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Writing Mappings

skill-celigo-ai-writing-mappings · by celigo

Write field mappings and transforms in Celigo integrations. Covers Mapper 2.0 (imports), Transformation 2.0 (exports), lookups, response mapping, and Mapper 1.0 (NetSuite/Salesforce). Use when editing mappings[], transform{}, responseMapping, or lookup configurations.

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About

Writing Mappings and Transforms

Mappings and transforms are the data reshaping layer in Celigo integrations. They control how fields from one system translate into fields for another. Mappings are used across flows, APIs, and tools.

Mapping Systems

Four systems handle data reshaping:

  • Mapper 2.0 -- modern recursive field mapping on imports (mappings[] array). Handles nested objects, arrays of any depth, lookups, conditionals, and date conversions. Default for new imports on all adaptor types except NetSuite and Salesforce
  • Mapper 1.0 -- legacy flat mapping on NetSuite and Salesforce imports (mapping.fields[] / mapping.lists[]). Body-level and sublist fields in separate flat arrays. Also present on many older HTTP/FTP/RDBMS imports created before Mapper 2.0 existed
  • Transformation 2.0 -- rule-based data reshaping on exports (transform.expression.rulesTwoDotZero). Uses the same Mapper 2.0 schema internally. Two modes: "create" (build new record from scratch) or "modify" (edit fields on existing record, unmapped fields pass through)
  • Response mapping -- simple extract/generate pairs that carry data from a lookup or import response back into the record (responseMapping on flow pageProcessors[]). Uses Transformation 1.0 syntax

Lookups are shared across all systems -- static key-value maps or references to LookupCache resources for large/dynamic datasets. NetSuite imports use a distinct lookup system that queries live NetSuite records.

Quick Reference

Which Mapping System?

| Context | System | Syntax | Read schema | |---|---|---|---| | Import field mapping (HTTP, RDBMS, FTP, S3, etc.) | Mapper 2.0 | mappings[] | [mappings.yml](references/schemas/mappings.yml) | | NetSuite/Salesforce import | Mapper 1.0 | mapping.fields[] | see import schema ([netsuitedistributed.yml](../configuring-imports/references/schemas/netsuitedistributed.yml), [salesforce.yml](../configuring-imports/references/schemas/salesforce.yml)) | | Export data reshaping | Transformation 2.0 | transform{} | [transform.yml](references/schemas/transform.yml) | | Response mapping (lookup/import carry-back) | Transformation 1.0 | extract/generate pairs | [response-mapping.yml](references/schemas/response-mapping.yml) | | Value translation | Lookups | lookups[] | [lookups.yml](references/schemas/lookups.yml) |

Editing existing imports: Many existing imports use Mapper 1.0 even for HTTP and RDBMS adaptor types (pre-dating Mapper 2.0). Always check whether an import uses mappings[] (2.0) or mapping.fields[] (1.0) before modifying -- never mix the two.

Schema Index

| Schema | Contents | |---|---| | [mappings.yml](references/schemas/mappings.yml) | Mapper 2.0 field definitions (generate, extract, dataType, buildArrayHelper, conditionals) | | [lookups.yml](references/schemas/lookups.yml) | Static and dynamic lookup definitions | | [transform.yml](references/schemas/transform.yml) | Transformation 2.0 envelope (mode, expression, script) | | [response-mapping.yml](references/schemas/response-mapping.yml) | Transformation 1.0 extract/generate pairs for response carry-back | | [netsuitedistributed.yml](../configuring-imports/references/schemas/netsuitedistributed.yml) | NetSuite Mapper 1.0 mapping + lookups | | [salesforce.yml](../configuring-imports/references/schemas/salesforce.yml) | Salesforce Mapper 1.0 mapping |

Related Skills

  • [configuring-imports > Quick Reference](../configuring-imports/SKILL.md#quick-reference) -- import adaptor types, operation logic, hooks
  • [configuring-exports > Quick Reference](../configuring-exports/SKILL.md#quick-reference) -- export adaptor types, delta syncs, webhooks
  • [writing-handlebars > Quick Reference](../writing-handlebars/SKILL.md#quick-reference) -- Handlebars expressions used inside mapping extract fields
  • [building-flows > How to Build a Flow](../building-flows/SKILL.md#how-to-build-a-flow) -- wiring exports and imports into a flow pipeline

Mapper 2.0 Workflow

The mappings[] array is recursive -- a mapping can contain nested child mappings of the same structure to any depth. This is the core design principle.

1. Check the existing resource

Before modifying mappings, always retrieve the current state of the resource. Check whether it uses Mapper 2.0 (mappings[]) or Mapper 1.0 (mapping.fields[]).

celigo imports get 
celigo account search 

2. Understand the source data shape

Invoke the upstream export to see real records, or query the source system's metadata for the full field list.

celigo exports invoke 
celigo metadata fields  

3. Understand the target data shape

Query metadata for the target system to discover required fields and types.

celigo metadata types 
celigo metadata fields  

4. Choose the input context

The input context controls what data is available to extract paths. Set via the "Input context" dropdown in the mapper UI:

  • record (default) -- extract paths reference the record directly. $.user_id accesses the user_id field on the record
  • envelope -- extract paths reference a wrapper object containing record, job, settings (with connection, flow, integration, flowGrouping), iClient, and import. Record fields shift to $.record.user_id, but you gain access to metadata like $.settings.connection.api_username, $.job.type, $.settings.flow.fieldName

When to use envelope: APIs and tools where you need request context (headers, path params, query params, connection settings) directly in mappings without Handlebars. Also useful on transforms at the beginning of API/tool steps where the envelope exposes the full request context. Envelope context eliminates the need for {{settings.connection.fieldName}} Handlebars expressions -- use $.settings.connection.fieldName instead.

5. Map by data type

Every mapping needs three properties: generate (target field name), dataType (output type), and extract (how to get data from source).

Extract supports three patterns (distinguished by syntax):

  • JSON path -- starts with $. (e.g., $.customer.email). Always references the top-level root, even in nested mappings
  • Handlebars -- contains {{ (e.g., {{record.firstName}} {{record.lastName}}). For computed values
  • Hard-coded -- plain string literal (e.g., "Active", "USD"). Neither $. prefix nor {{

Simple types (string, number, boolean, date) -- direct field-to-field mapping. For dates, set extractDateFormat/generateDateFormat for conversion.

Objects -- set dataType: "object", add child mappings in the mappings[] array. Never use dot notation in generate.

Arrays -- set dataType to an array type (stringarray, numberarray, booleanarray, objectarray, arrayarray) and configure buildArrayHelper[]. Three patterns for object arrays:

  • Extract only -- pull existing objects from source (extract: "$.items[*]")
  • Mappings only -- construct objects from individual fields (each buildArrayHelper entry creates one array element)
  • Extract + mappings -- iterate a source array and reshape each element. Uses the composite object mechanism: array brackets [*] in the extract path collapse to single objects inside the mappings, so $.orders[*].items[*] becomes $.orders.items.fieldName in child extract paths. Parent context remains accessible (e.g., $.orders.id, $.customerName)

6. Add lookups for value translation

Define lookups alongside mappings and reference them by name via lookupName on any mapping.

  • Static -- map object with key-value pairs. Best for small, fixed sets (country codes, status values)
  • Dynamic -- _lookupCacheId referencing a LookupCache resource, with optional extract JSON path to pull a specific field from the cached object
  • Set allowFailures: true + default to continue processing when lookup keys are missing

7. Add conditionals where needed

Control when a mapping applies: record_created (only on insert), record_updated (only on update), or extract_not_empty (skip when source is null/empty).

Schema reference

All Mapper 2.0 field definitions: [mappings.yml](references/schemas/mappings.yml), [lookups.yml](references/schemas/lookups.yml)

Transformation 2.0 Workflow

Transformation 2.0 reshapes data on exports before it enters the pipeline. It wraps Mapper 2.0 syntax in a transform envelope with a mode selector.

1. Check the existing resource

Before modifying transforms, retrieve the current export to inspect any existing transform configuration.

celigo exports get 
celigo account search 

2. Choose the mode

  • create -- build a completely new record. Only mapped fields appear in output. Use when the output structure differs significantly from the source
  • modify -- edit specific fields on the existing record. Unmapped fields pass through unchanged. Use for surgical adjustments (rename, add, remove a few fields)

3. Write the mappings

Same Mapper 2.0 syntax: generate, dataType, extract, nested mappings, buildArrayHelper, lookups. Everything described in the Mapper 2.0 section above applies here, including input context.

Input context is especially valuable on transforms for APIs and tools -- set it to envelope to access the full request context (headers, path params, query params, connection settings) directly via JSON path instead of Handlebars.

4. Configure the transform envelope

Set transform.type: "expression", expression.version: "2", then place mappings[] and lookups[] under expression.rulesTwoDotZero with the chosen mode.

Script alternative: Set transform.type: "script" with script._scriptId and script.function for programmatic transforms when expression rules aren't sufficient.

Schema reference

All Transformation 2.0 field definitions: [transform.yml](references/schemas/transform.yml), [mappings.yml](references/schemas/mappings.yml), [lookups.yml](references/schemas/lookups.yml)

Mapper 1.0 Reference (NetSuite and Salesforce)

NetSuite and Salesforce imports use the older flat mapping structure. Two arrays within the mapping object:

  • mapping.fields[] -- body-level field mappings. Each entry has extract (source path) or hardCodedValue (static value), generate (target field ID), and optional lookupName, dataType, internalId, immutable, discardIfEmpty, conditional
  • mapping.lists[] -- sublist/line-item mappings. Each entry has generate (sublist ID, e.g., "item"), jsonPath (source array path), and fields[] (column mappings with the same properties as body fields, plus isKey for matching existing lines)

NetSuite lookups are different -- they query live NetSuite records using recordType, searchField, resultField, and operator. Not static maps. Defined in netsuite_da.lookups[], referenced by lookupName in field mappings. To discover valid field IDs for searchField and resultField, run celigo metadata fields — the returned field IDs are the exact values to use.

Salesforce lookups follow the same Mapper 1.0 pattern but the lookup structure is simpler.

Sublist field discovery: For NetSuite mapping.lists[].generate, the sublist name (e.g., "item", "addressbook") comes from celigo metadata fields — sublists appear as field groups. For Salesforce related lists, use celigo metadata fields to discover relationship fields and child object names for distributed.relatedLists[].sObjectType.

Schema reference

NetSuite Mapper 1.0: see mapping and lookups in the configuring-imports skill's [netsuitedistributed.yml](../configuring-imports/references/schemas/netsuitedistributed.yml) Salesforce Mapper 1.0: see mapping in the configuring-imports skill's [salesforce.yml](../configuring-imports/references/schemas/salesforce.yml)

Response Mapping Reference (Transformation 1.0)

Response mapping extracts fields from a lookup or import API response back into the original record. It lives on the flow's pageProcessors[] entry, not on the resource itself -- but it's planned when building the resource.

Two sections:

  • fields.type[] -- field-level extract/generate pairs using dot notation
  • lists.type[] -- array mappings with generate (target array name) and fields[] (column mappings)

For lookup exports: the response contains data[] and errors[]. Use data[0].fieldName for single results, data[*].fieldName when multiple results are expected.

For imports: the response is available via _json. Use _json.fieldName (e.g., _json.id for a created record's ID, _json.output.1.content.0.text for AI model responses).

Schema reference

All response mapping field definitions: [response-mapping.yml](references/schemas/response-mapping.yml)

CLI Commands

# Discover resources
celigo account search               # Find imports/exports by name
celigo imports get                  # Inspect existing import (check mappings vs mapping)
celigo exports get                  # Inspect existing export (check transform)

# Understand data shapes
celigo exports invoke               # See real source records
celigo metadata types           # List entity types
celigo metadata fields    # List fields for an entity

# Update mappings (GET -> modify -> PUT)
celigo imports set  = [= ...]   # Field-level edit (dot/bracket paths, JSON values)
celigo exports set  = [= ...]
celigo imports update   < export.json

Pre-Submit Checklist

Before submitting any mapping configuration, verify:

  • [ ] Correct system identified -- mappings[] for Mapper 2.0, mapping.fields[] for Mapper 1.0; never mix
  • [ ] status: "Active" on every mapping entry -- API rejects entries without it
  • [ ] No dot notation in generate -- use nested dataType: "object" with child mappings[] instead
  • [ ] Extract paths start from root -- $. paths always reference the top-level input, even in nested mappings
  • [ ] Array mappings have buildArrayHelper -- required for all *array dataTypes
  • [ ] Lookups defined and referenced -- every lookupName on a mapping has a corresponding entry in lookups[]
  • [ ] Date formats specified -- extractDateFormat/generateDateFormat set when dataType: "date"
  • [ ] Full resource PUT -- GET the complete resource first, modify only the mapping section, PUT the whole object back
  • [ ] Response mapping on the flow -- responseMapping lives on flow.pageProcessors[], not on the import resource itself
  • [ ] Composite object paths adjusted -- when buildArrayHelper has both extract and mappings, child extract paths drop the [*] brackets

Gotchas

  1. Existing imports may use Mapper 1.0 even for HTTP/RDBMS/FTP. Mapper 2.0 is the default for new imports, but many older imports across all adaptor types use Mapper 1.0. Always check the existing format before editing -- mappings[] means 2.0, mapping.fields[] means 1.0. Never mix.
  2. Extract paths always reference the root of the input context. Even in deeply nested Mapper 2.0 mappings, $. paths start from the top level (the record in record context, or the envelope in envelope context), not the current nesting level.
  3. Composite object collapses arrays to single objects. When buildArrayHelper has both extract and mappings, array brackets in the extract path are replaced with single objects in child mapping contexts. $.orders[*].items[*] becomes $.orders.items.fieldName inside the mappings.
  4. Response mapping uses Transformation 1.0 syntax, not 2.0. Don't use rulesTwoDotZero structure in responseMapping. It uses simple extract/generate pairs with dot notation.
  5. NetSuite lookups query live data. A NetSuite import's netsuite_da.lookups[] searches NetSuite records at runtime (recordType

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.