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What this builds. A 3-metric dashboard fetched concurrently. You’ll end up with. Runs, failures, and mean latency for the last 7 days, all three calls issued in parallel via asyncio.gather. 
"""
Async pairs — every terminal has an `a*` sibling.

Same surface as query-basics, but using `aquery` and `acount` / `amean`.
Useful for fanning out multiple queries concurrently.
"""

import asyncio
from datetime import datetime, timedelta, timezone

from vectorshift import Analytics
from vectorshift.analytics import EventField


async def dashboard():
    """Fetch a 3-metric dashboard in parallel."""
    q = Analytics.aquery().where(
        EventField.EVENT_START_TIME > datetime.now(timezone.utc) - timedelta(days=7)
    )

    runs, failures, latency = await asyncio.gather(
        q.acount(),
        q.where(status="failure").acount(),
        q.amean("latency"),
    )

    print(f"runs:         {runs['count']}")
    print(f"failures:     {failures['count']}")
    print(f"mean latency: {latency:.2f} ms")


async def main():
    await dashboard()
    print("Done.")


if __name__ == "__main__":
    asyncio.run(main())

​
Expected output

runs:         ...
failures:     ...
mean latency: ... ms
Done.
Analytics.aquery(...) returns a Query whose terminals route to the a* pairs — every sync terminal in the reference has an a-prefixed sibling (acount, aevents, asum, atable, aexport, …).

​
See also

Query basics

The sync version of these scopes and terminals.

Aggregations & group-by

Bucket metrics by model, time, and more.

Reference

Every public method.