test commit

testdata.py

@@ -0,0 +1,34 @@
+import mlcroissant as mlc
+import pandas as pd
+import os
+
+# These values are used by mlcroissant
+# to perform the necessary auth to fetch the data
+# Provide your Kaggle username and API key
+os.environ['CROISSANT_BASIC_AUTH_USERNAME'] = 'enzetao'
+os.environ['CROISSANT_BASIC_AUTH_PASSWORD'] = "a97ddf556baf4db4723d78aab014b599"
+
+
+# Fetch the Croissant JSON-LD
+# croissant_dataset = mlc.Dataset('https://www.kaggle.com/datasets/yueyin27/refref/croissant/download')
+# croissant_dataset = mlc.Dataset('https://www.kaggle.com/datasets/nguyenhung1903/nerf-synthetic-dataset/croissant/download')
+# croissant_dataset = mlc.Dataset('https://www.kaggle.com/datasets/enzetao/refref/croissant/download')
+# croissant_dataset = mlc.Dataset('https://www.kaggle.com/datasets/muratkokludataset/rice-image-dataset/croissant/download')
+url = 'https://huggingface.co/api/datasets/fashion_mnist/croissant'
+
+print(mlc.Dataset(url).metadata.to_json())
+import tensorflow_datasets as tfds
+builder = tfds.core.dataset_builders.CroissantBuilder(
+    jsonld=url,
+    record_set_ids=["fashion_mnist"],
+    file_format='array_record',
+)
+builder.download_and_prepare()
+
+# # Check what record sets are in the dataset
+# record_sets = croissant_dataset.metadata.record_sets
+# print(record_sets)
+
+# # Fetch the records and put them in a DataFrame
+# record_set_df = pd.DataFrame(croissant_dataset.records(record_set=record_sets[0].uuid))
+# record_set_df.head()