Python library for doing things with Grid-like structures

• Read grid-like data in multiple formats, including string, and easily export to DataFrames
• Solve puzzles like largest product in a grid and low points in a grid
• Build board games like tic-tac-toe, connect-four, and bingo
• Analyze tabular data in interesting new ways

See the ./examples directory for solutions to a few puzzles with comments about how gridthings helps solve them.

import gridthings

data = '''
123
456
789
'''

grid = gridthings.IntGrid(data)
grid
<IntGrid shape=(3, 3)>

import pandas
df = pandas.DataFrame(grid.values())
df
>>>
        0	1	2
    0	1	2	3
    1	4	5	6
    2	7	8	9

grid.get(1, 1)
>>> IntCell(y=1, x=1, value=5)

grid.peek_linear(1, 1)
>>> <Collection [[IntCell(y=1, x=0, value=4), IntCell(y=1, x=2, value=6), IntCell(y=0, x=1, value=2), IntCell(y=2, x=1, value=8)]]>

sum(grid.peek_linear(1, 1))
>>> 20

max(grid.peek_linear(1, 1))
>>> IntCell(y=2, x=1, value=8)

max(grid.peek_diagonal(1, 1))
>>> IntCell(y=2, x=2, value=9)

The grid.op function is useful for traversing parts of the grid and checking some operator function. It's applicable for problems such as finding peaks and valleys.

For example, "count the distance in each direction one could see before sight is blocked by another item that's the same height or taller (or hits the edge of grid)":

import gridthings
import operator

text = """
30373
25512
65332
33549
35390
"""

grid = gridthings.IntGrid(text)
grid
>>> <IntGrid shape=(5, 5)>

grid.get(y=3, x=2)
>>> IntCell(y=3, x=2, value=5)

# traverse in each direction, continuing if the original cell is greater value than the next cell
grid.op_linear(y=3, x=2, op=operator.gt)
>>> [<Collection [[IntCell(y=3, x=1, value=3), IntCell(y=3, x=0, value=3)]]>,
     <Collection [[IntCell(y=3, x=3, value=4)]]>,
     <Collection [[IntCell(y=2, x=2, value=3)]]>,
     <Collection [[IntCell(y=4, x=2, value=3)]]>]

# Include the cell that caused the operator check fail
grid.op_linear(y=3, x=2, op=operator.gt, include_break_case=True)
>>> [<Collection [[IntCell(y=3, x=1, value=3), IntCell(y=3, x=0, value=3)]]>,
     <Collection [[IntCell(y=3, x=3, value=4), IntCell(y=3, x=4, value=9)]]>,
     <Collection [[IntCell(y=2, x=2, value=3), IntCell(y=1, x=2, value=5)]]>,
     <Collection [[IntCell(y=4, x=2, value=3)]]>]

This project uses poetry for dependency management, pre-commit for linting at commit, pytest as a test framework, and tox for running tests locally and on Github Actions (CI/CD). To get started developing against this library, you'll need to be able to install poetry, then use poetry install and pre-commit install.

1. pip install poetry on your system Python if it doesn't exist
2. poetry install, or poetry install -E examples to include Jupyter and pandas, used in the example notebooks
3. poetry shell to activate the poetry environment created at .venv
4. pre-commit install --install-hooks

All pre-commit hooks will run when you git commit, even without pushing to Github. You can manually check with pre-commit run --all-files. If you need to commit even with pre-commit throwing erros, you can override with git commit --no-verify.

• Prepare Changelog, move items from Unreleased into new section
• Update version with poetry version (patch, minor, major)
• Create a new release in Github. An action will publish to pypi.