Skip to content

python package to showcase, test and build your own version of Pickhardt Payments

License

Notifications You must be signed in to change notification settings

renepickhardt/pickhardtpayments

Repository files navigation

Pickhardt Payments Package

The pickhardtpayments package is a collection of classes and interfaces that help you to test and implement your dialect of Pickhardt Payments into your on Lightning Application.

What are Pickhardt Payments?

Pickhardt Payments are the method of deliverying satoshis from one Lightning network Node to another by using probabilistic payment delivery in a round based payment loop that updates our belief of the remote liquidity in the Uncertainty Network and generates optimally reliable and cheap payment flows in every round by solving a piece wise linearized min integer cost flow problem with a separable cost function.

As of now the two main features of the cost function are the linearized_uncertainty_unit_cost (effectively proportional to 1/channel_capacity) and the linearized_routing_unit_cost (effectively just the ppm).

Depenencies

For simplicity the library currently uses a min cost flow solver from google's ortools and internally it stores all graphs and networks in networkx. I do not recommend writing critical in production or enterprise software on top of networkx as the library is rather slow and has a huge overhead of handling memory.

The dependencies can be found at:

build and install

One step install is via pip by typing pip install pickhardtpayments to your command line

If you want to build and install the library yourself you can do:

git clone https://github.com/renepickhardt/pickhardtpayments.git
cd pickhardtpayments
python -m build
pip install -e .

Example Code

This is a very stripped down example that shows how to run the library. Have a look at the example folder to find a longer version and more examples for the future

from pickhardtpayments.ChannelGraph import ChannelGraph
from pickhardtpayments.UncertaintyNetwork import UncertaintyNetwork
from pickhardtpayments.OracleLightningNetwork import OracleLightningNetwork
from pickhardtpayments.SyncSimulatedPaymentSession import SyncSimulatedPaymentSession


#we first need to import the chanenl graph from core lightning jsondump
#you can get your own data set via:
# $: lightning-cli listchannels > listchannels20220412.json
# alternatively you can go to https://ln.rene-pickhardt.de to find a data dump
channel_graph = ChannelGraph("listchannels20220412.json")

uncertainty_network = UncertaintyNetwork(channel_graph)
oracle_lightning_network = OracleLightningNetwork(channel_graph)
#we create a payment session which in this case operates by sending out the onions
#sequentially 
payment_session = SyncSimulatedPaymentSession(oracle_lightning_network, 
                                 uncertainty_network,
                                 prune_network=False)

#we need to make sure we forget all learnt information on the Uncertainty Nework
payment_session.forget_information()

#we run the simulation of pickhardt payments and track all the results

#Rene Pickhardt's public node key
RENE = "03efccf2c383d7bf340da9a3f02e2c23104a0e4fe8ac1a880c8e2dc92fbdacd9df"
#Carsten Otto's public node key
C_OTTO = "027ce055380348d7812d2ae7745701c9f93e70c1adeb2657f053f91df4f2843c71"
tested_amount = 10_000_000 #10 million sats

payment_session.pickhardt_pay(RENE,C_OTTO, tested_amount,mu=0,base=0)

Acknowledgements & Funding

This work is funded via various sources including NTNU & BitMEX as well as many generous donors via https://donate.ln.rene-pickhardt.de or https://www.patreon.com/renepickhardt Feel free to go to my website at https://ln.rene-pickhardt.de to learn how I have been contributing to the open source community and why it is important to have independent open source contributors. In case you also wish to support me I will be very grateful

About

python package to showcase, test and build your own version of Pickhardt Payments

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Contributors 4

  •  
  •  
  •  
  •  

Languages