This should in theory result in increased burstiness since we remove
the plain `trio.sleep()` and instead always wait on the receive channel
as much as possible until the `trio.move_on_after()` (+ time diffing
calcs) times out and signals the next throttled send cycle. This also is
slightly easier to grok code-wise instead of the `try, except` and
another tight while loop until a `trio.WouldBlock`. The only simpler
way i can think to do it is with 2 tasks: 1 to collect ticks and the
other to read and send at the throttle rate.
Comment out the log msg for now to avoid latency and add much more
detailed comments. Add an overrun log msg to the main sample loop.
There was a lingering issue where the fsp daemon would sync its shm
array with the source data and we'd set the start/end indices to the
same value. Under some races a reader would then read an empty `.array`
which it wasn't expecting. This fixes that as well as tidies up the
`ShmArray.push()` logic and adds a temporary check in `.array` for zero
length if the array hasn't been written yet.
We can now start removing read array length checks in consumer code
and hopefully no more races will show up.
Try out he new broadcast channels from `tractor` for data feeds
we already have cached. Any time there's a cache hit we load the
cached feed and just slap a broadcast receiver on it for the local
consumer task.
If a client attaches to a quotes data feed and requests a throttle rate,
be sure to unsub that side-band memchan + task when it detaches and
especially so on any transport connection error.
Also, use an explicit `tractor.Context.cancel()` on the client feed
block exit since we removed the implicit cancel option from the
`tractor` api.
Adding binance's "hft" ws feeds has resulted in a lot of context
switching in our Qt charts, so much so it's chewin CPU and definitely
worth it to throttle to the detected display rate as per discussion in
issue #192.
This is a first very very naive attempt at throttling L1 tick feeds on
the `brokerd` end (producer side) using a constant and uniform delivery
rate by way of a `trio` task + mem chan. The new func is
`data._sampling.uniform_rate_send()`. Basically if a client request
a feed and provides a throttle rate we just spawn a task and queue up
ticks until approximately the next display rate's worth period of time
has passed before forwarding. It's definitely nothing fancy but does
provide fodder and a start point for an up and coming queueing eng to
start digging into both #107 and #109 ;)
This allows for more deterministically managing long running sub-daemon
services under `pikerd` using the new context api from `tractor`.
The contexts are allocated in an async exit stack and torn down at root
daemon termination. Spawn brokerds using this method by changing the
persistence entry point to be a `@tractor.context`.
Tyler Goodlet