Pious: The Pio Utility Suite

Pious provide a Python wrapper for a PioSOLVER instance and provides convenience functions and abstractions to make working with PioSOLVER easier.

Warning: This library is still under construction. All interfaces, classes, files, etc. will be changed. I'm open sourcing this for feedback/collaboration.

Install

Install with pip install pious. Requires Python 3.11 or later.

Solver Interface

Pious provides pious.pio.solver.Solver to wrap a PioSOLVER instance. This can be constructed directly, but we recommend using pious.pio.util.make_solver():

# examples/load_tree.py
from pious.pio.util import make_solver
from pious.pio.resources import get_test_tree

solver = make_solver()
solver.load_tree(get_test_tree())  # Replace with your tree
solver.load_all_nodes()  # Required for partial saves in Pio3
tree_info = solver.show_tree_info()
print(f"Board: {tree_info['Board']}")
print(f"Pot: {tree_info['Pot']}")
print(f"EffectiveStacks: {tree_info['EffectiveStacks']}")

lines = solver.show_all_lines()
print("Last 10 lines:", lines[-10:])

Configuration

By default make_solver will try to invoke C:\PioSOLVER\PioSOLVER3-edge.exe. You can configure default behavior by placing a pious.toml in your home directory. Here is a sample pious.toml:

[pio]
install_directory="C:\\PioSOLVER"
pio_version_no="2"
pio_version_type="pro"

Lines

PioSOLVER deals in lines (e.g., show_all_lines), such as r:0:c:c:b300:b850:c. Pious provides a high-level wrapper, Line, around low-level Pio lines that gives many quality-of-life improvements. See examples\line_example.py for details:

from pious.pio.line import Line

# ...
line = Line("r:0:c:b12:c:c:b77:b221:c:c")
print("Line:", line)
print("  IP?                 ", line.is_ip())
print("  Current Street?     ", line.current_street())
print("  Actions:            ", line.actions)
print("  Streets as Actions: ", line.streets_as_actions)
print("  Streets as Lines:   ", line.streets_as_lines)
print("  Facing Bet?         ", line.is_facing_bet())

Aggregation Reports

To use the AggregationReport, start a python session from the python directory, and import the aggregation report module. Then create a new AggregationReport by passing in the path to the folder containing the AggregationReport (and optionally including the path to the solve database that you used to generate the aggregation report). See examples\aggregation_example.py for more info:

# Excerpt from examples\aggregation_example.py

from pious.pio.aggregation import AggregationReport
import pious.pio.resources as resources

report = AggregationReport(get_aggregation_root(), get_database_root())
print(report)
print(report.describe())

report.ioff()  # turn off matplotlib's interactive mode
report.plot()  # exit report to continue

report.filter("r1 == 14") # filter for ace high boards
report.plot()

report.reset()
report.filter("r1 < 14 and flushdraw") # non ace high AND flushdraw boards
report.plot()

You can run r.plot() to get a nice visualization, r.filter() to focus only on boards you're interested in, and r.reset() to start over again.