DatasetsHub

A key aim of the Giza Datasets SDK is to simplify the process of searching the existing collection of datasets of various purposes, formats and sources. The most straightforward way to start is to use the DatasetsHub, the search and query feature for the Giza Datasets library. Using the DatasetsHub, you can search through the datasets within your ML development environment.

Dataset Object

Before using the DatasetsHub, it's useful to first understand Datasets themselves. Datasets in giza_datasets are represented as Dataset Class, which include details about a dataset such as the dataset's name, description, link to its documentation, tags, etc. You can query information about a given dataset with DatasetsHub

DatasetHub

The DatasetsHub class provides methods to manage and access datasets within the Giza Datasets library. Before we delve deeper into various methods, lets import the DatasetsHuband instantiate a DatasetsHub object.

from giza_datasets import DatasetsHub
hub = DatasetsHub()

Now we can call different DatasetsHub methods.

Use the show() method to print a table of all datasets in the hub:

hub.show()

Use the list() method to get a list of all datasets in the hub:

datasets = hub.list()
print(datasets)

Use the get() method to get a Dataset object with a given name:

dataset = hub.get('tvl-fee-per-protocol')

Use the describe() method to print a table of details for a given dataset:

hub.describe('tvl-fee-per-protocol')

Use the list_tags() method to print a list of all tags in the hub.

hub.list_tags()

Use the get_by_tag() method to a list of Dataset objects with the given tag.

hub.get_by_tag('Liquidity')

Great! Now we can use DatasetLoader to load our selected datasets.