Functional Domain Modeling - The ZIO 2 WayDebasish Ghosh
Principled way to design and implement functional domain models using some of the patterns of domain driven design. DDD, as the name suggests, is focused towards the domain model and the patterns of architecture that it encourages are also based on how we think of interactions amongst the basic abstractions of the domain. Of course the primary goal of the talk is to discuss how Scala and Zio 2 can be a potent combination in realizing the implementation of such models. This is not a talk on FP, the focus will be on how to structure and modularise an application based on some of the patterns of DDD.
Presentation given at OSCON 2009 and PostgreSQL West 09. Describes SQL solutions to a selection of object-oriented problems:
- Extensibility
- Polymorphism
- Hierarchies
- Using ORM in MVC application architecture
These slides are excerpted from another presentation, "SQL Antipatterns Strike Back."
Algebraic Thinking for Evolution of Pure Functional Domain ModelsDebasish Ghosh
The focus of the talk is to emphasize the importance of algebraic thinking when designing pure functional domain models. The talk begins with the definition of an algebra as consisting of a carrier type, a set of operations/functions and a set of laws on those operations. Using examples from the standard library, the talk shows how thinking of abstractions in terms of its algebra is more intuitive than discussing its operational semantics. The talk also discusses the virtues of parametricity and compositionality in designing proper algebras.
Algebras are compositional and help build larger algebras out of smaller ones. We start with base level types available in standard libraries and compose larger programs out of them. We take a real life use case for a domain model and illustrate how we can define the entire model using the power of algebraic composition of the various types. We talk about how to model side-effects as pure abstractions using algebraic effects. At no point we will talk about implementations.
At the end of the talk we will have a working model built completely out of the underlying algebra of the domain language.
Functional Domain Modeling - The ZIO 2 WayDebasish Ghosh
Principled way to design and implement functional domain models using some of the patterns of domain driven design. DDD, as the name suggests, is focused towards the domain model and the patterns of architecture that it encourages are also based on how we think of interactions amongst the basic abstractions of the domain. Of course the primary goal of the talk is to discuss how Scala and Zio 2 can be a potent combination in realizing the implementation of such models. This is not a talk on FP, the focus will be on how to structure and modularise an application based on some of the patterns of DDD.
Presentation given at OSCON 2009 and PostgreSQL West 09. Describes SQL solutions to a selection of object-oriented problems:
- Extensibility
- Polymorphism
- Hierarchies
- Using ORM in MVC application architecture
These slides are excerpted from another presentation, "SQL Antipatterns Strike Back."
Algebraic Thinking for Evolution of Pure Functional Domain ModelsDebasish Ghosh
The focus of the talk is to emphasize the importance of algebraic thinking when designing pure functional domain models. The talk begins with the definition of an algebra as consisting of a carrier type, a set of operations/functions and a set of laws on those operations. Using examples from the standard library, the talk shows how thinking of abstractions in terms of its algebra is more intuitive than discussing its operational semantics. The talk also discusses the virtues of parametricity and compositionality in designing proper algebras.
Algebras are compositional and help build larger algebras out of smaller ones. We start with base level types available in standard libraries and compose larger programs out of them. We take a real life use case for a domain model and illustrate how we can define the entire model using the power of algebraic composition of the various types. We talk about how to model side-effects as pure abstractions using algebraic effects. At no point we will talk about implementations.
At the end of the talk we will have a working model built completely out of the underlying algebra of the domain language.
Slidedeck presented at http://devternity.com/ around MongoDB internals. We review the usage patterns of MongoDB, the different storage engines and persistency models as well has the definition of documents and general data structures.
ZIO: Powerful and Principled Functional Programming in ScalaWiem Zine Elabidine
This is an introduction of purely functional programming type safe abstractions that provide a variety of features for building asynchronous and concurrent applications data structures built on ZIO.
You'll learn by examples about the power of functional programming to solve the hard problems of software development in a principled, without compromises.
This tutorial will provide you with a basic understanding of graph database technology and the ability to quickly begin development of a graph database application. You will have the capability to recognize graph-based problems and present the benefits of using graph technology for problem resolution.
The tutorial will give you an understanding of:
• Graph theory - origins and concepts
• Benefits of graph databases
• Different types of graph databases
• Typical graph database API
• Programming basics
• Use cases
Bring your laptops for a hands-on opportunity to practice some sample codes. A basic understanding of Java programming is a recommended prerequisite to understand this course. This session is led by the InfiniteGraph technical team and the demonstration code will be drawn from InfiniteGraph examples, however the broader educational presentation is product-neutral and not a commercial presentation of their products.
To participate in the hands-on portion of the graph tutorial users must have:
• Java programming experience
• Java Developer Kit (JDK)
• Current InfiniteGraph installed on laptop. (To download visit www.objectivity.com/infinitegraph)
• HelloGraph test – Upon installing IG, run HelloGraph to test the install. (HelloGraph can be found online at http://wiki.infinitegraph.com/2.1/w/index.php?title=Download_Sample_Code)
Leon Guzenda was one of the founding members of Objectivity in 1988 and one of the original architects of Objectivity/DB. He currently works with Objectivity's major customers to help them effectively develop and deploy complex applications and systems that use the industry's highest-performing, most reliable DBMS technology, Objectivity/DB. He also liaises with technology partners and industry groups to help ensure that Objectivity/DB remains at the forefront of database and distributed computing technology. Leon has more than 35 years experience in the software industry. At Automation Technology Products, he managed the development of the ODBMS for the Cimplex solid modeling and numerical control system. Before that, he was Principal Project Director for International Computers Ltd. in the United Kingdom, delivering major projects for NATO and leading multinationals. He was also design and development manager for ICL's 2900 IDMS product. He spent the first 7 years of his career working in defense and government systems. Leon has a B.S. degree in Electronic Engineering from the University of Wales.
ZIO-Direct allows direct style programming with ZIO. This library provides a *syntactic sugar* that is more powerful than for-comprehensions as well as more natural to use. Simply add the `.run` suffix to any ZIO effect in order to retrieve it's value.
Scala Intro training @ Lohika, Odessa, UA.
This is a basic Scala Programming Language overview intended to evangelize the language among any-language programmers.
Download for better quality.
Monads do not Compose. Not in a generic way - There is no general way of composing monads.
A comment from Rúnar Bjarnason, coauthor of FP in Scala: "They do compose in a different generic way. For any two monads F and G we can take the coproduct which is roughly Free of Either F or G (up to normalization)".
Another comment from Sergei Winitzki (which caused me to upload https://www.slideshare.net/pjschwarz/addendum-to-monads-do-not-compose): "It is a mistake to think that a traversable monad can be composed with another monad. It is true that, given `Traversable`, you can implement the monad's methods (pure and flatMap) for the composition with another monad (as in your slides 21 to 26), but this is a deceptive appearance. The laws of the `Traversable` typeclass are far insufficient to guarantee the laws of the resulting composed monad. The only traversable monads that work correctly are Option, Either, and Writer. It is true that you can implement the type signature of the `swap` function for any `Traversable` monad. However, the `swap` function for monads needs to satisfy very different and stronger laws than the `sequence` function from the `Traversable` type class. I'll have to look at the "Book of Monads"; but, if my memory serves, the FPiS book does not derive any of these laws." See https://www.linkedin.com/feed/update/urn:li:groupPost:41001-6523141414614814720?commentUrn=urn%3Ali%3Acomment%3A%28groupPost%3A41001-6523141414614814720%2C6532108273053761536%29
(Video of these slides here http://fsharpforfunandprofit.com/rop)
(My response to "this is just Either" here: http://fsharpforfunandprofit.com/rop/#monads)
Many examples in functional programming assume that you are always on the "happy path". But to create a robust real world application you must deal with validation, logging, network and service errors, and other annoyances.
So, how do you handle all this in a clean functional way? This talk will provide a brief introduction to this topic, using a fun and easy-to-understand railway analogy.
Purely functional libraries like ZIO can help you build high-performance, concurrent applications that don’t have deadlocks, don’t leak resources using purely functional code.
In this talk, Wiem will walk you through how to build a control system for the elevators at a fictional hotel, H&A Hotel. You’ll learn how to use basic control structures like Ref, Queue, STM and ZIO to build real world software.
Functional Programming Patterns (NDC London 2014)Scott Wlaschin
(video of these slides available here http://fsharpforfunandprofit.com/fppatterns/)
In object-oriented development, we are all familiar with design patterns such as the Strategy pattern and Decorator pattern, and design principles such as SOLID.
The functional programming community has design patterns and principles as well.
This talk will provide an overview of some of these, and present some demonstrations of FP design in practice.
Slidedeck presented at http://devternity.com/ around MongoDB internals. We review the usage patterns of MongoDB, the different storage engines and persistency models as well has the definition of documents and general data structures.
ZIO: Powerful and Principled Functional Programming in ScalaWiem Zine Elabidine
This is an introduction of purely functional programming type safe abstractions that provide a variety of features for building asynchronous and concurrent applications data structures built on ZIO.
You'll learn by examples about the power of functional programming to solve the hard problems of software development in a principled, without compromises.
This tutorial will provide you with a basic understanding of graph database technology and the ability to quickly begin development of a graph database application. You will have the capability to recognize graph-based problems and present the benefits of using graph technology for problem resolution.
The tutorial will give you an understanding of:
• Graph theory - origins and concepts
• Benefits of graph databases
• Different types of graph databases
• Typical graph database API
• Programming basics
• Use cases
Bring your laptops for a hands-on opportunity to practice some sample codes. A basic understanding of Java programming is a recommended prerequisite to understand this course. This session is led by the InfiniteGraph technical team and the demonstration code will be drawn from InfiniteGraph examples, however the broader educational presentation is product-neutral and not a commercial presentation of their products.
To participate in the hands-on portion of the graph tutorial users must have:
• Java programming experience
• Java Developer Kit (JDK)
• Current InfiniteGraph installed on laptop. (To download visit www.objectivity.com/infinitegraph)
• HelloGraph test – Upon installing IG, run HelloGraph to test the install. (HelloGraph can be found online at http://wiki.infinitegraph.com/2.1/w/index.php?title=Download_Sample_Code)
Leon Guzenda was one of the founding members of Objectivity in 1988 and one of the original architects of Objectivity/DB. He currently works with Objectivity's major customers to help them effectively develop and deploy complex applications and systems that use the industry's highest-performing, most reliable DBMS technology, Objectivity/DB. He also liaises with technology partners and industry groups to help ensure that Objectivity/DB remains at the forefront of database and distributed computing technology. Leon has more than 35 years experience in the software industry. At Automation Technology Products, he managed the development of the ODBMS for the Cimplex solid modeling and numerical control system. Before that, he was Principal Project Director for International Computers Ltd. in the United Kingdom, delivering major projects for NATO and leading multinationals. He was also design and development manager for ICL's 2900 IDMS product. He spent the first 7 years of his career working in defense and government systems. Leon has a B.S. degree in Electronic Engineering from the University of Wales.
ZIO-Direct allows direct style programming with ZIO. This library provides a *syntactic sugar* that is more powerful than for-comprehensions as well as more natural to use. Simply add the `.run` suffix to any ZIO effect in order to retrieve it's value.
Scala Intro training @ Lohika, Odessa, UA.
This is a basic Scala Programming Language overview intended to evangelize the language among any-language programmers.
Download for better quality.
Monads do not Compose. Not in a generic way - There is no general way of composing monads.
A comment from Rúnar Bjarnason, coauthor of FP in Scala: "They do compose in a different generic way. For any two monads F and G we can take the coproduct which is roughly Free of Either F or G (up to normalization)".
Another comment from Sergei Winitzki (which caused me to upload https://www.slideshare.net/pjschwarz/addendum-to-monads-do-not-compose): "It is a mistake to think that a traversable monad can be composed with another monad. It is true that, given `Traversable`, you can implement the monad's methods (pure and flatMap) for the composition with another monad (as in your slides 21 to 26), but this is a deceptive appearance. The laws of the `Traversable` typeclass are far insufficient to guarantee the laws of the resulting composed monad. The only traversable monads that work correctly are Option, Either, and Writer. It is true that you can implement the type signature of the `swap` function for any `Traversable` monad. However, the `swap` function for monads needs to satisfy very different and stronger laws than the `sequence` function from the `Traversable` type class. I'll have to look at the "Book of Monads"; but, if my memory serves, the FPiS book does not derive any of these laws." See https://www.linkedin.com/feed/update/urn:li:groupPost:41001-6523141414614814720?commentUrn=urn%3Ali%3Acomment%3A%28groupPost%3A41001-6523141414614814720%2C6532108273053761536%29
(Video of these slides here http://fsharpforfunandprofit.com/rop)
(My response to "this is just Either" here: http://fsharpforfunandprofit.com/rop/#monads)
Many examples in functional programming assume that you are always on the "happy path". But to create a robust real world application you must deal with validation, logging, network and service errors, and other annoyances.
So, how do you handle all this in a clean functional way? This talk will provide a brief introduction to this topic, using a fun and easy-to-understand railway analogy.
Purely functional libraries like ZIO can help you build high-performance, concurrent applications that don’t have deadlocks, don’t leak resources using purely functional code.
In this talk, Wiem will walk you through how to build a control system for the elevators at a fictional hotel, H&A Hotel. You’ll learn how to use basic control structures like Ref, Queue, STM and ZIO to build real world software.
Functional Programming Patterns (NDC London 2014)Scott Wlaschin
(video of these slides available here http://fsharpforfunandprofit.com/fppatterns/)
In object-oriented development, we are all familiar with design patterns such as the Strategy pattern and Decorator pattern, and design principles such as SOLID.
The functional programming community has design patterns and principles as well.
This talk will provide an overview of some of these, and present some demonstrations of FP design in practice.
Architectural Patterns in Building Modular Domain ModelsDebasish Ghosh
The main theme of the talk is how to use algebraic and functional techniques to build modular domain models that are pure and compositional even in the presence of side-effects. I discuss the use of pure algebraic effects to abstract side-effects thereby keeping the model compositional.
Static abstract members nelle interfacce di C# 11 e dintorni di .NET 7.pptxMarco Parenzan
Did interfaces in C# need evolution? Maybe yes. Are they violating some fundamental principles? We see. Are we asking for some hoops? Let's see all this by telling a story (of code, of course)
This is going to be a discussion about design patterns. But I promise it’s going to be very different from the Gang of Four patterns that we all have used and loved in Java.
It doesn’t have any mathematics or category theory - it’s about developing an insight that lets u identify code structures that u think may be improved with a beautiful transformation of an algebraic pattern.
In earlier days of Java coding we used to feel proud when we could locate a piece of code that could be transformed into an abstract factory and the factory bean could be injected using Spring DI. The result was we ended up maintaining not only Java code, but quite a bit of XML too, untyped and unsafe. This was the DI pattern in full glory. In this session we will discuss patterns that don’t look like external artifacts, they are part of the language, they have some mathematical foundations in the sense that they have an algebra that actually compose and compose organically to evolve larger abstractions.
ActionScript is a object oriented scripting language. Like ECMAScript the Actionscript is similar to the java script. Actionscript provides the interactive functionalitry to the the web site. Actionscript is mostly used in the flash software developer can set and control the actions of the Flash objects. Actionscript provide the additional features to the animation with flash and to create advance interactive animations and applications for the users. Actionscript is used for the kids tutorials and games so that kids can understand the lessons more easily. This is used by many advertisement companies to create the advertisements banners with flash and small animations http://www.myassignmenthelp.net/programming-assignment-help.php
This is an intermediate conversion course for C++, suitable for second year computing students who may have learned Java or another language in first year.
Scala: Object-Oriented Meets Functional, by Iulian Dragos3Pillar Global
A presentation from Iulian Dragos of Typesafe that gives an overview of the Scala programming language. The presentation was given at a Functional Angle conference in Timisoara, Romania sponsored by 3Pillar. Iulian Dragos has been working on Scala since 2004. He currently works for Typesafe, a start-up that was co-founded by Scala’s creator, Martin Odersky.
DSL - expressive syntax on top of a clean semantic modelDebasish Ghosh
Does a DSL mean compromising the domain model purity for an ultra-expressive syntax. This presentation discusses how to evolve your DSL syntax as a sublanguage of combinators on top of an expressive domain model.
Prosigns: Transforming Business with Tailored Technology SolutionsProsigns
Unlocking Business Potential: Tailored Technology Solutions by Prosigns
Discover how Prosigns, a leading technology solutions provider, partners with businesses to drive innovation and success. Our presentation showcases our comprehensive range of services, including custom software development, web and mobile app development, AI & ML solutions, blockchain integration, DevOps services, and Microsoft Dynamics 365 support.
Custom Software Development: Prosigns specializes in creating bespoke software solutions that cater to your unique business needs. Our team of experts works closely with you to understand your requirements and deliver tailor-made software that enhances efficiency and drives growth.
Web and Mobile App Development: From responsive websites to intuitive mobile applications, Prosigns develops cutting-edge solutions that engage users and deliver seamless experiences across devices.
AI & ML Solutions: Harnessing the power of Artificial Intelligence and Machine Learning, Prosigns provides smart solutions that automate processes, provide valuable insights, and drive informed decision-making.
Blockchain Integration: Prosigns offers comprehensive blockchain solutions, including development, integration, and consulting services, enabling businesses to leverage blockchain technology for enhanced security, transparency, and efficiency.
DevOps Services: Prosigns' DevOps services streamline development and operations processes, ensuring faster and more reliable software delivery through automation and continuous integration.
Microsoft Dynamics 365 Support: Prosigns provides comprehensive support and maintenance services for Microsoft Dynamics 365, ensuring your system is always up-to-date, secure, and running smoothly.
Learn how our collaborative approach and dedication to excellence help businesses achieve their goals and stay ahead in today's digital landscape. From concept to deployment, Prosigns is your trusted partner for transforming ideas into reality and unlocking the full potential of your business.
Join us on a journey of innovation and growth. Let's partner for success with Prosigns.
Providing Globus Services to Users of JASMIN for Environmental Data AnalysisGlobus
JASMIN is the UK’s high-performance data analysis platform for environmental science, operated by STFC on behalf of the UK Natural Environment Research Council (NERC). In addition to its role in hosting the CEDA Archive (NERC’s long-term repository for climate, atmospheric science & Earth observation data in the UK), JASMIN provides a collaborative platform to a community of around 2,000 scientists in the UK and beyond, providing nearly 400 environmental science projects with working space, compute resources and tools to facilitate their work. High-performance data transfer into and out of JASMIN has always been a key feature, with many scientists bringing model outputs from supercomputers elsewhere in the UK, to analyse against observational or other model data in the CEDA Archive. A growing number of JASMIN users are now realising the benefits of using the Globus service to provide reliable and efficient data movement and other tasks in this and other contexts. Further use cases involve long-distance (intercontinental) transfers to and from JASMIN, and collecting results from a mobile atmospheric radar system, pushing data to JASMIN via a lightweight Globus deployment. We provide details of how Globus fits into our current infrastructure, our experience of the recent migration to GCSv5.4, and of our interest in developing use of the wider ecosystem of Globus services for the benefit of our user community.
Your Digital Assistant.
Making complex approach simple. Straightforward process saves time. No more waiting to connect with people that matter to you. Safety first is not a cliché - Securely protect information in cloud storage to prevent any third party from accessing data.
Would you rather make your visitors feel burdened by making them wait? Or choose VizMan for a stress-free experience? VizMan is an automated visitor management system that works for any industries not limited to factories, societies, government institutes, and warehouses. A new age contactless way of logging information of visitors, employees, packages, and vehicles. VizMan is a digital logbook so it deters unnecessary use of paper or space since there is no requirement of bundles of registers that is left to collect dust in a corner of a room. Visitor’s essential details, helps in scheduling meetings for visitors and employees, and assists in supervising the attendance of the employees. With VizMan, visitors don’t need to wait for hours in long queues. VizMan handles visitors with the value they deserve because we know time is important to you.
Feasible Features
One Subscription, Four Modules – Admin, Employee, Receptionist, and Gatekeeper ensures confidentiality and prevents data from being manipulated
User Friendly – can be easily used on Android, iOS, and Web Interface
Multiple Accessibility – Log in through any device from any place at any time
One app for all industries – a Visitor Management System that works for any organisation.
Stress-free Sign-up
Visitor is registered and checked-in by the Receptionist
Host gets a notification, where they opt to Approve the meeting
Host notifies the Receptionist of the end of the meeting
Visitor is checked-out by the Receptionist
Host enters notes and remarks of the meeting
Customizable Components
Scheduling Meetings – Host can invite visitors for meetings and also approve, reject and reschedule meetings
Single/Bulk invites – Invitations can be sent individually to a visitor or collectively to many visitors
VIP Visitors – Additional security of data for VIP visitors to avoid misuse of information
Courier Management – Keeps a check on deliveries like commodities being delivered in and out of establishments
Alerts & Notifications – Get notified on SMS, email, and application
Parking Management – Manage availability of parking space
Individual log-in – Every user has their own log-in id
Visitor/Meeting Analytics – Evaluate notes and remarks of the meeting stored in the system
Visitor Management System is a secure and user friendly database manager that records, filters, tracks the visitors to your organization.
"Secure Your Premises with VizMan (VMS) – Get It Now"
Listen to the keynote address and hear about the latest developments from Rachana Ananthakrishnan and Ian Foster who review the updates to the Globus Platform and Service, and the relevance of Globus to the scientific community as an automation platform to accelerate scientific discovery.
Advanced Flow Concepts Every Developer Should KnowPeter Caitens
Tim Combridge from Sensible Giraffe and Salesforce Ben presents some important tips that all developers should know when dealing with Flows in Salesforce.
Globus Connect Server Deep Dive - GlobusWorld 2024Globus
We explore the Globus Connect Server (GCS) architecture and experiment with advanced configuration options and use cases. This content is targeted at system administrators who are familiar with GCS and currently operate—or are planning to operate—broader deployments at their institution.
Paketo Buildpacks : la meilleure façon de construire des images OCI? DevopsDa...Anthony Dahanne
Les Buildpacks existent depuis plus de 10 ans ! D’abord, ils étaient utilisés pour détecter et construire une application avant de la déployer sur certains PaaS. Ensuite, nous avons pu créer des images Docker (OCI) avec leur dernière génération, les Cloud Native Buildpacks (CNCF en incubation). Sont-ils une bonne alternative au Dockerfile ? Que sont les buildpacks Paketo ? Quelles communautés les soutiennent et comment ?
Venez le découvrir lors de cette session ignite
OpenFOAM solver for Helmholtz equation, helmholtzFoam / helmholtzBubbleFoamtakuyayamamoto1800
In this slide, we show the simulation example and the way to compile this solver.
In this solver, the Helmholtz equation can be solved by helmholtzFoam. Also, the Helmholtz equation with uniformly dispersed bubbles can be simulated by helmholtzBubbleFoam.
Climate Science Flows: Enabling Petabyte-Scale Climate Analysis with the Eart...Globus
The Earth System Grid Federation (ESGF) is a global network of data servers that archives and distributes the planet’s largest collection of Earth system model output for thousands of climate and environmental scientists worldwide. Many of these petabyte-scale data archives are located in proximity to large high-performance computing (HPC) or cloud computing resources, but the primary workflow for data users consists of transferring data, and applying computations on a different system. As a part of the ESGF 2.0 US project (funded by the United States Department of Energy Office of Science), we developed pre-defined data workflows, which can be run on-demand, capable of applying many data reduction and data analysis to the large ESGF data archives, transferring only the resultant analysis (ex. visualizations, smaller data files). In this talk, we will showcase a few of these workflows, highlighting how Globus Flows can be used for petabyte-scale climate analysis.
Quarkus Hidden and Forbidden ExtensionsMax Andersen
Quarkus has a vast extension ecosystem and is known for its subsonic and subatomic feature set. Some of these features are not as well known, and some extensions are less talked about, but that does not make them less interesting - quite the opposite.
Come join this talk to see some tips and tricks for using Quarkus and some of the lesser known features, extensions and development techniques.
How Does XfilesPro Ensure Security While Sharing Documents in Salesforce?XfilesPro
Worried about document security while sharing them in Salesforce? Fret no more! Here are the top-notch security standards XfilesPro upholds to ensure strong security for your Salesforce documents while sharing with internal or external people.
To learn more, read the blog: https://www.xfilespro.com/how-does-xfilespro-make-document-sharing-secure-and-seamless-in-salesforce/
How Recreation Management Software Can Streamline Your Operations.pptxwottaspaceseo
Recreation management software streamlines operations by automating key tasks such as scheduling, registration, and payment processing, reducing manual workload and errors. It provides centralized management of facilities, classes, and events, ensuring efficient resource allocation and facility usage. The software offers user-friendly online portals for easy access to bookings and program information, enhancing customer experience. Real-time reporting and data analytics deliver insights into attendance and preferences, aiding in strategic decision-making. Additionally, effective communication tools keep participants and staff informed with timely updates. Overall, recreation management software enhances efficiency, improves service delivery, and boosts customer satisfaction.
Designing for Privacy in Amazon Web ServicesKrzysztofKkol1
Data privacy is one of the most critical issues that businesses face. This presentation shares insights on the principles and best practices for ensuring the resilience and security of your workload.
Drawing on a real-life project from the HR industry, the various challenges will be demonstrated: data protection, self-healing, business continuity, security, and transparency of data processing. This systematized approach allowed to create a secure AWS cloud infrastructure that not only met strict compliance rules but also exceeded the client's expectations.
In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I ...Juraj Vysvader
In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I didn't get rich from it but it did have 63K downloads (powered possible tens of thousands of websites).
Cyaniclab : Software Development Agency Portfolio.pdfCyanic lab
CyanicLab, an offshore custom software development company based in Sweden,India, Finland, is your go-to partner for startup development and innovative web design solutions. Our expert team specializes in crafting cutting-edge software tailored to meet the unique needs of startups and established enterprises alike. From conceptualization to execution, we offer comprehensive services including web and mobile app development, UI/UX design, and ongoing software maintenance. Ready to elevate your business? Contact CyanicLab today and let us propel your vision to success with our top-notch IT solutions.
How to Position Your Globus Data Portal for Success Ten Good PracticesGlobus
Science gateways allow science and engineering communities to access shared data, software, computing services, and instruments. Science gateways have gained a lot of traction in the last twenty years, as evidenced by projects such as the Science Gateways Community Institute (SGCI) and the Center of Excellence on Science Gateways (SGX3) in the US, The Australian Research Data Commons (ARDC) and its platforms in Australia, and the projects around Virtual Research Environments in Europe. A few mature frameworks have evolved with their different strengths and foci and have been taken up by a larger community such as the Globus Data Portal, Hubzero, Tapis, and Galaxy. However, even when gateways are built on successful frameworks, they continue to face the challenges of ongoing maintenance costs and how to meet the ever-expanding needs of the community they serve with enhanced features. It is not uncommon that gateways with compelling use cases are nonetheless unable to get past the prototype phase and become a full production service, or if they do, they don't survive more than a couple of years. While there is no guaranteed pathway to success, it seems likely that for any gateway there is a need for a strong community and/or solid funding streams to create and sustain its success. With over twenty years of examples to draw from, this presentation goes into detail for ten factors common to successful and enduring gateways that effectively serve as best practices for any new or developing gateway.
Globus Compute wth IRI Workflows - GlobusWorld 2024Globus
As part of the DOE Integrated Research Infrastructure (IRI) program, NERSC at Lawrence Berkeley National Lab and ALCF at Argonne National Lab are working closely with General Atomics on accelerating the computing requirements of the DIII-D experiment. As part of the work the team is investigating ways to speedup the time to solution for many different parts of the DIII-D workflow including how they run jobs on HPC systems. One of these routes is looking at Globus Compute as a way to replace the current method for managing tasks and we describe a brief proof of concept showing how Globus Compute could help to schedule jobs and be a tool to connect compute at different facilities.
Multiple Your Crypto Portfolio with the Innovative Features of Advanced Crypt...Hivelance Technology
Cryptocurrency trading bots are computer programs designed to automate buying, selling, and managing cryptocurrency transactions. These bots utilize advanced algorithms and machine learning techniques to analyze market data, identify trading opportunities, and execute trades on behalf of their users. By automating the decision-making process, crypto trading bots can react to market changes faster than human traders
Hivelance, a leading provider of cryptocurrency trading bot development services, stands out as the premier choice for crypto traders and developers. Hivelance boasts a team of seasoned cryptocurrency experts and software engineers who deeply understand the crypto market and the latest trends in automated trading, Hivelance leverages the latest technologies and tools in the industry, including advanced AI and machine learning algorithms, to create highly efficient and adaptable crypto trading bots
3. Functional Programming
• programming with pure functions
• a function’s output is solely determined by the input
(much like mathematical functions)
• no assignment, no side-effects
•(pure) mapping between values
• functions compose
• expression-oriented programming
7. What is an Algebra ?
Algebra is the study of algebraic structures
In mathematics, and more specifically in abstract
algebra, an algebraic structure is
a set (called carrier set or underlying set)
with one or more finitary operations defined on it
that satisfies a list of axioms
-Wikipedia
(https://en.wikipedia.org/wiki/Algebraic_structure)
8. Set A
ϕ : A × A → A
fo r (a, b) ∈ A
ϕ(a, b)
a ϕ b
given
a binary operation
for specific a, b
or
The Algebra of Sets
9. Algebraic Thinking
• Thinking and reasoning about code in terms of the
data types and the operations they support
without considering a bit about the underlying
implementations
• f: A => B and g: B => C, we should be able to
reason that we can compose f and g algebraically
to build a larger function h: A => C
•algebraic composition
13. What is a domain model ?
A domain model in problem solving and software engineering is a
conceptual model of all the topics related to a specific problem. It
describes the various entities, their attributes, roles, and
relationships, plus the constraints that govern the problem domain.
It does not describe the solutions to the problem.
Wikipedia (http://en.wikipedia.org/wiki/Domain_model)
20. A Bounded Context
• has a consistent vocabulary
• a set of domain behaviors modeled as
functions on domain objects
implemented as types
• each of the behaviors honor a set of
business rules
• related behaviors grouped as modules
21. Domain Model = ∪(i) Bounded Context(i)
Bounded Context = { m[T1,T2,..] | T(i) ∈ Types }
Module = { f(x,y,..) | p(x,y) ∈ Domain Rules }
• domain function
• on an object of types x, y, ..
• composes with other functions
• closed under composition
• business rules
23. explicit verifiable
• types
• type constraints
• functions between types
• type constraints
• more constraints if you have DT
• algebraic property based testing
(algebra of types, functions & laws
of the solution domain model)
Domain Model Algebra
24. What is meant by the
algebra of a type ?
•Nothing
•Unit
•Boolean
•Byte
•String
25. What is meant by the
algebra of a type ?
•Nothing -> 0
•Unit -> 1
•Boolean -> 2
•Byte -> 256
•String -> a lot
26. What is meant by the
algebra of a type ?
•(Boolean, Unit)
•(Byte, Unit)
•(Byte, Boolean)
•(Byte, Byte)
•(String, String)
27. What is meant by the
algebra of a type ?
•(Boolean, Unit) -> 2x1 = 2
•(Byte, Unit) -> 256x1 = 256
•(Byte, Boolean) -> 256x2 = 512
•(Byte, Byte) -> 256x256 = 65536
•(String, String) -> a lot
28. What is meant by the
algebra of a type ?
• Quiz: Generically, how many inhabitants can we
have for a type (a, b)?
• Answer: 1 inhabitant for each combination of
a’s and b’s (a x b)
29. Product Types
• Ordered pairs of values one from each type in
the order specified - this and that
• Can be generalized to a finite product indexed by
a finite set of indices
30. Product Types in Scala
type Point = (Int, Int)
val p = (10, 12)
case class Account(no: String,
name: String,
address: String,
dateOfOpening: Date,
dateOfClosing: Option[Date]
)
31. What is meant by the
algebra of a type ?
•Boolean or Unit
•Byte or Unit
•Byte or Boolean
•Byte or Byte
•String or String
32. What is meant by the
algebra of a type ?
•Boolean or Unit -> 2+1 = 3
•Byte or Unit -> 256+1 = 257
•Byte or Boolean -> 256+2 = 258
•Byte or Byte -> 256+256 = 512
•String or String -> a lot
33. Sum Types
• Model data structures involving alternatives -
this or that
• A tree can have a leaf or an internal node which,
is again a tree
• In Scala, a sum type is usually referred to as an
Algebraic DataType (ADT)
34. Sum Types in Scala
sealed trait Shape
case class Circle(origin: Point,
radius: BigDecimal) extends Shape
case class Rectangle(diag_1: Point,
diag_2: Point) extends Shape
35. Sum Types are
Expressive
• Booleans - true or false
• Enumerations - sum types may be used to define finite
enumeration types, whose values are one of an explicitly
specified finite set
• Optionality - the Option data type in Scala is encoded using a
sum type
• Disjunction - this or that, the Either data type in Scala
• Failure encoding - the Try data type in Scala to indicate that
the computation may raise an exception
36. sealed trait InstrumentType
case object CCY extends InstrumentType
case object EQ extends InstrumentType
case object FI extends InstrumentType
sealed trait Instrument {
def instrumentType: InstrumentType
}
case class Equity(isin: String, name: String, issueDate: Date,
faceValue: Amount) extends Instrument {
final val instrumentType = EQ
}
case class FixedIncome(isin: String, name: String, issueDate: Date,
maturityDate: Option[Date], nominal: Amount) extends Instrument {
final val instrumentType = FI
}
case class Currency(isin: String) extends Instrument {
final val instrumentType = CCY
}
37. De-structuring with
Pattern Matching
def process(i: Instrument) = i match {
case Equity(isin, _, _, faceValue) => // ..
case FixedIncome(isin, _, issueDate, _, nominal) => // ..
case Currency(isin) => // ..
}
39. Sum Types and Domain
Models
• Models heterogeneity and heterogenous data
structures are ubiquitous in a domain model
• Allows modeling of expressive domain types in a
succinct and secure way - secure by construction
• Pattern matching makes encoding domain logic
easy and expressive
40. – Robert Harper in Practical Foundations of Programming Languages
“The absence of sums is the origin of C. A. R.
Hoare’s self-described ‘billion dollar mistake,’
the null pointer”
41. More algebra of types
• Exponentiation - f: A => B has b^a
inhabitants
• Taylor Series - Recursive Data Types
• Derivatives - Zippers
• …
42. Scaling of the Algebra
• Since a function is a mapping from the domain of types
to the co-domain of types, we can talk about the
algebra of a function
• A module is a collection of related functions - we can
think of the algebra of a module as the union of
the algebras of all functions that it encodes
• A domain model (one bounded context) can be loosely
thought of as a collection of modules, which gives rise
to the connotation of a domain model algebra
43. Algebraic Composition
• Functions compose based on types, which
means ..
• Algebras compose
• Giving rise to larger algebras / functions, which
in turn implies ..
• We can construct larger domain behaviors by
composing smaller behaviors
44. Algebras are Ubiquitous
• Generic, parametric and hence usable on an
infinite set of data types, including your domain
model’s types
45. Algebras are Ubiquitous
• Generic, parametric and hence usable on an
infinite set of data types, including your domain
model’s types
• Clear separation between the contract (the
algebra) and its implementations
(interpreters)
46. Algebras are Ubiquitous
• Generic, parametric and hence usable on an
infinite set of data types, including your domain
model’s types
• Clear separation between the contract (the
algebra) and its implementations
(interpreters)
• Standard vocabulary (like design patterns)
47. Algebras are Ubiquitous
• Generic, parametric and hence usable on an
infinite set of data types, including your domain
model’s types
• Clear separation between the contract (the
algebra) and its implementations (interpreters)
• Standard vocabulary (like design patterns)
• Existing set of reusable algebras offered by the
standard libraries
48. Roadmap to a Functional
and Algebraic Model
1. Identify domain behaviors
2. Identify the algebras of functions (not implementation)
3. Compose algebras to form larger behaviors - follow
the types depending on the semantics of
compositionality.We call this behavior a program that
models the use case
4. Plug in concrete types to complete the
implementation
49. Domain Model = ∪(i) Bounded Context(i)
Bounded Context = { m[T1,T2,..] | T(i) ∈ Types }
Module = { f(x,y,..) | p(x,y) ∈ Domain Rules }
• domain function
• on an object of types x, y
• composes with other functions
• closed under composition
• business rules
50. Domain Model = ∪(i) Bounded Context(i)
Bounded Context = { m[T1,T2,..] | T(i) ∈ Types }
Module = { f(x,y,..) | p(x,y) ∈ Domain Rules }
• domain function
• on an object of types x, y
• composes with other functions
• closed under composition
• business rules
Domain Algebra
Domain Algebra
51. Given all the properties of algebra, can we
consider algebraic composition to be the
basis of designing, implementing and modularizing
domain models ?
53. Client places order
- flexible format
Transform to internal domain
model entity and place for execution
1 2
54. Client places order
- flexible format
Transform to internal domain
model entity and place for execution
Trade & Allocate to
client accounts
1 2
3
55. def fromClientOrder: ClientOrder => Order
def execute(market: Market, brokerAccount: Account)
: Order => List[Execution]
def allocate(accounts: List[Account])
: List[Execution] => List[Trade]
trait Trading {
}
trait TradeComponent extends Trading
with Logging with Auditing
algebra of domain
behaviors / functions
functions aggregate
upwards into modules
modules aggregate
into larger modules
56. .. so we have a decent algebra of our module, the
names reflect the appropriate artifacts from the
domain (ubiquitous language), the types are
well published and we are quite explicit in what
the behaviors do ..
57. 1. Compositionality - How do we compose
the 3 behaviors that we published to
generate trade in the market and allocate
to client accounts ?
2. Side-effects - We need to compose them
alongside all side-effects that form a core
part of all non trivial domain model
implementations
58. • Error handling ?
• throw / catch exceptions is not RT
• Partiality ?
• partial functions can report runtime exceptions if invoked
with unhandled arguments (violates RT)
• Reading configuration information from environment ?
• may result in code repetition if not properly handled
• Logging ?
• side-effects
Side-effects
59. Side-effects
• Database writes
• Writing to a message queue
• Reading from stdin / files
• Interacting with any external resource
• Changing state in place
67. F[A]
The answer that the
effect computesThe additional stuff
modeling the computation
68. • The F[_] that we saw is an opaque type - it
has no denotation till we give it one
• The denotation that we give to F[_] depends
on the semantics of compositionality that we
would like to have for our domain model
behaviors
70. • Just the Algebra
• No denotation, no
concrete type
• Explicitly stating that we
have effectful functions
here
def fromClientOrder: ClientOrder => F[Order]
def execute(market: Market, brokerAccount: Account)
: Order => F[List[Execution]]
def allocate(accounts: List[Account])
: List[Execution] => F[List[Trade]]
trait Trading[F[_]] {
}
Effect Type
71. • .. we have intentionally kept the algebra open
for interpretation ..
• .. there are use cases where you would like to
have multiple interpreters for the same
algebra ..
72. The Program
def tradeGeneration[M[_]: Monad](T: Trading[M]) = for {
order <- T.fromClientOrder(cor)
executions <- T.execute(m1, ba, order)
trades <- T.allocate(List(ca1, ca2, ca3), executions)
} yield trades
73. class TradingInterpreter[F[_]]
(implicit me: MonadError[F, Throwable])
extends Trading[F] {
def fromClientOrder: ClientOrder => F[Order] = makeOrder(_) match {
case Left(dv) => me.raiseError(new Exception(dv.message))
case Right(o) => o.pure[F]
}
def execute(market: Market, brokerAccount: Account)
: Order => F[List[Execution]] = ...
def allocate(accounts: List[Account])
: List[Execution] => F[List[Trade]] = ...
}
One Sample Interpreter
74. • .. one lesson in modularity - commit to a
concrete implementation as late as
possible in the design ..
• .. we have just indicated that we want a
monadic effect - we haven’t committed to
any concrete monad type even in the
interpreter ..
75. The Program
def tradeGeneration[M[_]: Monad](T: Trading[M]) = for {
order <- T.fromClientOrder(cor)
executions <- T.execute(m1, ba, order)
trades <- T.allocate(List(ca1, ca2, ca3), executions)
} yield trades
import cats.effect.IO
object TradingComponent extends TradingInterpreter[IO]
tradeGeneration(TradingComponent).unsafeRunSync
76. The Program
def tradeGeneration[M[_]: Monad](T: Trading[M]) = for {
order <- T.fromClientOrder(cor)
executions <- T.execute(m1, ba, order)
trades <- T.allocate(List(ca1, ca2, ca3), executions)
} yield trades
import monix.eval.Task
object TradingComponent extends TradingInterpreter[Task]
tradeGeneration(TradingComponent)
77. The Program
def tradeGenerationLoggable[M[_]: Monad]
(T: Trading[M], L: Logging[M]) = for {
_ <- L.info("starting order processing")
order <- T.fromClientOrder(cor)
executions <- T.execute(m1, ba, order)
trades <- T.allocate(List(ca1, ca2, ca3), executions)
_ <- L.info("allocation done")
} yield trades
object TradingComponent extends TradingInterpreter[IO]
object LoggingComponent extends LoggingInterpreter[IO]
tradeGenerationLoggable(TradingComponent, LoggingComponent).unsafeRunSync
81. - Rob Norris at scale.bythebay.io talk - 2017 (https://www.youtube.com/
watch?v=po3wmq4S15A)
“Effects and side-effects are not the same thing. Effects are
good, side-effects are bugs.Their lexical similarity is really
unfortunate because people often conflate the two ideas”
82.
83.
84.
85. Takeaways
• Algebra scales from that of one single data type to
an entire bounded context
• Algebras compose enabling composition of
domain behaviors
• Algebras let you focus on the compositionality
without any context of implementation
• Statically typed functional programming is
programming with algebras
86. Takeaways
• Abstract early, interpret as late as possible
• Abstractions / functions compose only when they are
abstract and parametric
• Modularity in the presence of side-effects is a challenge
• Effects as algebras are pure values that can compose based
on laws
• Honor the law of using the least powerful abstraction
that works
87. From the Bible
“Name classes and operations to describe their effect and purpose,
without reference to the means by which they do what they
promise.This relieves the client developer of the need to understand
the internals.These names should conform to the UBIQUITOUS
LANGUAGE so that team members can quickly infer their meaning.
Write a test for a behavior before creating it, to force your thinking
into client developer mode.”
- Eric Evans (Domain Driven Design)
in the chapter on Supple Design, while discussing
Intention Revealing Interfaces
88. • All names are from the domain vocabulary
• Just the algebra describing the promise, no
implementation details
• Purpose and effect explicit - yes, literally
explicit with effects
def fromClientOrder: ClientOrder => F[Order]
def execute(market: Market, brokerAccount: Account)
: Order => F[List[Execution]]
def allocate(accounts: List[Account])
: List[Execution] => F[List[Trade]]
trait Trading[F[_]] {
}
89. From the Bible
“Place as much of the logic of the program as possible into
functions, operations that return results with no observable side-
effects.”
- Eric Evans (Domain Driven Design)
in the chapter on Supple Design, while discussing
Side-Effect-Free Functions
90. def tradeGeneration[M[_]: Monad](T: Trading[M]) = for {
order <- T.fromClientOrder(cor)
executions <- T.execute(m1, ba, order)
trades <- T.allocate(List(ca1, ca2, ca3), executions)
} yield trades
• The program tradeGeneration is completely side-effect free. It
generates a pure value.
• Since the program is pure, you can interpret it in many ways (as we saw
earlier).
• The side-effects occur only when you submit the program to the run time
system.
• This is also an example where using algebraic & functional approach we
get a clear separation between the building of an abstraction and
executing it.
91. From the Bible
“When it fits, define an operation whose return type is the same as
the type of its argument(s). If the implementer has state that is
used in the computation, then the implementer is effectively an
argument of the operation, so the argument(s) and return value
should be of the same type as the implementer. Such an operation
is closed under the set of instances of that type.A closed operation
provides a high-level interface without introducing any dependency
on other concepts.”
- Eric Evans (Domain Driven Design)
in the chapter on Supple Design, while discussing
Closure of Operations
92. trait Semigroup[A] {
def combine(x: A, y: A): A
}
trait Monoid[A] extends Semigroup[A] {
def empty: A
}
• With algebraic modeling, you can encode the closure of operations
through the algebra of a Monoid.
★ parametric
★ define the algebra once, implement it as many times based on the
context
★ compositionality at the algebra level
• For stateful computation, use the algebra of the State Monad and
manipulate state as a Monoid