Metadata-Version: 2.1
Name: cbrlib
Version: 2.0.3
Summary: Case Based Reasoning library for Python
License: LGPLv3
Author: Christian Dein
Author-email: christian.dein@dein-hosting.de
Requires-Python: >=3.10,<4.0
Classifier: License :: Other/Proprietary License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Project-URL: Repository, https://github.com/cdein/cbrlib.git
Description-Content-Type: text/markdown

# Case Based Reasoning the Pythonic Way

Case Based Reasoning library for Python

This library provides the possibility to integrate with native python. Basic implemetation can use instances of Python classes to calculate similarity between those objects.

Please also take a look at the (examples)[https://github.com/cdein/cbrlib/tree/main/examples].

```python
import dataclasses
import functools
from typing import Optional

from cbrlib import (
    Evaluator,
    FunctionCalculationParameter,
    NumericEvaluationOptions,
    ReasoningRequest,
    WeightedPropertyEvaluatorMapping,
)
from cbrlib import casebase, evaluate


@dataclasses.dataclass(slots=True, frozen=True)
class DataObject:
    color: Optional[str] = None
    shape: Optional[str] = None
    size: Optional[int] = None


color_lookup = {
    "red": {"red": 1, "orange": 0.8, "yellow": 0.4},
    "orange": {"orange": 1, "red": 0.8, "yellow": 0.8},
}
color_evaluator = functools.partial(evaluate.table_lookup, color_lookup)


def create_size_evaluator() -> Evaluator:
    options = NumericEvaluationOptions(
        min_=0,
        max_=100,
        if_less=FunctionCalculationParameter(tolerance=1.0),
        if_more=FunctionCalculationParameter(tolerance=1.0),
    )
    return functools.partial(evaluate.numeric, options)


def dataobject_evaluator() -> Evaluator:
    mappings = (
        WeightedPropertyEvaluatorMapping("color", color_evaluator, 2),
        WeightedPropertyEvaluatorMapping("size", create_size_evaluator(), 1),
        WeightedPropertyEvaluatorMapping("shape", evaluate.equality, 1),
    )
    return functools.partial(evaluate.case_average, mappings)


def main() -> None:
    data = [
        DataObject(color="red", shape="triangle", size=20),
        DataObject(color="orange", shape="circle", size=70),
        DataObject(color="green", shape="square", size=50),
    ]
    print("-" * 80)
    print(
        casebase.infer(
            data,
            ReasoningRequest(
                query=DataObject(color="red"),
            ),
            dataobject_evaluator(),
        )
    )
    print("-" * 80)
    print(
        casebase.infer(
            data,
            ReasoningRequest(
                query=DataObject(size=50),
            ),
            dataobject_evaluator(),
        )
    )
```

