RudderStack’s Transformations feature lets you write custom functions to implement specific use-cases on your event data, like:
- Filtering or sampling events
- Cleaning or aggregating data
- Data masking or removing sensitive PII to ensure data privacy
- Enriching events by implementing static logic or leveraging an external API
- Using an API to implement specific actions on the events
plans. See the Pricing
page for more information.
- Transformations are easy to build, manage, debug, and reuse.
- Enrich your events in-flight with custom logic before sending them to your destinations.
- Use prebuilt templates to create transformations for specific use-cases by leveraging Templates.
RudderStack’s Python transformations feature lets you use custom Python code to transform your source events on the fly. It is especially useful for the data teams that generally deal with Python.
- Python transformations are available only for:
- RudderStack supports Python version 3.11 for writing transformations.
- RudderStack supports only some of the built-in Python packages to write transformations. These are datetime, json, math, random, requests, time, and urllib, along with the external package python-dateutil.
In this section
See the following guides to learn more about the different Transformations features and their usage:
|Add and test new transformations in RudderStack.
|Use transformations in different RudderStack connection modes.
|Perform different operations on your transformations like connecting them to destinations, managing notifications, etc.
|Reuse transformation code with transformation libraries.
|Use prebuilt transformations to implement specific use cases on your event data.
|Fetch geolocation information from IP address using RudderStack’s geolocation service.
|Get full visibility into the transformation-specific metrics including errors.
|Debug various transformation and library errors.
|Answers to some of the commonly asked questions on transformations.
Questions? Contact us by email or on