Functional programing jargon

Sep 6, 2016Download as pptx, pdf

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Functional programming concepts like purity, immutability, and side effects can seem intimidating at first. However, they aim to make code more predictable by avoiding state mutations and ensuring the same output is always produced from the same inputs. Key concepts discussed include pure functions that are free of side effects; immutable objects whose state cannot change; partial application of fixing arguments; and currying of transforming functions to chains of functions that each take a single argument to enable easier composition of simple functions into more complex ones. Resources recommended for learning more include functional programming books and libraries like Ramda, RxJS, and Immutable.js.

Functional
Programming
Jargon
A DublinJS lighting talk by Remo H. Jansen

The functional programming jargon is “scary”!
● Function arity
● Pure functions
● Referential transparency
● Side effects
● Partial application
● Currying
● Function Composition
● Lazy evaluation

Fear not my friends!
● Encapsulation
● Class
● Property
● Method
● Object
● Inheritance
● Polymorphism
Do you remember how you felt the first time you encountered the Object-oriented jargon?

Pure Functions
Purity (AKA referential transparency) means “every time you pass the same inputs, you
always get the same outputs”.
A pure function is free of side effects. A side effect refers simply to
the modification of some kind of state.
Any operation which modifies the state of the computer or which
interacts with the outside world is said to have a side effect.

Immutability
An immutable object is an object whose state cannot be modified after it is created. In JavaScript
objects are not immutable and our pure functions should avoid mutating its arguments (side
effect). We can achieve this by using a library like immutable.js and avoiding the JavaScript
mutator methods!

Function Partial Application
Partial application is the process of fixing a number of arguments to a function, producing
another function of smaller arity.
Arity refers to the number of arguments a function can accept. This
might be none, one (unary), two (binary) or more (polyadic). You
can also have functions that take a variable number of arguments,
(variadic functions).

Currying
Currying is the process of taking a function that accepts N arguments and turning it into a
chained series of N functions each taking 1 argument.

Function Composition
The act or mechanism of combining simple functions to build more complicated ones.
Unary functions are easier to compose. Currying helps us to perform function composition.
Functional programming manages complexity via composition as opposed to data encapsulation.

How to learn more?
Books:
● Functional Programming in JavaScript by Dan Mantyla
● Functional Programming in JavaScript by Luis Atencio
● Reactive Programming with RxJS by Sergi Mansilla
Libraries:
● React & Redux
● Ramda
● RxJS
● Immutable
● Cycle

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🔌Tried restarting. 🔁Then updating. 🔎Then Googled a fix. And then it crashed. Guess who has to fix it? You. And who’ll help you? - Scalefusion. Scalefusion steps in with real-time access, not just remote hope. Support for Apple devices that support you (and them) to do more. For more: https://scalefusion.com/remote-access-software-mac https://scalefusion.com/es/remote-access-software-mac https://scalefusion.com/fr/remote-access-software-mac https://scalefusion.com/pt-br/remote-access-software-mac https://scalefusion.com/nl/remote-access-software-mac https://scalefusion.com/de/remote-access-software-mac https://scalefusion.com/ru/remote-access-software-mac

Essentials of Resource Planning in a DownturnOnePlan Solutions

Agentic Techniques in Retrieval-Augmented Generation with Azure AI SearchMaxim Salnikov

Discover how Agentic Retrieval in Azure AI Search takes Retrieval-Augmented Generation (RAG) to the next level by intelligently breaking down complex queries, leveraging full conversation history, and executing parallel searches through a new LLM-powered query planner. This session introduces a cutting-edge approach that delivers significantly more accurate, relevant, and grounded answers—unlocking new capabilities for building smarter, more responsive generative AI applications. Traditional Retrieval-Augmented Generation (RAG) pipelines work well for simple queries—but when users ask complex, multi-part questions or refer to previous conversation history, they often fall short. That’s where Agentic Retrieval comes in: a game-changing advancement in Azure AI Search that brings LLM-powered reasoning directly into the retrieval layer. This session unveils how agentic techniques elevate your RAG-based applications by introducing intelligent query planning, subquery decomposition, parallel execution, and result merging—all orchestrated by a new Knowledge Agent. You’ll learn how this approach significantly boosts relevance, groundedness, and answer quality, especially for sophisticated enterprise use cases. Key takeaways: - Understand the evolution from keyword and vector search to agentic query orchestration - See how full conversation context improves retrieval accuracy - Explore measurable improvements in answer relevance and completeness (up to 40% gains!) - Get hands-on guidance on integrating Agentic Retrieval with Azure AI Foundry and SDKs - Discover how to build scalable, AI-first applications powered by this new paradigm Whether you're building intelligent copilots, enterprise Q&A bots, or AI-driven search solutions, this session will equip you with the tools and patterns to push beyond traditional RAG.

Marketo & Dynamics can be Most Excellent to Each Other – The SequelBradBedford3

So you’ve built trust in your Marketo Engage-Dynamics integration—excellent. But now what? This sequel picks up where our last adventure left off, offering a step-by-step guide to move from stable sync to strategic power moves. We’ll share real-world project examples that empower sales and marketing to work smarter and stay aligned. If you’re ready to go beyond the basics and do truly most excellent stuff, this session is your guide.

The Future of Open Source Reporting Best Alternatives to Jaspersoft.pdfVarsha Nayak

In recent years, organizations have increasingly sought robust open source alternative to Jasper Reports as the landscape of open-source reporting tools rapidly evolves. While Jaspersoft has been a longstanding choice for generating complex business intelligence and analytics reports, factors such as licensing changes and growing demands for flexibility have prompted many businesses to explore other options. Among the most notable alternatives to Jaspersoft, Helical Insight stands out for its powerful open-source architecture, intuitive analytics, and dynamic dashboard capabilities. Designed to be both flexible and budget-friendly, Helical Insight empowers users with advanced features—such as in-memory reporting, extensive data source integration, and customizable visualizations—making it an ideal solution for organizations seeking a modern, scalable reporting platform. This article explores the future of open-source reporting and highlights why Helical Insight and other emerging tools are redefining the standards for business intelligence solutions.

Artificial Intelligence Applications Across IndustriesSandeepKS52

Artificial Intelligence is a rapidly growing field that influences many aspects of modern life, including transportation, healthcare, and finance. Understanding the basics of AI provides insight into how machines can learn and make decisions, which is essential for grasping its applications in various industries. In the automotive sector, AI enhances vehicle safety and efficiency through advanced technologies like self-driving systems and predictive maintenance. Similarly, in healthcare, AI plays a crucial role in diagnosing diseases and personalizing treatment plans, while in financial services, it helps in fraud detection and risk management. By exploring these themes, a clearer picture of AI's transformative impact on society emerges, highlighting both its potential benefits and challenges.

Online Queue Management System for Public Service Offices [Focused on Municip...Rishab Acharya

This report documents the design and development of an Online Queue Management System tailored specifically for municipal offices in Nepal. Municipal offices, as critical providers of essential public services, face challenges including overcrowded queues, long waiting times, and inefficient service delivery, causing inconvenience to citizens and pressure on municipal staff. The proposed digital platform allows citizens to book queue tokens online for various physical services, facilitating efficient queue management and real-time wait time updates. Beyond queue management, the system includes modules to oversee non-physical developmental programs, such as educational and social welfare initiatives, enabling better participation and progress monitoring. Furthermore, it incorporates a module for monitoring infrastructure development projects, promoting transparency and allowing citizens to report issues and track progress. The system development follows established software engineering methodologies, including requirement analysis, UML-based system design, and iterative testing. Emphasis has been placed on user-friendliness, security, and scalability to meet the diverse needs of municipal offices across Nepal. Implementation of this integrated digital platform will enhance service efficiency, increase transparency, and improve citizen satisfaction, thereby supporting the modernization and digital transformation of public service delivery in Nepal.

Automating Map Production With FME and PythonSafe Software

People still love a good paper map, but every time a request lands on a GIS team’s desk, it takes time to create that perfect, individual map—even when you're ready and have projects prepped. Then come the inevitable changes and iterations that add even more time to the process. This presentation explores a solution for automating map production using FME and Python. FME handles the setup of variables, leveraging GIS reference layers and parameters to manage details like map orientation, label sizes, and layout elements. Python takes over to export PDF maps for each location and template size, uploading them monthly to ArcGIS Online. The result? Fresh, regularly updated maps, ready for anyone to grab anytime—saving you time, effort, and endless revisions while keeping users happy with up-to-date, accessible maps.

Integration Ignited Redefining Event-Driven Architecture at Wix - EventCentricNatan Silnitsky

At Wix, we revolutionized our platform by making integration events the backbone of our 4,000-microservice ecosystem. By abandoning traditional domain events for standardized Protobuf events through Kafka, we created a universal language powering our entire architecture. We'll share how our "single-aggregate services" approach—where every CUD operation triggers semantic events—transformed scalability and extensibility, driving efficient event choreography, data lake ingestion, and search indexing. We'll address our challenges: balancing consistency with modularity, managing event overhead, and solving consumer lag issues. Learn how event-based data prefetches dramatically improved performance while preserving the decoupling that makes our platform infinitely extensible. Key Takeaways: - How integration events enabled unprecedented scale and extensibility - Practical strategies for event-based data prefetching that supercharge performance - Solutions to common event-driven architecture challenges - When to break conventional architectural rules for specific contexts