Using the CData ODBC Driver for Datadog in PyCharm
The CData ODBC Drivers can be used in any environment that supports loading an ODBC Driver. In this tutorial we will explore using the CData ODBC Driver for Datadog from within PyCharm. Included are steps for adding the CData ODBC Driver as a data source, as well as basic PyCharm code to query the data source and display results.
To begin, this tutorial will assume that you have already installed the CData ODBC Driver for Datadog as well as PyCharm.
Add Pyodbc to the Project
Follow the steps below to add the pyodbc module to your project.
- Click File -> Settings to open the project settings window.
- Click Project Interpreter from the Project: YourProjectName menu.
- To add pyodbc, click the + button and enter pyodbc.
- Click Install Package to install pyodbc.
Connect to Datadog
You can now connect with an ODBC connection string or a DSN. See the Getting Started section in the CData driver documentation for a guide to creating a DSN on your OS.
Start by setting the Profile connection property to the location of the Datadog Profile on disk (e.g. C:\profiles\Datadog.apip). Next, set the ProfileSettings connection property to the connection string for Datadog (see below).
Datadog API Profile Settings
In your Datadog account, navigate to Organization Settings > API Keys to create an API Key, and Organization Settings > Application Keys to create an Application Key. Both are required.
Below is the syntax for a DSN:
[CData API Source] Driver = CData ODBC Driver for Datadog Description = My Description Profile = C:\profiles\Datadog.apip ProfileSettings = 'APIKey = your_api_key ApplicationKey = your_app_key'
Execute SQL to Datadog
Instantiate a Cursor and use the execute method of the Cursor class to execute any SQL statement.
import pyodbc
cnxn = pyodbc.connect('DRIVER={CData ODBC Driver for API};Profile = C:\profiles\Datadog.apip;ProfileSettings = 'APIKey = your_api_key;ApplicationKey = your_app_key';')
cursor = cnxn.cursor()
cursor.execute("SELECT FilterId, Name FROM APMRetentionFilters WHERE IsEnabled = 'true'")
rows = cursor.fetchall()
for row in rows:
print(row.FilterId, row.Name)
After connecting to Datadog in PyCharm using the CData ODBC Driver, you will be able to build Python apps with access to Datadog data as if it were a standard database. If you have any questions, comments, or feedback regarding this tutorial, please contact us at [email protected].