piker/piker/accounting/_mktinfo.py

426 lines
11 KiB
Python

# 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/>.
'''
Market (pair) meta-info layer: sane addressing semantics and meta-data
for cross-provider marketplaces.
We intoduce the concept of,
- a FQMA: fully qualified market address,
- a sane schema for FQMAs including derivatives,
- a msg-serializeable description of markets for
easy sharing with other pikers B)
'''
from __future__ import annotations
from decimal import (
Decimal,
ROUND_HALF_EVEN,
)
from typing import (
Any,
Literal,
)
from ..data.types import Struct
_underlyings: list[str] = [
'stock',
'bond',
'crypto_currency',
'fiat_currency',
'commodity',
]
_derivs: list[str] = [
'swap',
'future',
'continuous_future',
'option',
'futures_option',
]
# NOTE: a tag for other subsystems to try
# and do default settings for certain things:
# - allocator does unit vs. dolla size limiting.
AssetTypeName: Literal[
_underlyings
+
_derivs
]
# egs. stock, futer, option, bond etc.
def float_digits(
value: float,
) -> int:
'''
Return the number of precision digits read from a decimal or float
value.
'''
if value == 0:
return 0
return int(
-Decimal(str(value)).as_tuple().exponent
)
def digits_to_dec(
ndigits: int,
) -> Decimal:
'''
Return the minimum float value for an input integer value.
eg. 3 -> 0.001
'''
if ndigits == 0:
return Decimal('0')
return Decimal('0.' + '0'*(ndigits-1) + '1')
class Asset(Struct, frozen=True):
'''
Container type describing any transactable asset's technology.
'''
name: str
atype: AssetTypeName
# minimum transaction size / precision.
# eg. for buttcoin this is a "satoshi".
tx_tick: Decimal
# NOTE: additional info optionally packed in by the backend, but
# should not be explicitly required in our generic API.
info: dict = {} # make it frozen?
def __str__(self) -> str:
return self.name
def quantize(
self,
size: float,
) -> Decimal:
'''
Truncate input ``size: float`` using ``Decimal``
quantized form of the digit precision defined
by ``self.lot_tick_size``.
'''
digits = float_digits(self.tx_tick)
return Decimal(size).quantize(
Decimal(f'1.{"0".ljust(digits, "0")}'),
rounding=ROUND_HALF_EVEN
)
class MktPair(Struct, frozen=True):
'''
Market description for a pair of assets which are tradeable:
a market which enables transactions of the form,
buy: source asset -> destination asset
sell: destination asset -> source asset
The main intention of this type is for a cross-asset, venue, broker
normalized descriptive data type from which all market-auctions can
be mapped, simply.
'''
# "source asset" (name) used to buy *from*
# (or used to sell *to*)
src: str | Asset
# "destination asset" (name) used to buy *to*
# (or used to sell *from*)
dst: str | Asset
@property
def key(self) -> str:
'''
The "endpoint key" for this market.
In most other tina platforms this is referred to as the
"symbol".
'''
return f'{self.src}{self.dst}'
# the tick size is the number describing the smallest step in value
# available in this market between the source and destination
# assets.
# https://en.wikipedia.org/wiki/Tick_size
# https://en.wikipedia.org/wiki/Commodity_tick
# https://en.wikipedia.org/wiki/Percentage_in_point
price_tick: Decimal # minimum price increment value increment
size_tick: Decimal # minimum size (aka vlm) increment value increment
# @property
# def size_tick_digits(self) -> int:
# return float_digits(self.size_tick)
broker: str | None = None # the middle man giving access
venue: str | None = None # market venue provider name
expiry: str | None = None # for derivs, expiry datetime parseable str
# destination asset's financial type/classification name
# NOTE: this is required for the order size allocator system,
# since we use different default settings based on the type
# of the destination asset, eg. futes use a units limits vs.
# equities a $limit.
dst_type: AssetTypeName | None = None
# source asset's financial type/classification name
# TODO: is a src type required for trading?
# there's no reason to need any more then the one-way alloc-limiter
# config right?
# src_type: AssetTypeName
# for derivs, info describing contract, egs.
# strike price, call or put, swap type, exercise model, etc.
contract_info: str | None = None
@classmethod
def from_msg(
self,
msg: dict[str, Any],
) -> MktPair:
'''
Constructor for a received msg-dict normally received over IPC.
'''
...
# fqa, fqma, .. etc. see issue:
# https://github.com/pikers/piker/issues/467
@property
def fqme(self) -> str:
'''
Return the fully qualified market endpoint-address for the
pair of transacting assets.
Yes, you can pronounce it colloquially as "f#$%-me"..
'''
# fqsn = fqme
def quantize(
self,
size: float,
quantity_type: Literal['price', 'size'] = 'size',
) -> Decimal:
'''
Truncate input ``size: float`` using ``Decimal``
and ``.size_tick``'s # of digits.
'''
match quantity_type:
case 'price':
digits = float_digits(self.price_tick)
case 'size':
digits = float_digits(self.size_tick)
return Decimal(size).quantize(
Decimal(f'1.{"0".ljust(digits, "0")}'),
rounding=ROUND_HALF_EVEN
)
# TODO: remove this?
@property
def type_key(self) -> str:
return list(self.broker_info.values())[0]['asset_type']
# @classmethod
# def from_fqme(
# cls,
# fqme: str,
# **kwargs,
# ) -> MktPair:
# broker, key, suffix = unpack_fqme(fqme)
def mk_fqsn(
provider: str,
symbol: str,
) -> str:
'''
Generate a "fully qualified symbol name" which is
a reverse-hierarchical cross broker/provider symbol
'''
return '.'.join([symbol, provider]).lower()
def unpack_fqsn(fqsn: str) -> tuple[str, str, str]:
'''
Unpack a fully-qualified-symbol-name to ``tuple``.
'''
venue = ''
suffix = ''
# TODO: probably reverse the order of all this XD
tokens = fqsn.split('.')
if len(tokens) < 3:
# probably crypto
symbol, broker = tokens
return (
broker,
symbol,
'',
)
elif len(tokens) > 3:
symbol, venue, suffix, broker = tokens
else:
symbol, venue, broker = tokens
suffix = ''
# head, _, broker = fqsn.rpartition('.')
# symbol, _, suffix = head.rpartition('.')
return (
broker,
'.'.join([symbol, venue]),
suffix,
)
unpack_fqme = unpack_fqsn
# TODO: rework the below `Symbol` (which was originally inspired and
# derived from stuff in quantdom) into a simpler, ipc msg ready, market
# endpoint meta-data container type as per the drafted interace above.
class Symbol(Struct):
'''
I guess this is some kinda container thing for dealing with
all the different meta-data formats from brokers?
'''
key: str
tick_size: float = 0.01
lot_tick_size: float = 0.0 # "volume" precision as min step value
suffix: str = ''
broker_info: dict[str, dict[str, Any]] = {}
@classmethod
def from_fqsn(
cls,
fqsn: str,
info: dict[str, Any],
) -> Symbol:
broker, key, suffix = unpack_fqsn(fqsn)
tick_size = info.get('price_tick_size', 0.01)
lot_size = info.get('lot_tick_size', 0.0)
return Symbol(
key=key,
tick_size=tick_size,
lot_tick_size=lot_size,
# tick_size_digits=float_digits(tick_size),
# lot_size_digits=float_digits(lot_size),
suffix=suffix,
broker_info={broker: info},
)
# compat name mapping
from_fqme = from_fqsn
@property
def type_key(self) -> str:
return list(self.broker_info.values())[0]['asset_type']
@property
def brokers(self) -> list[str]:
return list(self.broker_info.keys())
@property
def tick_size_digits(self) -> int:
return float_digits(self.lot_tick_size)
@property
def lot_size_digits(self) -> int:
return float_digits(self.lot_tick_size)
@property
def broker(self) -> str:
return list(self.broker_info.keys())[0]
@property
def fqsn(self) -> str:
'''
fqsn = "fully qualified symbol name"
Basically the idea here is for all client-ish code (aka programs/actors
that ask the provider agnostic layers in the stack for data) should be
able to tell which backend / venue / derivative each data feed/flow is
from by an explicit string key of the current form:
<instrumentname>.<venue>.<suffixwithmetadata>.<brokerbackendname>
TODO: I have thoughts that we should actually change this to be
more like an "attr lookup" (like how the web should have done
urls, but marketting peeps ruined it etc. etc.):
<broker>.<venue>.<instrumentname>.<suffixwithmetadata>
'''
broker = self.broker
key = self.key
if self.suffix:
tokens = (key, self.suffix, broker)
else:
tokens = (key, broker)
return '.'.join(tokens).lower()
fqme = fqsn
def quantize(
self,
size: float,
) -> Decimal:
'''
Truncate input ``size: float`` using ``Decimal``
quantized form of the digit precision defined
by ``self.lot_tick_size``.
'''
digits = float_digits(self.lot_tick_size)
return Decimal(size).quantize(
Decimal(f'1.{"0".ljust(digits, "0")}'),
rounding=ROUND_HALF_EVEN
)