Lpil/dogma
20 Dec 2017A code style linter for Elixir, powered by shame.
Wins the “best tag-line for a linter” award.
A code style linter for Elixir, powered by shame.
Wins the “best tag-line for a linter” award.
Bitcoin Could Cost Us Our Clean-energy Future
Digital financial transactions come with a real-world price: The tremendous growth of cryptocurrencies has created an exponential demand for computing power. As bitcoin grows, the math problems computers must solve to make more bitcoin (a process called “mining”) get more and more difficult — a wrinkle designed to control the currency’s supply.
Today, each bitcoin transaction requires the same amount of energy used to power nine homes in the U.S. for one day. And miners are constantly installing more and faster computers. Already, the aggregate computing power of the bitcoin network is nearly 100,000 times larger than the world’s 500 fastest supercomputers combined.
Energy is the fuel that keeps the Bitcoin engine running. Just to keep the exchange of BTC and verifying the transaction records takes energy. So what happens when the energy required becomes prohibitivly expensive?
Blazing fast, zero configuration web application bundler
I was just talking with some folks at a meetup last night about the pain of webpack configuration. In previous jobs, spinning up a new app was a regular thing so I got pretty adept at doing the webpack dance, but at the current gig, I’m working on a large React app that was setup before I got here so I havent had to dive into webpack for over a year! This is going on the short list of things to check out with my next pide project.
Builing Product Recommendations Using Elixir GenStage
I’ve wanted to build something using Flow since José Valim introduced the concepts behind it in his Elixir Conf 2016 keynote. I initially thought of building a product recommendation tool using crowdsourced reviews. As it would include both IO intensive stages, such as HTTP requests, and CPU intensive stages, like sentiment analysis. A good candidate for parallel processing and suitable for using Flow.
I’m still pretty new to Elixir but can see there’s a lot of great stuff in this project to learn from.
With Redux, you can use combineReducers to create nested reducers that only operate on a slice of state, but all reducers still respond to all actions. Often this is the point—a component can affect another component just by dispatching an action. But when we started creating multiple instances of the same component, we created a system where every instance responded to action meant for just one.