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Version: 0.5.4

extract.extract

data_to_sources​

def data_to_sources(
        data: Any,
        pipeline: SupportsPipeline,
        schema: Schema = None,
        table_name: str = None,
        parent_table_name: str = None,
        write_disposition: TWriteDispositionConfig = None,
        columns: TAnySchemaColumns = None,
        primary_key: TColumnNames = None,
        schema_contract: TSchemaContract = None) -> List[DltSource]

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Creates a list of sources for data items present in data and applies specified hints to all resources.

data may be a DltSource, DltResource, a list of those or any other data type accepted by pipeline.run

describe_extract_data​

def describe_extract_data(data: Any) -> List[ExtractDataInfo]

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Extract source and resource names from data passed to extract

Extract Objects​

class Extract(WithStepInfo[ExtractMetrics, ExtractInfo])

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original_data​

Original data from which the extracted DltSource was created. Will be used to describe in extract info

__init__​

def __init__(schema_storage: SchemaStorage,
             normalize_storage_config: NormalizeStorageConfiguration,
             collector: Collector = NULL_COLLECTOR,
             original_data: Any = None) -> None

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optionally saves originally extracted original_data to generate extract info

commit_packages​

def commit_packages() -> None

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Commits all extracted packages to normalize storage

This demo works on codespaces. Codespaces is a development environment available for free to anyone with a Github account. You'll be asked to fork the demo repository and from there the README guides you with further steps.
The demo uses the Continue VSCode extension.

Off to codespaces!

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