kedro.io.AbstractDataset(*args, **kwds)
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AbstractDataset is the base class for all data set implementations. All data set implementations should extend this abstract class and implement the methods marked as abstract. If a specific dataset implementation cannot be used in conjunction with the ParallelRunner, such user-defined dataset should have the attribute _SINGLE_PROCESS = True. Example: ::.
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kedro.io.AbstractVersionedDataset(filepath, ...)
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AbstractVersionedDataset is the base class for all versioned data set implementations.
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kedro.io.CachedDataSet
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alias of CachedDataset |
kedro.io.CachedDataset(dataset[, version, ...])
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CachedDataset is a dataset wrapper which caches in memory the data saved, so that the user avoids io operations with slow storage media.
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kedro.io.DataCatalog([data_sets, feed_dict, ...])
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DataCatalog stores instances of AbstractDataset implementations to provide load and save capabilities from anywhere in the program.
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kedro.io.IncrementalDataSet
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alias of IncrementalDataset |
kedro.io.IncrementalDataset(path, dataset[, ...])
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IncrementalDataset inherits from PartitionedDataset, which loads and saves partitioned file-like data using the underlying dataset definition.
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kedro.io.LambdaDataSet
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alias of LambdaDataset |
kedro.io.LambdaDataset(load, save[, exists, ...])
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LambdaDataset loads and saves data to a data set.
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kedro.io.MemoryDataSet
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alias of MemoryDataset |
kedro.io.MemoryDataset([data, copy_mode, ...])
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MemoryDataset loads and saves data from/to an in-memory Python object.
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kedro.io.PartitionedDataSet
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alias of PartitionedDataset |
kedro.io.PartitionedDataset(path, dataset[, ...])
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PartitionedDataset loads and saves partitioned file-like data using the underlying dataset definition.
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kedro.io.Version(load, save)
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This namedtuple is used to provide load and save versions for versioned data sets. |