How do 'Sphinx' invoice-less payments on the Lightning Network work? There was recently a WIP draft published to the lnd Github, for a 'Sphinx payment mode' for Lightning Network nodes. To quote Roasbeef from the Github PR : [this allows] the ability to send a payment to a destination without first needing to have an invoice Though this is a WIP, it can apparently be used on mainnet already, as long as all nodes involved are upgraded to include the new code. So how does this work? At a high level, what does the UX look like? At a low level, what differences are there in terms of completing the payment (passing HTLCs around), compared to a standard LN transaction? Whats going on under the hood? http://bit.ly/2FoFIgP
QUESTION ABOUT SLOW API do you know about api requests cryptocurrency exchanges? Simple ticker request may be viewed like this: https://api.kucoin.com/v1/open/tick or like this: https://www.okex.com/api/v1/ticker.do?symbol=ltc_btc Different: in first case we get info about all currencies in one request and then pick up certain symbols and parameters, we need. Symbols are the keys of dictionaries or lists and other params are their values. In second case I should create new request for each currencies I considering. Is it neccesary? If I consider, for instance 60 symbols, and do operations with them in Python - programm bot become slow enough. One-two ticker requests are long about 30 sec - for compare, in first case - 5 sec. How can I solve this problem? Thanks. http://ift.tt/2HpiAM0
Best way to calculate difficulty of generating specific vanity address? I'm now working at small tool, which purpose is to calculate difficulty (like number of attempts) of getting vanity address, like vanitygen ( https://github.com/samr7/vanitygen ) does. I've read some materials ( https://en.bitcoin.it/wiki/Vanitygen#Difficulty_of_finding_a_vanity ) and now i'm wondering about exact algorithm of how such calculation must be proceeded. There is no precise answer in the article at bitcoin.it wiki, so a look through the sources of vanitygen and ended up with some very basic ideas: All addresses are in a nutshell base58 numbers which can be converted to biginteger if needed. There is one final "biggest" address (like biggest number in the end of some range) Vanity address is any address from the range of addresses (if we think about them as numbers), that starts with specific pattern. So what is the best way of finding difficulty of getting specified vanity ad...
Comments
Post a Comment