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Make this repository as distributable package
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hitonanode committed Apr 24, 2024
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2 changes: 1 addition & 1 deletion README.md
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Expand Up @@ -6,7 +6,7 @@ The linprog-modeler, akin to the [PuLP](https://github.com/coin-or/pulp) interfa

To employ this modeler in AtCoder contests, one must:

1. Carefully copy the entirety of the [modeler.py](./modeler.py) script and incorporate it into your submission file.
1. Carefully copy the entirety of the [lpmodeler/model.py](./lpmodeler/model.py) script and incorporate it into your submission file.
2. Develop your algorithmic solution within the submission.

For additional information and a concrete example, please consult the [Submission Example](https://atcoder.jp/contests/abc326/submissions/49047540).
1 change: 1 addition & 0 deletions lpmodeler/__init__.py
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__version__ = "0.1.0"
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Empty file added lpmodeler/py.typed
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7 changes: 5 additions & 2 deletions pyproject.toml
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[tool.poetry]
name = "linprog-modeler"
name = "lpmodeler"
version = "0.1.0"
description = ""
description = "Simple wrapper around scipy.optimize.linprog for linear and mixed integer programming problems"
authors = ["hitonanode <[email protected]>"]
readme = "README.md"
packages = [
{ include = "lpmodeler" },
]

[tool.poetry.dependencies]
python = "^3.11"
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2 changes: 1 addition & 1 deletion test/test_corner_usage.py
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import pytest

from modeler import LPModel, LPStatus, LPVar, LPVarType
from lpmodeler.model import LPModel, LPStatus, LPVar, LPVarType


def test_lpvar_objective() -> None:
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2 changes: 1 addition & 1 deletion test/test_lp_var_types.py
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@@ -1,6 +1,6 @@
import pytest

from modeler import LPModel, LPStatus, LPVar, LPVarType
from lpmodeler.model import LPModel, LPStatus, LPVar, LPVarType


def test_semicontinuos() -> None:
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2 changes: 1 addition & 1 deletion test/test_maximize.py
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import pytest

from modeler import LPModel, LPSense, LPStatus, LPVar
from lpmodeler.model import LPModel, LPSense, LPStatus, LPVar


def test_maximize() -> None:
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2 changes: 1 addition & 1 deletion test/test_model.py
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import pytest

from modeler import LPModel, LPStatus, LPVar
from lpmodeler.model import LPModel, LPStatus, LPVar


def test_simple_lp() -> None:
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