Database for AI powered by a storage format optimized for deep-learning applications.
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A utility for managing ML datasets with support for local and cloud storage backends.
Creates new datasets at specified storage locations.
Opens existing datasets for read or write access.
Checks whether a dataset exists at a given location.
Permanently removes datasets from storage.
@generates
class DatasetManager:
"""
Manages dataset lifecycle operations.
"""
def create_dataset(self, path: str) -> object:
"""
Create a new dataset at the specified path.
Parameters:
- path: Location where dataset should be created
Returns:
Dataset object for data operations
"""
pass
def open_dataset(self, path: str) -> object:
"""
Open an existing dataset for access.
Parameters:
- path: Location of the dataset to open
Returns:
Dataset object for operations
"""
pass
def exists(self, path: str) -> bool:
"""
Check if a dataset exists at the specified path.
Parameters:
- path: Location to check
Returns:
True if dataset exists, False otherwise
"""
pass
def delete_dataset(self, path: str) -> None:
"""
Permanently delete a dataset.
Parameters:
- path: Location of dataset to delete
"""
passProvides database capabilities for AI with optimized storage for deep-learning applications.
@satisfied-by
Install with Tessl CLI
npx tessl i tessl/pypi-deeplakedocs
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