You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
{{ message }}
This repository was archived by the owner on Aug 30, 2025. It is now read-only.
Custom Transfomers are a great way to configure a system transformer with your own presets and publish it everywhere. Custom transformers are saved at the account level and
17
+
can be used across multiple jobs, saving your time during the schema configuration process.
In order to create a custom transformer, follow these steps:
24
+
25
+
1. Navigate to the **Transformers** page and click on **+ New Transformer**.
26
+
2. You'll be brought to the new transformer page where you can select a base transformer. A base transformer serves as the blueprint for the custom transformer. Select the base transformer for your custom transformer.
3. Once you've selected a base transformer, you'll be prompted to give the transformer a name and description. Additionally, you can preset custom default configurations depending on the transformer.
Once you've created a custom transformer, you'll see it appear in the transformer list in Transformers main page as well as the Schema configuration page. Above, we created a custom transformer
41
+
called `custom-string-transformer`, we can now see it both places.
42
+
43
+
In the transformers table under the Custom Transformer tab.
Copy file name to clipboardExpand all lines: docs/docs/transformers/introduction.mdx
+1-1Lines changed: 1 addition & 1 deletion
Display the source diff
Display the rich diff
Original file line number
Diff line number
Diff line change
@@ -21,7 +21,7 @@ import { DocsImage } from '@site/src/CustomComponents/DocsImage';
21
21
22
22
Transformers are data-type specific modules that anonymize or generate data. Tranformers are defined in the job workflow and are applied to every piece of data in the column they are assigned. Neosync ships with a number of transformers that are already built to handle common data types such as email, addresses, ssn, strings, integers and more.
0 commit comments