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Python Connector Libraries for IBM Cloud Object Storage Data Connectivity. Integrate IBM Cloud Object Storage with popular Python tools like Pandas, SQLAlchemy, Dash & petl.

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How to use SQLAlchemy ORM to access IBM Cloud Object Storage Data in Python


Create Python applications and scripts that use SQLAlchemy Object-Relational Mappings of IBM Cloud Object Storage data.

The rich ecosystem of Python modules lets you get to work quickly and integrate your systems effectively. With the CData Python Connector for IBM Cloud Object Storage and the SQLAlchemy toolkit, you can build IBM Cloud Object Storage-connected Python applications and scripts. This article shows how to use SQLAlchemy to connect to IBM Cloud Object Storage data to query IBM Cloud Object Storage data.

With built-in optimized data processing, the CData Python Connector offers unmatched performance for interacting with live IBM Cloud Object Storage data in Python. When you issue complex SQL queries from IBM Cloud Object Storage, the CData Connector pushes supported SQL operations, like filters and aggregations, directly to IBM Cloud Object Storage and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).

Connecting to IBM Cloud Object Storage Data

Connecting to IBM Cloud Object Storage data looks just like connecting to any relational data source. Create a connection string using the required connection properties. For this article, you will pass the connection string as a parameter to the create_engine function.

Register a New Instance of Cloud Object Storage

If you do not already have Cloud Object Storage in your IBM Cloud account, follow the procedure below to install an instance of SQL Query in your account:

  1. Log in to your IBM Cloud account.
  2. Navigate to the page, choose a name for your instance and click Create. You will be redirected to the instance of Cloud Object Storage you just created.

Connecting using OAuth Authentication

There are certain connection properties you need to set before you can connect. You can obtain these as follows:

API Key

To connect with IBM Cloud Object Storage, you need an API Key. You can obtain this as follows:

  1. Log in to your IBM Cloud account.
  2. Navigate to the Platform API Keys page.
  3. On the middle-right corner click "Create an IBM Cloud API Key" to create a new API Key.
  4. In the pop-up window, specify the API Key name and click "Create". Note the API Key as you can never access it again from the dashboard.

Cloud Object Storage CRN

If you have multiple accounts, you will need to specify the CloudObjectStorageCRN explicitly. To find the appropriate value, you can:

  • Query the Services view. This will list your IBM Cloud Object Storage instances along with the CRN for each.
  • Locate the CRN directly in IBM Cloud. To do so, navigate to your IBM Cloud Dashboard. In the Resource List, Under Storage, select your Cloud Object Storage resource to get its CRN.

Connecting to Data

You can now set the following to connect to data:

  • InitiateOAuth: Set this to GETANDREFRESH. You can use InitiateOAuth to avoid repeating the OAuth exchange and manually setting the OAuthAccessToken.
  • ApiKey: Set this to your API key which was noted during setup.
  • CloudObjectStorageCRN (Optional): Set this to the cloud object storage CRN you want to work with. While the connector attempts to retrieve this automatically, specifying this explicitly is recommended if you have more than Cloud Object Storage account.

When you connect, the connector completes the OAuth process.

  1. Extracts the access token and authenticates requests.
  2. Saves OAuth values in OAuthSettingsLocation to be persisted across connections.

Follow the procedure below to install SQLAlchemy and start accessing IBM Cloud Object Storage through Python objects.

Install Required Modules

Use the pip utility to install the SQLAlchemy toolkit and SQLAlchemy ORM package:

pip install sqlalchemy pip install sqlalchemy.orm

Be sure to import the appropriate modules:

from sqlalchemy import create_engine, String, Column from sqlalchemy.ext.declarative import declarative_base from sqlalchemy.orm import sessionmaker

Model IBM Cloud Object Storage Data in Python

You can now connect with a connection string. Use the create_engine function to create an Engine for working with IBM Cloud Object Storage data.

NOTE: Users should URL encode the any connection string properties that include special characters. For more information, refer to the SQL Alchemy documentation.

engine = create_engine("ibmcloudobjectstorage:///?ApiKey=myApiKey&CloudObjectStorageCRN=MyInstanceCRN&Region=myRegion&OAuthClientId=MyOAuthClientId&OAuthClientSecret=myOAuthClientSecret")

Declare a Mapping Class for IBM Cloud Object Storage Data

After establishing the connection, declare a mapping class for the table you wish to model in the ORM (in this article, we will model the Objects table). Use the sqlalchemy.ext.declarative.declarative_base function and create a new class with some or all of the fields (columns) defined.

base = declarative_base() class Objects(base): __tablename__ = "Objects" Key = Column(String,primary_key=True) Etag = Column(String) ...

Query IBM Cloud Object Storage Data

With the mapping class prepared, you can use a session object to query the data source. After binding the Engine to the session, provide the mapping class to the session query method.

Using the query Method

engine = create_engine("ibmcloudobjectstorage:///?ApiKey=myApiKey&CloudObjectStorageCRN=MyInstanceCRN&Region=myRegion&OAuthClientId=MyOAuthClientId&OAuthClientSecret=myOAuthClientSecret") factory = sessionmaker(bind=engine) session = factory() for instance in session.query(Objects).filter_by(Bucket="someBucket"): print("Key: ", instance.Key) print("Etag: ", instance.Etag) print("---------")

Alternatively, you can use the execute method with the appropriate table object. The code below works with an active session.

Using the execute Method

Objects_table = Objects.metadata.tables["Objects"] for instance in session.execute(Objects_table.select().where(Objects_table.c.Bucket == "someBucket")): print("Key: ", instance.Key) print("Etag: ", instance.Etag) print("---------")

For examples of more complex querying, including JOINs, aggregations, limits, and more, refer to the Help documentation for the extension.

Free Trial & More Information

Download a free, 30-day trial of the CData Python Connector for IBM Cloud Object Storage to start building Python apps and scripts with connectivity to IBM Cloud Object Storage data. Reach out to our Support Team if you have any questions.