pyconsensus 0.5.8

Standalone implementation of Augur's consensus mechanism

pyconsensus is a standalone Python implementation of Augur’s consensus mechanism. For details, please see the Augur whitepaper.

Installation

The easiest way to install pyconsensus is to use pip:

$ pip install pyconsensus

Usage

To use pyconsensus, import the Oracle class:

from pyconsensus import Oracle

# Example report matrix:
#   - each row represents a reporter
#   - each column represents an event in a prediction market
my_reports = [[0.2, 0.7,  1,  1],
              [0.3, 0.5,  1,  1],
              [0.1, 0.7,  1,  1],
              [0.5, 0.7,  2,  1],
              [0.1, 0.2,  2,  2],
              [0.1, 0.2,  2,  2]]
reputation = [1, 2, 10, 9, 4, 2]
my_event_bounds = [
    {"scaled": True, "min": 0.1, "max": 0.5},
    {"scaled": True, "min": 0.2, "max": 0.7},
    {"scaled": False, "min":  1, "max": 2},
    {"scaled": False, "min":  1, "max": 2},
]

oracle = Oracle(reports=my_reports,
                reputation=reputation,
                event_bounds=my_event_bounds)
oracle.consensus()

Tests

Unit tests are in the test/ directory.

pyconsensus is used in conjunction with the Augur Simulator to carry out randomized numerical (Monte Carlo) consensus tests. See the Simulator repository for details.