n0rdy-blog-code-samples
pippin
| n0rdy-blog-code-samples | pippin | |
|---|---|---|
| 4 | 3 | |
| 4 | 14 | |
| - | - | |
| 5.8 | 6.6 | |
| about 2 months ago | 13 days ago | |
| Go | Go | |
| GNU Affero General Public License v3.0 | Apache License 2.0 |
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n0rdy-blog-code-samples
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JWT, JWS, JWE and how to cook them
All the code examples are available here. If you run this code, you'll see the same JSON printed to the terminal as above.
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Understanding CORS
You can find it in this GitHub repo.
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Go concurrency simplified. Part 4: Post office as a data pipeline
The next step should be to replace the slice with a channel to define the customers' queue. But how should we get the customers to put in that channel? Another good question, you are on fire today! We need a function to generate random customers and, ideally, with random waiting to make it more realistic, as customers come to the post office at a different frequency. For that, I asked ChatGPT to generate a list of 50 random names and 50 random Xmas presents that fit into the postal package. I won't provide these lists here to save space, but feel free to check them out on a GitHub repo. Once we have it, the rest of the generator code is trivial:
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Go concurrency simplified. Part 1: Channels and goroutines
This and other code examples are available in this GitHub repo.
pippin
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Go concurrency simplified. Part 4: Post office as a data pipeline
take a look at the concurrent code written by other devs out there: for example, feel free to check the internals of my library Pippin, but I bet there are many better projects out there to learn from - Google/Bing/DuckDuckGo/Kagi and ChatGPT can help to find the right one
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Go concurrency simplified. Part 1: Channels and goroutines
Christmas season is around the corner, that's why another evening I was standing in a long queue at the post office with some Xmas presents packed inside the box. The line moved pretty slowly, as there was only one postman for the whole crowd of customers. The guy was running back and forth, and I felt really sorry for him. Not sure why, either out of boredom or because of several long evenings I spent working on my open-source library for managing asynchronous pipelines, but my brain turned engineering mode on and tried to optimize the process of handling parcels.
- Show HN: Pippin – Go library for creating and managing data pipelines
What are some alternatives?
ApacheKafka - A curated re-sources list for awesome Apache Kafka
Hunch - Hunch provides functions like: All, First, Retry, Waterfall etc., that makes asynchronous flow control more intuitive.
flink-kubernetes-operator - Apache Flink Kubernetes Operator
Flow - Package flow provides support for basic FBP / pipelines
svgo - Go Language Library for SVG generation
memphis - Memphis.dev is a highly scalable and effortless data streaming platform
kyoo - Unlimited job queue for go, using a pool of concurrent workers processing the job queue entries
pond - 🔘 Minimalistic and High-performance goroutine worker pool written in Go
go-workers - 👷 Library for safely running groups of workers concurrently or consecutively that require input and output through channels
Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing