This report covers January 19, 2020 to February 17, 2021.
Last touches to Node V2 and refreshed roadmap, user activity update and much Python love this month!
Core Code
Final touches and tests are being made to the code base.
Related tools like bootstrap servers and auto install scripts also need some care. We are close. Current work on the code is not that sexy but needs to be done so we can enter into the next phase with confidence.
Hypernodes
Current Hypernodes ROI is 18.4%, up from 17.7.6% in January. We count 248 active Hypernodes with a total amount of active collateral of 6,850,000 BIS. That’s a decrease of 11 active nodes since the last report.
The plot below shows all Hypernodes, both Active and Inactive, during the last 60 days. As can be seen from the plot, the number of Hypernodes is currently at 324, up by 4 nodes since the last report.
The plot below shows the total Hypernode collateral, both active and inactive, during the last 60 days. As can be seen, the total amount of collateral has risen to 8,670,000 during this period. The total amount of BIS in circulation is 27,05 million. Hence, the amount of active collateral accounts for 25.3% of the total supply, or 32.1% if the amount of inactive collateral is included.
Ecosystem
A new tool from our user Dingo: A realtime Hypernodes map. A reward was issued (link).
Krewshul does not spend all his free time playing (and winning!) with zircodice on Discord, he also coded a Python explorer client, give it a try (github) and give him some feedback as well as feature requests!
Media and news
In an effort to improve our social media presence, we started a few Twitter lists to reach out targeted users and reward our fan base.
We count on you to suggest accounts of interest to add.
More social activity is planned, and everyone has a role to play there.
Python Love
Python, finance and Machine learning
Python has a long history of love with scientific computing, finance and machine learning.
It’s a programming language of choice in universities, research labs and most of the Machine learning models are released as python libraries first.
As a result, with basic python knowledge you can leverage the power of incredibly powerful math and algorithms and use them for fun and profit.
Financial applications are legion, and examples are everywhere.
Last example was a (free for a day only) Ebook from Packt Publishing:
“Machine Learning for Finance”. The abstract reads “A guide to advances in machine learning for financial professionals, with working Python code”.
Here is the link if you want to have a peek at the table of content.
You can follow the Discord or Twitter, we relay these free offers when we see them.
This is just a single example, there are plenty more, paid as open source.
You will find python code to do anything, from sentiment analysis on tweets, to bayesian inference, neural networks, generative models, algorithmic trading and so on…
Last month, in addition to this free book we also provided free access to a Udemy course “Python Hacking Complete Beginner to Advanced Course” (tweet) as well as Python intro and regular expressions in Python (tweet) as well as “Expert python programming” Ebook (tweet), “Python GUI Programming Cookbook”, “Applied Unsupervised Learning with Python” “Design clever algorithms that can uncover interesting structures and hidden relationships in unstructured, unlabeled data”
Python packages and info you may like
- CCXT is a Python library providing homogeneous access to 250 or so exchanges. It also has python and js bindings. It’s worth noting qTrade supports that library. (github)
- From PyCoder’s weekly: “Archivy”.
Python, based upon flask, interesting app: “Archivy is a self-hosted knowledge repository that allows you to safely preserve useful content that contributes to your own personal, searchable and extensible wiki.” (github) - How to analyze volume profiles with Python? (link)
An online multiplayer game with Python and Bismuth?
Want to do something fun with Python? This could be your lucky day.
Here is a young library providing all the “under the hood” material to build online multiplayer text games, pure python.
By adding some interaction with Bismuth tokens for instance, you can take this to the next level and suggest something unique 🙂
Come and say hi if you want to flex your python muscles on such a game, there could be other users helping, as well as a reward!
Exchanges
FTX: You can help!
Friends of $BIS
Tokens on Nyzo
$BIS users are likely to know Nyzo as well. It’s another qTrade gem, that shares the same spirit as Bismuth, even-though the features and use cases of both chains are not the same.
Nyzo features very fast block times of 7s, with guaranteed finality.
We mention Nyzo since this month saw the birth of “Project Nytro”, that brings ERC-20 alike tokens on top of Nyzo.
This was made possible by a second layer protocol, close to – and inspired by – Bismuth tokens protocol.
We’re very glad to see that Bismuth tech spreads and is adopted by other blockchains. Cloning ETH and its complexity is not the only way: many, many things are possible with minimalism and simplicity in mind.
Angainor’s OTP Device
Angainor is a team of developers and hardware hackers who worked on several crypto projects, namely Nyzo, Idena and Bismuth so far. They are the authors of the Bismuth HD Paper wallet we mentioned in a previous progress report, as well as designers of a Hardware wallet that will support Bismuth transactions.
They just announced a new project, based upon the brand new Raspberry Pi Pico: a TOTP hardware device (Google Auth 2FA) running under Python.
Have a look at their Hackaday.io project, this is a promising device that could bring more users and developers into python crypto!
Bismuth 2.0
We know you are many to wait for practical news about Bismuth 2.0.
Thanks you for your patience!
The wait is soon to be over, with an official announcement that will be followed by a completely refreshed roadmap.