eliminating the need for packaging, distribution, and installation. Nomad Web client upgrades will be installed “automatically” in the background. This significantly reduces the administrative footprint compared to traditional HCL Notes clients. However, troubleshooting issues in Nomad Web present unique challenges compared to the Notes client.
Join Christoph and Marc as they demonstrate how to simplify the troubleshooting process in HCL Nomad Web, ensuring a smoother and more efficient user experience.
In this webinar, we will explore effective strategies for diagnosing and resolving common problems in HCL Nomad Web, including
- Accessing the console
- Locating and interpreting log files
- Accessing the data folder within the browser’s cache (using OPFS)
- Understand the difference between single- and multi-user scenarios
- Utilizing Client Clocking
Artificial Intelligence is providing benefits in many areas of work within the heritage sector, from image analysis, to ideas generation, and new research tools. However, it is more critical than ever for people, with analogue intelligence, to ensure the integrity and ethical use of AI. Including real people can improve the use of AI by identifying potential biases, cross-checking results, refining workflows, and providing contextual relevance to AI-driven results.
News about the impact of AI often paints a rosy picture. In practice, there are many potential pitfalls. This presentation discusses these issues and looks at the role of analogue intelligence and analogue interfaces in providing the best results to our audiences. How do we deal with factually incorrect results? How do we get content generated that better reflects the diversity of our communities? What roles are there for physical, in-person experiences in the digital world?
Vaibhav Gupta BAML: AI work flows without Hallucinationsjohn409870
Shipping Agents
Vaibhav Gupta
Cofounder @ Boundary
in/vaigup
boundaryml/baml
Imagine if every API call you made
failed only 5% of the time
boundaryml/baml
Imagine if every LLM call you made
failed only 5% of the time
boundaryml/baml
Imagine if every LLM call you made
failed only 5% of the time
boundaryml/baml
Fault tolerant systems are hard
but now everything must be
fault tolerant
boundaryml/baml
We need to change how we
think about these systems
Aaron Villalpando
Cofounder @ Boundary
Boundary
Combinator
boundaryml/baml
We used to write websites like this:
boundaryml/baml
But now we do this:
boundaryml/baml
Problems web dev had:
boundaryml/baml
Problems web dev had:
Strings. Strings everywhere.
boundaryml/baml
Problems web dev had:
Strings. Strings everywhere.
State management was impossible.
boundaryml/baml
Problems web dev had:
Strings. Strings everywhere.
State management was impossible.
Dynamic components? forget about it.
boundaryml/baml
Problems web dev had:
Strings. Strings everywhere.
State management was impossible.
Dynamic components? forget about it.
Reuse components? Good luck.
boundaryml/baml
Problems web dev had:
Strings. Strings everywhere.
State management was impossible.
Dynamic components? forget about it.
Reuse components? Good luck.
Iteration loops took minutes.
boundaryml/baml
Problems web dev had:
Strings. Strings everywhere.
State management was impossible.
Dynamic components? forget about it.
Reuse components? Good luck.
Iteration loops took minutes.
Low engineering rigor
boundaryml/baml
React added engineering rigor
boundaryml/baml
The syntax we use changes how we
think about problems
boundaryml/baml
We used to write agents like this:
boundaryml/baml
Problems agents have:
boundaryml/baml
Problems agents have:
Strings. Strings everywhere.
Context management is impossible.
Changing one thing breaks another.
New models come out all the time.
Iteration loops take minutes.
boundaryml/baml
Problems agents have:
Strings. Strings everywhere.
Context management is impossible.
Changing one thing breaks another.
New models come out all the time.
Iteration loops take minutes.
Low engineering rigor
boundaryml/baml
Agents need
the expressiveness of English,
but the structure of code
F*** You, Show Me The Prompt.
boundaryml/baml
<show don’t tell>
Less prompting +
More engineering
=
Reliability +
Maintainability
BAML
Sam
Greg Antonio
Chris
turned down
openai to join
ex-founder, one
of the earliest
BAML users
MIT PhD
20+ years in
compilers
made his own
database, 400k+
youtube views
Vaibhav Gupta
in/vaigup
[email protected]
boundaryml/baml
Thank you!
1. Polymorphism in Python - Detailed
Explanation
• An overview of polymorphism with examples
and real-life applications.
2. What is Polymorphism?
• • Derived from Greek: 'Poly' (many) + 'Morph'
(forms)
• • Ability of an object to take multiple forms
• • Same function/method behaves differently
based on the object
3. Why is Polymorphism Important?
• • Flexibility and code reusability
• • Generalization: One function works for
multiple object types
• • Enhances readability and maintenance
4. Types of Polymorphism in Python
• 1. Duck Typing
• 2. Method Overriding (Runtime
Polymorphism)
• 3. Operator Overloading
5. Duck Typing Example
•Duck Typing allows objects to be used
interchangeably as long as they
•implement the required behavior (i.e., they have
the expected methods), regardless of the class they
belong to.
•This is why Python doesn't care about the
"type" of the object, but rather if it can perform a
certain action.
6. Duck Typing Example
class Cat:
def sound(self):
return 'Meow'
class Dog:
def sound(self):
return 'Bark'
def animal_sound(animal):
print(animal.sound())
animal_sound(Cat()) # Meow
animal_sound(Dog()) # Bark
7. Duck Typing Example
Write a program to illustrate duck typing in
Python using Banking as a scenario
//use google collab
if hasattr
operator overloading
9. Operator Overloading
Operator Overloading (also called operator ad-hoc
polymorphism) allows you to define or change the
behavior of built-in operators (like +, -, *, etc.) for custom
classes.
•Operator Overloading allows you to use operators (such
as +, -, *, etc.) to work with objects of your class, just like
they work with primitive data types like integers and strings.
10. Operator Overloading
What is Operator Overloading?
In Python, operator overloading allows you to redefine the
meaning of standard operators (+, -, *, etc.) when they are
used with objects of your own class. This means you can
customize how an operator behaves when applied to your
objects.
13. We use operator overloading when we want to
make custom classes behave more like built-in
types, especially when using operators such as
+, -, *, ==, etc.
When Do We Use Operator Overloading?
17. Real-Life Example - Payment System
class Payment:
def pay(self):
pass
class CreditCard(Payment):
def pay(self):
return 'Paid using Credit Card'
class Paypal(Payment):
def pay(self):
return 'Paid using Paypal'
def make_payment(payment_method):
print(payment_method.pay())
make_payment(CreditCard())
make_payment(Paypal())
18. Benefits of Polymorphism
• Code Reusability: Same interface for multiple
object types
• Extensibility: Easy to add new classes
• Maintenance: Easier to maintain and scale
code
• Cleaner Code: Reduces complex if-else
structures