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What are Fields?

A Field in Flatfile is like a column in a spreadsheet — it defines the data type, format, and any constraints for a single piece of data in your import. Fields are defined inside a Blueprint, which acts as the master schema for your import setup. The hierarchy works like this:
  • A Blueprint defines the structure of one or more Workbooks.
  • Each Workbook contains Sheets (like tabs in a spreadsheet).
  • Each Sheet contains Fields (columns), which describe the individual data points to be collected.
When you configure a Field, you’re telling Flatfile what kind of data to expect in that column—whether it’s text, a number, a date, or another supported type. You can also apply constraints like “required,” “unique,” or “computed” to control how data is handled during import. Fields play a key role in ensuring data structure and quality from the moment users start importing.

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Basic Blueprint Structure

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Basic Field Configuration

The following examples demonstrate the configuration of isolated fields, which are intended to be used in the context of a Blueprint configuration under a Sheet definition.

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Simple Field Definition

This example configures a single string Field that is required and another a number Field with a decimalPlaces config. 
// Basic string field
const nameField = {
  key: "firstName",
  type: "string",
  label: "First Name",
  description: "The customer's first name",
  required: true,
};

// Number field with config
const ageField = {
  key: "age",
  type: "number",
  label: "Age",
  description: "Customer age in years",
  config: {
    decimalPlaces: 2,
  },
};

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Field with Multiple Options

This example configures a single enum field with a status key, Customer Status label, and Current status of the customer description. It also defines four options for the field: active, inactive, pending, and suspended. 
const statusField = {
  key: "status",
  type: "enum",
  label: "Customer Status",
  description: "Current status of the customer",
  options: [
    { value: "active", label: "Active" },
    { value: "inactive", label: "Inactive" },
    { value: "pending", label: "Pending" },
    { value: "suspended", label: "Suspended" },
  ],
};

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Field Types

Flatfile supports 9 field types for defining data structure: Basic Types:
  • string - Basic text data
  • number - Integer or floating point numbers
  • boolean - True/false values
  • date - GMT date values in YYYY-MM-DD format
Single Selection:
  • enum - Single selection from predefined options
Multiple Value Types:
  • string-list - Array of string values
  • enum-list - Multiple selections from predefined options
Reference Types:
  • reference - Single reference to another sheet
  • reference-list - Multiple references to another sheet

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string

A property that should be stored and read as a basic string. 
{
  "key": "productCode",
  "label": "Product Code",
  "type": "string",
  "appearance": {
    "size": "m"
  }
}
Note: String fields don’t have type-specific config options, but support appearance settings.

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string-list

Stores an array of string values. Useful for fields that contain multiple text entries. 
{
  "key": "tags",
  "label": "Product Tags",
  "type": "string-list"
}

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number

A property that should be stored and read as either an integer or floating point number. config.decimalPlaces The number of decimal places to preserve accuracy to. 
{
  "key": "price",
  "label": "Retail Price",
  "type": "number",
  "config": {
    "decimalPlaces": 2
  }
}

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enum

Defines an enumerated list of options for the user to select from (single selection). The maximum number of options for this list is 100. For multiple selections, use enum-list. config.allowCustom Allow users to create new options for this field. When enabled, users will be able to import their custom value to the review table, but it will not be considered a valid enum option. config.sortBy The field to sort the options by (label, value, ordinal). config.options An array of valid options the user can select from: 
{
  "key": "status",
  "label": "Status",
  "type": "enum",
  "config": {
    "options": [
      {
        "value": "active",
        "label": "Active"
      },
      {
        "value": "inactive",
        "label": "Disabled"
      }
    ]
  }
}

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enum-list

Allows multiple selections from a predefined list of options. Values are stored as an array. Use this instead of enum when users need to select multiple options. config.allowCustom Allow users to create new options for this field. When enabled, users will be able to import their custom value to the review table, but it will not be considered a valid enum option. config.sortBy Sort options by: label, value, or ordinal. config.options Array of option objects: 
{
  "key": "categories",
  "label": "Product Categories",
  "type": "enum-list",
  "config": {
    "allowCustom": false,
    "sortBy": "label",
    "options": [
      {
        "value": "electronics",
        "label": "Electronics"
      },
      {
        "value": "clothing",
        "label": "Clothing"
      },
      {
        "value": "books",
        "label": "Books"
      }
    ]
  }
}

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boolean

A true or false value type. Usually displayed as a checkbox. config.allowIndeterminate Allow a neither true or false state to be stored as null. 
{
  "key": "is_active",
  "label": "Active",
  "type": "boolean",
  "config": {
    "allowIndeterminate": true
  }
}

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date

Store a field as a GMT date. Data hooks must convert this value into a YYYY-MM-DD format in order for it to be considered a valid value. 
{
  "key": "start_date",
  "label": "Start Date",
  "type": "date"
}

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reference

Defines a singular one-to-one reference to a field another sheet. config.ref The sheet slug of the referenced field. Must be in the same workbook. config.key The key of the property to use as the reference key. config.filter Optional filter to narrow the set of records in the reference sheet used as valid values. When provided, only records where the refField value matches the current record’s recordField value will be available as options. 
{
  "key": "author",
  "type": "reference",
  "label": "Authors",
  "config": {
    "ref": "authors",
    "key": "name"
  }
}

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Reference Field Filtering

Reference fields can be filtered to show only relevant options based on the value of another field in the same record. This enables cascading dropdowns and dependent field relationships.
Dynamic EnumsThis feature, along with the ENUM_REFERENCE sheet treatment, may be collectively referred to as Dynamic Enums. By combining these two features, you can create a drop-down list for any cell in your sheet that’s dynamically controlled by the value of another field in the same record – and to the end-user, it will just work like a dynamically-configured enum field.
Filter Configuration The filter property accepts a ReferenceFilter object with two required properties:
PropertyTypeDescription
refFieldstringThe field key in the referenced sheet to filter with
recordFieldstringThe field key in the current record used for filtering
How Filtering Works When a filter is applied:
  1. The system looks at the value in the recordField of the current record
  2. It then filters the referenced sheet to only show records where refField matches that value
  3. Only the filtered records become available as options in the reference field
Example: Country and State Cascading Dropdown Consider a scenario where you want state options to be filtered based on the selected country.
This example also demonstrates the use of the ENUM_REFERENCE sheet treatment to hide the reference sheet from the UI. You may wish to disable this treatment for testing purposes.
{
  "sheets": [
    {
      "name": "Reference Data",
      "slug": "ref-data",
      "treatments": ["ENUM_REFERENCE"],
      "fields": [
        {
          "key": "country-name",
          "label": "Country",
          "type": "string"
        },
        {
          "key": "state-name",
          "label": "State/Province",
          "type": "string"
        }
      ]
    },
    {
      "name": "Addresses",
      "slug": "addresses",
      "fields": [
        {
          "key": "country",
          "label": "Country",
          "type": "reference",
          "config": {
            "ref": "ref-data",
            "key": "country-name"
          }
        },
        {
          "key": "state",
          "label": "State/Province",
          "type": "reference",
          "config": {
            "ref": "ref-data",
            "key": "state-name",
            "filter": {
              "refField": "country-name",
              "recordField": "country"
            }
          }
        }
      ]
    }
  ]
}
Reference Data Sheet:
country-namestate-name
USACalifornia
USANew York
USATexas
CanadaOntario
CanadaQuebec
Behavior
  • When USA is selected in the country field, the state dropdown will only show California, New York, and Texas
  • When Canada is selected in the country field, the state dropdown will only show Ontario and Quebec
The following diagram illustrates how reference field filtering works: And this is how it looks in the UI:
Reference Field Filtering

Filtering for USA States based on the selected country

Reference Field Filtering

Filtering for Canadian Provinces based on the selected country

Reference Field Filtering

If data is imported that does not match the filtered options, it will result in a validation error

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reference-list

Defines multiple references to records in another sheet within the same workbook. config.ref The sheet slug of the referenced field. Must be in the same workbook. config.key The key of the property to use as the reference key. config.filter Optional filter to narrow the set of records in the reference sheet used as valid values. 
{
  "key": "authors",
  "type": "reference-list",
  "label": "Book Authors",
  "config": {
    "ref": "authors",
    "key": "name"
  }
}

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Reference List Filtering

The filter property on reference-list fields works identically to reference field filters, but allows for multiple selections. 
{
  "key": "categories",
  "label": "Product Categories",
  "type": "reference-list",
  "config": {
    "ref": "category-data",
    "key": "category-name",
    "filter": {
      "refField": "department",
      "recordField": "product-department"
    }
  }
}
Multi-Level Cascading Example You can create complex, multi-level cascading dropdowns by chaining filtered reference fields together. This example shows a product taxonomy where department selection filters available categories, and category selection filters available subcategories: 
{
  "sheets": [
    {
      "name": "Product Taxonomy",
      "slug": "taxonomy",
      "fields": [
        { "key": "department", "label": "Department", "type": "string" },
        { "key": "category", "label": "Category", "type": "string" },
        { "key": "subcategory", "label": "Subcategory", "type": "string" }
      ]
    },
    {
      "name": "Products",
      "slug": "products",
      "fields": [
        {
          "key": "department",
          "label": "Department",
          "type": "reference",
          "config": { "ref": "taxonomy", "key": "department" }
        },
        {
          "key": "category",
          "label": "Category",
          "type": "reference",
          "config": {
            "ref": "taxonomy",
            "key": "category",
            "filter": { "refField": "department", "recordField": "department" }
          }
        },
        {
          "key": "subcategory",
          "label": "Subcategory",
          "type": "reference-list",
          "config": {
            "ref": "taxonomy",
            "key": "subcategory",
            "filter": { "refField": "category", "recordField": "category" }
          }
        }
      ]
    }
  ]
}
Product Taxonomy Sheet:
departmentcategorysubcategory
ElectronicsComputersLaptops
ElectronicsComputersDesktops
ElectronicsComputersTablets
ElectronicsAudioHeadphones
ElectronicsAudioSpeakers
ClothingMen’sShirts
ClothingMen’sPants
ClothingWomen’sDresses
ClothingWomen’sShoes
BooksFictionNovels
BooksFictionShort Stories
BooksNon-FictionBiography
BooksNon-FictionHistory
Behavior This creates a three-level cascade: Department → Category → Subcategory, where users can select multiple subcategories from the filtered options.
  • When Electronics is selected in the department field, the category dropdown will only show Computers and Audio
  • When Computers is selected, the subcategory dropdown will show Laptops, Desktops, and Tablets. Users may then select multiple subcategories from the filtered options
  • When Clothing is selected, the category dropdown will only show Men’s and Women’s
  • When Men’s is selected, the subcategory dropdown will show Shirts and Pants. Users may then select multiple subcategories from the filtered options

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Field Constraints

Field constraints are system-level validation rules that enforce data integrity and business logic on data in individual fields.

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required

Ensures that a field must have a non-null value. Empty cells are considered null values and will fail this constraint. 
{
  "key": "email",
  "type": "string",
  "label": "Email Address",
  "constraints": [{ "type": "required" }]
}
By default, if a required constraint fails, an error will be added to the field with the message “<field label> is required”. You can override the message and/or the error level of the message by supplying a config object with the constraint. For example: 
{
  "key": "email",
  "type": "string",
  "label": "Email Address",
  "constraints": [{
    "type": "required",
    "config": {
      "message": "This record is missing an email address",
      "level": "warn"
    }
  }]
}

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unique

Ensures that field values appear only once across all records in the sheet. Note that null values can appear multiple times as they don’t count toward uniqueness validation. 
{
  "key": "employeeId",
  "type": "string",
  "label": "Employee ID",
  "constraints": [{ "type": "unique" }]
}
By default, if a required constraint fails, an error will be added to the field with the message “Value is not unique”. You can override the message and/or the error level of the message by supplying a config object with the constraint — see the example with the required constraint above.

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computed

Marks a field as computed, hiding it from the mapping process. Users will not be able to map imported data to fields with this constraint. 
{
  "key": "calculatedField",
  "type": "string",
  "label": "Calculated Value",
  "constraints": [{ "type": "computed" }]
}
Sheet-level constraints that apply to multiple fields are covered in Sheet Constraints.

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Field-level access

readonly On a field level you can restrict a user’s interaction with the data to readonly. This feature is useful if you’re inviting others to view uploaded data, but do not want to allow them to edit that field. 
{
  "fields": [
    {
      "key": "salary",
      "type": "number",
      "readonly": true
    }
  ]
}

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Field Options

Configurable properties for a Field that define its structure and behavior:
OptionTypeRequiredDefaultDescription
keystring✓The system name of this field. Primarily informs JSON and egress structures
typestring✓One of string, number, boolean, date, enum, reference, string-list, enum-list, reference-list. Defines the handling of this property
labelstringkeyA user-facing descriptive label designed to be displayed in the UI such as a table header
descriptionstringA long form description of the property intended to be displayed to an end user (supports Markdown)
constraintsarray[]An array of system level validation rules (max 10). Learn more about field constraints
configobjectConfiguration relevant to the type of column. See type documentation below
readonlybooleanfalsePrevents user input on this field
appearanceobjectUI appearance settings. Currently supports size property with values: "xs", "s", "m", "l", "xl"
actionsarray[]User actions available for this field. See Field Actions for detailed configuration
| alternativeNames | array | | [] | Alternative field names for mapping assistance | | metadata | object | | | Arbitrary object of values to pass through to hooks and egress |