awswrangler.s3.to_json

awswrangler.s3.to_json(df: pandas.core.frame.DataFrame, path: str, boto3_session: Optional[boto3.session.Session] = None, s3_additional_kwargs: Optional[Dict[str, Any]] = None, use_threads: bool = True, **pandas_kwargs: Any) → None

Write JSON file on Amazon S3.

Note

In case of use_threads=True the number of threads that will be spawned will be gotten from os.cpu_count().

Parameters
  • df (pandas.DataFrame) – Pandas DataFrame https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.html

  • path (str) – Amazon S3 path (e.g. s3://bucket/filename.csv).

  • boto3_session (boto3.Session(), optional) – Boto3 Session. The default boto3 Session will be used if boto3_session receive None.

  • s3_additional_kwargs (Optional[Dict[str, Any]]) – Forward to botocore requests. Valid parameters: “ACL”, “Metadata”, “ServerSideEncryption”, “StorageClass”, “SSECustomerAlgorithm”, “SSECustomerKey”, “SSEKMSKeyId”, “SSEKMSEncryptionContext”, “Tagging”. e.g. s3_additional_kwargs={‘ServerSideEncryption’: ‘aws:kms’, ‘SSEKMSKeyId’: ‘YOUR_KMY_KEY_ARN’}

  • use_threads (bool) – True to enable concurrent requests, False to disable multiple threads. If enabled os.cpu_count() will be used as the max number of threads.

  • pandas_kwargs – KEYWORD arguments forwarded to pandas.DataFrame.to_json(). You can NOT pass pandas_kwargs explicit, just add valid Pandas arguments in the function call and Wrangler will accept it. e.g. wr.s3.to_json(df, path, lines=True, date_format=’iso’) https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.to_json.html

Returns

None.

Return type

None

Examples

Writing JSON file

>>> import awswrangler as wr
>>> import pandas as pd
>>> wr.s3.to_json(
...     df=pd.DataFrame({'col': [1, 2, 3]}),
...     path='s3://bucket/filename.json',
... )

Writing JSON file using pandas_kwargs

>>> import awswrangler as wr
>>> import pandas as pd
>>> wr.s3.to_json(
...     df=pd.DataFrame({'col': [1, 2, 3]}),
...     path='s3://bucket/filename.json',
...     lines=True,
...     date_format='iso'
... )

Writing CSV file encrypted with a KMS key

>>> import awswrangler as wr
>>> import pandas as pd
>>> wr.s3.to_json(
...     df=pd.DataFrame({'col': [1, 2, 3]}),
...     path='s3://bucket/filename.json',
...     s3_additional_kwargs={
...         'ServerSideEncryption': 'aws:kms',
...         'SSEKMSKeyId': 'YOUR_KMY_KEY_ARN'
...     }
... )