No point having duplicate data when we already stash the `expiry` on the
mkt info type and can just read it (and cast to `datetime` obj).
Further this fixes a regression caused by converting `._clears` to
a list by adding a `._events: dict[str, Transaction]` which prevents
double entering transactions based on checking the events table for the
existing id.. Further add a sanity check that all events are popped
(for now) after serializing the clearing table for the toml account
file.
In the longer run, ideally we don't have the separate sequences ._clears
and ._events by choosing a better data structure (sorted unique set of
mkt events) maybe a specially used `polars.DataFrame` (which we kind
need eventually anyway)?
Shows how to boot the piker runtime, submit an order to the ems, cancel
said order right away. NOTE, this uses piker's built in paper engine but
can be easily tweaked to use a live backend at the user's whim.
When you look at usage we don't end up really needing clear entries to
be keyed by their `Transaction.tid`, instead it's much more important to
ensure the time sorted order of trade-clearing transactions such that
position properties such as the size and ppu are calculated correctly.
Thus, this instead simplified the `.clears` table to a list of clear
dict entries making a bunch of things simpler:
- object form `Position._clears` compared to the offline TOML schema
(saved in account files) is now data-structure-symmetrical.
- `Position.add_clear()` now uses `bisect.insort()` to
datetime-field-sort-insert into the *list* which saves having to worry
about sorting on every sequence *read*.
Further deats:
- adjust `.accounting._ledger.iter_by_dt()` to expect an input `list`.
- change `Position.iter_clears()` to iterate only the clearing entry
dicts without yielding a key/tid; no more tuples.
- drop `Position.to_dict()` since parent `Struct` already implements it.
Since it may be handy to get the latest ticks first, add a `reverse:
bool` to `iterticks()` and add some cleaner logic and a proper doc
string to `frame_ticks()`.
Allows for tracking paper engine orders despite the ems not necessarily
being opened by the current order mode instance (UI) in "paper"
execution mode; useful for tracking bots/strats running against the same
EMS daemon.
Like you'd think:
- `load_ledger()` -> ._ledger
- `load_accounrt()` -> ._pos
Also fixup the old `load_pps_from_ledger()` and expose it from a new
`.accounting.cli.disect` cli cmd for trying to figure out why pp calcs
are totally mucked on stupid ib..
Should be the final production backend to switch this over B)
Also tidy up the `update_and_audit_msgs()` validator to log vs. raise
when `validate: bool` is set; turn it off by default to avoid raises
until we figure out wtf is up with ib ledger processing or wtv..
We might as well start standardizing on `brokerd` init such that it can
be used more generally in client code (such as the `.accounting.cli`
stuff).
Deats of `broker_init()` impl:
- loads appropriate py pkg module,
- reads any declared `__enable_modules__: listr[str]` which will be
passed to `tractor.ActorNursery.start_actor(enabled_modules=<this>)`
- loads the `.brokers._daemon._setup_persistent_brokerd
As expected the `accounting.cli` tools can now import directly from this
new location and use the common daemon fixture definition.
After #520 we've moved to better supporting explicit venues for cex
backends which is important where a provider offers both spot and
derivatives markets (kraken, binance, kucoin) and we need to distinguish
which is being traded given a common asset pair (eg. BTC/USDT). So, make
this work for `kraken`'s brokerd such that requests and pre-existing
live order are (un)packed to/from EMS messaging form.
Since crypto backends now also may expand an FQME like `xbteur.kraken`
-> `xbteur.spot.kraken` (by filling in the venue token), we need to use
this identifier when looking up per-market order dialogs or submitting
new requests. The simple fix is to simply look up that expanded from
from the `Feed.flumes` table which is always keyed by the `MktPair.fqme:
str` - the expanded form.
Drop the older `dict[str, ChainMap]` prototype we had since the new
`OrderDialogs` built-out while adding `binance` order support is more
refined and general. Also, handle new and now expect `.spot` venue token
in FQMEs since kraken too has futes markets that we'll likely want to
support eventually.
Use dynamic lookups instead by mapping to the correct http session and
endpoints path using the venue routing/mode key. This let's us simplify
from 3 methods down to a single `Client._api()` which either can be
passed the `venue: str` explicitly by the caller (as is needed in the
`._cache_pairs()` case) or falls back to the client's current
`.mkt_mode: str` setting B)
Deatz:
- add couple more tables to suffice all authed-endpoint use cases:
- `.venue2configkey: dict[str, str]` which maps the venue key to the
`brokers.toml` subsection which should be used for auth creds and
testnet config.
- `.confkey2venuekeys: dict[str, list[str]]` which maps each config
subsection key to the list of venue name keys for doing config to
venues lookup.
- always build out testnet sessions for spot and futes venues (though if
not set the sessions obviously won't ever be used).
- add and use new `config.ConfigurationError` custom exceptions when api
creds are missing.
- rename `action: str` to `method: str` in `._api()` since it's the
proper ReST term and switch what was "method" to be `endpoint: str`.
- mask out `.get_positions()` since we can get that from a user stream
wss request (and are doing that).
- (in theory) import and use spot testnet url as necessary.
Do parsing of the `'symbol'` and check for an `_<expiry>` suffix, in
which case we re-format in capitalized FQME style, do the
`Client._pairs[str, Pair]` lookup and then send the `Pair.bs_fqme` in
the `Order.fqme: str` field.
It's finally a decent little design / interface and definitely can be
used in other backends like `kraken` which rolled something lower level
but more or less the same without a wrapper class.
Tyler Goodlet
Ebisu