976 lines
30 KiB
Python
976 lines
30 KiB
Python
# piker: trading gear for hackers
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# Copyright (C) Tyler Goodlet (in stewardship for pikers)
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# This program is free software: you can redistribute it and/or modify
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# it under the terms of the GNU Affero General Public License as published by
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# the Free Software Foundation, either version 3 of the License, or
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# (at your option) any later version.
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# This program is distributed in the hope that it will be useful,
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# but WITHOUT ANY WARRANTY; without even the implied warranty of
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# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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# GNU Affero General Public License for more details.
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# You should have received a copy of the GNU Affero General Public License
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# along with this program. If not, see <https://www.gnu.org/licenses/>.
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'''
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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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(looking at you `ib` and dirt-bird friends)
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'''
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from contextlib import contextmanager as cm
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from pprint import pformat
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import os
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from os import path
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from math import copysign
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import re
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import time
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from typing import (
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Any,
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Optional,
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Union,
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)
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import pendulum
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from pendulum import datetime, now
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import tomli
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import toml
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from . import config
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from .brokers import get_brokermod
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from .clearing._messages import BrokerdPosition, Status
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from .data._source import Symbol
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from .log import get_logger
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from .data.types import Struct
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log = get_logger(__name__)
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@cm
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def open_trade_ledger(
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broker: str,
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account: str,
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) -> str:
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'''
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Indempotently create and read in a trade log file from the
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``<configuration_dir>/ledgers/`` directory.
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Files are named per broker account of the form
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``<brokername>_<accountname>.toml``. The ``accountname`` here is the
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name as defined in the user's ``brokers.toml`` config.
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'''
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ldir = path.join(config._config_dir, 'ledgers')
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if not path.isdir(ldir):
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os.makedirs(ldir)
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fname = f'trades_{broker}_{account}.toml'
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tradesfile = path.join(ldir, fname)
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if not path.isfile(tradesfile):
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log.info(
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f'Creating new local trades ledger: {tradesfile}'
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)
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with open(tradesfile, 'w') as cf:
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pass # touch
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with open(tradesfile, 'rb') as cf:
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start = time.time()
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ledger = tomli.load(cf)
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print(f'Ledger load took {time.time() - start}s')
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cpy = ledger.copy()
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try:
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yield cpy
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finally:
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if cpy != ledger:
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# TODO: show diff output?
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# https://stackoverflow.com/questions/12956957/print-diff-of-python-dictionaries
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print(f'Updating ledger for {tradesfile}:\n')
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ledger.update(cpy)
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# we write on close the mutated ledger data
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with open(tradesfile, 'w') as cf:
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toml.dump(ledger, cf)
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class Transaction(Struct, frozen=True):
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# TODO: should this be ``.to`` (see below)?
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fqsn: str
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tid: Union[str, int] # unique transaction id
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size: float
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price: float
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cost: float # commisions or other additional costs
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dt: datetime
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expiry: Optional[datetime] = None
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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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# is for is truly unique.
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bsuid: Optional[Union[str, int]] = None
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# optional fqsn for the source "asset"/money symbol?
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# from: Optional[str] = None
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class Position(Struct):
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'''
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Basic pp (personal/piker position) model with attached clearing
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transaction history.
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'''
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symbol: Symbol
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# can be +ve or -ve for long/short
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size: float
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# "breakeven price" above or below which pnl moves above and below
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# zero for the entirety of the current "trade state".
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ppu: float
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# unique backend symbol id
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bsuid: str
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split_ratio: Optional[int] = None
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# ordered record of known constituent trade messages
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clears: dict[
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Union[str, int, Status], # trade id
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dict[str, Any], # transaction history summaries
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] = {}
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first_clear_dt: Optional[datetime] = None
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expiry: Optional[datetime] = None
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def to_dict(self) -> dict:
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return {
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f: getattr(self, f)
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for f in self.__struct_fields__
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}
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def to_pretoml(self) -> tuple[str, dict]:
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'''
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Prep this position's data contents for export to toml including
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re-structuring of the ``.clears`` table to an array of
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inline-subtables for better ``pps.toml`` compactness.
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'''
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d = self.to_dict()
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clears = d.pop('clears')
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expiry = d.pop('expiry')
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if self.split_ratio is None:
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d.pop('split_ratio')
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# should be obvious from clears/event table
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d.pop('first_clear_dt')
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# TODO: we need to figure out how to have one top level
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# listing venue here even when the backend isn't providing
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# it via the trades ledger..
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# drop symbol obj in serialized form
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s = d.pop('symbol')
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fqsn = s.front_fqsn()
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if self.expiry is None:
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d.pop('expiry', None)
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elif expiry:
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d['expiry'] = str(expiry)
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toml_clears_list = []
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# reverse sort so latest clears are at top of section?
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for tid, data in sorted(
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list(clears.items()),
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# sort by datetime
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key=lambda item: item[1]['dt'],
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):
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inline_table = toml.TomlDecoder().get_empty_inline_table()
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# serialize datetime to parsable `str`
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inline_table['dt'] = str(data['dt'])
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# insert optional clear fields in column order
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for k in ['ppu', 'accum_size']:
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val = data.get(k)
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if val:
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inline_table[k] = val
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# insert required fields
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for k in ['price', 'size', 'cost']:
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inline_table[k] = data[k]
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inline_table['tid'] = tid
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toml_clears_list.append(inline_table)
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d['clears'] = toml_clears_list
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return fqsn, d
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def ensure_state(self) -> None:
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'''
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Audit either the `.size` and `.ppu` local instance vars against
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the clears table calculations and return the calc-ed values if
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they differ and log warnings to console.
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'''
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clears = list(self.clears.values())
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self.first_clear_dt = min(list(entry['dt'] for entry in clears))
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last_clear = clears[-1]
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csize = self.calc_size()
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accum = last_clear['accum_size']
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if not self.expired():
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if (
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csize != accum
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and csize != round(accum * self.split_ratio or 1)
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):
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raise ValueError(f'Size mismatch: {csize}')
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else:
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assert csize == 0, 'Contract is expired but non-zero size?'
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if self.size != csize:
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log.warning(
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'Position state mismatch:\n'
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f'{self.size} => {csize}'
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)
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self.size = csize
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cppu = self.calc_ppu()
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ppu = last_clear['ppu']
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if (
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cppu != ppu
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and self.split_ratio is not None
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# handle any split info entered (for now) manually by user
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and cppu != (ppu / self.split_ratio)
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):
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raise ValueError(f'PPU mismatch: {cppu}')
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if self.ppu != cppu:
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log.warning(
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'Position state mismatch:\n'
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f'{self.ppu} => {cppu}'
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)
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self.ppu = cppu
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def update_from_msg(
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self,
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msg: BrokerdPosition,
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) -> None:
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# XXX: better place to do this?
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symbol = self.symbol
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lot_size_digits = symbol.lot_size_digits
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ppu, size = (
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round(
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msg['avg_price'],
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ndigits=symbol.tick_size_digits
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),
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round(
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msg['size'],
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ndigits=lot_size_digits
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),
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)
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self.ppu = ppu
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self.size = size
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@property
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def dsize(self) -> float:
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'''
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The "dollar" size of the pp, normally in trading (fiat) unit
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terms.
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'''
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return self.ppu * self.size
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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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# the (set of) trade(s) is below the breakeven price
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# it may be that the trader took a +ve pnl on a short(er)
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# term trade in the same account.
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# - in this case we could recalc the be price to
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# be reverted back to it's prior value before the nearest term
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# trade was opened.?
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# def lifo_price() -> float:
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# ...
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def calc_ppu(
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self,
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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_scalar: float = 2,
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) -> float:
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'''
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Compute the "price-per-unit" price for the given non-zero sized
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rolling position.
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The recurrence relation which computes this (exponential) mean
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per new clear which **increases** the accumulative postiion size
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is:
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ppu[-1] = (
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ppu[-2] * accum_size[-2]
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+
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ppu[-1] * size
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) / accum_size[-1]
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where `cost_basis` for the current step is simply the price
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* size of the most recent clearing transaction.
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'''
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asize_h: list[float] = [] # historical accumulative size
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ppu_h: list[float] = [] # historical price-per-unit
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clears = list(self.clears.items())
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for i, (tid, entry) in enumerate(clears):
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clear_size = entry['size']
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clear_price = entry['price']
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last_accum_size = asize_h[-1] if asize_h else 0
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accum_size = last_accum_size + clear_size
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accum_sign = copysign(1, accum_size)
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sign_change: bool = False
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if accum_size == 0:
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ppu_h.append(0)
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asize_h.append(0)
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continue
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# test if the pp somehow went "passed" a net zero size state
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# resulting in a change of the "sign" of the size (+ve for
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# long, -ve for short).
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sign_change = (
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copysign(1, last_accum_size) + accum_sign == 0
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and last_accum_size != 0
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)
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# since we passed the net-zero-size state the new size
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# after sum should be the remaining size the new
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# "direction" (aka, long vs. short) for this clear.
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if sign_change:
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clear_size = accum_size
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abs_diff = abs(accum_size)
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asize_h.append(0)
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ppu_h.append(0)
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else:
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# old size minus the new size gives us size diff with
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# +ve -> increase in pp size
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# -ve -> decrease in pp size
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abs_diff = abs(accum_size) - abs(last_accum_size)
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# XXX: LIFO breakeven price update. only an increaze in size
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# of the position contributes the breakeven price,
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# a decrease does not (i.e. the position is being made
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# smaller).
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# abs_clear_size = abs(clear_size)
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abs_new_size = abs(accum_size)
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if abs_diff > 0:
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cost_basis = (
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# cost basis for this clear
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clear_price * abs(clear_size)
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+
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# transaction cost
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accum_sign * cost_scalar * entry['cost']
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)
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if asize_h:
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size_last = abs(asize_h[-1])
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cb_last = ppu_h[-1] * size_last
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ppu = (cost_basis + cb_last) / abs_new_size
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else:
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ppu = cost_basis / abs_new_size
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ppu_h.append(ppu)
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asize_h.append(accum_size)
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else:
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# on "exit" clears from a given direction,
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# only the size changes not the price-per-unit
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# need to be updated since the ppu remains constant
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# and gets weighted by the new size.
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asize_h.append(accum_size)
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ppu_h.append(ppu_h[-1])
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final_ppu = ppu_h[-1] if ppu_h else 0
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# handle any split info entered (for now) manually by user
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if self.split_ratio is not None:
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final_ppu /= self.split_ratio
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return final_ppu
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def expired(self) -> bool:
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'''
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Predicate which checks if the contract/instrument is past its expiry.
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'''
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return bool(self.expiry) and self.expiry < now()
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def calc_size(self) -> float:
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'''
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Calculate the unit size of this position in the destination
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asset using the clears/trade event table; zero if expired.
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'''
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size: float = 0
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# time-expired pps (normally derivatives) are "closed"
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# and have a zero size.
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if self.expired():
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return 0
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for tid, entry in self.clears.items():
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size += entry['size']
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if self.split_ratio is not None:
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size = round(size * self.split_ratio)
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return size
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def minimize_clears(
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self,
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) -> dict[str, dict]:
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'''
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Minimize the position's clears entries by removing
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all transactions before the last net zero size to avoid
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unecessary history irrelevant to the current pp state.
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'''
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size: float = 0
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clears_since_zero: list[tuple(str, dict)] = []
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# TODO: we might just want to always do this when iterating
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# a ledger? keep a state of the last net-zero and only do the
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# full iterate when no state was stashed?
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# scan for the last "net zero" position by iterating
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# transactions until the next net-zero size, rinse, repeat.
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for tid, clear in self.clears.items():
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size += clear['size']
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clears_since_zero.append((tid, clear))
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if size == 0:
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clears_since_zero.clear()
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self.clears = dict(clears_since_zero)
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return self.clears
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def add_clear(
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self,
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t: Transaction,
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) -> dict:
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'''
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Update clearing table and populate rolling ppu and accumulative
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size in both the clears entry and local attrs state.
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'''
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clear = self.clears[t.tid] = {
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'cost': t.cost,
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'price': t.price,
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'size': t.size,
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'dt': t.dt,
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}
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# TODO: compute these incrementally instead
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# of re-looping through each time resulting in O(n**2)
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# behaviour..?
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# NOTE: we compute these **after** adding the entry in order to
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# make the recurrence relation math work inside
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# ``.calc_size()``.
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self.size = clear['accum_size'] = self.calc_size()
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self.ppu = clear['ppu'] = self.calc_ppu()
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return clear
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def sugest_split(self) -> float:
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...
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class PpTable(Struct):
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brokername: str
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acctid: str
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pps: dict[str, Position]
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conf: Optional[dict] = {}
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def update_from_trans(
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self,
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trans: dict[str, Transaction],
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cost_scalar: float = 2,
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) -> dict[str, Position]:
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pps = self.pps
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updated: dict[str, Position] = {}
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# lifo update all pps from records
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for tid, t in trans.items():
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pp = pps.setdefault(
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t.bsuid,
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# if no existing pp, allocate fresh one.
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Position(
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Symbol.from_fqsn(
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t.fqsn,
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info={},
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),
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size=0.0,
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ppu=0.0,
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bsuid=t.bsuid,
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expiry=t.expiry,
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)
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)
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clears = pp.clears
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if clears:
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first_clear_dt = pp.first_clear_dt
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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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if (
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t.tid in clears
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or first_clear_dt and t.dt < first_clear_dt
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):
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# NOTE: likely you'll see repeats of the same
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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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# 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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continue
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# update clearing table
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pp.add_clear(t)
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updated[t.bsuid] = pp
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# minimize clears tables and update sizing.
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for bsuid, pp in updated.items():
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pp.ensure_state()
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return updated
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def dump_active(
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self,
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) -> tuple[
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dict[str, Position],
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|
dict[str, Position]
|
|
]:
|
|
'''
|
|
Iterate all tabulated positions, render active positions to
|
|
a ``dict`` format amenable to serialization (via TOML) and drop
|
|
from state (``.pps``) as well as return in a ``dict`` all
|
|
``Position``s which have recently closed.
|
|
|
|
'''
|
|
# 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 (for example removing the breakeven line
|
|
# and clearing the entry from any lists/monitors).
|
|
closed_pp_objs: dict[str, Position] = {}
|
|
open_pp_objs: dict[str, Position] = {}
|
|
|
|
pp_objs = self.pps
|
|
for bsuid in list(pp_objs):
|
|
pp = pp_objs[bsuid]
|
|
|
|
# XXX: debug hook for size mismatches
|
|
# qqqbsuid = 320227571
|
|
# if bsuid == qqqbsuid:
|
|
# breakpoint()
|
|
|
|
pp.ensure_state()
|
|
|
|
if (
|
|
# "net-zero" is a "closed" position
|
|
pp.size == 0
|
|
|
|
# time-expired pps (normally derivatives) are "closed"
|
|
or (pp.expiry and pp.expiry < now())
|
|
):
|
|
# for expired cases
|
|
pp.size = 0
|
|
|
|
# NOTE: we DO NOT pop the pp here since it can still be
|
|
# used to check for duplicate clears that may come in as
|
|
# new transaction from some backend API and need to be
|
|
# ignored; the closed positions won't be written to the
|
|
# ``pps.toml`` since ``pp_active_entries`` above is what's
|
|
# written.
|
|
closed_pp_objs[bsuid] = pp
|
|
|
|
else:
|
|
open_pp_objs[bsuid] = pp
|
|
|
|
return open_pp_objs, closed_pp_objs
|
|
|
|
def to_toml(
|
|
self,
|
|
) -> dict[str, Any]:
|
|
|
|
active, closed = self.dump_active()
|
|
|
|
# ONLY dict-serialize all active positions; those that are closed
|
|
# we don't store in the ``pps.toml``.
|
|
to_toml_dict = {}
|
|
|
|
for bsuid, pos in active.items():
|
|
|
|
# keep the minimal amount of clears that make up this
|
|
# position since the last net-zero state.
|
|
pos.minimize_clears()
|
|
pos.ensure_state()
|
|
|
|
# serialize to pre-toml form
|
|
fqsn, asdict = pos.to_pretoml()
|
|
log.info(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.removeprefix(f'{self.brokername}.')
|
|
to_toml_dict[brokerless_key] = asdict
|
|
|
|
return to_toml_dict
|
|
|
|
def write_config(self) -> None:
|
|
'''
|
|
Write the current position table to the user's ``pps.toml``.
|
|
|
|
'''
|
|
# TODO: show diff output?
|
|
# https://stackoverflow.com/questions/12956957/print-diff-of-python-dictionaries
|
|
print(f'Updating ``pps.toml`` for {path}:\n')
|
|
|
|
# active, closed_pp_objs = table.dump_active()
|
|
pp_entries = self.to_toml()
|
|
self.conf[self.brokername][self.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(
|
|
self.conf,
|
|
'pps',
|
|
encoder=enc,
|
|
)
|
|
|
|
|
|
def load_pps_from_ledger(
|
|
|
|
brokername: str,
|
|
acctname: str,
|
|
|
|
# post normalization filter on ledger entries to be processed
|
|
filter_by: Optional[list[dict]] = None,
|
|
|
|
) -> tuple[
|
|
dict[str, Transaction],
|
|
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 update the equivalent ``Pptable`` and deliver the two
|
|
bsuid-mapped dict-sets of the transactions and pps.
|
|
|
|
'''
|
|
with (
|
|
open_trade_ledger(brokername, acctname) as ledger,
|
|
open_pps(brokername, acctname) as table,
|
|
):
|
|
if not ledger:
|
|
# null case, no ledger file with content
|
|
return {}
|
|
|
|
mod = get_brokermod(brokername)
|
|
src_records: dict[str, Transaction] = mod.norm_trade_records(ledger)
|
|
|
|
if filter_by:
|
|
records = {}
|
|
bsuids = set(filter_by)
|
|
for tid, r in src_records.items():
|
|
if r.bsuid in bsuids:
|
|
records[tid] = r
|
|
else:
|
|
records = src_records
|
|
|
|
updated = table.update_from_trans(records)
|
|
|
|
return records, updated
|
|
|
|
|
|
# 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)
|
|
|
|
|
|
@cm
|
|
def open_pps(
|
|
brokername: str,
|
|
acctid: str,
|
|
write_on_exit: bool = True,
|
|
|
|
) -> PpTable:
|
|
'''
|
|
Read out broker-specific position entries from
|
|
incremental update file: ``pps.toml``.
|
|
|
|
'''
|
|
conf, path = config.load('pps')
|
|
brokersection = conf.setdefault(brokername, {})
|
|
pps = brokersection.setdefault(acctid, {})
|
|
|
|
# TODO: ideally we can pass in an existing
|
|
# pps state to this right? such that we
|
|
# don't have to do a ledger reload all the
|
|
# time.. a couple ideas I can think of,
|
|
# - mirror this in some client side actor which
|
|
# does the actual ledger updates (say the paper
|
|
# engine proc if we decide to always spawn it?),
|
|
# - do diffs against updates from the ledger writer
|
|
# actor and the in-mem state here?
|
|
|
|
pp_objs = {}
|
|
table = PpTable(
|
|
brokername,
|
|
acctid,
|
|
pp_objs,
|
|
conf=conf,
|
|
)
|
|
|
|
# unmarshal/load ``pps.toml`` config entries into object form
|
|
# and update `PpTable` obj entries.
|
|
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 = pp_objs.setdefault(bsuid, {})
|
|
|
|
# TODO: should be make a ``Struct`` for clear/event entries?
|
|
# convert "clear events table" from the toml config (list of
|
|
# a dicts) and load it into object form for use in position
|
|
# processing of new clear events.
|
|
trans: list[Transaction] = []
|
|
|
|
for clears_table in clears_list:
|
|
tid = clears_table.pop('tid')
|
|
dtstr = clears_table['dt']
|
|
dt = pendulum.parse(dtstr)
|
|
clears_table['dt'] = dt
|
|
trans.append(Transaction(
|
|
fqsn=bsuid,
|
|
bsuid=bsuid,
|
|
tid=tid,
|
|
size=clears_table['size'],
|
|
price=clears_table['price'],
|
|
cost=clears_table['cost'],
|
|
dt=dt,
|
|
))
|
|
clears[tid] = clears_table
|
|
|
|
size = entry['size']
|
|
|
|
# TODO: remove but, handle old field name for now
|
|
ppu = entry.get('ppu', entry.get('be_price', 0))
|
|
split_ratio = entry.get('split_ratio')
|
|
|
|
expiry = entry.get('expiry')
|
|
if expiry:
|
|
expiry = pendulum.parse(expiry)
|
|
|
|
pp = pp_objs[bsuid] = Position(
|
|
Symbol.from_fqsn(fqsn, info={}),
|
|
size=size,
|
|
ppu=ppu,
|
|
split_ratio=split_ratio,
|
|
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!
|
|
for t in trans:
|
|
pp.add_clear(t)
|
|
|
|
# audit entries loaded from toml
|
|
pp.ensure_state()
|
|
|
|
try:
|
|
yield table
|
|
finally:
|
|
if write_on_exit:
|
|
table.write_config()
|
|
|
|
|
|
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('.')
|
|
trans, updated_pps = load_pps_from_ledger(broker, name)
|
|
print(
|
|
f'Processing transactions into pps for {broker}:{acctid}\n'
|
|
f'{pformat(trans)}\n\n'
|
|
f'{pformat(updated_pps)}'
|
|
)
|