Turns out we don't really need it directly for most "txn processing" AND
if we do it's usually related to some `Account`-ing related calcs; which
means we can instead just rely on the new `SymbologyCache` lookup to get
it when needed. So, basically just get rid of it and rely instead on the
`.fqme` to be the god-key to getting `MktPair` info (from the cache).
Further, extend the `TransactionLedger` to contain much more info on the
pertaining backend:
- `.mod` mapping to the (pkg) py mod.
- `.filepath` pointing to the actual ledger TOML file.
- `_symcache` for doing any needed asset or mkt lookup as mentioned
above.
- rename `.iter_trans()` -> `.iter_txns()` and allow passing in
a symcache or using the init provided one.
- rename `.to_trans()` similarly.
- delegate paper account txn processing to the `.clearing._paper_engine`
mod's `norm_trade()` (and expect this similarly from other backends!)
- use new `SymbologyCache.search()` to find the best but
un-fully-qualified fqme for a given `txdict` being processed when
writing a config (aka always try to expand to the most verbose `.fqme`
possible).
- add a `rewrite: bool` control to `open_trade_ledger()`.
Since we now fully support interchange-as-dict-msg, use the msg codec
API and drop manual `Asset` unpacking. Also, wrap `get_symcache()` in
a `pdbp` crash handler block for now B)
As part of loading the cache we can now fill the asset sub-tables:
`.mktmaps` and `.assets` with their deserialized struct instances!
In theory this might be possible for the backend defined `Pair` structs
as well but we need to figure out probably an endpoint to offer
the conversion?
Also, add a `SymbologyCache.search()` which allows sync code to scan the
existing (known via cache) symbol set just like how async code can use the
(much slower) `open_symbol_search()` ctx endpoint 💥
Previously we weren't necessarily serializing mkt pairs (for IPC msging)
entirely bc the assets `.src/.dst` were being sent just by their
str-names. This now properly supports fully serializing `Asset`s as
`dict`-msgs such that use of `MktPair.to_dict()` can be transmitted over
`tractor.MsgStream`s and deserialized entirely back to struct from on
the receiver end.
Deats:
- implement `Asset.to_dict()` and `.from_msg()`
- adjust `MktPair.to_dict()` and `.from_msg()` to use these methods.
- drop all the hacky "if .src/.dst is str" handling.
- add better `MktPair.from_fqme()` input handling for expiry and venue;
ensure that either can be extracted from passed fqme *and* if so they
are also popped from any duplicate passed in `**kwargs**`.
For starters rename the cache type to `SymbologyCache` and fill out its
interface to include an (async) `.reload()` which can be used to populate
the in-mem asset-table sets such that any tractor-runtime task can
actually directly call it. Use a symcache file name schema of
`_cache/<backend>.symcache.toml`.
Dirtier deatz:
- make `.open_symcache()` a `@cm` such that it can be used from sync code
and will actually call `trio.run()` in the case where it needs to do a
full (re)load; also don't write on exit only on reloads.
- add `.get_symcache()` a simple non-ctx-mngr reader which again can
mostly be called willy-nilly from sync code without the full runtime
being up (but likely will only work if symcache files already exist
for the backend).
New mod is `.data._symcache` and it needs backend clients to declare
`Client.get_assets()` and `.get_mkt_pairs()` to generate the cache files
which now go in the config dir under `_cache/`.
We're probably going to move to implementing all accounting using
`polars.DataFrame` and friends and thus this rejig preps for a much more
"stateless" implementation of our `Position` type and its internal
pos-accounting metrics: `ppu` and `cumsize`.
Summary:
- wrt to `._pos.Position`:
- rename `.size`/`.accum_size` to `.cumsize` to be more in line
with `polars.DataFrame.cumsum()`.
- make `Position.expiry` delegate to the underlying `.mkt: MktPair`
handling (hopefully) all edge cases..
- change over to a new `._events: dict[str, Transaction]` in prep
for #510 (and friends) and enforce a new `Transaction.etype: str`
which is by default `clear`.
- add `.iter_by_type()` which iterates, filters and sorts the
entries in `._events` from above.
- add `Position.clearsdict()` which returns the dict-ified and
datetime-sorted table which can more-or-less be stored in the
toml account file.
- add `.minimized_clears()` a new (and close) version of the old
method which always grabs at least one clear before
a position-side-polarity-change.
- mask-drop `.ensure_state()` since there is no more `.size`/`.price`
state vars (per say) as we always re-calc the ppu and cumsize from
the clears records on every read.
- `.add_clear` no longer does bisec insorting since all sorting is
done on position properties *reads*.
- move the PPU (price per unit) calculator to a new `.accounting.calcs`
as well as add in the `iter_by_dt()` clearing transaction sorted
iterator.
- also make some fixes to this to handle both lists of `Transaction`
as well as `dict`s as before.
- start rename of `PpTable` -> `Account` and make a note about adding
a `.balances` table.
- always `float()` the transaction size/price values since it seems if
they get processed as `tomlkit.Integer` there's some suuper weird
double negative on read-then-write to the clears table?
- something like `cumsize = -1` -> `cumsize = --1` !?!?
- make `load_pps_from_ledger()` work again but now includes some very
very first draft `polars` df processing from a transaction ledger.
- use this from the `accounting.cli.disect` subcmd which is also in
*super early draft* mode ;)
- obviously as mentioned in the `Position` section, add the new `.calcs`
module with a `.ppu()` calculator func B)
Also finally adds full `FeedInit` and `MktPair` support for this backend
by handling:
- all "currency" fields for each `Contract` by constructing
and `Asset` and setting the `MktPair.src` with `.atype='fiat'`.
- always render the `MktPair.src` name in the `.fqme` for fiat pairs
(aka forex) but never for other instruments.
In an effort to properly support fiat pairs (aka forex) as well as more
generally insert a fully-qualified `MktPair` in for the
`Transaction.sys`. Note that there's a bit of special handling for API
`Contract`s-as-dict records vs. flex-report-from-xml equivalents.
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.
Tyler Goodlet
Ebisu