I have a bucket set up on Google Cloud containing a few hundred json files and am trying to work with them in a datalab instance running python 3.
So, I can easily see them as objects using
gcs list --objects gs://<BUCKET_NAME>
Further, I can read in an individual file/object using
import google.datalab.storage as storage
import pandas as pd
from io import BytesIO
myBucket = storage.Bucket('<BUCKET_NAME')
data_csv = myBucket.object('<FILE_NAME.json')
uri = data_csv.uri
%gcs read --object $uri --variable data
df = pd.read_csv(BytesIO(data))
df.head()
(FYI, I understand that my example is reading a json as a csv, but let's ignore that- I'll cross that bridge on my own)
What I can't figure out is how to loop through the bucket and pull all of the json files into pandas...how do I do that? Is that the way I should be thinking of this- is there a way to call the files in the bucket from pandas directly (since they're already treated as objects)?
As an extra bit- what if a file is saved as a json, but isn't actually that structure? How can I handle that?
Essentially, I guess, I'm looking for the functionality of the blob package, but using cloud buckets + datalab.
Any help is greatly appreciated.