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51 lines
1.7 KiB
Python
51 lines
1.7 KiB
Python
from typing import Dict, List, TypedDict
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from unstructured.documents.elements import Text
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from unstructured.staging.base import flatten_dict
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class BaseplateRow(TypedDict):
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"""Typed dictionary for an individual Baseplate row. Baseplate docs show what the JSON
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representation should look like:
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https://docs.baseplate.ai/api-reference/documents/overview
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"""
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data: Dict[str, str]
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metadata: Dict[str, str]
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class BaseplateRows(TypedDict):
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"""Typed dictionary for multiple Baseplate rows. Baseplate docs show what the JSON
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representation should look like. This is the JSON that is submitted to the Baseplate
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API to upload data.
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https://docs.baseplate.ai/api-reference/documents/overview
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"""
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rows: List[BaseplateRow]
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def stage_for_baseplate(elements: List[Text]) -> BaseplateRows:
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"""Converts a list of unstructured elements into a dictionary of rows that can be uploaded
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into Baseplate via the API.
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References
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----------
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https://docs.baseplate.ai/api-reference/documents/overview
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https://docs.baseplate.ai/api-reference/documents/upsert-data-rows
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"""
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rows: List[BaseplateRow] = []
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for element in elements:
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element_dict = element.to_dict()
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metadata = element_dict.pop("metadata")
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row: BaseplateRow = {
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# Baseplate maps each key in the row's data object to a column in the dataset and
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# each key in the row's metadata object to a metadata column in the dataset.
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# We infer that Baseplate cannot map a nested object to a column in its dataset.
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"data": flatten_dict(element_dict),
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"metadata": flatten_dict(metadata),
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}
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rows.append(row)
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return {"rows": rows}
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