Open amotl opened 9 months ago
Those patches add a corresponding miniature subsystem, and bring it into application. With them, cratedb-toolkit will provide convenient access to cratedb-datasets.
from cratedb_toolkit.datasets import load_dataset
dataset = load_dataset("tutorial/weather-basic")
dataset.dbtable(dburi="crate://crate@localhost/", table="weather_data").load()
Provide access to datasets at Kaggle, to be easily consumed by tutorials and/or production applications.
from cratedb_toolkit.datasets import load_dataset
dataset = load_dataset("kaggle://guillemservera/global-daily-climate-data/daily_weather.parquet")
# Only download once, nothing else.
dataset.acquire()
# Create table schema in database.
dataset.dbtable(dburi="crate://crate@localhost/", table="kaggle_daily_weather").create()
About
Easily consume datasets from tutorials and/or production applications like others are doing it, using Python code.
References
cratedb_toolkit.tutorial.load_dataset
likedatasets.load_dataset
, xarray.tutorial.load_dataset, orazureml.opendatasets
.from sklearn.datasets import load_iris
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