Getting started¶
By executing the steps below you can set up lnsimulator for your environment in a few minutes.
Requirements¶
- UNIX or macOS environment
- For macOS users: you need to have wget (brew install wget)
- This package was developed in Python 3.5 (conda environment) but it works with Python 3.6 and 3.7 as well.
Install¶
After cloning the repository from GitHub you can install the simulator with pip.
git clone https://github.com/ferencberes/LNTrafficSimulator.git
cd LNTrafficSimulator
pip install .
Data¶
By providing daily LN snapshots as input (you can bring and use your own!), our simulator models the flow of daily transactions.
i.) Download¶
You can download the data files, that we used in our research by executing the following command:
a.) Linux¶
bash ./scripts/download_data.sh
ls ln_data
ii.) Content¶
The download_data.sh script downloads 4 data files into the ln_data folder with the following content:
| File | Simulator input? | Content |
|---|---|---|
| sample.json | Yes | sample JSON file containing a daily LN snapshot |
| ln_edges.csv | Yes | preprocessed LN snapshots in the form of a directed graph |
| 1ml_meta_data.csv | Yes | merchant meta data that we downloaded from 1ml.com |
| ln.tsv | No | edge stream data about LN channels |
First example¶
Execute the following code to see whether your configuration was successful.
from lnsimulator.ln_utils import preprocess_json_file
import lnsimulator.simulator.transaction_simulator as ts
data_dir = "..." # path to the ln_data folder that contains the downloaded data
amount = 60000
count = 7000
epsilon = 0.8
drop_disabled = True
drop_low_cap = True
with_depletion = True
find_alternative_paths = False
print("# 1. Load LN graph data")
directed_edges = preprocess_json_file("%s/sample.json" % data_dir)
print("\n# 2. Load meta data")
node_meta = pd.read_csv("%s/1ml_meta_data.csv" % data_dir)
providers = list(node_meta["pub_key"])
print("\n# 3. Simulation")
simulator = ts.TransactionSimulator(directed_edges, providers, amount, count, drop_disabled=drop_disabled, drop_low_cap=drop_low_cap, eps=epsilon, with_depletion=with_depletion)
transactions = simulator.transactions
_, _, all_router_fees, _ = simulator.simulate(weight="total_fee", with_node_removals=find_alternative_paths, max_threads=1)
print(all_router_fees.head())
print("Done")
If your configuration works then you should proceed to the detailed documentation of the LN traffic simulator.