Overview
Thefilter_by
parameter refines your search results based on specific field values. Use filters to narrow down large datasets and find exactly what you’re looking for.
Filters work with any search query, including the wildcard *
, and support various operators for different data types.
Quick start
Here’s a basic filter that demonstrates the most common pattern:Filter operators
Exact match (:=
)
Match field values exactly:
Partial match (:
)
Match fields containing the value:
Comparison operators
Compare numeric values and dates:Operator | Meaning | Example |
---|---|---|
> | Greater than | amount:>1000 |
>= | Greater than or equal | balance:>=5000 |
< | Less than | created_at:<1720396800 |
<= | Less than or equal | balance:<=50000 |
Range operator ([min..max]
)
Filter values within a range:
Use Unix timestamps for date ranges. The example above filters for July 7-8, 2024.
IN operator ([value1, value2]
)
Match any value from a list:
AND operator (&&
)
Combine multiple conditions where ALL must be true:
Partial match (:
)
Match fields containing the value:
Not equal (:!=
)
Exclude specific values:
Common patterns
1
Filter by transaction status
Find all successful and pending transactions.
2
Filter transactions by amount range
Find USD transactions between $1,000 and $10,000.
3
Filter by creation date
Find transactions created within a specific date range using Unix timestamps.
4
Filter by multiple currencies
Find balances in major currencies with positive amounts.
Best practices
- Use exact matches (
:=
) for IDs, statuses, and currencies - Combine with AND (
&&
) for precise filtering - Use ranges for amounts and dates instead of multiple comparisons
- Test complex filters with simple queries first
Related topics
Querying
Learn how to combine filters with search queries for powerful data retrieval.
Search overview
Return to the main Search API documentation for a complete overview.