Data transforms
Filter and manipulate data with transform actions and inline functions.
If you’re looking to transform data directly in the action inputs editor, check out Tracecat inline functions.
Data transforms allow you to filter, reshape, and manipulate data within your workflows. Tracecat supports the following transform actions:
core.transform.reshape
: Reshape and manipulate data.core.transform.filter
: Filter a list of items.core.transform.is_in
: Check if an item is in a list.core.transform.not_in
: Check if an item is not in a list.core.transform.deduplicate
: Deduplicate a list of JSON objects given a list of keys.core.transform.apply
: Apply apython_lambda
function to a value.core.transform.map
: Apply apython_lambda
function to each item in a list.
Deduplicate
Deduplicate a list of JSON objects given a list of keys.
Examples
Python Lambda
Some transform actions (e.g. core.transform.filter
, core.transform.map
) accept an input called python_lambda
.
python_lambda
is a Python Lambda function given as a string.
It allows you to use small snippets of Python code to transform data and define conditions.
Python lambda functions are small anonymous functions that are used to define simple functions that are passed to other functions. You can learn more about them here.
It can be hard to escape special characters in YAML.
Werecommend using python_lambda
with the >-
and >
YAML block modifiers
to avoid these issues:
Filter
Filter a list of items given a Python lambda function. This function should return a truthy or falsy value.
Apply
Apply a Python lambda function to a value.
Map
Apply a Python lambda function to each item in a list.