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`kraken`: parse and load info `Transaction.sym: Symbol` 

Also includes a retyping of `Client._pair: dict[str, Pair]` to look up
pair structs and map all alt-key-name-sets to each for easy precision
info lookup to set the `.sym` field for each transaction including for
on-chain transfers which kraken provides as an "asset decimals" field,
presumably pulled from the particular block-token's limitation info.
backward_compat_trans_with_symbolinfo
Tyler Goodlet 2023-03-02 19:25:43 -05:00
parent 69b85aa7e5
commit b4a1cc8f22
3 changed files with 129 additions and 77 deletions
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131
piker/brokers/kraken/api.py
View File

@ -40,6 +40,8 @@ import base64
import trio
from piker import config
from piker.data.types import Struct
from piker.data._source import Symbol
from piker.brokers._util import (
resproc,
SymbolNotFound,
@ -113,11 +115,53 @@ class InvalidKey(ValueError):
'''
# https://www.kraken.com/features/api#get-tradable-pairs
class Pair(Struct):
altname: str # alternate pair name
wsname: str # WebSocket pair name (if available)
aclass_base: str # asset class of base component
base: str # asset id of base component
aclass_quote: str # asset class of quote component
quote: str # asset id of quote component
lot: str # volume lot size
cost_decimals: int
costmin: float
pair_decimals: int # scaling decimal places for pair
lot_decimals: int # scaling decimal places for volume
# amount to multiply lot volume by to get currency volume
lot_multiplier: float
# array of leverage amounts available when buying
leverage_buy: list[int]
# array of leverage amounts available when selling
leverage_sell: list[int]
# fee schedule array in [volume, percent fee] tuples
fees: list[tuple[int, float]]
# maker fee schedule array in [volume, percent fee] tuples (if on
# maker/taker)
fees_maker: list[tuple[int, float]]
fee_volume_currency: str # volume discount currency
margin_call: str # margin call level
margin_stop: str # stop-out/liquidation margin level
ordermin: float # minimum order volume for pair
tick_size: float # min price step size
status: str
short_position_limit: float = 0
long_position_limit: float = float('inf')
class Client:
# global symbol normalization table
_ntable: dict[str, str] = {}
_atable: bidict[str, str] = bidict()
_pairs: dict[str, Pair] = {}
def __init__(
self,
@ -133,13 +177,12 @@ class Client:
'krakenex/2.1.0 (+https://github.com/veox/python3-krakenex)'
})
self.conf: dict[str, str] = config
self._pairs: list[str] = []
self._name = name
self._api_key = api_key
self._secret = secret
@property
def pairs(self) -> dict[str, Any]:
def pairs(self) -> dict[str, Pair]:
if self._pairs is None:
raise RuntimeError(
"Make sure to run `cache_symbols()` on startup!"
@ -295,15 +338,28 @@ class Client:
trans: dict[str, Transaction] = {}
for entry in xfers:
# look up the normalized name
asset = self._atable[entry['asset']].lower()
# look up the normalized name and asset info
asset_key = entry['asset']
asset_info = self.assets[asset_key]
asset = self._atable[asset_key].lower()
# XXX: this is in the asset units (likely) so it isn't
# quite the same as a commisions cost necessarily..)
cost = float(entry['fee'])
fqsn = asset + '.kraken'
pairinfo = Symbol.from_fqsn(
fqsn,
info={
'asset_type': 'crypto',
'lot_tick_size': asset_info['decimals'],
},
)
tran = Transaction(
fqsn=asset + '.kraken',
fqsn=fqsn,
sym=pairinfo,
tid=entry['txid'],
dt=pendulum.from_timestamp(entry['time']),
bsuid=f'{asset}{src_asset}',
@ -317,7 +373,7 @@ class Client:
price='NaN',
# XXX: see note above
cost=0,
cost=cost,
)
trans[tran.tid] = tran
@ -372,7 +428,7 @@ class Client:
self,
pair: Optional[str] = None,
) -> dict[str, dict[str, str]]:
) -> dict[str, Pair] | Pair:
if pair is not None:
pairs = {'pair': pair}
@ -389,19 +445,36 @@ class Client:
if pair is not None:
_, data = next(iter(pairs.items()))
return data
return Pair(**data)
else:
return pairs
return {key: Pair(**data) for key, data in pairs.items()}
async def cache_symbols(
self,
) -> dict:
async def cache_symbols(self) -> dict:
'''
Load all market pair info build and cache it for downstream use.
A ``._ntable: dict[str, str]`` is available for mapping the
websocket pair name-keys and their http endpoint API (smh)
equivalents to the "alternative name" which is generally the one
we actually want to use XD
'''
if not self._pairs:
self._pairs = await self.symbol_info()
self._pairs.update(await self.symbol_info())
ntable = {}
for restapikey, info in self._pairs.items():
ntable[restapikey] = ntable[info['wsname']] = info['altname']
# table of all ws and rest keys to their alt-name values.
ntable: dict[str, str] = {}
for rest_key in list(self._pairs.keys()):
pair: Pair = self._pairs[rest_key]
altname = pair.altname
wsname = pair.wsname
ntable[rest_key] = ntable[wsname] = altname
# register the pair under all monikers, a giant flat
# surjection of all possible names to each info obj.
self._pairs[altname] = self._pairs[wsname] = pair
self._ntable.update(ntable)
@ -411,26 +484,34 @@ class Client:
self,
pattern: str,
limit: int = None,
) -> dict[str, Any]:
if self._pairs is not None:
data = self._pairs
else:
data = await self.symbol_info()
'''
Search for a symbol by "alt name"..
It is expected that the ``Client._pairs`` table
gets populated before conducting the underlying fuzzy-search
over the pair-key set.
'''
if not len(self._pairs):
await self.cache_symbols()
assert self._pairs, '`Client.cache_symbols()` was never called!?'
matches = fuzzy.extractBests(
pattern,
data,
self._pairs,
score_cutoff=50,
)
# repack in dict form
return {item[0]['altname']: item[0] for item in matches}
return {item[0].altname: item[0] for item in matches}
async def bars(
self,
symbol: str = 'XBTUSD',
# UTC 2017-07-02 12:53:20
since: Optional[Union[int, datetime]] = None,
since: Union[int, datetime] | None = None,
count: int = 720, # <- max allowed per query
as_np: bool = True,
@ -506,7 +587,7 @@ class Client:
def normalize_symbol(
cls,
ticker: str
) -> str:
) -> tuple[str, Pair]:
'''
Normalize symbol names to to a 3x3 pair from the global
definition map which we build out from the data retreived from
@ -514,7 +595,7 @@ class Client:
'''
ticker = cls._ntable[ticker]
return ticker.lower()
return ticker.lower(), cls._pairs[ticker]
@acm

16
piker/brokers/kraken/broker.py
View File

@ -48,6 +48,7 @@ from piker.pp import (
open_trade_ledger,
open_pps,
)
from piker.data._source import Symbol
from piker.clearing._messages import (
Order,
Status,
@ -1196,10 +1197,21 @@ def norm_trade_records(
}[record['type']]
# we normalize to kraken's `altname` always..
bsuid = norm_sym = Client.normalize_symbol(record['pair'])
bsuid, pair_info = Client.normalize_symbol(record['pair'])
fqsn = f'{bsuid}.kraken'
mktpair = Symbol.from_fqsn(
fqsn,
info={
'lot_size_digits': pair_info.lot_decimals,
'tick_size_digits': pair_info.pair_decimals,
'asset_type': 'crypto',
},
)
records[tid] = Transaction(
fqsn=f'{norm_sym}.kraken',
fqsn=fqsn,
sym=mktpair,
tid=tid,
size=size,
price=float(record['price']),

59
piker/brokers/kraken/feed.py
View File

@ -42,56 +42,15 @@ from piker.brokers._util import (
DataUnavailable,
)
from piker.log import get_console_log
from piker.data import ShmArray
from piker.data.types import Struct
from piker.data._web_bs import open_autorecon_ws, NoBsWs
from . import log
from .api import (
Client,
Pair,
)
# https://www.kraken.com/features/api#get-tradable-pairs
class Pair(Struct):
altname: str # alternate pair name
wsname: str # WebSocket pair name (if available)
aclass_base: str # asset class of base component
base: str # asset id of base component
aclass_quote: str # asset class of quote component
quote: str # asset id of quote component
lot: str # volume lot size
cost_decimals: int
costmin: float
pair_decimals: int # scaling decimal places for pair
lot_decimals: int # scaling decimal places for volume
# amount to multiply lot volume by to get currency volume
lot_multiplier: float
# array of leverage amounts available when buying
leverage_buy: list[int]
# array of leverage amounts available when selling
leverage_sell: list[int]
# fee schedule array in [volume, percent fee] tuples
fees: list[tuple[int, float]]
# maker fee schedule array in [volume, percent fee] tuples (if on
# maker/taker)
fees_maker: list[tuple[int, float]]
fee_volume_currency: str # volume discount currency
margin_call: str # margin call level
margin_stop: str # stop-out/liquidation margin level
ordermin: float # minimum order volume for pair
tick_size: float # min price step size
status: str
short_position_limit: float
long_position_limit: float
class OHLC(Struct):
'''
Description of the flattened OHLC quote format.
@ -336,14 +295,14 @@ async def stream_quotes(
# transform to upper since piker style is always lower
sym = sym.upper()
sym_info = await client.symbol_info(sym)
try:
si = Pair(**sym_info) # validation
except TypeError:
fields_diff = set(sym_info) - set(Pair.__struct_fields__)
raise TypeError(
f'Missing msg fields {fields_diff}'
)
si: Pair = await client.symbol_info(sym)
# try:
# si = Pair(**sym_info) # validation
# except TypeError:
# fields_diff = set(sym_info) - set(Pair.__struct_fields__)
# raise TypeError(
# f'Missing msg fields {fields_diff}'
# )
syminfo = si.to_dict()
syminfo['price_tick_size'] = 1. / 10**si.pair_decimals
syminfo['lot_tick_size'] = 1. / 10**si.lot_decimals