Accessing the Oracle Object Store


OCI Object Store Examples

The following are a series of examples showing the loading of data into the Oracle Object Store. For these to work with your own data you'll need to have your own Oracle Cloud account and uploaded a key. You can find details on how to achieve this here

I'll be using the Oracle OCI Python SDK which wrappers the REST API. You can find details on the API here

Before we do anything we'll need to load the required needed Python modules.

In [127]:
import oci
import keyring
import ast
import os

Configuration needed to connect

I'm using the "keyring" Python module to hold the config for my connection to OCI (to avoid needlessly exposing sensitive information). It's of the form

    "user": "your user ocid",
    "key_file": "the path to your private key file",
    "fingerprint": "the fingerprint of your public key",
    "tenancy": "your tenancy ocid",
    "region": "the region you are working with"

After retrieving it from my keyring store I then need to convert it into a dictionary before using it. You can also validate the config you are using as well. Handy if this is the first time you've configured it.

In [128]:
my_config = ast.literal_eval(keyring.get_password('oci_opj','doms'))

Create object storage client

Then I just need to retireve a Object Storage client to start working with data

In [129]:
object_storage_client = oci.object_storage.ObjectStorageClient(my_config)
In [130]:
namespace = object_storage_client.get_namespace().data
bucket_name = "doms_object_store"

Upload the contents of user directory to a bucket

I'll create a bucket and then select all of the files from a user defined directory and upload them to the newly created bucket

In [131]:
import os, io

directory = '/Users/dgiles/datagenerator/bin/generateddata'
files_to_process = [file for file in os.listdir(directory) if file.endswith('csv')]

Create a bucket named "Sales_Data" and give it the tenancy ocid from your config.

In [132]:
    create_bucket_response = object_storage_client.create_bucket(
except Exception as e:

Then we just need to loop through the list of files in the directory specified and upload them to the newly created bucket

In [133]:
bucket_name = 'Sales_Data'
for upload_file in files_to_process:
    print('Uploading file {}'.format(upload_file))
    object_storage_client.put_object(namespace, bucket_name, upload_file,,upload_file),'r'))
Uploading file CUSTOMERS.csv
Uploading file PRODUCTS.csv
Uploading file COUNTRIES.csv
Uploading file PROMOTIONS.csv
Uploading file CHANNELS.csv
Uploading file SALES.csv

Retrieve a list of objects in a bucket

The folowing retrieves a bucket and gets a list of objects in the bucket

In [134]:
bucket = object_storage_client.get_bucket(namespace, bucket_name)
object_list = object_storage_client.list_objects(namespace, bucket_name)

for o in

Download the contents of an object

The following downloads a file from a named bucket in chunks and writes it to user defined directory on the client

In [135]:
# Attempt to download a file

object_name = "CUSTOMERS.csv"
destination_dir = '/Users/dgiles/Downloads'.format(object_name) 
get_obj = object_storage_client.get_object(namespace, bucket_name, object_name)
with open(os.path.join(destination_dir,object_name), 'wb') as f:
    for chunk in * 1024, decode_content=False):

Delete a bucket

We can just as simply delete the bucket we've just created but first we'll need to delete all of the objects inside of it.

In [136]:
object_list = object_storage_client.list_objects(namespace, bucket_name)

for o in
    print('Deleting object {}'.format(
    object_storage_client.delete_object(namespace, bucket_name,

print('Deleting bucket')    
response = object_storage_client.delete_bucket(namespace, bucket_name)
Deleting object CHANNELS.csv
Deleting object COUNTRIES.csv
Deleting object CUSTOMERS.csv
Deleting object PRODUCTS.csv
Deleting object PROMOTIONS.csv
Deleting object SALES.csv
Deleting bucket