writing Datasets in a human readable format
{'login': 'ghost', 'id': 10137, 'node_id': 'MDQ6VXNlcjEwMTM3', 'avatar_url': 'https://avatars.githubusercontent.com/u/10137?v=4', 'gravatar_id': '', 'url': 'https://api.github.com/users/ghost', 'html_url': 'https://github.com/ghost', 'followers_url': 'https://api.github.com/users/ghost/followers', 'following_url': 'https://api.github.com/users/ghost/following{/other_user}', 'gists_url': 'https://api.github.com/users/ghost/gists{/gist_id}', 'starred_url': 'https://api.github.com/users/ghost/starred{/owner}{/repo}', 'subscriptions_url': 'https://api.github.com/users/ghost/subscriptions', 'organizations_url': 'https://api.github.com/users/ghost/orgs', 'repos_url': 'https://api.github.com/users/ghost/repos', 'events_url': 'https://api.github.com/users/ghost/events{/privacy}', 'received_events_url': 'https://api.github.com/users/ghost/received_events', 'type': 'User', 'site_admin': False}
[{'id': 1935892871, 'node_id': 'MDU6TGFiZWwxOTM1ODkyODcx', 'url': 'https://api.github.com/repos/huggingface/datasets/labels/enhancement', 'name': 'enhancement', 'color': 'a2eeef', 'default': True, 'description': 'New feature or request'}
 {'id': 1935892912, 'node_id': 'MDU6TGFiZWwxOTM1ODkyOTEy', 'url': 'https://api.github.com/repos/huggingface/datasets/labels/question', 'name': 'question', 'color': 'd876e3', 'default': True, 'description': 'Further information is requested'}]
[]
['AFAIK, there is currently no built-in method on the `Dataset` object to do this.\r\nHowever, a workaround is to directly use the Arrow table backing the dataset, **but it implies loading the whole dataset in memory** (correct me if I\'m mistaken @lhoestq).\r\n\r\nYou can convert the Arrow table to a pandas dataframe to save the data as csv as follows:\r\n```python\r\narrow_table = dataset.data\r\ndataframe = arrow_table.to_pandas()\r\ndataframe.to_csv("/path/to/file.csv")\r\n```\r\n\r\nSimilarly, you can convert the dataset to a Python dict and save it as JSON:\r\n```python\r\nimport json\r\narrow_table = dataset.data\r\npy_dict = arrow_table.to_pydict()\r\nwith open("/path/to/file.json", "w+") as f:\r\n    json.dump(py_dict, f)\r\n```'
 'Indeed this works as long as you have enough memory.\r\nIt would be amazing to have export options like csv, json etc. !\r\n\r\nIt should be doable to implement something that iterates through the dataset batch by batch to write to csv for example.\r\nThere is already an `export` method but currently the only export type that is supported is `tfrecords`.'
 'Hi! `datasets` now supports `Dataset.to_csv` and `Dataset.to_json` for saving data in a human readable format.']
Hi
I see there is a save_to_disk function to save data, but this is not human readable format, is there a way I could save a Dataset object in a human readable  format to a file like json? thanks @lhoestq 
{'url': 'https://api.github.com/repos/huggingface/datasets/issues/1808/reactions', 'total_count': 0, '+1': 0, '-1': 0, 'laugh': 0, 'hooray': 0, 'confused': 0, 'heart': 0, 'rocket': 0, 'eyes': 0}