| name | writing-mappings |
| description | 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. |
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?
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
Related Skills
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 <importId>
celigo account search <keyword>
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 <exportId>
celigo metadata fields <sourceConnectionId> <entityType>
3. Understand the target data shape
Query metadata for the target system to discover required fields and types.
celigo metadata types <targetConnectionId>
celigo metadata fields <targetConnectionId> <entityType>
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, 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 <exportId>
celigo account search <keyword>
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, mappings.yml, 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 <connectionId> <recordType> — 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 <connectionId> <recordType> — sublists appear as field groups. For Salesforce related lists, use celigo metadata fields <connectionId> <sObjectType> 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
Salesforce Mapper 1.0: see mapping in the configuring-imports skill's 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
CLI Commands
celigo account search <keyword>
celigo imports get <importId>
celigo exports get <exportId>
celigo exports invoke <exportId>
celigo metadata types <connectionId>
celigo metadata fields <connectionId> <type>
celigo imports set <importId> <key>=<value> [<key2>=<value2> ...]
celigo exports set <exportId> <key>=<value> [<key2>=<value2> ...]
celigo imports update <importId> < import.json
celigo exports update <exportId> < export.json
Pre-Submit Checklist
Before submitting any mapping configuration, verify:
Gotchas
- 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.
- 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.
- 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 $.orders.items.fieldName inside the mappings.
- Response mapping uses Transformation 1.0 syntax, not 2.0. Don't use
rulesTwoDotZero structure in responseMapping. It uses simple extract/generate pairs with dot notation.
- NetSuite lookups query live data. A NetSuite import's
netsuite_da.lookups[] searches NetSuite records at runtime (recordType, searchField, resultField), unlike Mapper 2.0 static map lookups.
generate must not use dot notation in Mapper 2.0. Build nested structures with dataType: "object" and child mappings[]. "generate": "customer.name" silently creates a field literally named "customer.name".
- Empty
generate indicates inner array in arrayarray. For nested array structures, inner array mappings have no generate field -- this is expected, not an error.
- Transformation 2.0 "modify" passes through unmapped fields. "Create" mode only outputs explicitly mapped fields. Choose based on whether you want a clean slate or surgical edits.
- PUT erases omitted fields on the parent resource. When updating mappings on an import or transform on an export, always GET the full resource first, modify the mapping/transform section, then PUT the complete object. The
set command handles this.
Common Errors
| Error | Cause | Fix |
|---|
| "Mapping object must have status field present" | Missing status on a mapping entry | Add status: "Active" to every mapping object |
Import silently creates field named "customer.name" | Dot notation in generate | Use nested dataType: "object" with child mappings[] |
| Mapped fields missing in output | Using Mapper 2.0 syntax on a Mapper 1.0 import (or vice versa) | Check existing format: mappings[] = 2.0, mapping.fields[] = 1.0 |
Extract returns null in nested mapping | Extract path relative to nesting level | Extract paths always start from root ($.), not the current level |
| Array output is empty | Missing buildArrayHelper on array dataType | Add buildArrayHelper[] for all *array dataTypes |
| Lookup key not found / processing stops | allowFailures not set on lookup | Set allowFailures: true and provide a default value |
| Response mapping not applied | responseMapping placed on the import resource | Move to flow.pageProcessors[] entry for that import |
| Composite object paths return wrong data | [*] brackets still in child extract paths | Drop [*] -- arrays collapse to single objects inside buildArrayHelper mappings |
| Date values malformed in output | Missing date format configuration | Set extractDateFormat and generateDateFormat on date mappings |
| PUT overwrites entire resource | Partial JSON sent without GET first | Always GET full resource, modify mapping section, PUT complete object |