HTTP Live Streaming is a communication protocol for adaptive bitrate streaming.
What this means is that with HLS we can enable HTML5 video clients to stream video online. One of the main benefits of the HLS protocol is that it allows clients to change the video quality on the fly based on several factors. This ability to change the video quality improves the overall user experience as it helps reduce buffering times, provides the best possible video resolution based on your screen size and more.
KT-Robots is a port of the λ-Robots Team Hackathon challenge
The original idea can be traced back to the 70s game RobotWar.
This repository is an implementation of the game in the kotlin programming language and the spring framework.
KT-Robots is a Team Hakcathon programming challenge build using serverless technologies. You can get access to the code on GitHub
In KT-Robots, you program a battle robot that participates in a square game field.
Pre-Build Lambda-Robots The lambda-robots/src/main/kotlin/io.onema.ktrobots.lambda/functions/ folder contains additional robots that are deployed, these have different behaviors. Next, we need a few robots to battle it out.
TargetRobot: This is a stationary robot for other robots to practice on. YosemiteSam: This robot runs around shooting in random directions as fast as it can. HotShot: This robot uses its radar to find other robots and fire at them. When hit, this robot moves around the board.
The last week of November 2018 Amazon Web Services announced a new feature for AWS Lambda functions called layers. Layers are a handy way to share common libraries and dependencies between your lambda functions without having to add them to your package. This is useful when you are using libraries that are large and can take considerable time to upload or update.
I have had a tough time trying to package my code plus scikit-learn and associated dependencies to under 50MB which is the AWS Lambda max limit from a compressed package.
In many programing languages using JSON (serializing and deserializing values) is an every day thing, and it can be done easily :
import json json_string = json.dumps([1, 2, 3, {‘4’: 5, ‘6’: 7}]) # json_string -> ‘[1,2,3,{"4":5,"6":7}]’ json_object = json.loads(json_string) # json_object -> [1, 2, 3, {‘4’: 5, ‘6’: 7}] Furthermore, in C# using Json.NET, I’m able to quickly deserialize json to an object model and from an object to a json string and get all the benefits of static types:
For the past eight months, I have have been playing and programming in Scala for fun. One of the many things I wanted to do was to convert a collection of case classes into a CSV file. This sounds like a problem that has already been solved see “PureCSV: A type-safe and boilerplate-free CSV library for Scala”, and it has… to an extent.
In my specific use case, I wanted to parse some data from JSON into a case class and eventually convert a collection of these classes into a CSV file.
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