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Fix size quantization and closed position popping.. 

Turns out we actually had further pp entry bugs due to *not quantizing*
the size inside `.minimize_clears()` method calcs; fix that using
`Position.sys.mkt.quantize()` as is done in `Position.calc_size()`.

Fix `PpTable.write_config()` to drop from the TOML config any
`closed: dict[str, Position]` entries delivered by `.dump_active()`.

Add a more detailed doc string for our position type and a little todo
for the `.bep` B)
rekt_pps
Tyler Goodlet 2023-04-17 15:18:43 -04:00
parent bba1ee43ff
commit f106472bcb
1 changed files with 60 additions and 22 deletions
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82
piker/accounting/_pos.py
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@ -63,19 +63,42 @@ log = get_logger(__name__)
class Position(Struct):
'''
Basic pp (personal/piker position) model with attached clearing
transaction history.
An asset "position" model with attached clearing transaction history.
A financial "position" in `piker` terms is a summary of accounting
metrics computed from a transaction ledger; generally it describes
some acumulative "size" and "average price" from the summarized
underlying transaction set.
In piker we focus on the `.ppu` (price per unit) and the `.bep`
(break even price) including all transaction entries and exits since
the last "net-zero" size of the destination asset's holding.
This interface serves as an object API for computing and tracking
positions as well as supports serialization for storage in the local
file system (in TOML) and to interchange as a msg over IPC.
'''
symbol: Symbol | MktPair
@property
def mkt(self) -> MktPair:
return self.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".
# "price-per-unit price" above or below which pnl moves above and
# below zero for the entirety of the current "trade state". The ppu
# is only modified on "increases of" the absolute size of a position
# in one of a long/short "direction" (i.e. abs(.size_i) > 0 after
# the next transaction given .size was > 0 before that tx, and vice
# versa for -ve sized positions).
ppu: float
# TODO: break-even-price support!
# bep: float
# unique "backend system market id"
bs_mktid: str
@ -164,7 +187,8 @@ class Position(Struct):
inline_table = toml.TomlDecoder().get_empty_inline_table()
# serialize datetime to parsable `str`
inline_table['dt'] = str(data['dt'])
dtstr = inline_table['dt'] = str(data['dt'])
assert 'Datetime' not in dtstr
# insert optional clear fields in column order
for k in ['ppu', 'accum_size']:
@ -191,7 +215,9 @@ class Position(Struct):
'''
clears = list(self.clears.values())
self.first_clear_dt = min(list(entry['dt'] for entry in clears))
self.first_clear_dt = min(
list(entry['dt'] for entry in clears)
)
last_clear = clears[-1]
csize = self.calc_size()
@ -413,15 +439,21 @@ class Position(Struct):
asset using the clears/trade event table; zero if expired.
'''
size: float = 0
size: float = 0.
# time-expired pps (normally derivatives) are "closed"
# and have a zero size.
if self.expired():
return 0
return 0.
for tid, entry in self.clears.items():
size += entry['size']
# XXX: do we need it every step?
# no right since rounding is an LT?
# size = self.mkt.quantize(
# size + entry['size'],
# quantity_type='size',
# )
if self.split_ratio is not None:
size = round(size * self.split_ratio)
@ -450,7 +482,9 @@ class Position(Struct):
# scan for the last "net zero" position by iterating
# transactions until the next net-zero size, rinse, repeat.
for tid, clear in self.clears.items():
size += clear['size']
size = float(
self.mkt.quantize(size + clear['size'])
)
clears_since_zero.append((tid, clear))
if size == 0:
@ -504,8 +538,6 @@ class PpTable(Struct):
trans: dict[str, Transaction],
cost_scalar: float = 2,
force_mkt: MktPair | None = None,
) -> dict[str, Position]:
pps = self.pps
@ -523,15 +555,7 @@ class PpTable(Struct):
# template the mkt-info presuming a legacy market ticks
# if no info exists in the transactions..
mkt: MktPair | Symbol | None = force_mkt or t.sys
if not mkt:
mkt = MktPair.from_fqme(
fqme,
price_tick='0.01',
size_tick='0.0',
bs_mktid=bs_mktid,
)
mkt: MktPair = t.sys
pp = pps.get(bs_mktid)
if not pp:
# if no existing pp, allocate fresh one.
@ -633,14 +657,18 @@ class PpTable(Struct):
def to_toml(
self,
active: dict[str, Position] | None = None,
) -> dict[str, Any]:
active, closed = self.dump_active()
if active is None:
active, _ = self.dump_active()
# ONLY dict-serialize all active positions; those that are
# closed we don't store in the ``pps.toml``.
to_toml_dict = {}
pos: Position
for bs_mktid, pos in active.items():
# keep the minimal amount of clears that make up this
@ -650,6 +678,8 @@ class PpTable(Struct):
# serialize to pre-toml form
fqme, asdict = pos.to_pretoml()
# assert 'Datetime' not in asdict['dt']
log.info(f'Updating active pp: {fqme}')
# XXX: ugh, it's cuz we push the section under
@ -667,7 +697,9 @@ class PpTable(Struct):
# TODO: show diff output?
# https://stackoverflow.com/questions/12956957/print-diff-of-python-dictionaries
# active, closed_pp_objs = table.dump_active()
pp_entries = self.to_toml()
active, closed = self.dump_active()
pp_entries = self.to_toml(active=active)
if pp_entries:
log.info(
f'Updating positions in ``{self.conf_path}``:\n'
@ -688,6 +720,12 @@ class PpTable(Struct):
self.conf.update(pp_entries)
# drop any entries that are computed as net-zero
# we don't care about storing in the pps file.
if closed:
for fqme in closed:
self.conf.pop(fqme, None)
# if there are no active position entries according
# to the toml dump output above, then clear the config
# file of all entries.