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Which Distributed Hash Table (DHT) is easiest to implement in Python? Any good example that is not bloated?
I not am looking for a definition of DHT because I am more oriented and focused on design and implementation of such.
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A distributed hash table (DHT) is a distributed system for mapping keys to values. In IPFS, the DHT is used as the fundamental component of the content routing system and acts like a cross between a catalog and a navigation system. It maps what the user is looking for to the peer that is storing the matching content.
A distributed hash table (DHT) is a distributed system that provides a lookup service similar to a hash table: key–value pairs are stored in a DHT, and any participating node can efficiently retrieve the value associated with a given key.
Why Is a Distributed Hash Table Used? Distributed hash tables provide an easy way to find information in a large collection of data because all keys are in a consistent format, and the entire set of keys can be partitioned in a way that allows fast identification on where the key/value pair resides.
In my job I'm working with entagled. I can't say it's great code, but it seems to be the only Kademlia implementation for Python around.
I think Kademlia has become the default DHT for most applications today, because it's quite simple and has fast lookups. At least in the academic world that I've seen so far.
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If you are focused on implementation, rather than looking for an out-of-the-box solution, this article might help a bit: http://www.linuxjournal.com/article/6797
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