Import & Export

Move data in and out seamlessly

Bulk CSV import with preview and validation before persisting. Export to JSON or CSV with dimension-aware scope flattening for clean, channel-ready data files.

CSV Import

Upload rows mapped to schema attributes. Preview validates every row before committing — catch errors before they persist.

Scope Flattening

Export with a scope parameter to flatten dimension-scoped values into simple columns. Perfect for language-specific CSV feeds.

Column Mapping

Map CSV column headers to attribute aliases via columnMapping. Use "_id" to target existing records for updates.

Dual Formats

Export as application/json for API consumers or text/csv with Content-Disposition for direct file downloads.

Endpoints

Method	Path	Description
POST	`/import/preview`	Preview import — validate rows without persisting
POST	`/import/execute`	Execute import — create or update records
GET	`/export`	Export records as JSON or CSV

POST /import/preview

Validate import data without persisting any records. Returns per-row validation results so you can review and fix errors before executing the actual import.

Request Body

Field	Type	Description
`rows`	`Record<string, string>[]`	Array of row objects. Each key is a CSV column name, each value is the cell string.
`schemaId`	`string`	The schema ID to import records into.
`columnMapping`	`Record<string, string>`	Maps CSV column names to attribute aliases. Use `"_id"` as the target to match existing records for updates.

Example — Preview a CSV import

curl -X POST https://api.sigma-pim.com/api/v1/import/preview \
  -H "Authorization: Bearer eyJhbGciOiJIUzI1NiIs..." \
  -H "Content-Type: application/json" \
  -d '{
    "schemaId": "schema-apparel",
    "columnMapping": {
      "Name": "product-name",
      "SKU": "sku",
      "Price": "price"
    },
    "rows": [
      { "Name": "Coastal Windbreaker", "SKU": "CW-001", "Price": "129.99" },
      { "Name": "Summit Parka", "SKU": "SP-002", "Price": "249.50" },
      { "Name": "", "SKU": "XX-003", "Price": "not-a-number" }
    ]
  }'

// Response
{
  "valid": false,
  "totalRows": 3,
  "validRows": 2,
  "invalidRows": 1,
  "results": [
    {
      "row": 0,
      "valid": true,
      "errors": []
    },
    {
      "row": 1,
      "valid": true,
      "errors": []
    },
    {
      "row": 2,
      "valid": false,
      "errors": [
        "product-name: required attribute is missing",
        "price: expected a number value"
      ]
    }
  ]
}

POST /import/execute

Execute the import, creating new records or updating existing ones. Accepts the same request body as /import/preview. When a row's columnMapping includes "_id", the importer matches existing records by ID and updates them instead of creating duplicates.

Request Body

Same schema as POST /import/preview — rows, schemaId, and columnMapping.

Example — Execute a CSV import

curl -X POST https://api.sigma-pim.com/api/v1/import/execute \
  -H "Authorization: Bearer eyJhbGciOiJIUzI1NiIs..." \
  -H "Content-Type: application/json" \
  -d '{
    "schemaId": "schema-apparel",
    "columnMapping": {
      "Name": "product-name",
      "SKU": "sku",
      "Price": "price"
    },
    "rows": [
      { "Name": "Coastal Windbreaker", "SKU": "CW-001", "Price": "129.99" },
      { "Name": "Summit Parka", "SKU": "SP-002", "Price": "249.50" }
    ]
  }'

// Response
{
  "created": 2,
  "updated": 0,
  "errors": []
}

Example — Update existing records by ID

curl -X POST https://api.sigma-pim.com/api/v1/import/execute \
  -H "Authorization: Bearer eyJhbGciOiJIUzI1NiIs..." \
  -H "Content-Type: application/json" \
  -d '{
    "schemaId": "schema-apparel",
    "columnMapping": {
      "ID": "_id",
      "Price": "price"
    },
    "rows": [
      { "ID": "ent-abc123", "Price": "139.99" },
      { "ID": "ent-def456", "Price": "259.00" }
    ]
  }'

// Response
{
  "created": 0,
  "updated": 2,
  "errors": []
}

GET /export

Export records as JSON or CSV. When exporting as CSV with a scope parameter, dimension-scoped attribute values are flattened into simple columns — perfect for generating language- or market-specific product feeds.

Query Parameters

Parameter	Type	Default	Description
`format`	`"json" \| "csv"`	`"json"`	Output format. CSV responses include `Content-Disposition: attachment`.
`schemaId`	`string`	—	Filter to records belonging to this schema.
`scope`	`string`	—	JSON-encoded DimensionScope object for CSV flattening. Example: `{"dim-language":"seg-en"}`

Example — Export as JSON

curl https://api.sigma-pim.com/api/v1/export \
  -H "Authorization: Bearer eyJhbGciOiJIUzI1NiIs..."

// Response — Content-Type: application/json
[
  {
    "id": "ent-abc123",
    "schemaId": "schema-apparel",
    "values": {
      "product-name": [
        { "scope": {}, "value": "Coastal Windbreaker" },
        { "scope": { "dim-language": "seg-da" }, "value": "Kyst Vindjakke" }
      ],
      "sku": [{ "scope": {}, "value": "CW-001" }],
      "price": [{ "scope": {}, "value": 129.99 }]
    }
  }
]

Example — Export as CSV with English scope flattening

curl "https://api.sigma-pim.com/api/v1/export?format=csv&schemaId=schema-apparel&scope=%7B%22dim-language%22%3A%22seg-en%22%7D" \
  -H "Authorization: Bearer eyJhbGciOiJIUzI1NiIs..."

# Response — Content-Type: text/csv
# Content-Disposition: attachment; filename="export.csv"

id,product-name,sku,price
ent-abc123,Coastal Windbreaker,CW-001,129.99
ent-def456,Summit Parka,SP-002,249.50
ent-ghi789,Alpine Fleece,AF-003,89.00

When scope is provided, the exporter resolves each scoped attribute to a single value matching the given dimension segments. This turns multi-scope JSON arrays into flat CSV columns.

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