get positions from trades
Konstantine Tsafatinos
Tyler Goodlet
parent
0bab95eaa6
commit
20a5ffdc2b
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@ -20,7 +20,7 @@ Kraken backend.
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"""
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from contextlib import asynccontextmanager
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from dataclasses import asdict, field
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from typing import List, Dict, Any, Tuple, Optional
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from typing import List, Dict, Any, Tuple, Optional, AsyncIterator
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import time
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from trio_typing import TaskStatus
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@ -34,12 +34,13 @@ from pydantic.dataclasses import dataclass
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from pydantic import BaseModel
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import wsproto
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from . import config
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from .. import config
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from .._cacheables import open_cached_client
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from ._util import resproc, SymbolNotFound, BrokerError
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from ..log import get_logger, get_console_log
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from ..data import ShmArray
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from ..data._web_bs import open_autorecon_ws
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from ..clearing._messages import BrokerdPosition
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import urllib.parse
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import hashlib
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@ -229,41 +230,35 @@ class Client:
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print(err)
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return resp['result']
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async def get_ledger(
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async def get_positions(
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self,
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data: Dict[str, Any]
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) -> pd.DataFrame:
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ledgers = await self.get_user_data('Ledgers', data)
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num_entries = int(ledgers['count'])
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crypto_transactions = np.empty((num_entries, 5), dtype=object)
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if num_entries // 50 < 0 or num_entries == 50:
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# NOTE: Omitting the following values from the kraken ledger:
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# -> 'refid', 'type', 'subtype', 'aclass'
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for i, entry in enumerate(ledgers['ledger'].items()):
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crypto_transactions[i] = [
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entry[1]['time'],
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entry[1]['amount'],
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entry[1]['fee'],
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entry[1]['asset'],
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entry[1]['balance']
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]
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data: Dict[str, Any] = {}
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) -> Dict[str, Any]:
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balances = await self.get_user_data('Balance', data)
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## TODO: grab all entries, not just first 50
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traders = await self.get_user_data('TradesHistory', data)
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positions = {}
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vols = {}
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# positions
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## TODO: Make sure to add option to include fees in positions calc
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for trade in traders['trades'].values():
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sign = -1 if trade['type'] == 'sell' else 1
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try:
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positions[trade['pair']] += sign * float(trade['cost'])
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vols[trade['pair']] += sign * float(trade['vol'])
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except KeyError:
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positions[trade['pair']] = sign * float(trade['cost'])
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vols[trade['pair']] = sign * float(trade['vol'])
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for pair in positions.keys():
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asset_balance = vols[pair]
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if asset_balance == 0:
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positions[pair] = 0
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else:
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for n in range(num_entries // 50 + 1):
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data['ofs'] = n * 50
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ledgers = await self.get_user_data('Ledgers', data)
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for i, entry in enumerate(ledgers['ledger'].items()):
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crypto_transactions[i + n * 50] = [
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entry[1]['time'],
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entry[1]['amount'],
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entry[1]['fee'],
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entry[1]['asset'],
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entry[1]['balance']
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]
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ledger = pd.DataFrame(
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columns = ['time', 'amount', 'fee', 'asset', 'balance'],
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data = crypto_transactions
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)
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return ledger
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positions[pair] /= asset_balance
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return positions
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async def symbol_info(
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self,
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@ -385,80 +380,9 @@ async def get_client() -> Client:
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data = {
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# add non-nonce and non-ofs vars
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}
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# positions = await client.get_positions(data)
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balances = await client.get_user_data('Balance', data)
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traders = await client.get_user_data('TradesHistory', data)
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ledger = await client.get_ledger(data)
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# positions
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## TODO: Make sure to add option with fees
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n, m = ledger.shape
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ledger['time'] = ledger['time'].apply(lambda x: int(x))
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assets = set(ledger['asset'])
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trade_times = set(ledger['time'])
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trades = {}
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positions = {}
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# for index, row in ledger.iterrows():
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# if index == n:
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# break
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# asset = row['asset']
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# ## TODO: Look into a way to generalize this
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# if asset != 'ZEUR' and ledger.loc[index+1, 'asset'] == 'ZEUR':
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# try:
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# trades[asset]['amounts'].append(float(ledger.loc[index, 'amount']))
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# trades[asset]['prices'].append(float(ledger.loc[index+1, 'amount']))
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# except KeyError:
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# trades[asset] = {
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# 'amounts': [float(ledger.loc[index+1, 'amount'])],
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# 'prices': [float(ledger.loc[index+1, 'amount'])]
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# }
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## TODO: Look into a way to generalize this for any fiat
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## TODO: Figure out how to handle coin for coin trades
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for trade_time in trade_times:
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trade = ledger[ledger['time'] == trade_time]
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coin = trade[trade['asset'] != 'ZEUR']
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fiat = trade[trade['asset'] == 'ZEUR']
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if len(coin) == 0 or len(coin) > 1:
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continue
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asset = list(coin.loc[:, 'asset'])[0]
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amount = np.sum(coin['amount'].apply(lambda x: float(x)))
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if amount > 0:
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sign = -1
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price = sign * np.sum(fiat['amount'].apply(lambda x: float(x)))
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try:
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trades[asset]['trade_amounts'].append(amount)
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trades[asset]['trade_prices'].append(price)
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trades[asset]['enter_amounts'].append(amount)
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except KeyError:
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trades[asset] = {
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'trade_amounts': [amount],
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'trade_prices': [price],
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'enter_amounts': [amount]
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}
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else:
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price = 0
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# continue
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try:
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trades[asset]['trade_amounts'].append(amount)
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trades[asset]['trade_prices'].append(price)
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except KeyError:
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trades[asset] = {
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'trade_amounts': [amount],
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'trade_prices': [price],
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'enter_amounts': []
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}
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for asset in assets:
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if asset == 'ZEUR':
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continue
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t_amounts = np.array(trades[asset]['trade_amounts'])
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t_prices = np.array(trades[asset]['trade_prices'])
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e_amounts = np.array(trades[asset]['enter_amounts'])
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positions[asset] = np.dot(np.divide(t_prices, t_amounts), t_amounts) / np.sum(e_amounts)
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await tractor.breakpoint()
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# await tractor.breakpoint()
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# at startup, load all symbols locally for fast search
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await client.cache_symbols()
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@ -466,27 +390,32 @@ async def get_client() -> Client:
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yield client
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# @tractor.context
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# async def trades_dialogue(
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# ctx: tractor.Context,
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# loglevel: str = None,
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# ) -> AsyncIterator[Dict[str, Any]]:
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#
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# # XXX: required to propagate ``tractor`` loglevel to piker logging
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# get_console_log(loglevel or tractor.current_actor().loglevel)
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#
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# # deliver positions to subscriber before anything else
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@tractor.context
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async def trades_dialogue(
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ctx: tractor.Context,
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loglevel: str = None,
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) -> AsyncIterator[Dict[str, Any]]:
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# XXX: required to propagate ``tractor`` loglevel to piker logging
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get_console_log(loglevel or tractor.current_actor().loglevel)
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# deliver positions to subscriber before anything else
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# positions = await _trio_run_client_method(method='positions')
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#
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# all_positions = {}
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#
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# for pos in positions:
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# msg = pack_position(pos)
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# all_positions[msg.symbol] = msg.dict()
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#
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# await ctx.started(all_positions)
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global _accounts2clients
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positions = await client.get_positions()
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await tractor.breakpoint()
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all_positions = {}
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for pos in positions:
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msg = pack_position(pos)
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all_positions[msg.symbol] = msg.dict()
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await ctx.started(all_positions)
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async def stream_messages(ws):
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