Merge pull request #336 from pikers/lifo_pps_ib

LIFO/"breakeven" pps for `ib`
ib_rt_pp_update_hotfix
goodboy 2022-06-29 10:07:56 -04:00 committed by GitHub
commit d5bc43e8dd
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14 changed files with 1695 additions and 341 deletions

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@ -38,7 +38,10 @@ from .feed import (
open_symbol_search,
stream_quotes,
)
from .broker import trades_dialogue
from .broker import (
trades_dialogue,
norm_trade_records,
)
__all__ = [
'get_client',

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@ -38,15 +38,21 @@ import time
from types import SimpleNamespace
from bidict import bidict
import trio
import tractor
from tractor import to_asyncio
import ib_insync as ibis
from ib_insync.wrapper import RequestError
from ib_insync.contract import Contract, ContractDetails
from ib_insync.order import Order
from ib_insync.ticker import Ticker
from ib_insync.objects import Position
import ib_insync as ibis
from ib_insync.objects import (
Position,
Fill,
Execution,
CommissionReport,
)
from ib_insync.wrapper import Wrapper
from ib_insync.client import Client as ib_Client
import numpy as np
@ -155,30 +161,23 @@ class NonShittyIB(ibis.IB):
self.client.apiEnd += self.disconnectedEvent
# map of symbols to contract ids
_adhoc_cmdty_data_map = {
# https://misc.interactivebrokers.com/cstools/contract_info/v3.10/index.php?action=Conid%20Info&wlId=IB&conid=69067924
# NOTE: some cmdtys/metals don't have trade data like gold/usd:
# https://groups.io/g/twsapi/message/44174
'XAUUSD': ({'conId': 69067924}, {'whatToShow': 'MIDPOINT'}),
}
_futes_venues = (
'GLOBEX',
'NYMEX',
'CME',
'CMECRYPTO',
'COMEX',
'CMDTY', # special name case..
)
_adhoc_futes_set = {
# equities
'nq.globex',
'mnq.globex',
'mnq.globex', # micro
'es.globex',
'mes.globex',
'mes.globex', # micro
# cypto$
'brr.cmecrypto',
@ -195,20 +194,46 @@ _adhoc_futes_set = {
# metals
'xauusd.cmdty', # gold spot
'gc.nymex',
'mgc.nymex',
'mgc.nymex', # micro
# oil & gas
'cl.nymex',
'xagusd.cmdty', # silver spot
'ni.nymex', # silver futes
'qi.comex', # mini-silver futes
}
# map of symbols to contract ids
_adhoc_symbol_map = {
# https://misc.interactivebrokers.com/cstools/contract_info/v3.10/index.php?action=Conid%20Info&wlId=IB&conid=69067924
# NOTE: some cmdtys/metals don't have trade data like gold/usd:
# https://groups.io/g/twsapi/message/44174
'XAUUSD': ({'conId': 69067924}, {'whatToShow': 'MIDPOINT'}),
}
for qsn in _adhoc_futes_set:
sym, venue = qsn.split('.')
assert venue.upper() in _futes_venues, f'{venue}'
_adhoc_symbol_map[sym.upper()] = (
{'exchange': venue},
{},
)
# exchanges we don't support at the moment due to not knowing
# how to do symbol-contract lookup correctly likely due
# to not having the data feeds subscribed.
_exch_skip_list = {
'ASX', # aussie stocks
'MEXI', # mexican stocks
'VALUE', # no idea
# no idea
'VALUE',
'FUNDSERV',
'SWB2',
}
# https://misc.interactivebrokers.com/cstools/contract_info/v3.10/index.php?action=Conid%20Info&wlId=IB&conid=69067924
@ -261,27 +286,29 @@ class Client:
# NOTE: the ib.client here is "throttled" to 45 rps by default
async def trades(
self,
# api_only: bool = False,
async def trades(self) -> dict[str, Any]:
'''
Return list of trade-fills from current session in ``dict``.
) -> dict[str, Any]:
# orders = await self.ib.reqCompletedOrdersAsync(
# apiOnly=api_only
# )
fills = await self.ib.reqExecutionsAsync()
norm_fills = []
'''
fills: list[Fill] = self.ib.fills()
norm_fills: list[dict] = []
for fill in fills:
fill = fill._asdict() # namedtuple
for key, val in fill.copy().items():
if isinstance(val, Contract):
fill[key] = asdict(val)
for key, val in fill.items():
match val:
case Contract() | Execution() | CommissionReport():
fill[key] = asdict(val)
norm_fills.append(fill)
return norm_fills
async def orders(self) -> list[Order]:
return await self.ib.reqAllOpenOrdersAsync(
apiOnly=False,
)
async def bars(
self,
fqsn: str,
@ -483,6 +510,14 @@ class Client:
return con
async def get_con(
self,
conid: int,
) -> Contract:
return await self.ib.qualifyContractsAsync(
ibis.Contract(conId=conid)
)
async def find_contract(
self,
pattern: str,
@ -553,7 +588,7 @@ class Client:
# commodities
elif exch == 'CMDTY': # eg. XAUUSD.CMDTY
con_kwargs, bars_kwargs = _adhoc_cmdty_data_map[sym]
con_kwargs, bars_kwargs = _adhoc_symbol_map[sym]
con = ibis.Commodity(**con_kwargs)
con.bars_kwargs = bars_kwargs
@ -811,10 +846,23 @@ _scan_ignore: set[tuple[str, int]] = set()
def get_config() -> dict[str, Any]:
conf, path = config.load()
conf, path = config.load('brokers')
section = conf.get('ib')
accounts = section.get('accounts')
if not accounts:
raise ValueError(
'brokers.toml -> `ib.accounts` must be defined\n'
f'location: {path}'
)
names = list(accounts.keys())
accts = section['accounts'] = bidict(accounts)
log.info(
f'brokers.toml defines {len(accts)} accounts: '
f'{pformat(names)}'
)
if section is None:
log.warning(f'No config section found for ib in {path}')
return {}
@ -990,7 +1038,7 @@ async def load_aio_clients(
for acct, client in _accounts2clients.items():
log.info(f'Disconnecting {acct}@{client}')
client.ib.disconnect()
_client_cache.pop((host, port))
_client_cache.pop((host, port), None)
async def load_clients_for_trio(
@ -1019,9 +1067,6 @@ async def load_clients_for_trio(
await asyncio.sleep(float('inf'))
_proxies: dict[str, MethodProxy] = {}
@acm
async def open_client_proxies() -> tuple[
dict[str, MethodProxy],
@ -1044,13 +1089,14 @@ async def open_client_proxies() -> tuple[
if cache_hit:
log.info(f'Re-using cached clients: {clients}')
proxies = {}
for acct_name, client in clients.items():
proxy = await stack.enter_async_context(
open_client_proxy(client),
)
_proxies[acct_name] = proxy
proxies[acct_name] = proxy
yield _proxies, clients
yield proxies, clients
def get_preferred_data_client(
@ -1199,11 +1245,13 @@ async def open_client_proxy(
event_table = {}
async with (
to_asyncio.open_channel_from(
open_aio_client_method_relay,
client=client,
event_consumers=event_table,
) as (first, chan),
trio.open_nursery() as relay_n,
):

File diff suppressed because it is too large Load Diff

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@ -217,8 +217,8 @@ async def get_bars(
)
elif (
err.code == 162
and 'HMDS query returned no data' in err.message
err.code == 162 and
'HMDS query returned no data' in err.message
):
# XXX: this is now done in the storage mgmt layer
# and we shouldn't implicitly decrement the frame dt
@ -237,6 +237,13 @@ async def get_bars(
frame_size=2000,
)
# elif (
# err.code == 162 and
# 'Trading TWS session is connected from a different IP address' in err.message
# ):
# log.warning("ignoring ip address warning")
# continue
elif _pacing in msg:
log.warning(
@ -909,17 +916,17 @@ async def open_symbol_search(
# trigger async request
await trio.sleep(0)
# match against our ad-hoc set immediately
adhoc_matches = fuzzy.extractBests(
pattern,
list(_adhoc_futes_set),
score_cutoff=90,
)
log.info(f'fuzzy matched adhocs: {adhoc_matches}')
adhoc_match_results = {}
if adhoc_matches:
# TODO: do we need to pull contract details?
adhoc_match_results = {i[0]: {} for i in adhoc_matches}
# # match against our ad-hoc set immediately
# adhoc_matches = fuzzy.extractBests(
# pattern,
# list(_adhoc_futes_set),
# score_cutoff=90,
# )
# log.info(f'fuzzy matched adhocs: {adhoc_matches}')
# adhoc_match_results = {}
# if adhoc_matches:
# # TODO: do we need to pull contract details?
# adhoc_match_results = {i[0]: {} for i in adhoc_matches}
log.debug(f'fuzzy matching stocks {stock_results}')
stock_matches = fuzzy.extractBests(
@ -928,7 +935,8 @@ async def open_symbol_search(
score_cutoff=50,
)
matches = adhoc_match_results | {
# matches = adhoc_match_results | {
matches = {
item[0]: {} for item in stock_matches
}
# TODO: we used to deliver contract details

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@ -23,53 +23,10 @@ from typing import Optional
from bidict import bidict
from pydantic import BaseModel, validator
# from msgspec import Struct
from ..data._source import Symbol
from ._messages import BrokerdPosition, Status
class Position(BaseModel):
'''
Basic pp (personal position) model with attached fills history.
This type should be IPC wire ready?
'''
symbol: Symbol
# last size and avg entry price
size: float
avg_price: float # TODO: contextual pricing
# ordered record of known constituent trade messages
fills: list[Status] = []
def update_from_msg(
self,
msg: BrokerdPosition,
) -> None:
# XXX: better place to do this?
symbol = self.symbol
lot_size_digits = symbol.lot_size_digits
avg_price, size = (
round(msg['avg_price'], ndigits=symbol.tick_size_digits),
round(msg['size'], ndigits=lot_size_digits),
)
self.avg_price = avg_price
self.size = size
@property
def dsize(self) -> float:
'''
The "dollar" size of the pp, normally in trading (fiat) unit
terms.
'''
return self.avg_price * self.size
from ..pp import Position
_size_units = bidict({
@ -173,7 +130,7 @@ class Allocator(BaseModel):
l_sub_pp = self.units_limit - abs_live_size
elif size_unit == 'currency':
live_cost_basis = abs_live_size * live_pp.avg_price
live_cost_basis = abs_live_size * live_pp.be_price
slot_size = currency_per_slot / price
l_sub_pp = (self.currency_limit - live_cost_basis) / price
@ -205,7 +162,7 @@ class Allocator(BaseModel):
if size_unit == 'currency':
# compute the "projected" limit's worth of units at the
# current pp (weighted) price:
slot_size = currency_per_slot / live_pp.avg_price
slot_size = currency_per_slot / live_pp.be_price
else:
slot_size = u_per_slot
@ -244,7 +201,12 @@ class Allocator(BaseModel):
if order_size < slot_size:
# compute a fractional slots size to display
slots_used = self.slots_used(
Position(symbol=sym, size=order_size, avg_price=price)
Position(
symbol=sym,
size=order_size,
be_price=price,
bsuid=sym,
)
)
return {
@ -271,8 +233,8 @@ class Allocator(BaseModel):
abs_pp_size = abs(pp.size)
if self.size_unit == 'currency':
# live_currency_size = size or (abs_pp_size * pp.avg_price)
live_currency_size = abs_pp_size * pp.avg_price
# live_currency_size = size or (abs_pp_size * pp.be_price)
live_currency_size = abs_pp_size * pp.be_price
prop = live_currency_size / self.currency_limit
else:
@ -342,7 +304,7 @@ def mk_allocator(
# if the current position is already greater then the limit
# settings, increase the limit to the current position
if alloc.size_unit == 'currency':
startup_size = startup_pp.size * startup_pp.avg_price
startup_size = startup_pp.size * startup_pp.be_price
if startup_size > alloc.currency_limit:
alloc.currency_limit = round(startup_size, ndigits=2)

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@ -258,6 +258,6 @@ class BrokerdPosition(BaseModel):
broker: str
account: str
symbol: str
currency: str
size: float
avg_price: float
currency: str = ''

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@ -31,6 +31,8 @@ import tractor
from dataclasses import dataclass
from .. import data
from ..data._source import Symbol
from ..pp import Position
from ..data._normalize import iterticks
from ..data._source import unpack_fqsn
from ..log import get_logger
@ -257,29 +259,14 @@ class PaperBoi:
)
)
# "avg position price" calcs
# TODO: eventually it'd be nice to have a small set of routines
# to do this stuff from a sequence of cleared orders to enable
# so called "contextual positions".
new_size = size + pp_msg.size
# old size minus the new size gives us size differential with
# +ve -> increase in pp size
# -ve -> decrease in pp size
size_diff = abs(new_size) - abs(pp_msg.size)
if new_size == 0:
pp_msg.avg_price = 0
elif size_diff > 0:
# only update the "average position price" when the position
# size increases not when it decreases (i.e. the position is
# being made smaller)
pp_msg.avg_price = (
abs(size) * price + pp_msg.avg_price * abs(pp_msg.size)
) / abs(new_size)
pp_msg.size = new_size
# delegate update to `.pp.Position.lifo_update()`
pp = Position(
Symbol(key=symbol),
size=pp_msg.size,
be_price=pp_msg.avg_price,
bsuid=symbol,
)
pp_msg.size, pp_msg.avg_price = pp.lifo_update(size, price)
await self.ems_trades_stream.send(pp_msg.dict())
@ -390,7 +377,8 @@ async def handle_order_requests(
account = request_msg['account']
if account != 'paper':
log.error(
'This is a paper account, only a `paper` selection is valid'
'This is a paper account,'
' only a `paper` selection is valid'
)
await ems_order_stream.send(BrokerdError(
oid=request_msg['oid'],
@ -464,7 +452,7 @@ async def trades_dialogue(
# TODO: load paper positions per broker from .toml config file
# and pass as symbol to position data mapping: ``dict[str, dict]``
# await ctx.started(all_positions)
await ctx.started(({}, {'paper',}))
await ctx.started(({}, ['paper']))
async with (
ctx.open_stream() as ems_stream,

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@ -83,9 +83,9 @@ def pikerd(loglevel, host, tl, pdb, tsdb):
)
log.info(
f'`marketstore` up!\n'
f'`marketstored` pid: {pid}\n'
f'docker container id: {cid}\n'
f'`marketstored` up!\n'
f'pid: {pid}\n'
f'container id: {cid[:12]}\n'
f'config: {pformat(config)}'
)

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@ -21,6 +21,7 @@ Broker configuration mgmt.
import platform
import sys
import os
from os import path
from os.path import dirname
import shutil
from typing import Optional
@ -111,6 +112,7 @@ if _parent_user:
_conf_names: set[str] = {
'brokers',
'pps',
'trades',
'watchlists',
}
@ -147,19 +149,21 @@ def get_conf_path(
conf_name: str = 'brokers',
) -> str:
"""Return the default config path normally under
``~/.config/piker`` on linux.
'''
Return the top-level default config path normally under
``~/.config/piker`` on linux for a given ``conf_name``, the config
name.
Contains files such as:
- brokers.toml
- pp.toml
- watchlists.toml
- trades.toml
# maybe coming soon ;)
- signals.toml
- strats.toml
"""
'''
assert conf_name in _conf_names
fn = _conf_fn_w_ext(conf_name)
return os.path.join(
@ -173,7 +177,7 @@ def repodir():
Return the abspath to the repo directory.
'''
dirpath = os.path.abspath(
dirpath = path.abspath(
# we're 3 levels down in **this** module file
dirname(dirname(os.path.realpath(__file__)))
)
@ -182,7 +186,9 @@ def repodir():
def load(
conf_name: str = 'brokers',
path: str = None
path: str = None,
**tomlkws,
) -> (dict, str):
'''
@ -190,6 +196,7 @@ def load(
'''
path = path or get_conf_path(conf_name)
if not os.path.isfile(path):
fn = _conf_fn_w_ext(conf_name)
@ -202,8 +209,11 @@ def load(
# if one exists.
if os.path.isfile(template):
shutil.copyfile(template, path)
else:
with open(path, 'w'):
pass # touch
config = toml.load(path)
config = toml.load(path, **tomlkws)
log.debug(f"Read config file {path}")
return config, path
@ -212,6 +222,7 @@ def write(
config: dict, # toml config as dict
name: str = 'brokers',
path: str = None,
**toml_kwargs,
) -> None:
''''
@ -235,11 +246,14 @@ def write(
f"{path}"
)
with open(path, 'w') as cf:
return toml.dump(config, cf)
return toml.dump(
config,
cf,
**toml_kwargs,
)
def load_accounts(
providers: Optional[list[str]] = None
) -> bidict[str, Optional[str]]:

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@ -23,7 +23,7 @@ import decimal
from bidict import bidict
import numpy as np
from pydantic import BaseModel
from msgspec import Struct
# from numba import from_dtype
@ -126,7 +126,7 @@ def unpack_fqsn(fqsn: str) -> tuple[str, str, str]:
)
class Symbol(BaseModel):
class Symbol(Struct):
'''
I guess this is some kinda container thing for dealing with
all the different meta-data formats from brokers?
@ -152,9 +152,7 @@ class Symbol(BaseModel):
info: dict[str, Any],
suffix: str = '',
# XXX: like wtf..
# ) -> 'Symbol':
) -> None:
) -> Symbol:
tick_size = info.get('price_tick_size', 0.01)
lot_tick_size = info.get('lot_tick_size', 0.0)
@ -175,9 +173,7 @@ class Symbol(BaseModel):
fqsn: str,
info: dict[str, Any],
# XXX: like wtf..
# ) -> 'Symbol':
) -> None:
) -> Symbol:
broker, key, suffix = unpack_fqsn(fqsn)
return cls.from_broker_info(
broker,
@ -240,7 +236,7 @@ class Symbol(BaseModel):
'''
tokens = self.tokens()
fqsn = '.'.join(tokens)
fqsn = '.'.join(map(str.lower, tokens))
return fqsn
def iterfqsns(self) -> list[str]:

781
piker/pp.py 100644
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@ -0,0 +1,781 @@
# piker: trading gear for hackers
# Copyright (C) Tyler Goodlet (in stewardship for pikers)
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU Affero General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Affero General Public License for more details.
# You should have received a copy of the GNU Affero General Public License
# along with this program. If not, see <https://www.gnu.org/licenses/>.
'''
Personal/Private position parsing, calculating, summarizing in a way
that doesn't try to cuk most humans who prefer to not lose their moneys..
(looking at you `ib` and dirt-bird friends)
'''
from collections import deque
from contextlib import contextmanager as cm
# from pprint import pformat
import os
from os import path
from math import copysign
import re
import time
from typing import (
Any,
Optional,
Union,
)
from msgspec import Struct
import pendulum
from pendulum import datetime, now
import tomli
import toml
from . import config
from .brokers import get_brokermod
from .clearing._messages import BrokerdPosition, Status
from .data._source import Symbol
from .log import get_logger
log = get_logger(__name__)
@cm
def open_trade_ledger(
broker: str,
account: str,
) -> str:
'''
Indempotently create and read in a trade log file from the
``<configuration_dir>/ledgers/`` directory.
Files are named per broker account of the form
``<brokername>_<accountname>.toml``. The ``accountname`` here is the
name as defined in the user's ``brokers.toml`` config.
'''
ldir = path.join(config._config_dir, 'ledgers')
if not path.isdir(ldir):
os.makedirs(ldir)
fname = f'trades_{broker}_{account}.toml'
tradesfile = path.join(ldir, fname)
if not path.isfile(tradesfile):
log.info(
f'Creating new local trades ledger: {tradesfile}'
)
with open(tradesfile, 'w') as cf:
pass # touch
with open(tradesfile, 'rb') as cf:
start = time.time()
ledger = tomli.load(cf)
print(f'Ledger load took {time.time() - start}s')
cpy = ledger.copy()
try:
yield cpy
finally:
if cpy != ledger:
# TODO: show diff output?
# https://stackoverflow.com/questions/12956957/print-diff-of-python-dictionaries
print(f'Updating ledger for {tradesfile}:\n')
ledger.update(cpy)
# we write on close the mutated ledger data
with open(tradesfile, 'w') as cf:
return toml.dump(ledger, cf)
class Transaction(Struct):
# TODO: should this be ``.to`` (see below)?
fqsn: str
tid: Union[str, int] # unique transaction id
size: float
price: float
cost: float # commisions or other additional costs
dt: datetime
expiry: Optional[datetime] = None
# optional key normally derived from the broker
# backend which ensures the instrument-symbol this record
# is for is truly unique.
bsuid: Optional[Union[str, int]] = None
# optional fqsn for the source "asset"/money symbol?
# from: Optional[str] = None
class Position(Struct):
'''
Basic pp (personal/piker position) model with attached clearing
transaction history.
'''
symbol: Symbol
# can be +ve or -ve for long/short
size: float
# "breakeven price" above or below which pnl moves above and below
# zero for the entirety of the current "trade state".
be_price: float
# unique backend symbol id
bsuid: str
# ordered record of known constituent trade messages
clears: dict[
Union[str, int, Status], # trade id
dict[str, Any], # transaction history summaries
] = {}
expiry: Optional[datetime] = None
def to_dict(self) -> dict:
return {
f: getattr(self, f)
for f in self.__struct_fields__
}
def to_pretoml(self) -> dict:
'''
Prep this position's data contents for export to toml including
re-structuring of the ``.clears`` table to an array of
inline-subtables for better ``pps.toml`` compactness.
'''
d = self.to_dict()
clears = d.pop('clears')
expiry = d.pop('expiry')
if expiry:
d['expiry'] = str(expiry)
clears_list = []
for tid, data in clears.items():
inline_table = toml.TomlDecoder().get_empty_inline_table()
inline_table['tid'] = tid
for k, v in data.items():
inline_table[k] = v
clears_list.append(inline_table)
d['clears'] = clears_list
return d
def update_from_msg(
self,
msg: BrokerdPosition,
) -> None:
# XXX: better place to do this?
symbol = self.symbol
lot_size_digits = symbol.lot_size_digits
be_price, size = (
round(
msg['avg_price'],
ndigits=symbol.tick_size_digits
),
round(
msg['size'],
ndigits=lot_size_digits
),
)
self.be_price = be_price
self.size = size
@property
def dsize(self) -> float:
'''
The "dollar" size of the pp, normally in trading (fiat) unit
terms.
'''
return self.be_price * self.size
def update(
self,
t: Transaction,
) -> None:
self.clears[t.tid] = {
'cost': t.cost,
'price': t.price,
'size': t.size,
'dt': str(t.dt),
}
def lifo_update(
self,
size: float,
price: float,
cost: float = 0,
# TODO: idea: "real LIFO" dynamic positioning.
# - when a trade takes place where the pnl for
# the (set of) trade(s) is below the breakeven price
# it may be that the trader took a +ve pnl on a short(er)
# term trade in the same account.
# - in this case we could recalc the be price to
# be reverted back to it's prior value before the nearest term
# trade was opened.?
# dynamic_breakeven_price: bool = False,
) -> (float, float):
'''
Incremental update using a LIFO-style weighted mean.
'''
# "avg position price" calcs
# TODO: eventually it'd be nice to have a small set of routines
# to do this stuff from a sequence of cleared orders to enable
# so called "contextual positions".
new_size = self.size + size
# old size minus the new size gives us size diff with
# +ve -> increase in pp size
# -ve -> decrease in pp size
size_diff = abs(new_size) - abs(self.size)
if new_size == 0:
self.be_price = 0
elif size_diff > 0:
# XXX: LOFI incremental update:
# only update the "average price" when
# the size increases not when it decreases (i.e. the
# position is being made smaller)
self.be_price = (
# weight of current exec = (size * price) + cost
(abs(size) * price)
+
(copysign(1, new_size) * cost) # transaction cost
+
# weight of existing be price
self.be_price * abs(self.size) # weight of previous pp
) / abs(new_size) # normalized by the new size: weighted mean.
self.size = new_size
return new_size, self.be_price
def minimize_clears(
self,
) -> dict[str, dict]:
'''
Minimize the position's clears entries by removing
all transactions before the last net zero size to avoid
unecessary history irrelevant to the current pp state.
'''
size: float = 0
clears_since_zero: deque[tuple(str, dict)] = deque()
# scan for the last "net zero" position by
# iterating clears in reverse.
for tid, clear in reversed(self.clears.items()):
size += clear['size']
clears_since_zero.appendleft((tid, clear))
if size == 0:
break
self.clears = dict(clears_since_zero)
return self.clears
def update_pps(
records: dict[str, Transaction],
pps: Optional[dict[str, Position]] = None
) -> dict[str, Position]:
'''
Compile a set of positions from a trades ledger.
'''
pps: dict[str, Position] = pps or {}
# lifo update all pps from records
for r in records:
pp = pps.setdefault(
r.bsuid,
# if no existing pp, allocate fresh one.
Position(
Symbol.from_fqsn(
r.fqsn,
info={},
),
size=0.0,
be_price=0.0,
bsuid=r.bsuid,
expiry=r.expiry,
)
)
# don't do updates for ledger records we already have
# included in the current pps state.
if r.tid in pp.clears:
# NOTE: likely you'll see repeats of the same
# ``Transaction`` passed in here if/when you are restarting
# a ``brokerd.ib`` where the API will re-report trades from
# the current session, so we need to make sure we don't
# "double count" these in pp calculations.
continue
# lifo style "breakeven" price calc
pp.lifo_update(
r.size,
r.price,
# include transaction cost in breakeven price
# and presume the worst case of the same cost
# to exit this transaction (even though in reality
# it will be dynamic based on exit stratetgy).
cost=2*r.cost,
)
# track clearing data
pp.update(r)
assert len(set(pp.clears)) == len(pp.clears)
return pps
def load_pps_from_ledger(
brokername: str,
acctname: str,
# post normalization filter on ledger entries to be processed
filter_by: Optional[list[dict]] = None,
) -> dict[str, Position]:
'''
Open a ledger file by broker name and account and read in and
process any trade records into our normalized ``Transaction``
form and then pass these into the position processing routine
and deliver the two dict-sets of the active and closed pps.
'''
with open_trade_ledger(
brokername,
acctname,
) as ledger:
if not ledger:
# null case, no ledger file with content
return {}
brokermod = get_brokermod(brokername)
src_records = brokermod.norm_trade_records(ledger)
if filter_by:
bsuids = set(filter_by)
records = list(filter(lambda r: r.bsuid in bsuids, src_records))
else:
records = src_records
return update_pps(records)
def get_pps(
brokername: str,
acctids: Optional[set[str]] = set(),
) -> dict[str, dict[str, Position]]:
'''
Read out broker-specific position entries from
incremental update file: ``pps.toml``.
'''
conf, path = config.load(
'pps',
# load dicts as inlines to preserve compactness
# _dict=toml.decoder.InlineTableDict,
)
all_active = {}
all_closed = {}
# try to load any ledgers if no section found
bconf, path = config.load('brokers')
accounts = bconf[brokername]['accounts']
for account in accounts:
# TODO: instead of this filter we could
# always send all known pps but just not audit
# them since an active client might not be up?
if (
acctids and
f'{brokername}.{account}' not in acctids
):
continue
active, closed = update_pps_conf(brokername, account)
all_active.setdefault(account, {}).update(active)
all_closed.setdefault(account, {}).update(closed)
return all_active, all_closed
# TODO: instead see if we can hack tomli and tomli-w to do the same:
# - https://github.com/hukkin/tomli
# - https://github.com/hukkin/tomli-w
class PpsEncoder(toml.TomlEncoder):
'''
Special "styled" encoder that makes a ``pps.toml`` redable and
compact by putting `.clears` tables inline and everything else
flat-ish.
'''
separator = ','
def dump_list(self, v):
'''
Dump an inline list with a newline after every element and
with consideration for denoted inline table types.
'''
retval = "[\n"
for u in v:
if isinstance(u, toml.decoder.InlineTableDict):
out = self.dump_inline_table(u)
else:
out = str(self.dump_value(u))
retval += " " + out + "," + "\n"
retval += "]"
return retval
def dump_inline_table(self, section):
"""Preserve inline table in its compact syntax instead of expanding
into subsection.
https://github.com/toml-lang/toml#user-content-inline-table
"""
val_list = []
for k, v in section.items():
# if isinstance(v, toml.decoder.InlineTableDict):
if isinstance(v, dict):
val = self.dump_inline_table(v)
else:
val = str(self.dump_value(v))
val_list.append(k + " = " + val)
retval = "{ " + ", ".join(val_list) + " }"
return retval
def dump_sections(self, o, sup):
retstr = ""
if sup != "" and sup[-1] != ".":
sup += '.'
retdict = self._dict()
arraystr = ""
for section in o:
qsection = str(section)
value = o[section]
if not re.match(r'^[A-Za-z0-9_-]+$', section):
qsection = toml.encoder._dump_str(section)
# arrayoftables = False
if (
self.preserve
and isinstance(value, toml.decoder.InlineTableDict)
):
retstr += (
qsection
+
" = "
+
self.dump_inline_table(o[section])
+
'\n' # only on the final terminating left brace
)
# XXX: this code i'm pretty sure is just blatantly bad
# and/or wrong..
# if isinstance(o[section], list):
# for a in o[section]:
# if isinstance(a, dict):
# arrayoftables = True
# if arrayoftables:
# for a in o[section]:
# arraytabstr = "\n"
# arraystr += "[[" + sup + qsection + "]]\n"
# s, d = self.dump_sections(a, sup + qsection)
# if s:
# if s[0] == "[":
# arraytabstr += s
# else:
# arraystr += s
# while d:
# newd = self._dict()
# for dsec in d:
# s1, d1 = self.dump_sections(d[dsec], sup +
# qsection + "." +
# dsec)
# if s1:
# arraytabstr += ("[" + sup + qsection +
# "." + dsec + "]\n")
# arraytabstr += s1
# for s1 in d1:
# newd[dsec + "." + s1] = d1[s1]
# d = newd
# arraystr += arraytabstr
elif isinstance(value, dict):
retdict[qsection] = o[section]
elif o[section] is not None:
retstr += (
qsection
+
" = "
+
str(self.dump_value(o[section]))
)
# if not isinstance(value, dict):
if not isinstance(value, toml.decoder.InlineTableDict):
# inline tables should not contain newlines:
# https://toml.io/en/v1.0.0#inline-table
retstr += '\n'
else:
raise ValueError(value)
retstr += arraystr
return (retstr, retdict)
def load_pps_from_toml(
brokername: str,
acctid: str,
# XXX: there is an edge case here where we may want to either audit
# the retrieved ``pps.toml`` output or reprocess it since there was
# an error on write on the last attempt to update the state file
# even though the ledger *was* updated. For this cases we allow the
# caller to pass in a symbol set they'd like to reload from the
# underlying ledger to be reprocessed in computing pps state.
reload_records: Optional[dict[str, str]] = None,
update_from_ledger: bool = False,
) -> tuple[dict, dict[str, Position]]:
'''
Load and marshal to objects all pps from either an existing
``pps.toml`` config, or from scratch from a ledger file when
none yet exists.
'''
conf, path = config.load('pps')
brokersection = conf.setdefault(brokername, {})
pps = brokersection.setdefault(acctid, {})
pp_objs = {}
# no pps entry yet for this broker/account so parse any available
# ledgers to build a brand new pps state.
if not pps or update_from_ledger:
pp_objs = load_pps_from_ledger(
brokername,
acctid,
)
# Reload symbol specific ledger entries if requested by the
# caller **AND** none exist in the current pps state table.
elif (
pps and reload_records
):
# no pps entry yet for this broker/account so parse
# any available ledgers to build a pps state.
pp_objs = load_pps_from_ledger(
brokername,
acctid,
filter_by=reload_records,
)
if not pps:
log.warning(
f'No trade history could be loaded for {brokername}:{acctid}'
)
# unmarshal/load ``pps.toml`` config entries into object form.
for fqsn, entry in pps.items():
bsuid = entry['bsuid']
# convert clears sub-tables (only in this form
# for toml re-presentation) back into a master table.
clears_list = entry['clears']
# index clears entries in "object" form by tid in a top
# level dict instead of a list (as is presented in our
# ``pps.toml``).
clears = {}
for clears_table in clears_list:
tid = clears_table.pop('tid')
clears[tid] = clears_table
size = entry['size']
# TODO: an audit system for existing pps entries?
# if not len(clears) == abs(size):
# pp_objs = load_pps_from_ledger(
# brokername,
# acctid,
# filter_by=reload_records,
# )
# reason = 'size <-> len(clears) mismatch'
# raise ValueError(
# '`pps.toml` entry is invalid:\n'
# f'{fqsn}\n'
# f'{pformat(entry)}'
# )
expiry = entry.get('expiry')
if expiry:
expiry = pendulum.parse(expiry)
pp_objs[bsuid] = Position(
Symbol.from_fqsn(fqsn, info={}),
size=size,
be_price=entry['be_price'],
expiry=expiry,
bsuid=entry['bsuid'],
# XXX: super critical, we need to be sure to include
# all pps.toml clears to avoid reusing clears that were
# already included in the current incremental update
# state, since today's records may have already been
# processed!
clears=clears,
)
return conf, pp_objs
def update_pps_conf(
brokername: str,
acctid: str,
trade_records: Optional[list[Transaction]] = None,
ledger_reload: Optional[dict[str, str]] = None,
) -> tuple[
dict[str, Position],
dict[str, Position],
]:
# this maps `.bsuid` values to positions
pp_objs: dict[Union[str, int], Position]
if trade_records and ledger_reload:
for r in trade_records:
ledger_reload[r.bsuid] = r.fqsn
conf, pp_objs = load_pps_from_toml(
brokername,
acctid,
reload_records=ledger_reload,
)
# update all pp objects from any (new) trade records which
# were passed in (aka incremental update case).
if trade_records:
pp_objs = update_pps(
trade_records,
pps=pp_objs,
)
pp_entries = {} # dict-serialize all active pps
# NOTE: newly closed position are also important to report/return
# since a consumer, like an order mode UI ;), might want to react
# based on the closure.
closed_pp_objs: dict[str, Position] = {}
for bsuid in list(pp_objs):
pp = pp_objs[bsuid]
pp.minimize_clears()
if (
pp.size == 0
# drop time-expired positions (normally derivatives)
or (pp.expiry and pp.expiry < now())
):
# if expired the position is closed
pp.size = 0
# position is already closed aka "net zero"
closed_pp = pp_objs.pop(bsuid, None)
if closed_pp:
closed_pp_objs[bsuid] = closed_pp
else:
# serialize to pre-toml form
asdict = pp.to_pretoml()
if pp.expiry is None:
asdict.pop('expiry', None)
# TODO: we need to figure out how to have one top level
# listing venue here even when the backend isn't providing
# it via the trades ledger..
# drop symbol obj in serialized form
s = asdict.pop('symbol')
fqsn = s.front_fqsn()
print(f'Updating active pp: {fqsn}')
# XXX: ugh, it's cuz we push the section under
# the broker name.. maybe we need to rethink this?
brokerless_key = fqsn.rstrip(f'.{brokername}')
pp_entries[brokerless_key] = asdict
conf[brokername][acctid] = pp_entries
# TODO: why tf haven't they already done this for inline tables smh..
enc = PpsEncoder(preserve=True)
# table_bs_type = type(toml.TomlDecoder().get_empty_inline_table())
enc.dump_funcs[toml.decoder.InlineTableDict] = enc.dump_inline_table
config.write(
conf,
'pps',
encoder=enc,
)
# deliver object form of all pps in table to caller
return pp_objs, closed_pp_objs
if __name__ == '__main__':
import sys
args = sys.argv
assert len(args) > 1, 'Specifiy account(s) from `brokers.toml`'
args = args[1:]
for acctid in args:
broker, name = acctid.split('.')
update_pps_conf(broker, name)

View File

@ -19,6 +19,7 @@ Position info and display
"""
from __future__ import annotations
from copy import copy
from dataclasses import dataclass
from functools import partial
from math import floor, copysign
@ -105,8 +106,8 @@ async def update_pnl_from_feed(
# compute and display pnl status
order_mode.pane.pnl_label.format(
pnl=copysign(1, size) * pnl(
# live.avg_price,
order_mode.current_pp.live_pp.avg_price,
# live.be_price,
order_mode.current_pp.live_pp.be_price,
tick['price'],
),
)
@ -356,7 +357,7 @@ class SettingsPane:
# last historical close price
last = feed.shm.array[-1][['close']][0]
pnl_value = copysign(1, size) * pnl(
tracker.live_pp.avg_price,
tracker.live_pp.be_price,
last,
)
@ -476,7 +477,7 @@ class PositionTracker:
self.alloc = alloc
self.startup_pp = startup_pp
self.live_pp = startup_pp.copy()
self.live_pp = copy(startup_pp)
view = chart.getViewBox()
@ -556,7 +557,7 @@ class PositionTracker:
pp = position or self.live_pp
self.update_line(
pp.avg_price,
pp.be_price,
pp.size,
self.chart.linked.symbol.lot_size_digits,
)
@ -570,7 +571,7 @@ class PositionTracker:
self.hide()
else:
self._level_marker.level = pp.avg_price
self._level_marker.level = pp.be_price
# these updates are critical to avoid lag on view/scene changes
self._level_marker.update() # trigger paint

View File

@ -33,10 +33,10 @@ import trio
from PyQt5.QtCore import Qt
from .. import config
from ..pp import Position
from ..clearing._client import open_ems, OrderBook
from ..clearing._allocate import (
mk_allocator,
Position,
)
from ._style import _font
from ..data._source import Symbol
@ -59,7 +59,8 @@ log = get_logger(__name__)
class OrderDialog(BaseModel):
'''Trade dialogue meta-data describing the lifetime
'''
Trade dialogue meta-data describing the lifetime
of an order submission to ``emsd`` from a chart.
'''
@ -87,7 +88,8 @@ def on_level_change_update_next_order_info(
tracker: PositionTracker,
) -> None:
'''A callback applied for each level change to the line
'''
A callback applied for each level change to the line
which will recompute the order size based on allocator
settings. this is assigned inside
``OrderMode.line_from_order()``
@ -604,7 +606,10 @@ async def open_order_mode(
startup_pp = Position(
symbol=symbol,
size=0,
avg_price=0,
be_price=0,
# XXX: BLEH, do we care about this on the client side?
bsuid=symbol,
)
msg = pps_by_account.get(account_name)
if msg:

View File

@ -41,6 +41,7 @@ setup(
},
install_requires=[
'toml',
'tomli', # fastest pure py reader
'click',
'colorlog',
'attrs',