Ideas on how to represent Cree morphological data.

cree-classes.py

#!/usr/bin/env python3
# -*- coding: UTF-8 -*-

"""
Some ideas about how to organize data from the FST, to how to store Cree
wordforms.

Usage:

Analyzing a wordform descriptively yields "raw" FST output:

>>> analysis = next(lookup('kiwapamin'))
>>> type(analysis)
FSTOutput
>>> analysis.input
'wapamew'
>>> analysis.output
('w', 'â', 'p', 'a', 'm', 'ê', 'w', '+V', '+TA', '+Ind', '+Prs',
 '+2Sg', '+1SgO')
>>> analysis.weight
0.0

There should be a function that parses the FSTOutput and creates a Cree
wordform, which can then be queried for linguistic information:

>>> kiwâpamin = to_wordform(analysis)
>>> type(kiwâpamin)
CreeWordform
>>> kiwâpamin.prelemma_tags
()
>>> kiwâpamin.lemma
'wâpamêw'
>>> kiwâpamin.postlemma_tags
(<Tag pos='V'>, <Tag animacy='TA'>, <Tag indicative='Ind'>, <Tag tense='Prs'>,
 <Tag actor='2Sg'>, <Tag goal='1Sg'>)
>>> kiwâpamin.tag['pos']
<Tag pos='V'>
>>> kiwâpamin.tag['pos'] == 'V'
True
>>> kiwâpamin.tag['actor']
'2Sg'
>>> kiwâpamin.tag['goal']
'1Sg'
>>> kiwâpamin.to_sro()
'kiwâpamin'
>>> kiwâpamin.to_syllabics()
'ᑭᐚᐸᒥᐣ'

FST inputs that are not accepted will

>>> analysis = next(lookup('fhqwhgads'))
>>> analysis.accepted
False
>>> analysis.output
('f', 'h', 'q', 'w', 'h', 'g', 'a', 'd', 's', '+?')
>>> analysis.weight
inf
"""

from dataclasses import dataclass
from typing import Sequence, Mapping


@dataclass
class FSTOutput:
    # The input string.
    input: str
    # One possible transduction, as a sequence of strings.
    output: Sequence[str]
    # The weight of the transduction.
    weight: float

    @property
    def accepted(self):
        """
        Returns whether the transduction succeeded.
        """
        from math import inf
        return weight < inf


@dataclass
class Tag:
    ...


@dataclass
class CreeWordform:
    prelemma_tags: Sequence[Tag]
    lemma: str
    postlemma_tags: Sequence[Tag]
    tags: Mapping[str, Tag]