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
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.
The document discusses object-oriented programming in Python. It defines key OOP concepts like classes, objects, and methods. It provides examples of defining classes and methods in Python. It also covers inheritance, polymorphism, and data abstraction in OOP. Database programming in Python is also discussed, including connecting to databases and performing CRUD operations using the Python DB API.
The document discusses basic inheritance in Python. It explains that all classes inherit from the base Object class. Inheritance allows creating subclasses that inherit attributes and methods from a parent superclass. This allows code reuse and adding specialized behavior. An example creates a Contact class to store names and emails, with a Supplier subclass that adds an "order" method. A SupplierCheck subclass then overrides the order method to check the customer balance before processing orders.
This document provides an overview of object-oriented programming concepts in Python including objects, classes, inheritance, polymorphism, and encapsulation. It defines key terms like objects, classes, and methods. It explains how to create classes and objects in Python. It also discusses special methods, modules, and the __name__ variable.
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.
This document discusses Python modules, classes, inheritance, and properties. Some key points:
- Modules allow the organization of Python code into reusable libraries by saving code in files with a .py extension. Modules can contain functions, variables, and be imported into other code.
- Classes are templates that define the properties and methods common to all objects of a certain kind. The __init__() method initializes new objects. Inheritance allows child classes to inherit properties and methods from parent classes.
- Properties provide a way to control access to class attributes, allowing them to be accessed like attributes while hiding the implementation details behind getter and setter methods.
The document discusses Python classes and object-oriented programming concepts. It defines key terms like class, object, method, and inheritance. It provides examples of creating a basic Employee class with methods and instance variables. It also covers class variables, accessing object attributes, adding/removing attributes, inheritance, and overriding methods in subclasses. The goal is to teach Python language essentials for object-oriented programming.
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
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.
The document discusses object-oriented programming in Python. It defines key OOP concepts like classes, objects, and methods. It provides examples of defining classes and methods in Python. It also covers inheritance, polymorphism, and data abstraction in OOP. Database programming in Python is also discussed, including connecting to databases and performing CRUD operations using the Python DB API.
The document discusses basic inheritance in Python. It explains that all classes inherit from the base Object class. Inheritance allows creating subclasses that inherit attributes and methods from a parent superclass. This allows code reuse and adding specialized behavior. An example creates a Contact class to store names and emails, with a Supplier subclass that adds an "order" method. A SupplierCheck subclass then overrides the order method to check the customer balance before processing orders.
This document provides an overview of object-oriented programming concepts in Python including objects, classes, inheritance, polymorphism, and encapsulation. It defines key terms like objects, classes, and methods. It explains how to create classes and objects in Python. It also discusses special methods, modules, and the __name__ variable.
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.
This document discusses Python modules, classes, inheritance, and properties. Some key points:
- Modules allow the organization of Python code into reusable libraries by saving code in files with a .py extension. Modules can contain functions, variables, and be imported into other code.
- Classes are templates that define the properties and methods common to all objects of a certain kind. The __init__() method initializes new objects. Inheritance allows child classes to inherit properties and methods from parent classes.
- Properties provide a way to control access to class attributes, allowing them to be accessed like attributes while hiding the implementation details behind getter and setter methods.
The document discusses Python classes and object-oriented programming concepts. It defines key terms like class, object, method, and inheritance. It provides examples of creating a basic Employee class with methods and instance variables. It also covers class variables, accessing object attributes, adding/removing attributes, inheritance, and overriding methods in subclasses. The goal is to teach Python language essentials for object-oriented programming.
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,
The document provides instructions for completing a Java lab assignment involving classes for drawing shapes and colors. It describes the required classes - ColorHolder, ColorButton, CircleButton, SquareButton, and SimpleDraw - and their relationships. ColorHolder stores and sets the current color. ColorButton defines a buttonPressed method. CircleButton and SquareButton add shapes to the Window when pressed and reference the single Window object. SimpleDraw initializes instances of these classes and adds them to the Window.
In the publication I briefly describe what metaclasses are in Python. The writeup is a living item and will be extended with more detail shortly.
Please enjoy and comment.
This document provides an overview of object-oriented programming concepts in Python including classes, objects, inheritance, polymorphism and data hiding. It defines key OOP terms like class, object, method, and inheritance. It also demonstrates how to define classes with attributes and methods, create object instances, and extend functionality via inheritance. The document shows how operators and methods can be overloaded in classes.
The document discusses Scala programming concepts including object-oriented programming, functional programming, collections, pattern matching, and more. It provides code examples of defining objects and classes, functions, for expressions, match expressions, case classes, traits, generics, and collections like List and Map.
This document discusses abstract classes and interfaces in Python. It provides examples of using abstract methods and abstract classes to define common behavior for subclasses while allowing subclasses to provide their own specific implementations. Interfaces are defined as abstract classes that contain only abstract methods, allowing subclasses to fully implement the interface. Concrete methods can also be defined in abstract classes to provide shared behavior across subclasses.
The document discusses Doctrine2, an ORM (object-relational mapper) for PHP. It describes how Doctrine2 allows transparent persistence of PHP objects to a database without restrictions on classes or properties. It provides several examples of how to map PHP classes to database tables using annotations, YAML, XML or PHP code. The document also covers common Doctrine2 practices like using protected properties with getter/setter methods.
The Ring programming language version 1.6 book - Part 33 of 189Mahmoud Samir Fayed
The document provides documentation on Ring programming language features including functions, operators, inheritance, dynamic attributes, packages, printing objects, finding and sorting lists of objects, using self and this, and functional programming concepts like pure functions, first-class functions, higher-order functions, and anonymous functions.
This document discusses Python classes and objects. It defines a class as a user-defined prototype that defines attributes and methods to characterize objects of that class. Classes contain data members like class and instance variables that are accessed via dot notation. The document also covers creating classes, class variables, inheritance between classes, and calling parent and child methods.
Ruby is an object-oriented programming language; that much, everyone knows. But Ruby's objects work very differently from many other languages, especially if you're coming from a complied, statically typed language. In this lecture, I'll review the surprisingly simple rules that govern Ruby's objects. I discuss methods, classes, instances, and modules, and how these various pieces fit together into an integrated whole -- including such topics as inheritance, instance variables, class variables, mixins, and "include" vs. "extend".
Object Orientation vs Functional Programming in PythonTendayi Mawushe
This document compares and contrasts object-oriented programming and functional programming, and discusses how Python supports both paradigms. It provides examples of common patterns like inheritance, composition, decorators, and callbacks in both styles. The conclusion is that Python facilitates using either paradigm depending on needs, and the two approaches complement each other.
Be Smart, Constrain Your Types to Free Your Brain!Jorge Vásquez
The document discusses different approaches to representing data with smart types in Scala to validate data at compile time. It describes using smart constructors with Either types, the Newtype library, and the Refined library to define types for a Person case class that validate fields like names, emails and addresses. Using these approaches helps prevent invalid data from being stored by catching errors at compile time rather than runtime.
The document discusses using smart constructors and opaque types to improve data modeling in Scala. It describes problems with representing all data as simple types, like case classes, which can allow invalid data. The presentation introduces using smart constructors with opaque types to define domain-specific types for name, email, address, etc. and validate values when constructing instances of these types and the Person case class. This ensures invalid data cannot be stored.
The Ring programming language version 1.8 book - Part 36 of 202Mahmoud Samir Fayed
This document provides examples and explanations of object-oriented programming concepts in Ring including: defining classes with attributes and methods, instantiating objects, operator overloading, inheritance, dynamic attributes, packages, printing objects, finding objects in lists, sorting lists of objects, using self/this, default attribute values, and more. Key OOP concepts like encapsulation, abstraction, and polymorphism are demonstrated through multiple examples.
The topics covers in this presentation is overloading methods,Construcotr
1 Objects as parameter to methods
2 objects as parameter to construcotr
3 Returning objects
4 String Class
5 String Buffer Class
6 Command line arguments
7 Access Controle
8 Static keyword usage
9 Final keyword usage
The document discusses Django's contenttypes framework which allows working with models generically without having to know the specific model being used. It presents several patterns for implementing generic functionality, including self-aware models, improved generic views, universal URLs, and dynamic forms. The key benefits are the ability to perform CRUD operations and create relationships between any objects without having to pre-program for each specific model.
Exploring type level programming in ScalaJorge Vásquez
In this introduction to type-level programming in Scala, we are going to discuss how we can leverage the full power of the type system to verify domain properties of an application at compile-time, instead of doing runtime verifications at the value-level
We learned how to implement ORM in Python using peewee. This includes creating a ZooAnimal class that inherits from peewee's Model class and defines the database fields, creating a database table for the class, and saving ZooAnimal instances to the database. We also discussed useful Python concepts like properties for private attributes, importing packages, and using *args and **kwargs to allow flexible function arguments.
The Ring programming language version 1.4 book - Part 20 of 30Mahmoud Samir Fayed
Ring provides syntax flexibility through commands that allow changing language keywords and operators:
1. The ChangeRingKeyword command allows changing existing Ring keywords to new keywords. This is done at the scanner stage before parsing.
2. Similarly, the ChangeRingOperator command allows changing existing operators to new operators at the scanner stage.
3. Syntax files storing groups of ChangeRingKeyword and ChangeRingOperator commands can be created to customize syntax for projects. However, these files cannot be loaded directly since the commands must be executed during scanning before parsing.
The Ring programming language version 1.9 book - Part 39 of 210Mahmoud Samir Fayed
The document discusses various concepts in functional programming, including pure functions, first-class functions, higher-order functions, anonymous and nested functions, and equality of functions. Pure functions are defined as functions that don't change the state by copying variables passed to the function rather than modifying the original data. Examples are provided to demonstrate pure functions using a list and how assignment copies the list by value rather than reference.
In Python, operator overloading is accomplished via "magic methods" -- specially named methods that begin and end with double underscore ("dunder"). Most Python developers know about __init__ and even __str__, but magic methods are used to accomplish many things in the Python world. In this talk, I introduce a number of these methods, and show how they can be used to make our objects more expressive.
Object.__class__.__dict__ - python object model and friends - with examplesRobert Lujo
Python object model - advanced and some not so advanced features, lot of code examples:
building blocks, objects, classes, functions, mutable and immutable, everything is an object, variables, global context, "executing" the module, standard types inheritance, multiple inheritance, mixins and mro, dynamic classes, metaclasses, property function and descriptors context managers & with, useful __methods__
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,
The document provides instructions for completing a Java lab assignment involving classes for drawing shapes and colors. It describes the required classes - ColorHolder, ColorButton, CircleButton, SquareButton, and SimpleDraw - and their relationships. ColorHolder stores and sets the current color. ColorButton defines a buttonPressed method. CircleButton and SquareButton add shapes to the Window when pressed and reference the single Window object. SimpleDraw initializes instances of these classes and adds them to the Window.
In the publication I briefly describe what metaclasses are in Python. The writeup is a living item and will be extended with more detail shortly.
Please enjoy and comment.
This document provides an overview of object-oriented programming concepts in Python including classes, objects, inheritance, polymorphism and data hiding. It defines key OOP terms like class, object, method, and inheritance. It also demonstrates how to define classes with attributes and methods, create object instances, and extend functionality via inheritance. The document shows how operators and methods can be overloaded in classes.
The document discusses Scala programming concepts including object-oriented programming, functional programming, collections, pattern matching, and more. It provides code examples of defining objects and classes, functions, for expressions, match expressions, case classes, traits, generics, and collections like List and Map.
This document discusses abstract classes and interfaces in Python. It provides examples of using abstract methods and abstract classes to define common behavior for subclasses while allowing subclasses to provide their own specific implementations. Interfaces are defined as abstract classes that contain only abstract methods, allowing subclasses to fully implement the interface. Concrete methods can also be defined in abstract classes to provide shared behavior across subclasses.
The document discusses Doctrine2, an ORM (object-relational mapper) for PHP. It describes how Doctrine2 allows transparent persistence of PHP objects to a database without restrictions on classes or properties. It provides several examples of how to map PHP classes to database tables using annotations, YAML, XML or PHP code. The document also covers common Doctrine2 practices like using protected properties with getter/setter methods.
The Ring programming language version 1.6 book - Part 33 of 189Mahmoud Samir Fayed
The document provides documentation on Ring programming language features including functions, operators, inheritance, dynamic attributes, packages, printing objects, finding and sorting lists of objects, using self and this, and functional programming concepts like pure functions, first-class functions, higher-order functions, and anonymous functions.
This document discusses Python classes and objects. It defines a class as a user-defined prototype that defines attributes and methods to characterize objects of that class. Classes contain data members like class and instance variables that are accessed via dot notation. The document also covers creating classes, class variables, inheritance between classes, and calling parent and child methods.
Ruby is an object-oriented programming language; that much, everyone knows. But Ruby's objects work very differently from many other languages, especially if you're coming from a complied, statically typed language. In this lecture, I'll review the surprisingly simple rules that govern Ruby's objects. I discuss methods, classes, instances, and modules, and how these various pieces fit together into an integrated whole -- including such topics as inheritance, instance variables, class variables, mixins, and "include" vs. "extend".
Object Orientation vs Functional Programming in PythonTendayi Mawushe
This document compares and contrasts object-oriented programming and functional programming, and discusses how Python supports both paradigms. It provides examples of common patterns like inheritance, composition, decorators, and callbacks in both styles. The conclusion is that Python facilitates using either paradigm depending on needs, and the two approaches complement each other.
Be Smart, Constrain Your Types to Free Your Brain!Jorge Vásquez
The document discusses different approaches to representing data with smart types in Scala to validate data at compile time. It describes using smart constructors with Either types, the Newtype library, and the Refined library to define types for a Person case class that validate fields like names, emails and addresses. Using these approaches helps prevent invalid data from being stored by catching errors at compile time rather than runtime.
The document discusses using smart constructors and opaque types to improve data modeling in Scala. It describes problems with representing all data as simple types, like case classes, which can allow invalid data. The presentation introduces using smart constructors with opaque types to define domain-specific types for name, email, address, etc. and validate values when constructing instances of these types and the Person case class. This ensures invalid data cannot be stored.
The Ring programming language version 1.8 book - Part 36 of 202Mahmoud Samir Fayed
This document provides examples and explanations of object-oriented programming concepts in Ring including: defining classes with attributes and methods, instantiating objects, operator overloading, inheritance, dynamic attributes, packages, printing objects, finding objects in lists, sorting lists of objects, using self/this, default attribute values, and more. Key OOP concepts like encapsulation, abstraction, and polymorphism are demonstrated through multiple examples.
The topics covers in this presentation is overloading methods,Construcotr
1 Objects as parameter to methods
2 objects as parameter to construcotr
3 Returning objects
4 String Class
5 String Buffer Class
6 Command line arguments
7 Access Controle
8 Static keyword usage
9 Final keyword usage
The document discusses Django's contenttypes framework which allows working with models generically without having to know the specific model being used. It presents several patterns for implementing generic functionality, including self-aware models, improved generic views, universal URLs, and dynamic forms. The key benefits are the ability to perform CRUD operations and create relationships between any objects without having to pre-program for each specific model.
Exploring type level programming in ScalaJorge Vásquez
In this introduction to type-level programming in Scala, we are going to discuss how we can leverage the full power of the type system to verify domain properties of an application at compile-time, instead of doing runtime verifications at the value-level
We learned how to implement ORM in Python using peewee. This includes creating a ZooAnimal class that inherits from peewee's Model class and defines the database fields, creating a database table for the class, and saving ZooAnimal instances to the database. We also discussed useful Python concepts like properties for private attributes, importing packages, and using *args and **kwargs to allow flexible function arguments.
The Ring programming language version 1.4 book - Part 20 of 30Mahmoud Samir Fayed
Ring provides syntax flexibility through commands that allow changing language keywords and operators:
1. The ChangeRingKeyword command allows changing existing Ring keywords to new keywords. This is done at the scanner stage before parsing.
2. Similarly, the ChangeRingOperator command allows changing existing operators to new operators at the scanner stage.
3. Syntax files storing groups of ChangeRingKeyword and ChangeRingOperator commands can be created to customize syntax for projects. However, these files cannot be loaded directly since the commands must be executed during scanning before parsing.
The Ring programming language version 1.9 book - Part 39 of 210Mahmoud Samir Fayed
The document discusses various concepts in functional programming, including pure functions, first-class functions, higher-order functions, anonymous and nested functions, and equality of functions. Pure functions are defined as functions that don't change the state by copying variables passed to the function rather than modifying the original data. Examples are provided to demonstrate pure functions using a list and how assignment copies the list by value rather than reference.
In Python, operator overloading is accomplished via "magic methods" -- specially named methods that begin and end with double underscore ("dunder"). Most Python developers know about __init__ and even __str__, but magic methods are used to accomplish many things in the Python world. In this talk, I introduce a number of these methods, and show how they can be used to make our objects more expressive.
Object.__class__.__dict__ - python object model and friends - with examplesRobert Lujo
Python object model - advanced and some not so advanced features, lot of code examples:
building blocks, objects, classes, functions, mutable and immutable, everything is an object, variables, global context, "executing" the module, standard types inheritance, multiple inheritance, mixins and mro, dynamic classes, metaclasses, property function and descriptors context managers & with, useful __methods__
This document provides an overview of Python classes, including classic and new-style classes. It discusses key concepts like the method resolution order (MRO), descriptors, and super. Descriptors allow implementing features like properties and methods. The document explains that functions are non-data descriptors and super returns a proxy object that delegates to the appropriate class in the MRO.
Chap 3 Python Object Oriented Programming - Copy.pptmuneshwarbisen1
The document discusses object oriented programming concepts in Python including classes, objects, instances, methods, inheritance, and class attributes. It provides examples of defining classes, instantiating objects, using methods, and the difference between class and instance attributes. Key concepts covered include defining classes with the class keyword, creating object instances, using the __init__() method for initialization, and allowing derived classes to inherit from base classes.
A brief introduction to functional programming.
Even if slides present some simple Python code, functional programming patterns applies to other languages too.
An object oriented concept in python is detailed for the students or anyone who aspire to learn more powerful concept that helps in developing software or any web development to the persons who work in a tech filed
This document discusses classes and objects in Python. It introduces defining a class with fields and methods, using a class by creating objects and calling methods, constructors, the __init__ method, the __str__ method for string representation, operator overloading, inheritance between classes, and calling superclass methods from a subclass. Examples of a Point class are provided throughout to demonstrate various object-oriented programming concepts in Python.
This document discusses classes and objects in Python. It introduces defining a class with fields and methods, using a class by creating objects and calling methods, constructors, the self parameter, overriding methods like __str__ and adding operator overloading. It also covers inheritance, calling superclass methods, and generating exceptions. The document uses the Point class as a running example and includes exercises to write methods for it.
Implementing and analyzing online experimentsSean Taylor
Randomized experiments are the gold standard for understanding and quantifying causal relationships. This talk is divided into two parts corresponding to before and after the experiment is run. In the first section, we discuss how to design and implement online experiments using PlanOut, an open-source toolkit for advanced online experimentation used at Facebook. We will show how basic “A/B tests”, within-subjects designs, as well as more sophisticated experiments can be implemented. In the second section, we cover methods to estimate causal quantities of interest and construct appropriate confidence intervals. Particular attention will be given to scalable methods suitable for “big data”, including working with weighted data and clustered bootstrapping.
This document provides an overview of the Python programming language. It discusses what Python is, its key features like being multi-purpose, readable, and productive. It then demonstrates Hello World programs in Python, C++, Java, and PHP. The rest of the document covers Python concepts like operators, variables, strings, lists, conditions, loops, functions, object oriented programming, and design patterns like strategy, closure, generator, and decorator patterns.
This document provides an overview of advanced Python concepts including: inheritance and the MRO; mixins; variable scope; iterators and generators; list comprehensions; itertools; coroutines; operator overloading; __getattr__ and __dict__; decorators; descriptors; properties; functions vs methods; type and metaprogramming; and using __metaclass__. It includes code examples to demonstrate these concepts.
The document discusses key concepts of object-oriented programming such as classes, objects, encapsulation, inheritance, and polymorphism. It provides examples of defining a Point class in Python with methods like translate() and distance() as well as using concepts like constructors, private and protected members, and naming conventions using underscores. The document serves as an introduction to object-oriented programming principles and their implementation in Python.
This document contains a lesson plan for a programming session on object-oriented programming in Java. The agenda includes reviewing previous knowledge, discussing the utility of OOP, an introduction to objects and classes, practical exercises, and a closing session. The introduction defines objects as things with characteristics and behaviors, and classes as templates for objects. It also covers attributes, methods, constructors, and how objects are created from classes. Practical exercises demonstrate creating classes for trees, humans, and cars with attributes and methods.
This document provides an introduction to the Python programming language. It covers basic Python concepts like data types, strings, data structures, classes, methods, exceptions, iterations, generators, and scopes. Python is described as an easy to learn, read, and use dynamic language with a large selection of stable libraries. It is presented as being much easier than bash scripts for building and maintaining complex system infrastructure.
Slides accompanying talk at : https://youtu.be/vtUiZkHVi-w
Come learn about Python typing, and we'll cover the type system as well as the mypy tool and all the tools that you need for your typing needs.
Given to HSV.py on Nov 8th, 2019
This document provides an introduction to object-oriented programming in Python. It discusses how everything in Python is an object with a type, and how to create new object types using classes. Key points covered include defining classes with attributes like __init__() and methods, creating instances of classes, and defining special methods like __str__() to customize object behavior and representations. The document uses examples like Coordinate and Fraction classes to illustrate how to implement and use custom object types in Python.
This document summarizes Kotlin lambda basics and advanced topics:
1. Lambdas allow defining anonymous functions that can be passed as parameters or returned as values. They simplify code by removing the need for anonymous classes.
2. The Kotlin standard library provides many higher-order functions that operate on collections using lambdas, such as filter, map, reduce, and more.
3. Advanced lambda topics include higher-order functions, using lambdas with Java interfaces, closure, and applying lambdas in design patterns like the strategy pattern.
JQuery is a JavaScript library that simplifies HTML document manipulation, event handling, animations, and Ajax interactions. It works across browsers and makes tasks like DOM traversal and manipulation, event handling, animation, and Ajax much simpler. JQuery's versatility, extensibility, and cross-browser compatibility have made it popular, with millions of developers using it to write JavaScript.
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Imagine a world where instead of blue and brown trucks dropping parcels on our porches, a buzzing drove of drones delivered our goods. Now imagine those drones are controlled by 3 purpose-built AI designed to ensure all packages were delivered as quickly and as economically as possible That's what Stork is all about.
Why Apache Kafka Clusters Are Like Galaxies (And Other Cosmic Kafka Quandarie...Paul Brebner
Closing talk for the Performance Engineering track at Community Over Code EU (Bratislava, Slovakia, June 5 2024) https://eu.communityovercode.org/sessions/2024/why-apache-kafka-clusters-are-like-galaxies-and-other-cosmic-kafka-quandaries-explored/ Instaclustr (now part of NetApp) manages 100s of Apache Kafka clusters of many different sizes, for a variety of use cases and customers. For the last 7 years I’ve been focused outwardly on exploring Kafka application development challenges, but recently I decided to look inward and see what I could discover about the performance, scalability and resource characteristics of the Kafka clusters themselves. Using a suite of Performance Engineering techniques, I will reveal some surprising discoveries about cosmic Kafka mysteries in our data centres, related to: cluster sizes and distribution (using Zipf’s Law), horizontal vs. vertical scalability, and predicting Kafka performance using metrics, modelling and regression techniques. These insights are relevant to Kafka developers and operators.
Superpower Your Apache Kafka Applications Development with Complementary Open...Paul Brebner
Kafka Summit talk (Bangalore, India, May 2, 2024, https://events.bizzabo.com/573863/agenda/session/1300469 )
Many Apache Kafka use cases take advantage of Kafka’s ability to integrate multiple heterogeneous systems for stream processing and real-time machine learning scenarios. But Kafka also exists in a rich ecosystem of related but complementary stream processing technologies and tools, particularly from the open-source community. In this talk, we’ll take you on a tour of a selection of complementary tools that can make Kafka even more powerful. We’ll focus on tools for stream processing and querying, streaming machine learning, stream visibility and observation, stream meta-data, stream visualisation, stream development including testing and the use of Generative AI and LLMs, and stream performance and scalability. By the end you will have a good idea of the types of Kafka “superhero” tools that exist, which are my favourites (and what superpowers they have), and how they combine to save your Kafka applications development universe from swamploads of data stagnation monsters!
In this infographic, we have explored cost-effective strategies for iOS app development, focusing on building high-quality apps within a budget. Key points covered include prioritizing essential features, leveraging existing tools and libraries, adopting cross-platform development approaches, optimizing for a Minimum Viable Product (MVP), and integrating with cloud services and third-party APIs. By implementing these strategies, businesses and developers can create functional and engaging iOS apps while minimizing development costs and time-to-market.
Unlock the Secrets to Effortless Video Creation with Invideo: Your Ultimate G...The Third Creative Media
"Navigating Invideo: A Comprehensive Guide" is an essential resource for anyone looking to master Invideo, an AI-powered video creation tool. This guide provides step-by-step instructions, helpful tips, and comparisons with other AI video creators. Whether you're a beginner or an experienced video editor, you'll find valuable insights to enhance your video projects and bring your creative ideas to life.
🏎️Tech Transformation: DevOps Insights from the Experts 👩💻campbellclarkson
Connect with fellow Trailblazers, learn from industry experts Glenda Thomson (Salesforce, Principal Technical Architect) and Will Dinn (Judo Bank, Salesforce Development Lead), and discover how to harness DevOps tools with Salesforce.
Baha Majid WCA4Z IBM Z Customer Council Boston June 2024.pdfBaha Majid
IBM watsonx Code Assistant for Z, our latest Generative AI-assisted mainframe application modernization solution. Mainframe (IBM Z) application modernization is a topic that every mainframe client is addressing to various degrees today, driven largely from digital transformation. With generative AI comes the opportunity to reimagine the mainframe application modernization experience. Infusing generative AI will enable speed and trust, help de-risk, and lower total costs associated with heavy-lifting application modernization initiatives. This document provides an overview of the IBM watsonx Code Assistant for Z which uses the power of generative AI to make it easier for developers to selectively modernize COBOL business services while maintaining mainframe qualities of service.
Streamlining End-to-End Testing Automation with Azure DevOps Build & Release Pipelines
Automating end-to-end (e2e) test for Android and iOS native apps, and web apps, within Azure build and release pipelines, poses several challenges. This session dives into the key challenges and the repeatable solutions implemented across multiple teams at a leading Indian telecom disruptor, renowned for its affordable 4G/5G services, digital platforms, and broadband connectivity.
Challenge #1. Ensuring Test Environment Consistency: Establishing a standardized test execution environment across hundreds of Azure DevOps agents is crucial for achieving dependable testing results. This uniformity must seamlessly span from Build pipelines to various stages of the Release pipeline.
Challenge #2. Coordinated Test Execution Across Environments: Executing distinct subsets of tests using the same automation framework across diverse environments, such as the build pipeline and specific stages of the Release Pipeline, demands flexible and cohesive approaches.
Challenge #3. Testing on Linux-based Azure DevOps Agents: Conducting tests, particularly for web and native apps, on Azure DevOps Linux agents lacking browser or device connectivity presents specific challenges in attaining thorough testing coverage.
This session delves into how these challenges were addressed through:
1. Automate the setup of essential dependencies to ensure a consistent testing environment.
2. Create standardized templates for executing API tests, API workflow tests, and end-to-end tests in the Build pipeline, streamlining the testing process.
3. Implement task groups in Release pipeline stages to facilitate the execution of tests, ensuring consistency and efficiency across deployment phases.
4. Deploy browsers within Docker containers for web application testing, enhancing portability and scalability of testing environments.
5. Leverage diverse device farms dedicated to Android, iOS, and browser testing to cover a wide range of platforms and devices.
6. Integrate AI technology, such as Applitools Visual AI and Ultrafast Grid, to automate test execution and validation, improving accuracy and efficiency.
7. Utilize AI/ML-powered central test automation reporting server through platforms like reportportal.io, providing consolidated and real-time insights into test performance and issues.
These solutions not only facilitate comprehensive testing across platforms but also promote the principles of shift-left testing, enabling early feedback, implementing quality gates, and ensuring repeatability. By adopting these techniques, teams can effectively automate and execute tests, accelerating software delivery while upholding high-quality standards across Android, iOS, and web applications.
2. WHO AM I?
• Work at indico (small local
company)
• Previously at Olin College,
Pearson, edX, fetchnotes,
and freelance work
• Semi-retired SO & quora user
• Love playing with the dirty
little secrets of python
7. class StubbornObject(object):
def __setattr__(self, key, value):
if hasattr(self, key):
raise ValueError(“Already set in my ways")
else:
object.__setattr__(self, key, value)
>>> test = StubbornObject()
>>> test.a = "one"
>>> test.a = “two” # Now actually errors
ACTUALLY STOPPING PEOPLE FROM TOUCHING
YOUR ATTRIBUTES
9. results = my_object.attribute
if not isinstance(results, list):
results = list(results)
# Do Something
EVER WRITTEN CODE LIKE THIS?
10. class ChangelingObject(object):
list_fields = {"a", "b", "c"}
def __setattr__(self, key, value):
if key in self.list_fields:
value = [value]
object.__setattr__(self, key, value)
>>> test = ChangelingObject()
>>> test.a = 1
>>> print test.a
[1]
NEVER AGAIN WITH SPECIAL PYTHON MAGIC
13. class User(object):
# Standard ORM stuff
def __iadd__(self, other):
current = user_object.balance
try:
user_object.balance = current + other
session.commit()
except ORMException:
session.rollback()
14. def add_money(user_id, amount):
session = Session()
user_object =
session.query(User).filter_by(id=user_id).first()
user_object += amount
SHORT CODE, BUT AT WHAT COST?