The Fan-out/Fan-in pattern is a concurrency pattern that distributes work across multiple workers (fan-out) and then collects results from all workers (fan-in). This pattern is essential for parallel processing of independent tasks, load balancing, and improving throughput for CPU-intensive operations.
NOTE: For other posts on concurrency patterns, check out the index post to this series of concurrency patterns.
The Pipeline pattern is a fundamental concurrency pattern that connects multiple stages of processing where each stage processes data and passes it to the next stage. This pattern is particularly useful for data transformation workflows, stream processing, and multi-step computations.
NOTE: For other posts on concurrency patterns, check out the index post to this series of concurrency patterns.
Concurrency is one of those topics that can make even experienced developers break out in a cold sweat. It’s like trying to juggle flaming chainsaws while riding a unicycle on a tightrope. But here’s the thing – in today’s world of multi-core processors, distributed systems, and high-performance applications, understanding concurrency isn’t just a nice-to-have skill; it’s absolutely essential.
Go, with its goroutines and channels, makes concurrency more approachable than most languages. But just because it’s easier doesn’t mean it’s easy. You still need to understand the patterns, the pitfalls, and the best practices to build robust, scalable systems.
That’s what this series is about. We’re going to dive deep into the concurrency patterns that every Go developer should know. Not just the theory – we’ll look at real, working code examples that you can run, modify, and learn from. This blog post is going to also act as the index to the posts, with today starting with the Pipeline Pattern.
This series covers 12 essential concurrency patterns, each with practical examples and detailed explanations. Here’s what’s coming:
Continue reading “Concurrency Patterns in Go: A *Short* Deep Dive Series”Programming Problems & Solutions : “Exploring IP Address Ranges in Go”. The introduction to this series is here and includes all links to every post in the series. This is the 8th of a dozen programming challenges I’m doing to setup for an eventual blog post on AI coding. The intent is to setup these programming challenges, get a solution, find a good refactoring, and then see how the AI tooling performs going through the same thing or refactoring what is in place. If you’re interested in how AI performs, and checking out these experiments and tests, subscribe to the blog to have the articles delivered directly to your email!
Hey there, fellow code adventurers! Today, we’re diving into the world of IP addresses and ranges. We’ve got an exciting coding challenge on our hands, and we’ll be tackling it using the Go programming language. So, grab your favorite beverage, and let’s get started!
The Challenge
Our mission, should we choose to accept it, is to implement a function that takes two IPv4 addresses as input and returns the number of addresses between them (including the first one, but excluding the last one). We’ll be working with valid IPv4 addresses in the form of strings, and the last address will always be greater than the first one.
Continue reading “Calculating IP Address Ranges in Go: Learn IPv4 Range Between Addresses”Programming Problems & Solutions : “Transforming 2D Arrays to CSV Format in Go”. The introduction to this series is here and includes all links to every post in the series. This is the 7th of a dozen programming challenges I’m doing to setup for an eventual blog post on AI coding. The intent is to setup these programming challenges, get a solution, find a good refactoring, and then see how the AI tooling performs going through the same thing or refactoring what is in place. If you’re interested in how AI performs, and checking out these experiments and tests, subscribe to the blog to have the articles delivered directly to your email!
Hey there, coding enthusiasts! Today, I’m diving into an interesting problem that involves converting a two-dimensional numeric array into its CSV (Comma-Separated Values) representation. This is a common task when working with data in various formats, and I’ll explore how to tackle it using Go.
The Problem: Imagine you have a 2D array filled with numbers, and you need to convert it into a CSV string. Each row of the array should be represented as a line in the CSV, with the elements separated by commas. For example, consider the following input array:
Continue reading “Converting 2D Arrays to CSV in Go: Problem-Solving and Testing”
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