from .layers import tokenization_layer
from .layers import parsing_layer


def make_yield_pipe(layers, knowledge_base, example):
    if len(layers) < 1:
        yield example
        return

    input_generator = make_yield_pipe(layers[:-1], knowledge_base, example)
    for input in input_generator:
        print("-->", input)
        for d in list(layers[-1].integrate(knowledge_base, input)):
            yield d


class BaseModel:
    def __init__(self, knowledge_base):
        self.tokenization = tokenization_layer.TokenizationLayer(knowledge_base)
        self.parsing = parsing_layer.ParsingLayer()

        self.layers = [
            self.tokenization,
            self.parsing,
        ]

    def reprocess(self, examples):
        for example in examples:
            self._reprocess_single(example)

    def _reprocess_single(self, example):
        return 
        pattern_examples = []
        for i, sample in enumerate(examples):
            other = examples[:i] + examples[i + 1:]
            match = get_matching(sample, other)
            if len(match) > 0:
                sample = (match, sample[1],)
            pattern_examples.append(sample)

        return pattern_examples

    def integrate(self, knowledge_base, example):
        yield from make_yield_pipe(self.layers, knowledge_base, example)    

    def tokenize(self, row, return_one=True):
        return self.tokenization.to_tokens(row)