More or less we need to be able to audit not only simple "make trades
check pps.toml files" tests (which btw were great to get started!).
We also need more sophisticated and granular order mgmt and service
config scenarios,
- full e2e EMS msg flow verification
- multi-client (dis)connection scenarios and/or monitoring
- dark order clearing and offline storage
- accounting schema and position calcs detailing
As such, this is the beginning to "modularlizingz" the components needed
in the test harness to this end by breaking up the `OrderClient` control
flows vs. position checking logic so as to allow for more flexible test
scenario cases and likely `pytest` parametrizations over different
transaction sequences.
Not sure how this worked before but we need to also override the
`piker._config_dir: Path` in the root actor when running in `pytest`; my
guess is something in the old test suite was masking this problem after
the change to passing the dir path down through the runtime vars via
`tractor`?
Also this drops the ems related fixtures/factories since they're
specific enough to define in the clearing engine tests directly.
Due to making ahabd supervisor init more async we need to be more
tolerant to mkts server startup: the grpc machinery needs to be up
otherwise a client which connects to early may just hang on requests..
Add a reconnect loop (which might end up getting factored into client
code too) so that we only block on requests once we know the client
connection is actually responsive.
Add decimal quantize API to Symbol to simplify by-broker truncation
Add symbol info to `pps.toml`
Move _assert call to outside the _async_main context manager
Minor indentation and styling changes, also convert a few prints to log calls
Fix multi write / race condition on open_pps call
Switch open_pps to not write by default
Fix integer math kraken syminfo _tick_size initialization
ensure not to write pp header on startup
Comment out pytest settings
Add comments explaining delete_testing_dir fixture
use nonlocal instead of global for test state
Add unpacking get_fqsn method
Format test_paper
Add comments explaining sync/async book.send calls
Sync per-symbol sampler loop start to subscription registers such that
the loop can't start until the consumer's stream subscription is added;
the task-sync uses a `trio.Event`. This patch also drops a ton of
commented cruft.
Further adjustments needed to get parity with prior functionality:
- pass init msg 'symbol_info' field to the `Symbol.broker_info: dict`.
- ensure the `_FeedsBus._subscriptions` table uses the broker specific
(without brokername suffix) as keys for lookup so that the sampler
loop doesn't have to append in the brokername as a suffix.
- ensure the `open_feed_bus()` flumes-table-msg returned sent by
`tractor.Context.started()` uses the `.to_msg()` form of all flume
structs.
- ensure `maybe_open_feed()` uses `tractor.MsgStream.subscribe()` on all
`Flume.stream`s on cache hits using the
`tractor.trionics.gather_contexts()` helper.
Orient shm-flow-arrays around the new idea of a `Flume` which provides
access, mgmt and basic measure of real-time data flow sets (see water
flow management semantics).
- We discard the previous idea of a "init message" which contained all
the shm attachment info and instead send a startup message full of
`Flume.to_msg()`s which are symmetrically loaded on the caller actor
side.
- Create data-flows "entries" for every passed in fqsn such that the consumer gets back
streams and shm for each, now all wrapped in `Flume` types. For now we
allocate `brokermod.stream_quotes()` tasks 1-to-1 for each fqsn
(instead of expecting each backend to do multi-plexing, though we
might want that eventually) as well a `_FeedsBus._subscriber` entry
for each. The pause/resume management loop is adjusted to match.
Previously `Feed`s were allocated 1-to-1 with each fqsn.
- Make `Feed` a `Struct` subtype instead of a `@dataclass` and move all
flow specific attrs to the new `Flume`:
- move `.index_stream()`, `.get_ds_info()` to `Flume`.
- drop `.receive()`: each fqsn entry will now require knowledge of
separate streams by feed users.
- add multi-fqsn tables: `.flumes`, `.streams` which point to the
appropriate per-symbol entries.
- Async load all `Flume`s from all contexts and all quote streams using
`tractor.trionics.gather_contexts()` on the client `open_feed()` side.
- Update feeds test to include streaming 2 symbols on the same (binance)
backend.
Initial test that starts a `binance` feed and reads the quote messages
alongside shm buffers for 1s and 1m OHLC; just prints to console for
now.
Template out parametrization for multi-symbol quote-multiplexed feeds
which coming soon B)
They need to be run with a local private API key and haven't been ported
to latest data apis anyway. It's also a broker most peeps aren't going
to be using any time soon.
Questrade is the default broker backend (for now) so the CI
can run using a practice account token handed down through an
env variable. If we add a cached directory to the build then the token
should remain persistent in the brokers config and will only need to be
updated if something goes wrong.
Also, add a `--confdir` flag for pytest much in the same way as for
the `piker` cli.
Tyler Goodlet
Guillermo Rodriguez
jaredgoldman
algorandpa
Guillermo Rodriguez
Esmeralda Gallardo
Tyler Goodlet