Simplify `Symbol` extend `MktPair`, add `Asset`
Drop everything we can in terms of methods and attrs from `Symbol`: - kill `.tokens()`, `.front_feed()`, `.tokens()`, `.nearest_tick()`, `.front_fqsn()`, instead moving logic from these methods into dependents (and obviously removing any usage from rest of code base, coming in follow up commits). - rename `.quantize_size()` -> `.quantize()`. - re-implement `.brokers`, `.lot_size_digits`, `.tick_size_digits` as `@property` methods; for the latter two, allows us to minimize to only accepting min tick decimal values on alternative constructor class methods and to drop the equivalent instance vars. - map `_fqsn` related variable names to new and preferred `_fqme`. We also juggle around some utility functions, moving limited precision related `decimal.Decimal` routines to the top of module and soon-to-be legacy `fqsn` related routines to the bottom. `MktPair` draft type extensions: - drop requirements for `src_type`, and offer the optional `.dst_type` field as either a `str` or (new `typing.Literal`) `AssetTypeName`. - define an equivalent `.quantize()` as (re)defined in `Symbol` but with `quantity_type: str` field which specifies whether to use the price or the size precision. - add a lot more docs, a `.key` property for the "symbol" name, draft property for a `.fqme: str` - allow `.src` and `.dst` to be of type `str | Asset` Add a new `Asset` to capture "things which can be used in markets and/or transactions" XD - defines a `.name`, `.atype: AssetTypeName` a financial category tag, `tx_tick: Decimal` the precision limit for transactions and of course a `.quantime()` method for doing accounting arithmetic on a given tech stack. - define the `atype: AssetTypeName` type as a finite set of `str`s expected to be used in various ways for default settings in other parts of the data and order control layers..pre_overruns_ctxcancelled
Tyler Goodlet
parent
c0a3c6dff7
commit
e9cedc6613
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@ -34,34 +34,169 @@ from decimal import (
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)
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from typing import (
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Any,
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Literal,
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)
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from ..data.types import Struct
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_underlyings: list[str] = [
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'stock',
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'bond',
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'crypto_currency',
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'fiat_currency',
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'commodity',
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]
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_derivs: list[str] = [
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'swap',
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'future',
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'continuous_future',
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'option',
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'futures_option',
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]
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# NOTE: a tag for other subsystems to try
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# and do default settings for certain things:
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# - allocator does unit vs. dolla size limiting.
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AssetTypeName: Literal[
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_underlyings
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+
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_derivs
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]
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# egs. stock, futer, option, bond etc.
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def float_digits(
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value: float,
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) -> int:
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'''
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Return the number of precision digits read from a decimal or float
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value.
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'''
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if value == 0:
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return 0
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return int(
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-Decimal(str(value)).as_tuple().exponent
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)
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def digits_to_dec(
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ndigits: int,
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) -> Decimal:
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'''
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Return the minimum float value for an input integer value.
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eg. 3 -> 0.001
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'''
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if ndigits == 0:
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return Decimal('0')
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return Decimal('0.' + '0'*(ndigits-1) + '1')
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class Asset(Struct, frozen=True):
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'''
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Container type describing any transactable asset's technology.
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'''
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name: str
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atype: AssetTypeName
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# minimum transaction size / precision.
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# eg. for buttcoin this is a "satoshi".
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tx_tick: Decimal
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# NOTE: additional info optionally packed in by the backend, but
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# should not be explicitly required in our generic API.
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info: dict = {} # make it frozen?
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def __str__(self) -> str:
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return self.name
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def quantize(
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self,
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size: float,
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) -> Decimal:
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'''
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Truncate input ``size: float`` using ``Decimal``
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quantized form of the digit precision defined
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by ``self.lot_tick_size``.
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'''
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digits = float_digits(self.tx_tick)
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return Decimal(size).quantize(
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Decimal(f'1.{"0".ljust(digits, "0")}'),
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rounding=ROUND_HALF_EVEN
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)
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class MktPair(Struct, frozen=True):
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'''
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Market description for a pair of assets which are tradeable:
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a market which enables transactions of the form,
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buy: source asset -> destination asset
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sell: destination asset -> source asset
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src: str # source asset name being used to buy
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src_type: str # source asset's financial type/classification name
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# ^ specifies a "class" of financial instrument
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# egs. stock, futer, option, bond etc.
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The main intention of this type is for a cross-asset, venue, broker
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normalized descriptive data type from which all market-auctions can
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be mapped, simply.
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dst: str # destination asset name being bought
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dst_type: str # destination asset's financial type/classification name
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'''
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# "source asset" (name) used to buy *from*
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# (or used to sell *to*)
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src: str | Asset
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# "destination asset" (name) used to buy *to*
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# (or used to sell *from*)
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dst: str | Asset
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price_tick: float # minimum price increment value increment
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price_tick_digits: int # required decimal digits for above
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size_tick: float # minimum size (aka vlm) increment value increment
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# size_tick_digits: int # required decimal digits for above
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@property
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def size_tick_digits(self) -> int:
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return self.size_tick
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def key(self) -> str:
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'''
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The "endpoint key" for this market.
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In most other tina platforms this is referred to as the
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"symbol".
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'''
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return f'{self.src}{self.dst}'
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# the tick size is the number describing the smallest step in value
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# available in this market between the source and destination
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# assets.
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# https://en.wikipedia.org/wiki/Tick_size
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# https://en.wikipedia.org/wiki/Commodity_tick
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# https://en.wikipedia.org/wiki/Percentage_in_point
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price_tick: Decimal # minimum price increment value increment
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size_tick: Decimal # minimum size (aka vlm) increment value increment
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# @property
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# def size_tick_digits(self) -> int:
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# return float_digits(self.size_tick)
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broker: str | None = None # the middle man giving access
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venue: str | None = None # market venue provider name
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expiry: str | None = None # for derivs, expiry datetime parseable str
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# destination asset's financial type/classification name
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# NOTE: this is required for the order size allocator system,
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# since we use different default settings based on the type
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# of the destination asset, eg. futes use a units limits vs.
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# equities a $limit.
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dst_type: AssetTypeName | None = None
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# source asset's financial type/classification name
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# TODO: is a src type required for trading?
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# there's no reason to need any more then the one-way alloc-limiter
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# config right?
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# src_type: AssetTypeName
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# for derivs, info describing contract, egs.
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# strike price, call or put, swap type, exercise model, etc.
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contract_info: str | None = None
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@ -81,13 +216,53 @@ class MktPair(Struct, frozen=True):
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# fqa, fqma, .. etc. see issue:
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# https://github.com/pikers/piker/issues/467
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@property
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def fqsn(self) -> str:
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def fqme(self) -> str:
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'''
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Return the fully qualified market (endpoint) name for the
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Return the fully qualified market endpoint-address for the
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pair of transacting assets.
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Yes, you can pronounce it colloquially as "f#$%-me"..
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'''
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...
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# fqsn = fqme
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def quantize(
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self,
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size: float,
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quantity_type: Literal['price', 'size'] = 'size',
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) -> Decimal:
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'''
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Truncate input ``size: float`` using ``Decimal``
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and ``.size_tick``'s # of digits.
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'''
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match quantity_type:
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case 'price':
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digits = float_digits(self.price_tick)
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case 'size':
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digits = float_digits(self.size_tick)
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return Decimal(size).quantize(
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Decimal(f'1.{"0".ljust(digits, "0")}'),
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rounding=ROUND_HALF_EVEN
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)
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# TODO: remove this?
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@property
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def type_key(self) -> str:
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return list(self.broker_info.values())[0]['asset_type']
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# @classmethod
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# def from_fqme(
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# cls,
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# fqme: str,
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# **kwargs,
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# ) -> MktPair:
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# broker, key, suffix = unpack_fqme(fqme)
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def mk_fqsn(
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@ -103,34 +278,6 @@ def mk_fqsn(
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return '.'.join([symbol, provider]).lower()
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def float_digits(
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value: float,
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) -> int:
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'''
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Return the number of precision digits read from a float value.
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'''
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if value == 0:
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return 0
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return int(-Decimal(str(value)).as_tuple().exponent)
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def digits_to_dec(
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ndigits: int,
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) -> Decimal:
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'''
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Return the minimum float value for an input integer value.
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eg. 3 -> 0.001
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'''
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if ndigits == 0:
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return Decimal('0')
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return Decimal('0.' + '0'*(ndigits-1) + '1')
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def unpack_fqsn(fqsn: str) -> tuple[str, str, str]:
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'''
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Unpack a fully-qualified-symbol-name to ``tuple``.
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@ -164,6 +311,10 @@ def unpack_fqsn(fqsn: str) -> tuple[str, str, str]:
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suffix,
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)
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unpack_fqme = unpack_fqsn
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# TODO: rework the below `Symbol` (which was originally inspired and
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# derived from stuff in quantdom) into a simpler, ipc msg ready, market
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# endpoint meta-data container type as per the drafted interace above.
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@ -176,37 +327,9 @@ class Symbol(Struct):
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key: str
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tick_size: float = 0.01
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lot_tick_size: float = 0.0 # "volume" precision as min step value
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tick_size_digits: int = 2
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lot_size_digits: int = 0
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suffix: str = ''
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broker_info: dict[str, dict[str, Any]] = {}
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@classmethod
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def from_broker_info(
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cls,
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broker: str,
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symbol: str,
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info: dict[str, Any],
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suffix: str = '',
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) -> Symbol:
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tick_size = info.get('price_tick_size', 0.01)
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lot_size = info.get('lot_tick_size', 0.0)
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return Symbol(
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key=symbol,
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tick_size=tick_size,
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lot_tick_size=lot_size,
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tick_size_digits=float_digits(tick_size),
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lot_size_digits=float_digits(lot_size),
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suffix=suffix,
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broker_info={broker: info},
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)
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@classmethod
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def from_fqsn(
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cls,
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@ -215,13 +338,25 @@ class Symbol(Struct):
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) -> Symbol:
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broker, key, suffix = unpack_fqsn(fqsn)
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return cls.from_broker_info(
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broker,
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key,
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info=info,
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tick_size = info.get('price_tick_size', 0.01)
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lot_size = info.get('lot_tick_size', 0.0)
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return Symbol(
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key=key,
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tick_size=tick_size,
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lot_tick_size=lot_size,
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# tick_size_digits=float_digits(tick_size),
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# lot_size_digits=float_digits(lot_size),
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suffix=suffix,
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broker_info={broker: info},
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)
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# compat name mapping
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from_fqme = from_fqsn
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@property
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def type_key(self) -> str:
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return list(self.broker_info.values())[0]['asset_type']
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@ -230,38 +365,20 @@ class Symbol(Struct):
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def brokers(self) -> list[str]:
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return list(self.broker_info.keys())
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def nearest_tick(self, value: float) -> float:
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'''
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Return the nearest tick value based on mininum increment.
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@property
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def tick_size_digits(self) -> int:
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return float_digits(self.lot_tick_size)
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'''
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mult = 1 / self.tick_size
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return round(value * mult) / mult
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@property
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def lot_size_digits(self) -> int:
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return float_digits(self.lot_tick_size)
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def front_feed(self) -> tuple[str, str]:
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'''
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Return the "current" feed key for this symbol.
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(i.e. the broker + symbol key in a tuple).
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'''
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return (
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list(self.broker_info.keys())[0],
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self.key,
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)
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def tokens(self) -> tuple[str]:
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broker, key = self.front_feed()
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if self.suffix:
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return (key, self.suffix, broker)
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else:
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return (key, broker)
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@property
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def broker(self) -> str:
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return list(self.broker_info.keys())[0]
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@property
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def fqsn(self) -> str:
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return '.'.join(self.tokens()).lower()
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def front_fqsn(self) -> str:
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'''
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fqsn = "fully qualified symbol name"
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@ -279,24 +396,30 @@ class Symbol(Struct):
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<broker>.<venue>.<instrumentname>.<suffixwithmetadata>
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'''
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tokens = self.tokens()
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fqsn = '.'.join(map(str.lower, tokens))
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return fqsn
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broker = self.broker
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key = self.key
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if self.suffix:
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tokens = (key, self.suffix, broker)
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else:
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tokens = (key, broker)
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def quantize_size(
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return '.'.join(tokens).lower()
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fqme = fqsn
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def quantize(
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self,
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size: float,
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) -> Decimal:
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'''
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Truncate input ``size: float`` using ``Decimal``
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and ``.lot_size_digits``.
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quantized form of the digit precision defined
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by ``self.lot_tick_size``.
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'''
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digits = self.lot_size_digits
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digits = float_digits(self.lot_tick_size)
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return Decimal(size).quantize(
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Decimal(f'1.{"0".ljust(digits, "0")}'),
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rounding=ROUND_HALF_EVEN
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)
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Loading…
Reference in New Issue