62 lines
1.2 KiB
Python
62 lines
1.2 KiB
Python
from beakers.recipe import Recipe
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import pydantic
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class Word(pydantic.BaseModel):
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word: str
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class ClassifiedWord(pydantic.BaseModel):
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normalized_word: str
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is_fruit: bool
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class Sentence(pydantic.BaseModel):
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sentence: list[str]
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def word_classifier(item) -> ClassifiedWord:
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return ClassifiedWord(
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normalized_word=item.word.lower(),
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is_fruit=item.word.lower()
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in (
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"apple",
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"banana",
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"fig",
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"grape",
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"lemon",
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"mango",
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"orange",
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"pear",
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"raspberry",
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),
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)
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recipe = Recipe("fruits-example")
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recipe.add_beaker("word", Word)
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recipe.add_beaker("classified_word", ClassifiedWord)
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recipe.add_beaker("sentence", Sentence)
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recipe.add_transform("word", "classified_word", word_classifier)
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recipe.add_conditional(
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"classified_word",
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lambda cw: cw.is_fruit,
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"fruits",
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)
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recipe.add_transform(
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"fruits",
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"sentence",
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lambda x: Sentence(sentence=f"I love a fresh {x.normalized_word}".split()),
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)
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recipe.add_seed(
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"word",
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[
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Word(word="apple"),
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Word(word="bAnAnA"),
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Word(word="hammer"),
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Word(word="orange"),
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Word(word="EGG"),
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],
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)
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