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Conditionals

Equals Any

Checks if a field's value matches any of the provided values.

Overview

The equals_any condition evaluates whether a specific field in a record contains one of several acceptable values. It's ideal for routing based on categories, statuses, regions, or any field with a defined set of possible values.

Use Cases

• Status-based Routing: Route records based on order status, user state, or processing stage
• Geographic Distribution: Direct data to regional endpoints based on country or region codes
• Priority Handling: Route high-priority items to dedicated processing queues
• Customer Segmentation: Handle different customer tiers or types separately
• Environment Separation: Keep production, staging, and test data in separate streams

Configuration

Setting	Type	Required	Description
key	string	Yes	The field path to check. Supports dot notation for nested fields. Use * to check all keys.
values	array	Yes	Array of acceptable values. The condition matches if the field equals any of these values.
case_insensitive	boolean	No	If true, performs case-insensitive string comparison.
not	boolean	No	If true, inverts the condition (matches if value is NOT in the list).

Values Format

Internally, all values are stored as strings. This means 123 matches both the number 123 and the string "123" in your data. To match only a specific type, wrap the value in quotes:

Input	Matches
hello	"hello"
123	123 (number) and "123" (string)
"123"	"123" (string only, not the number 123)
true	true (boolean) and "true" (string)
"true"	"true" (string only, not the boolean true)
["a","b"]	["a","b"] or ["b","a"] (order-independent)
{"k":"v"}	{"k":"v"}

Use quotes when you need to distinguish between a string and its numeric or boolean equivalent.

Examples

Simple Value Matching

Route based on status:

Code
{
  "type_id": "equals_any",
  "config": {
    "key": "status",
    "values": ["active", "pending"]
  }
}

Matches:

Code
{"status": "active", "user_id": "123"}
{"status": "pending", "user_id": "456"}

Does not match:

Code
{"status": "inactive", "user_id": "789"}
{"status": "deleted", "user_id": "012"}
{"user_id": "345"}

Nested Field Matching

Check values in nested objects:

Code
{
  "type_id": "equals_any",
  "config": {
    "key": "user.account.type",
    "values": ["premium", "enterprise"]
  }
}

Matches:

Code
{
  "user": {
    "account": {
      "type": "premium"
    }
  }
}

Multiple Values

Route records from multiple regions:

Code
{
  "type_id": "equals_any",
  "config": {
    "key": "region",
    "values": ["us-east", "us-west", "us-central"]
  }
}

Matches any of:

Code
{"region": "us-east", "data": "..."}
{"region": "us-west", "data": "..."}
{"region": "us-central", "data": "..."}

Case-Insensitive Matching

Match status values regardless of case:

Code
{
  "type_id": "equals_any",
  "config": {
    "key": "status",
    "values": ["active", "pending"],
    "case_insensitive": true
  }
}

Matches:

Code
{"status": "Active", "id": "1"}
{"status": "PENDING", "id": "2"}
{"status": "active", "id": "3"}

Exclusion Matching

Route records that are NOT in a specific set:

Code
{
  "type_id": "equals_any",
  "config": {
    "key": "environment",
    "values": ["test", "staging", "development"],
    "not": true
  }
}

Matches:

Code
{"environment": "production", "data": "..."}

Does not match:

Code
{"environment": "test", "data": "..."}
{"environment": "staging", "data": "..."}

Numeric Values

Match specific numeric values:

Code
{
  "type_id": "equals_any",
  "config": {
    "key": "priority",
    "values": ["1", "2"]
  }
}

Note: Numbers in the record are converted to strings for comparison, so this will match {"priority": 1} as well as {"priority": "1"}.

Common Patterns

Status-Based Routing

Route different order statuses to appropriate handlers:

Code
{
  "operator": "and",
  "conditions": [
    {"type_id": "equals_any", "config": {"key": "type", "values": ["order"]}},
    {"type_id": "equals_any", "config": {"key": "status", "values": ["paid", "processing"]}}
  ]
}

Multi-Region Distribution

Route data to region-specific endpoints:

Code
{
  "operator": "or",
  "conditions": [
    {"type_id": "equals_any", "config": {"key": "country", "values": ["GB", "FR", "DE", "IT", "ES"]}},
    {"type_id": "equals_any", "config": {"key": "region", "values": ["eu-west", "eu-central"]}}
  ]
}

Environment Filtering

Separate production from non-production data:

Code
{
  "operator": "and",
  "conditions": [
    {"type_id": "equals_any", "config": {"key": "environment", "values": ["production"]}},
    {"type_id": "equals_any", "config": {"key": "severity", "values": ["error", "critical", "warning"]}}
  ]
}

Exclude Non-Production Data

Filter out test and development records:

Code
{
  "operator": "and",
  "conditions": [
    {
      "type_id": "equals_any",
      "config": {
        "key": "environment",
        "values": ["test", "development", "staging"],
        "not": true
      }
    }
  ]
}

Best Practices

1. Use case_insensitive when appropriate: If your data may have inconsistent casing, enable case-insensitive matching to avoid missed matches.

2. Handle Missing Fields: If the field doesn't exist in the record, the condition returns false (or true if not is set). Consider combining with key_exists if you need to handle missing fields differently.

3. Minimize Value Lists: Very long lists of values can impact readability. Consider restructuring your data if you need many values.

4. Use Consistent Formats: Standardize value formats (e.g., always lowercase status values) to simplify matching.

5. Use not for exclusions: Instead of listing all values you DO want, sometimes it's easier to list the ones you DON'T want with not: true.

Type Handling

The condition handles different value types as follows:

• Strings: Direct comparison (case-sensitive by default)
• Numbers: Converted to strings for comparison
• Booleans: Compared against "true" or "false" strings
• Nulls: Field exists but won't match any value in the list
• Arrays/Objects: Supported with deep equality comparison

Limitations

• No wildcard or pattern matching (use matches_regex for patterns)
• No numeric range comparisons (use greater_than/less_than)

Troubleshooting

Values not matching:

• Check for exact case matching (use case_insensitive: true if needed)
• Verify the field path is correct
• Look for trailing spaces or hidden characters

Numeric comparisons failing:

• Numbers are converted to strings: "10" and "10.0" may differ
• Leading zeros matter: "01" ≠ "1"
• Use consistent number formats

Boolean fields not matching:

• Use "true" and "false" as string values
• Check your data serialization format