How to Visualize IBM Cloud Object Storage Data in Python with pandas via CData Connect AI

The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData Connect AI Python SDK, the pandas and Matplotlib modules, you can build IBM Cloud Object Storage-connected Python applications and scripts for visualizing IBM Cloud Object Storage data. This article shows how to connect to Connect AI and use the pandas and Matplotlib built-in functions to query IBM Cloud Object Storage data and visualize the results.

The Connect AI Python SDK (cdata-connect-ai) is a DB-API 2.0 (PEP 249) compliant client, so pandas can read query results directly from the SDK connection object. There is no driver to install per source and no SQLAlchemy engine to configure: connect with a Personal Access Token and pass the connection straight to pandas.read_sql.

Connect to IBM Cloud Object Storage in Connect AI

CData Connect AI uses a straightforward, point-and-click interface to connect to data sources.

1. Log into Connect AI, click Sources, and then click Add Connection

2. Select "IBM Cloud Object Storage" from the Add Connection panel

3. Enter the necessary authentication properties to connect to IBM Cloud Object Storage.

   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, 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.
   
4. Click Save & Test
5. Navigate to the Permissions tab and update the user-based permissions.

Generate a Personal Access Token (PAT)

The Python SDK authenticates to Connect AI with your account email and a Personal Access Token (PAT). It is best practice to create a separate PAT for each application to maintain granularity of access.

1. Click the Gear icon () at the top right of the Connect AI app to open the Settings page.
2. On the Settings page, go to the Access Tokens section and click Create PAT.
3. Give the PAT a name and click Create.
4. The PAT is only visible at creation, so copy it and store it securely.

Install Required Modules

Install the SDK (with the pandas extra) and Matplotlib using the pip utility:

pip install "cdata-connect-ai[full]"
pip install matplotlib

Visualize IBM Cloud Object Storage Data in Python

Import the modules, then connect to Connect AI with your account email and PAT. Identifiers are three-part: <Connection>.<Schema>.<Table>, where the connection name defaults to the source name (for example, IBMCloudObjectStorage1).

import pandas
import matplotlib.pyplot as plt
import cdata_connect_ai

conn = cdata_connect_ai.connect(
    username="[email protected]",
    password="<your_pat>",
)

Query IBM Cloud Object Storage with pandas

Use the read_sql function from pandas to execute a SQL statement and store the result set in a DataFrame. Pass the SDK connection directly, no engine required.

df = pandas.read_sql(
    "SELECT Key, Etag "
    "FROM [IBMCloudObjectStorage1].[IBMCloudObjectStorage].[Objects] "
    "WHERE Bucket = 'someBucket'",
    conn,
)

Note: pandas may print a UserWarning stating that it only officially supports SQLAlchemy connectables. This is expected when passing a DB-API connection directly—the query runs correctly and the warning is safe to ignore.

Visualize IBM Cloud Object Storage Data

With the query results stored in a DataFrame, use the plot function to build a chart. The show method displays the chart in a new window.

df.plot(kind="bar", x="Key", y="Etag")
plt.show()

conn.close()

More Information and Free Trial

Now you can read live IBM Cloud Object Storage data into pandas through the CData Connect AI Python SDK. For more information on connecting to IBM Cloud Object Storage (and hundreds of other data sources), visit the Connect AI page. Sign up for a free trial and start working with live IBM Cloud Object Storage data in Python.

Full Source Code

import pandas
import matplotlib.pyplot as plt
import cdata_connect_ai

conn = cdata_connect_ai.connect(
    username="[email protected]",
    password="<your_pat>",
)

df = pandas.read_sql(
    "SELECT Key, Etag "
    "FROM [IBMCloudObjectStorage1].[IBMCloudObjectStorage].[Objects] "
    "WHERE Bucket = 'someBucket'",
    conn,
)

df.plot(kind="bar", x="Key", y="Etag")
plt.show()

conn.close()