Transform

The Transform component lets you transform a data source, whether internal (PandaSuite collection) or external (REST API, JSON), to adapt it to the expected format of another service or component – all without writing a single line of code. It’s a true bridge between the PandaSuite world (collections, references, multi-references) and external formats (JSON tables, third-party services).

It automatically detects elements compatible with Panda types and uses functions when PandaSuite types are detected (e.g., parseCord) to process GPS strings separated by ;.

Use cases

• You already have a PandaSuite collection and need to send this data to an external service (Airtable, REST API, Firebase…) that expects a specific table format.
• You call an external API (via the HTTP component); the response is an array of objects that PandaSuite doesn’t yet recognize as an exploitable collection.
• You want to normalize or enrich your data: remove unnecessary fields, add calculated values, rename keys, convert GPS coordinates, etc.

Setting up the component

Inserting into your project

1. Open your project in PandaSuite Studio.
2. In the Components menu, search for Transform.
3. Drag and drop the component onto your scene.

Component features

Properties

Property	Description	Notes
Source	Link to an array or a collection.	Required
Mode	Type of transformation. Currently fixed to Map (disabled in the UI, reserved for future modes).	Read-only
Format	Output format choice: Table (JavaScript array) or Collection.	Impacts how PandaSuite exposes the result
Item	JSON template describing how each source element is transformed.	Auto-generated from source, fully editable

Real-Time preview

Double-click the Transform component to enter its context. You have two views:

• JSON: shows the raw response as it will be provided to other components.
• Table: a tabular preview, easier to quickly validate your mapping.

Practical examples

Preparing to send a PandaSuite Collection to Airtable

Goal: update the “Records” table in Airtable from a PandaSuite collection.

1. Source: select your PandaSuite collection (e.g., leads).
2. Format: choose Table (Airtable expects an array of objects).
3. Item (Auto-generated): Transform pre-fills the JSON with all fields from leads.
   • Remove unnecessary keys.
   • Wrap everything in the fields node.
   • Add static fields or bindings if needed (e.g., current date).
4. Sending: use this Transform as the Body of the PATCH or POST request in the HTTP component.

Converting an API response into a PandaSuite Collection

Goal: display Airtable records (native API format) in a Collection / List.

2. Source:

• Configure the GET request to Airtable via the HTTP component.
• The response contains a records array.
• Select records (the array) as the Source of Transform.

3. Format: choose Collection.

4. Item (Auto-generated): Transform detects the structure and suggests keys such as fields.Name, fields.Image, etc.

5. The output of Transform becomes the Source of a Collection / List component; you can then use references, multi-references, filters, dynamic pages…

Best practices

• Always test the transformation in the preview panel before connecting other components.
• Clearly name your Transform (e.g., Transform to Airtable or API → Collection) to keep logic readable.
• Centralize transformations: one Transform can be used as a source for several components (HTTP, Condition, etc.).
• Keep the Item light; the simpler it is, the easier it is to maintain.

FAQ

The output JSON looks correct but my API returns an error; what should I do?
Check headers and format (array vs. object). Use the JSON preview to confirm.

Can I chain multiple Transforms?
Yes. The output of one Transform can be the source of a second Transform for more complex transformations.

Does Transform affect my original collection?
No. It only reads the source and creates a new output object; your data remains intact.