eth_uninstallFilter
Hyperliquid node API
eth_uninstallFilter | Hyperliquid EVM
The eth_uninstallFilter JSON-RPC method uninstalls a filter with the given ID. eth_uninstallFilter on Hyperliquid EVM via Chainstack.
POST
eth_uninstallFilter
This method is available on Chainstack. Not all Hyperliquid methods are available on Chainstack, as the open-source node implementation does not support them yet — see Hyperliquid methods for the full availability breakdown.
eth_uninstallFilter JSON-RPC method uninstalls a filter with the given ID. This method should be called when polling is no longer needed to free up server resources and maintain optimal performance. Filters may also be automatically uninstalled if they are not polled for an extended period of time.
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Parameters
- filter_id (string) — The filter ID to uninstall (returned by
eth_newFilteroreth_newBlockFilter)
Response
The method returns a boolean value indicating whether the filter was successfully uninstalled.Response structure
Return values:true— Filter was successfully uninstalledfalse— Filter was not found (may have already expired or been uninstalled)
Filter lifecycle
Automatic cleanup:- Filters may be automatically uninstalled after a period of inactivity
- The exact timeout varies by node implementation
- Always explicitly uninstall filters when done to ensure cleanup
- Each filter consumes server resources for tracking state
- Uninstalling filters frees these resources for other operations
- Good practice to uninstall filters when no longer needed
Usage example
Basic implementation
Example request
Use your own endpoint in your code. The code examples use a placeholder Chainstack endpoint (YOUR_CHAINSTACK_ENDPOINT) — replace it with your own Hyperliquid node endpoint from the Chainstack console. The curl above uses a shared public endpoint for quick checks only; do not use it in production.
Use cases
Theeth_uninstallFilter method is essential for applications that need to:
- Resource management: Free up server resources when filters are no longer needed
- Memory cleanup: Prevent memory leaks from accumulating unused filters
- Performance optimization: Maintain optimal node performance by cleaning up filters
- Application lifecycle: Properly clean up resources when applications shut down
- Session management: Clean up filters when user sessions end
- Batch operations: Clean up multiple filters efficiently
- Error handling: Clean up filters when errors occur during processing
- Testing cleanup: Clean up test filters in automated testing environments
- Load balancing: Manage filter load across multiple connections
- Connection management: Clean up filters when connections are lost
- Scheduled cleanup: Implement scheduled cleanup of old filters
- Resource monitoring: Monitor and manage filter resource usage
- Graceful shutdowns: Ensure proper cleanup during application shutdowns
- Filter rotation: Rotate filters to prevent resource exhaustion
- Development workflows: Clean up filters during development and debugging
Body
application/json
Last modified on June 24, 2026