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The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData API Driver for Python, the pandas & Matplotlib modules, and the SQLAlchemy toolkit, you can build Webex-connected Python applications and scripts for visualizing Webex data. This article shows how to use the pandas, SQLAlchemy, and Matplotlib built-in functions to connect to Webex data, execute queries, and visualize the results.
With built-in optimized data processing, the CData Python Connector offers unmatched performance for interacting with live Webex data in Python. When you issue complex SQL queries from Webex, the driver pushes supported SQL operations, like filters and aggregations, directly to Webex and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).
Connecting to Webex 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.
To authenticate to Webex, and connect to your own data or to allow other users to connect to their data, you can use the OAuth standard.
First, you will need to register an OAuth application with Webex. To do so, navigate to the Webex Developer Portal and create a new integration. Your OAuth application will be assigned a client id and a client secret.
After setting the following connection properties, you are ready to connect:
Profile=C:\profiles\Webex.apip;Authscheme=OAuth;InitiateOAuth=GETANDREFRESH;OAuthClientId=your_client_id;OAuthClientSecret=your_client_secret;CallbackUrl=your_callback_url;ProfileSettings='Scope=your_scopes';
Follow the procedure below to install the required modules and start accessing Webex through Python objects.
Use the pip utility to install the pandas & Matplotlib modules and the SQLAlchemy toolkit:
pip install pandas pip install matplotlib pip install sqlalchemy
Be sure to import the module with the following:
import pandas import matplotlib.pyplot as plt from sqlalchemy import create_engine
You can now connect with a connection string. Use the create_engine function to create an Engine for working with Webex data.
engine = create_engine("api:///?Profile=C:\profiles\Webex.apip&Authscheme=OAuth&InitiateOAuth=GETANDREFRESH&OAuthClientId=your_client_id&OAuthClientSecret=your_client_secret&CallbackUrl=your_callback_url&ProfileSettings='Scope=your_scopes'")
Use the read_sql function from pandas to execute any SQL statement and store the resultset in a DataFrame.
df = pandas.read_sql("SELECT , FROM AdminAuditEvents WHERE OrgId = 'org123'", engine)
With the query results stored in a DataFrame, use the plot function to build a chart to display the Webex data. The show method displays the chart in a new window.
df.plot(kind="bar", x="", y="") plt.show()👁 Webex data in a Python plot (Salesforce is shown).
Download a free, 30-day trial of the CData API Driver for Python to start building Python apps and scripts with connectivity to Webex data. Reach out to our Support Team if you have any questions.
import pandas
import matplotlib.pyplot as plt
from sqlalchemy import create_engin
engine = create_engine("api:///?Profile=C:\profiles\Webex.apip&Authscheme=OAuth&InitiateOAuth=GETANDREFRESH&OAuthClientId=your_client_id&OAuthClientSecret=your_client_secret&CallbackUrl=your_callback_url&ProfileSettings='Scope=your_scopes'")
df = pandas.read_sql("SELECT , FROM AdminAuditEvents WHERE OrgId = 'org123'", engine)
df.plot(kind="bar", x="", y="")
plt.show()
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