Add transaction costs to "fills"
This makes a few major changes but mostly is centered around including transaction (aka trade-clear) costs in the avg breakeven price calculation. TL;DR: - rename `TradeRecord` -> `Transaction`. - make `Position.fills` a `dict[str, float]` which holds each clear's cost value. - change `Transaction.symkey` -> `.bsuid` for "backend symbol unique id". - drop `brokername: str` arg to `update_pps()` - rename `._split_active()` -> `dump_active()` and use input keys verbatim in output map. - in `update_pps_conf()` always incrementally update from trade records even when no `pps.toml` exists yet since it may be both the case that the ledger needs loading **and** the caller is handing new records not yet in the ledger.lifo_pps_ib
parent
c1b63f4757
commit
412138a75b
128
piker/pp.py
128
piker/pp.py
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@ -15,9 +15,9 @@
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# along with this program. If not, see <https://www.gnu.org/licenses/>.
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# along with this program. If not, see <https://www.gnu.org/licenses/>.
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'''
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'''
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Personal/Private position parsing, calculmating, summarizing in a way
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Personal/Private position parsing, calculating, summarizing in a way
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that doesn't try to cuk most humans who prefer to not lose their moneys..
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that doesn't try to cuk most humans who prefer to not lose their moneys..
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(looking at you `ib` and shitzy friends)
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(looking at you `ib` and dirt-bird friends)
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'''
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'''
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from contextlib import contextmanager as cm
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from contextlib import contextmanager as cm
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@ -86,9 +86,9 @@ def open_trade_ledger(
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return toml.dump(ledger, cf)
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return toml.dump(ledger, cf)
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class TradeRecord(Struct):
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class Transaction(Struct):
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fqsn: str # normally fqsn
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fqsn: str # normally fqsn
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tid: Union[str, int]
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tid: Union[str, int] # unique transaction id
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size: float
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size: float
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price: float
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price: float
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cost: float # commisions or other additional costs
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cost: float # commisions or other additional costs
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@ -98,7 +98,7 @@ class TradeRecord(Struct):
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# optional key normally derived from the broker
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# optional key normally derived from the broker
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# backend which ensures the instrument-symbol this record
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# backend which ensures the instrument-symbol this record
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# is for is truly unique.
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# is for is truly unique.
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symkey: Optional[Union[str, int]] = None
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bsuid: Optional[Union[str, int]] = None
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class Position(Struct):
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class Position(Struct):
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@ -113,9 +113,14 @@ class Position(Struct):
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# last size and avg entry price
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# last size and avg entry price
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size: float
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size: float
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avg_price: float # TODO: contextual pricing
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avg_price: float # TODO: contextual pricing
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bsuid: str
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# ordered record of known constituent trade messages
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# ordered record of known constituent trade messages
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fills: list[Union[str, int, Status]] = []
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fills: dict[
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Union[str, int, Status], # trade id
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float, # cost
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] = {}
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def to_dict(self):
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def to_dict(self):
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return {
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return {
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@ -160,6 +165,7 @@ class Position(Struct):
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self,
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self,
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size: float,
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size: float,
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price: float,
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price: float,
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cost: float = 0,
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# TODO: idea: "real LIFO" dynamic positioning.
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# TODO: idea: "real LIFO" dynamic positioning.
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# - when a trade takes place where the pnl for
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# - when a trade takes place where the pnl for
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@ -198,6 +204,8 @@ class Position(Struct):
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self.avg_price = (
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self.avg_price = (
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abs(size) * price # weight of current exec
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abs(size) * price # weight of current exec
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+
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+
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cost # transaction cost
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+
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self.avg_price * abs(self.size) # weight of previous pp
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self.avg_price * abs(self.size) # weight of previous pp
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) / abs(new_size)
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) / abs(new_size)
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@ -207,9 +215,7 @@ class Position(Struct):
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def update_pps(
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def update_pps(
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brokername: str,
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records: dict[str, Transaction],
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records: dict[str, TradeRecord],
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pps: Optional[dict[str, Position]] = None
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pps: Optional[dict[str, Position]] = None
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) -> dict[str, Position]:
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) -> dict[str, Position]:
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@ -223,7 +229,7 @@ def update_pps(
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for r in records:
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for r in records:
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pp = pps.setdefault(
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pp = pps.setdefault(
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r.fqsn or r.symkey,
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r.fqsn or r.bsuid,
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# if no existing pp, allocate fresh one.
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# if no existing pp, allocate fresh one.
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Position(
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Position(
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@ -233,27 +239,39 @@ def update_pps(
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),
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),
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size=0.0,
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size=0.0,
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avg_price=0.0,
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avg_price=0.0,
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bsuid=r.bsuid,
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)
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)
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)
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)
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# don't do updates for ledger records we already have
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# don't do updates for ledger records we already have
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# included in the current pps state.
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# included in the current pps state.
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if r.tid in pp.fills:
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if r.tid in pp.fills:
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# NOTE: likely you'll see repeats of the same
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# NOTE: likely you'll see repeats of the same
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# ``TradeRecord`` passed in here if/when you are restarting
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# ``Transaction`` passed in here if/when you are restarting
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# a ``brokerd.ib`` where the API will re-report trades from
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# a ``brokerd.ib`` where the API will re-report trades from
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# the current session, so we need to make sure we don't
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# the current session, so we need to make sure we don't
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# "double count" these in pp calculations.
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# "double count" these in pp calculations.
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continue
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continue
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# lifo style average price calc
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# lifo style "breakeven" price calc
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pp.lifo_update(r.size, r.price)
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pp.lifo_update(
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pp.fills.append(r.tid)
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r.size,
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r.price,
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# include transaction cost in breakeven price
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# and presume the worst case of the same cost
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# to exit this transaction (even though in reality
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# it will be dynamic based on exit stratetgy).
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cost=2*r.cost,
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)
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# track clearing costs
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pp.fills[r.tid] = r.cost
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assert len(set(pp.fills)) == len(pp.fills)
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assert len(set(pp.fills)) == len(pp.fills)
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return pps
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return pps
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def _split_active(
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def dump_active(
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pps: dict[str, Position],
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pps: dict[str, Position],
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) -> tuple[
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) -> tuple[
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@ -277,9 +295,9 @@ def _split_active(
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fqsn = pp.symbol.front_fqsn()
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fqsn = pp.symbol.front_fqsn()
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asdict = pp.to_dict()
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asdict = pp.to_dict()
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if pp.size == 0:
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if pp.size == 0:
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closed[fqsn] = asdict
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closed[k] = asdict
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else:
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else:
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active[fqsn] = asdict
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active[k] = asdict
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return active, closed
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return active, closed
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@ -292,7 +310,7 @@ def load_pps_from_ledger(
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) -> tuple[dict, dict]:
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) -> tuple[dict, dict]:
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'''
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'''
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Open a ledger file by broker name and account and read in and
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Open a ledger file by broker name and account and read in and
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process any trade records into our normalized ``TradeRecord``
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process any trade records into our normalized ``Transaction``
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form and then pass these into the position processing routine
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form and then pass these into the position processing routine
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and deliver the two dict-sets of the active and closed pps.
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and deliver the two dict-sets of the active and closed pps.
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@ -305,9 +323,8 @@ def load_pps_from_ledger(
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brokermod = get_brokermod(brokername)
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brokermod = get_brokermod(brokername)
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records = brokermod.norm_trade_records(ledger)
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records = brokermod.norm_trade_records(ledger)
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pps = update_pps(brokername, records)
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pps = update_pps(records)
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return dump_active(pps)
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return _split_active(pps)
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def get_pps(
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def get_pps(
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@ -326,57 +343,55 @@ def get_pps(
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def update_pps_conf(
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def update_pps_conf(
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brokername: str,
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brokername: str,
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acctid: str,
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acctid: str,
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trade_records: Optional[list[TradeRecord]] = None,
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trade_records: Optional[list[Transaction]] = None,
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) -> dict[str, Position]:
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) -> dict[str, Position]:
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conf, path = config.load('pps')
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conf, path = config.load('pps')
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brokersection = conf.setdefault(brokername, {})
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brokersection = conf.setdefault(brokername, {})
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entries = brokersection.setdefault(acctid, {})
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accountsection = pps = brokersection.setdefault(acctid, {})
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if not entries:
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if not pps:
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# no pps entry yet for this broker/account so parse
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# no pps entry yet for this broker/account so parse
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# any available ledgers to build a pps state.
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# any available ledgers to build a pps state.
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active, closed = load_pps_from_ledger(
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pps, closed = load_pps_from_ledger(
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brokername,
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brokername,
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acctid,
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acctid,
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)
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)
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if not pps:
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elif trade_records:
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log.warning(
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f'No trade history could be loaded for {brokername}:{acctid}'
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# table for map-back to object form
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pps = {}
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# load ``pps.toml`` config entries back into object form.
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for fqsn, entry in entries.items():
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pps[f'{fqsn}.{brokername}'] = Position(
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Symbol.from_fqsn(fqsn, info={}),
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size=entry['size'],
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avg_price=entry['avg_price'],
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# XXX: super critical, we need to be sure to include
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# all pps.toml fills to avoid reusing fills that were
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# already included in the current incremental update
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# state, since today's records may have already been
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# processed!
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fills=entry['fills'],
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)
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)
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pps = update_pps(
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# unmarshal/load ``pps.toml`` config entries into object form.
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brokername,
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pp_objs = {}
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trade_records,
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for fqsn, entry in pps.items():
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pps=pps,
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pp_objs[fqsn] = Position(
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Symbol.from_fqsn(fqsn, info={}),
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size=entry['size'],
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avg_price=entry['avg_price'],
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bsuid=entry['bsuid'],
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# XXX: super critical, we need to be sure to include
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# all pps.toml fills to avoid reusing fills that were
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# already included in the current incremental update
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# state, since today's records may have already been
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# processed!
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fills=entry['fills'],
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)
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)
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active, closed = _split_active(pps)
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else:
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# update all pp objects from any (new) trade records which
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raise ValueError('wut wut')
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# were passed in (aka incremental update case).
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if trade_records:
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pp_objs = update_pps(
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trade_records,
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pps=pp_objs,
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)
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for fqsn in closed:
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active, closed = dump_active(pp_objs)
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print(f'removing closed pp: {fqsn}')
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entries.pop(fqsn, None)
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# dict-serialize all active pps
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pp_entries = {}
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for fqsn, pp_dict in active.items():
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for fqsn, pp_dict in active.items():
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print(f'Updating active pp: {fqsn}')
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print(f'Updating active pp: {fqsn}')
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@ -386,8 +401,9 @@ def update_pps_conf(
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# XXX: ugh, it's cuz we push the section under
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# XXX: ugh, it's cuz we push the section under
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# the broker name.. maybe we need to rethink this?
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# the broker name.. maybe we need to rethink this?
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brokerless_key = fqsn.rstrip(f'.{brokername}')
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brokerless_key = fqsn.rstrip(f'.{brokername}')
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entries[brokerless_key] = pp_dict
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pp_entries[brokerless_key] = pp_dict
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conf[brokername][acctid] = pp_entries
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config.write(
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config.write(
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conf,
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conf,
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'pps',
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'pps',
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