piker/piker/brokers/kraken/api.py

700 lines
19 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/>.
'''
Kraken web API wrapping.
'''
from contextlib import asynccontextmanager as acm
from datetime import datetime
from decimal import Decimal
import itertools
from typing import (
Any,
Union,
)
import time
from bidict import bidict
import pendulum
import asks
from fuzzywuzzy import process as fuzzy
import numpy as np
import urllib.parse
import hashlib
import hmac
import base64
import trio
from piker import config
from piker.data.types import Struct
from piker.accounting._mktinfo import (
Asset,
MktPair,
digits_to_dec,
)
from piker.brokers._util import (
resproc,
SymbolNotFound,
BrokerError,
DataThrottle,
)
from piker.accounting import Transaction
from . import log
# <uri>/<version>/
_url = 'https://api.kraken.com/0'
# Broker specific ohlc schema which includes a vwap field
_ohlc_dtype = [
('index', int),
('time', int),
('open', float),
('high', float),
('low', float),
('close', float),
('volume', float),
('count', int),
('bar_wap', float),
]
# UI components allow this to be declared such that additional
# (historical) fields can be exposed.
ohlc_dtype = np.dtype(_ohlc_dtype)
_show_wap_in_history = True
_symbol_info_translation: dict[str, str] = {
'tick_decimals': 'pair_decimals',
}
def get_config() -> dict[str, Any]:
conf, path = config.load()
section = conf.get('kraken')
if section is None:
log.warning(f'No config section found for kraken in {path}')
return {}
return section
def get_kraken_signature(
urlpath: str,
data: dict[str, Any],
secret: str
) -> str:
postdata = urllib.parse.urlencode(data)
encoded = (str(data['nonce']) + postdata).encode()
message = urlpath.encode() + hashlib.sha256(encoded).digest()
mac = hmac.new(base64.b64decode(secret), message, hashlib.sha512)
sigdigest = base64.b64encode(mac.digest())
return sigdigest.decode()
class InvalidKey(ValueError):
'''
EAPI:Invalid key
This error is returned when the API key used for the call is
either expired or disabled, please review the API key in your
Settings -> API tab of account management or generate a new one
and update your application.
'''
# 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')
@property
def price_tick(self) -> Decimal:
return digits_to_dec(self.pair_decimals)
@property
def size_tick(self) -> Decimal:
return digits_to_dec(self.lot_decimals)
class Client:
# symbol mapping from all names to the altname
_ntable: dict[str, str] = {}
# 2-way map of symbol names to their "alt names" ffs XD
_altnames: bidict[str, str] = bidict()
_pairs: dict[str, Pair] = {}
def __init__(
self,
config: dict[str, str],
name: str = '',
api_key: str = '',
secret: str = ''
) -> None:
self._sesh = asks.Session(connections=4)
self._sesh.base_location = _url
self._sesh.headers.update({
'User-Agent':
'krakenex/2.1.0 (+https://github.com/veox/python3-krakenex)'
})
self._name = name
self._api_key = api_key
self._secret = secret
self.conf: dict[str, str] = config
self.assets: dict[str, Asset] = {}
@property
def pairs(self) -> dict[str, Pair]:
if self._pairs is None:
raise RuntimeError(
"Make sure to run `cache_symbols()` on startup!"
)
# retreive and cache all symbols
return self._pairs
async def _public(
self,
method: str,
data: dict,
) -> dict[str, Any]:
resp = await self._sesh.post(
path=f'/public/{method}',
json=data,
timeout=float('inf')
)
return resproc(resp, log)
async def _private(
self,
method: str,
data: dict,
uri_path: str
) -> dict[str, Any]:
headers = {
'Content-Type':
'application/x-www-form-urlencoded',
'API-Key':
self._api_key,
'API-Sign':
get_kraken_signature(uri_path, data, self._secret)
}
resp = await self._sesh.post(
path=f'/private/{method}',
data=data,
headers=headers,
timeout=float('inf')
)
return resproc(resp, log)
async def endpoint(
self,
method: str,
data: dict[str, Any]
) -> dict[str, Any]:
uri_path = f'/0/private/{method}'
data['nonce'] = str(int(1000*time.time()))
return await self._private(method, data, uri_path)
async def get_balances(
self,
) -> dict[str, float]:
'''
Return the set of asset balances for this account
by symbol.
'''
resp = await self.endpoint(
'Balance',
{},
)
by_bsmktid = resp['result']
# TODO: we need to pull out the "asset" decimals
# data and return a `decimal.Decimal` instead here!
# using the underlying Asset
return {
self._altnames[sym].lower(): float(bal)
for sym, bal in by_bsmktid.items()
}
async def get_assets(self) -> dict[str, dict]:
'''
Get all assets available for trading and xfer.
https://docs.kraken.com/rest/#tag/Market-Data/operation/getAssetInfo
return msg:
"asset1": {
"aclass": "string",
"altname": "string",
"decimals": 0,
"display_decimals": 0,
"collateral_value": 0,
"status": "string"
}
'''
resp = await self._public('Assets', {})
return resp['result']
async def cache_assets(self) -> None:
'''
Load and cache all asset infos and pack into
our native ``Asset`` struct.
'''
assets = await self.get_assets()
for bs_mktid, info in assets.items():
aname = self._altnames[bs_mktid] = info['altname']
aclass = info['aclass']
self.assets[bs_mktid] = Asset(
name=aname.lower(),
atype=f'crypto_{aclass}',
tx_tick=digits_to_dec(info['decimals']),
info=info,
)
async def get_trades(
self,
fetch_limit: int | None = None,
) -> dict[str, Any]:
'''
Get the trades (aka cleared orders) history from the rest endpoint:
https://docs.kraken.com/rest/#operation/getTradeHistory
'''
ofs = 0
trades_by_id: dict[str, Any] = {}
for i in itertools.count():
if (
fetch_limit
and i >= fetch_limit
):
break
# increment 'ofs' pagination offset
ofs = i*50
resp = await self.endpoint(
'TradesHistory',
{'ofs': ofs},
)
by_id = resp['result']['trades']
trades_by_id.update(by_id)
# can get up to 50 results per query, see:
# https://docs.kraken.com/rest/#tag/User-Data/operation/getTradeHistory
if (
len(by_id) < 50
):
err = resp.get('error')
if err:
raise BrokerError(err)
# we know we received the max amount of
# trade results so there may be more history.
# catch the end of the trades
count = resp['result']['count']
break
# santity check on update
assert count == len(trades_by_id.values())
return trades_by_id
async def get_xfers(
self,
asset: str,
src_asset: str = '',
) -> dict[str, Transaction]:
'''
Get asset balance transfer transactions.
Currently only withdrawals are supported.
'''
resp = await self.endpoint(
'WithdrawStatus',
{'asset': asset},
)
try:
xfers: list[dict] = resp['result']
except KeyError:
log.exception(f'Kraken suxxx: {resp}')
return []
# eg. resp schema:
# 'result': [{'method': 'Bitcoin', 'aclass': 'currency', 'asset':
# 'XXBT', 'refid': 'AGBJRMB-JHD2M4-NDI3NR', 'txid':
# 'b95d66d3bb6fd76cbccb93f7639f99a505cb20752c62ea0acc093a0e46547c44',
# 'info': 'bc1qc8enqjekwppmw3g80p56z5ns7ze3wraqk5rl9z',
# 'amount': '0.00300726', 'fee': '0.00001000', 'time':
# 1658347714, 'status': 'Success'}]}
trans: dict[str, Transaction] = {}
for entry in xfers:
# look up the normalized name and asset info
asset_key = entry['asset']
asset = self.assets[asset_key]
asset_key = self._altnames[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'])
fqme = asset_key + '.kraken'
tx = Transaction(
fqsn=fqme,
sym=asset,
tid=entry['txid'],
dt=pendulum.from_timestamp(entry['time']),
bs_mktid=f'{asset_key}{src_asset}',
size=-1*(
float(entry['amount'])
+
cost
),
# since this will be treated as a "sell" it
# shouldn't be needed to compute the be price.
price='NaN',
# XXX: see note above
cost=cost,
)
trans[tx.tid] = tx
return trans
async def submit_limit(
self,
symbol: str,
price: float,
action: str,
size: float,
reqid: str = None,
validate: bool = False # set True test call without a real submission
) -> dict:
'''
Place an order and return integer request id provided by client.
'''
# Build common data dict for common keys from both endpoints
data = {
"pair": symbol,
"price": str(price),
"validate": validate
}
if reqid is None:
# Build order data for kraken api
data |= {
"ordertype": "limit",
"type": action,
"volume": str(size),
}
return await self.endpoint('AddOrder', data)
else:
# Edit order data for kraken api
data["txid"] = reqid
return await self.endpoint('EditOrder', data)
async def submit_cancel(
self,
reqid: str,
) -> dict:
'''
Send cancel request for order id ``reqid``.
'''
# txid is a transaction id given by kraken
return await self.endpoint('CancelOrder', {"txid": reqid})
async def pair_info(
self,
pair: str | None = None,
) -> dict[str, Pair] | Pair:
if pair is not None:
pairs = {'pair': pair}
else:
pairs = None # get all pairs
resp = await self._public('AssetPairs', pairs)
err = resp['error']
if err:
symbolname = pairs['pair'] if pair else None
raise SymbolNotFound(f'{symbolname}.kraken')
pairs = resp['result']
if pair is not None:
_, data = next(iter(pairs.items()))
return Pair(**data)
else:
return {
key: Pair(**data)
for key, data in pairs.items()
}
async def mkt_info(
self,
pair_str: str,
) -> MktPair:
(
bs_mktid, # str
pair_info, # Pair
) = Client.normalize_symbol(pair_str)
dst_asset = self.assets[pair_info.base]
# NOTE XXX parse out the src asset name until we figure out
# how to get the src asset's `Pair` info from kraken..
src_key = pair_str.lstrip(dst_asset.name.upper()).lower()
return MktPair(
dst=dst_asset,
price_tick=pair_info.price_tick,
size_tick=pair_info.size_tick,
bs_mktid=bs_mktid,
src=src_key,
broker='kraken',
)
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.update(await self.pair_info())
# 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[altname] = 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)
return self._pairs
async def search_symbols(
self,
pattern: str,
limit: int = None,
) -> dict[str, Any]:
'''
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,
self._pairs,
score_cutoff=50,
)
# repack in dict form
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: Union[int, datetime] | None = None,
count: int = 720, # <- max allowed per query
as_np: bool = True,
) -> dict:
if since is None:
since = pendulum.now('UTC').start_of('minute').subtract(
minutes=count).timestamp()
elif isinstance(since, int):
since = pendulum.from_timestamp(since).timestamp()
else: # presumably a pendulum datetime
since = since.timestamp()
# UTC 2017-07-02 12:53:20 is oldest seconds value
since = str(max(1499000000, int(since)))
json = await self._public(
'OHLC',
data={
'pair': symbol,
'since': since,
},
)
try:
res = json['result']
res.pop('last')
bars = next(iter(res.values()))
new_bars = []
first = bars[0]
last_nz_vwap = first[-3]
if last_nz_vwap == 0:
# use close if vwap is zero
last_nz_vwap = first[-4]
# convert all fields to native types
for i, bar in enumerate(bars):
# normalize weird zero-ed vwap values..cmon kraken..
# indicates vwap didn't change since last bar
vwap = float(bar.pop(-3))
if vwap != 0:
last_nz_vwap = vwap
if vwap == 0:
vwap = last_nz_vwap
# re-insert vwap as the last of the fields
bar.append(vwap)
new_bars.append(
(i,) + tuple(
ftype(bar[j]) for j, (name, ftype) in enumerate(
_ohlc_dtype[1:]
)
)
)
array = np.array(new_bars, dtype=_ohlc_dtype) if as_np else bars
return array
except KeyError:
errmsg = json['error'][0]
if 'not found' in errmsg:
raise SymbolNotFound(errmsg + f': {symbol}')
elif 'Too many requests' in errmsg:
raise DataThrottle(f'{symbol}')
else:
raise BrokerError(errmsg)
@classmethod
def normalize_symbol(
cls,
ticker: 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
the 'AssetPairs' endpoint, see methods above.
'''
ticker = cls._ntable[ticker]
return ticker.lower(), cls._pairs[ticker]
@acm
async def get_client() -> Client:
conf = get_config()
if conf:
client = Client(
conf,
name=conf['key_descr'],
api_key=conf['api_key'],
secret=conf['secret']
)
else:
client = Client({})
# at startup, load all symbols, and asset info in
# batch requests.
async with trio.open_nursery() as nurse:
nurse.start_soon(client.cache_assets)
await client.cache_symbols()
yield client