The Big Picture
Allows finding events by their topic (usually event type hash).
Use Cases
- Filter events by type
From Chain Metadata
Mapping between a topic (represented by T::Hash) and a vector of indexes of events in the `<Events<T>>` list. All topic vectors have deterministic storage locations depending on the topic. This allows light-clients to leverage the changes trie storage tracking mechanism and in case of changes fetch the list of events of interest. The value has the type `(T::BlockNumber, EventIndex)` because if we used only just the `EventIndex` then in case if the topic has the same contents on the next block no notification will be triggered thus the event might be lost.
Purpose & Usage
Purpose
Enable efficient event filtering by topic.
Common Query Patterns
- Query by topic hash
Query Keys
| # | Name | Type | Description |
|---|---|---|---|
| 1 | topic raw: key1 | H256 [u8; 32] | key1 (H256) |
Stored Value
value (Vec<(u32, u32)>)
Default Value
Absent keys read as this value — querying a key that has never been written returns this default, not an error or empty result.
Code Examples
import { createClient, Binary } from "polkadot-api";
import { getWsProvider } from "polkadot-api/ws";
import { sub } from "@polkadot-api/descriptors"; // generated by: npx papi add sub -w wss://entrypoint-finney.opentensor.ai:443
const client = createClient(getWsProvider("wss://entrypoint-finney.opentensor.ai:443"));
const api = client.getTypedApi(sub);
// Query EventTopics storage
const key1 = "0x0000000000000000000000000000000000000000000000000000000000000000";
const result = await api.query.System.EventTopics.getValue(key1);
console.log("EventTopics:", result);Runtime Info
- Pallet
- System
- Storage Kind
- Map
- First Version
- v101
- Current Version
- v472