Loading / saving features doesn't support file-like objects as input

[rwedge]

Currently Featuretools supports saving a list of features to disk and loading them from disk using a file path as an input. If these functions supported file-like objects as an alternate input we could save features to string buffers or unnamed temporary files.

[bschreck]

It would be great if we could also have the option to serialize to a string rather than a file-like object using cloudpickle.dumps(), cloudpickle.loads(). Maybe if the file parameter is omitted.

This is similar to how pandas.DataFrame.to_csv() works: https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.to_csv.html

[kmax12]

a related question was recently asked about on stackoverflow. I left potential workaround for the S3 case: https://stackoverflow.com/questions/55482233/can-feature-tools-save-feature-list-directly-to-s3/55486555#55486555.

this issue could be extended to also handle writing to s3 if the filepath begins with s3://

[rwedge]

To summarize the expected calls:

• Returns the serialized features as a string

ft.save_features(features) 

• Saves the serialized features as a file

ft.save_features(features, '/path/to/save/to.txt')

• Save the features to open file f

ft.save_features(features, f)

• Save the features to s3 file

ft.save_features(features, "s3://bucket/file.txt")