Merge branch 'develop'

This commit is contained in:
Frederic Fortier
2018-01-04 01:55:39 -05:00
66 changed files with 3953 additions and 4079 deletions
+3 -3
View File
@@ -11,13 +11,13 @@
#
# https://127.0.0.1
#
# default password is jupyter. to provide another, see:
# Default password is 'jupyter'. To provide another, see:
# http://jupyter-notebook.readthedocs.org/en/latest/public_server.html#preparing-a-hashed-password
#
# once generated, you can pass the new value via `docker run --env` the first time
# Once generated, you can pass the new value via `docker run --env` the first time
# you start the container.
#
# You can also run an algo using the docker exec command. For example:
# You can also run an algo using the docker exec command. For example:
#
# docker exec -it catalyst catalyst run -f /projects/my_algo.py --start 2015-1-1 --end 2016-1-1 /projects/result.pickle
#
+4 -4
View File
@@ -5,7 +5,7 @@
#
# Note: the dev build requires a quantopian/catalyst image, which you can build as follows:
#
# docker build -t quantopian/catalyst -f Dockerfile
# docker build -t quantopian/catalyst -f Dockerfile .
#
# To run the container:
#
@@ -15,13 +15,13 @@
#
# https://127.0.0.1
#
# default password is jupyter. to provide another, see:
# Default password is 'jupyter'. To provide another, see:
# http://jupyter-notebook.readthedocs.org/en/latest/public_server.html#preparing-a-hashed-password
#
# once generated, you can pass the new value via `docker run --env` the first time
# Once generated, you can pass the new value via `docker run --env` the first time
# you start the container.
#
# You can also run an algo using the docker exec command. For example:
# You can also run an algo using the docker exec command. For example:
#
# docker exec -it catalystdev catalyst run -f /projects/my_algo.py --start 2015-1-1 --end 2016-1-1 /projects/result.pickle
#
+1 -1
View File
@@ -9,7 +9,7 @@ from six import text_type
from catalyst.data import bundles as bundles_module
from catalyst.exchange.exchange_bundle import ExchangeBundle
from catalyst.exchange.exchange_utils import delete_algo_folder
from catalyst.exchange.utils.exchange_utils import delete_algo_folder
from catalyst.utils.cli import Date, Timestamp
from catalyst.utils.run_algo import _run, load_extensions
+2 -1
View File
@@ -17,6 +17,7 @@
"""
Cythonized Asset object.
"""
import hashlib
cimport cython
@@ -38,7 +39,7 @@ from numpy cimport int64_t
import warnings
cimport numpy as np
from catalyst.exchange.exchange_utils import get_sid
from catalyst.exchange.utils.exchange_utils import get_sid
from catalyst.utils.calendars import get_calendar
from catalyst.exchange.exchange_errors import InvalidSymbolError, SidHashError
+1 -1
View File
@@ -7,7 +7,7 @@ import logbook
For example, if you want to see the DEBUG messages, run:
$ export CATALYST_LOG_LEVEL=10
'''
LOG_LEVEL = int(os.environ.get('CATALYST_LOG_LEVEL', logbook.INFO))
LOG_LEVEL = int(os.environ.get('CATALYST_LOG_LEVEL', logbook.DEBUG))
SYMBOLS_URL = 'https://s3.amazonaws.com/enigmaco/catalyst-exchanges/' \
'{exchange}/symbols.json'
+10 -9
View File
@@ -1,16 +1,16 @@
import os
import time
import shutil
import json
import csv
import json
import os
import shutil
import time
from datetime import datetime
import logbook
import pandas as pd
import requests
import logbook
from catalyst.exchange.exchange_utils import get_exchange_symbols_filename
from catalyst.exchange.utils.exchange_utils import \
get_exchange_symbols_filename
DT_START = int(time.mktime(datetime(2010, 1, 1, 0, 0).timetuple()))
DT_END = pd.to_datetime('today').value // 10 ** 9
@@ -193,7 +193,8 @@ class PoloniexCurator(object):
for this currencyPair
'''
try:
if('end_file' in locals() and end_file + 3600 < end):
if(temp is not None
or ('end_file' in locals() and end_file + 3600 < end)):
if (temp is None):
temp = os.tmpfile()
tempcsv = csv.writer(temp)
@@ -261,7 +262,7 @@ class PoloniexCurator(object):
vol = df['total'].to_frame('volume') # set Vol aside
df.drop('total', axis=1, inplace=True) # Drop volume data
ohlc = df.resample('T').ohlc() # Resample OHLC 1min
ohlc.cols = ohlc.cols.map(lambda t: t[1]) # Raname cols
ohlc.columns = ohlc.columns.map(lambda t: t[1]) # Rename cols
closes = ohlc['close'].fillna(method='pad') # Pad fwd missing close
ohlc = ohlc.apply(lambda x: x.fillna(closes)) # Fill NA w/ last close
vol = vol.resample('T').sum().fillna(0) # Add volumes by bin
+2 -3
View File
@@ -22,6 +22,7 @@ from pandas_datareader.data import DataReader
from six import iteritems
from six.moves.urllib_error import HTTPError
from catalyst.constants import LOG_LEVEL
from catalyst.utils.calendars import get_calendar
from . import treasuries, treasuries_can
from .benchmarks import get_benchmark_returns
@@ -31,8 +32,6 @@ from ..utils.paths import (
data_root,
)
from catalyst.constants import LOG_LEVEL
logger = logbook.Logger('Loader', level=LOG_LEVEL)
# Mapping from index symbol to appropriate bond data
@@ -143,7 +142,7 @@ def load_crypto_market_data(trading_day=None, trading_days=None,
if exchange is None:
# This is exceptional, since placing the import at the module scope
# breaks things and it's only needed here
from catalyst.exchange.factory import get_exchange
from catalyst.exchange.utils.factory import get_exchange
exchange = get_exchange(
exchange_name='poloniex', base_currency='usdt'
)
@@ -6,7 +6,7 @@ from catalyst.api import (
symbol,
get_open_orders
)
from catalyst.exchange.stats_utils import get_pretty_stats
from catalyst.exchange.utils.stats_utils import get_pretty_stats
from catalyst.utils.run_algo import run_algorithm
algo_namespace = 'arbitrage_eth_btc'
+47 -52
View File
@@ -1,19 +1,7 @@
'''
This algorithm requires an additional library (ta-lib) beyond those
required by catalyst. Install it first by running:
$ pip install TA-Lib
If you get build errors like:
"fatal error: ta-lib/ta_libc.h: No such file or directory"
it typically means that it can't find the underlying TA-Lib library and it
needs to be installed. See https://mrjbq7.github.io/ta-lib/install.html for
instructions on how to install the required dependencies.
'''
import talib
import pandas as pd
from logbook import Logger
from catalyst import run_algorithm
from catalyst.api import (
order,
order_target_percent,
@@ -21,59 +9,52 @@ from catalyst.api import (
record,
get_open_orders,
)
from catalyst.exchange.stats_utils import get_pretty_stats
import pandas as pd
from catalyst.exchange.utils.stats_utils import get_pretty_stats
from catalyst.utils.run_algo import run_algorithm
algo_namespace = 'buy_low_sell_high_xrp'
log = Logger(algo_namespace)
algo_namespace = 'buy_the_dip_live'
log = Logger('buy low sell high')
def initialize(context):
log.info('initializing algo')
context.ASSET_NAME = 'XRP_USDT'
context.ASSET_NAME = 'btc_usdt'
context.asset = symbol(context.ASSET_NAME)
context.TARGET_POSITIONS = 5000
context.TARGET_POSITIONS = 30
context.PROFIT_TARGET = 0.1
context.SLIPPAGE_ALLOWED = 0.05
context.retry_check_open_orders = 10
context.retry_update_portfolio = 10
context.retry_order = 5
context.swallow_errors = True
context.SLIPPAGE_ALLOWED = 0.02
context.errors = []
pass
def _handle_data(context, data):
price = data.current(context.asset, 'price')
log.info('got price {price}'.format(price=price))
prices = data.history(
context.asset,
fields='price',
bar_count=20,
frequency='15m'
frequency='1D'
)
rsi = talib.RSI(prices.values, timeperiod=14)[-1]
log.info('got rsi: {}'.format(rsi))
# Buying more when RSI is low, this should lower our cost basis
if rsi <= 30:
buy_increment = 50
buy_increment = 1
elif rsi <= 40:
buy_increment = 20
buy_increment = 0.5
elif rsi <= 70:
buy_increment = 5
buy_increment = 0.2
else:
buy_increment = None
buy_increment = 0.1
cash = context.portfolio.cash
log.info('base currency available: {cash}'.format(cash=cash))
price = data.current(context.asset, 'price')
log.info('got price {price}'.format(price=price))
record(
price=price,
rsi=rsi,
@@ -141,11 +122,11 @@ def _handle_data(context, data):
def handle_data(context, data):
log.info('handling bar {}'.format(data.current_dt))
try:
_handle_data(context, data)
except Exception as e:
log.warn('aborting the bar on error {}'.format(e))
context.errors.append(e)
# try:
_handle_data(context, data)
# except Exception as e:
# log.warn('aborting the bar on error {}'.format(e))
# context.errors.append(e)
log.info('completed bar {}, total execution errors {}'.format(
data.current_dt,
@@ -162,15 +143,29 @@ def analyze(context, stats):
if __name__ == '__main__':
run_algorithm(
capital_base=10000,
data_frequency='daily',
initialize=initialize,
handle_data=handle_data,
analyze=analyze,
exchange_name='poloniex',
algo_namespace='buy_and_hodl',
base_currency='usd',
start=pd.to_datetime('2015-03-01', utc=True),
end=pd.to_datetime('2017-10-31', utc=True),
)
live = False
if live:
run_algorithm(
capital_base=0.001,
initialize=initialize,
handle_data=handle_data,
analyze=analyze,
exchange_name='binance',
live=True,
algo_namespace=algo_namespace,
base_currency='btc',
simulate_orders=True,
)
else:
run_algorithm(
capital_base=10000,
data_frequency='daily',
initialize=initialize,
handle_data=handle_data,
analyze=analyze,
exchange_name='poloniex',
algo_namespace='buy_and_hodl',
base_currency='usdt',
start=pd.to_datetime('2015-03-01', utc=True),
end=pd.to_datetime('2017-10-31', utc=True),
)
-160
View File
@@ -1,160 +0,0 @@
import talib
from logbook import Logger
import pandas as pd
from catalyst.api import (
order,
order_target_percent,
symbol,
record,
get_open_orders,
)
from catalyst.exchange.stats_utils import get_pretty_stats
from catalyst.utils.run_algo import run_algorithm
algo_namespace = 'buy_the_dip_live'
log = Logger('buy low sell high')
def initialize(context):
log.info('initializing algo')
context.ASSET_NAME = 'btc_usdt'
context.asset = symbol(context.ASSET_NAME)
context.TARGET_POSITIONS = 30
context.PROFIT_TARGET = 0.1
context.SLIPPAGE_ALLOWED = 0.02
context.retry_check_open_orders = 10
context.retry_update_portfolio = 10
context.retry_order = 5
context.errors = []
pass
def _handle_data(context, data):
price = data.current(context.asset, 'price')
log.info('got price {price}'.format(price=price))
prices = data.history(
context.asset,
fields='price',
bar_count=20,
frequency='1D'
)
rsi = talib.RSI(prices.values, timeperiod=14)[-1]
log.info('got rsi: {}'.format(rsi))
# Buying more when RSI is low, this should lower our cost basis
if rsi <= 30:
buy_increment = 1
elif rsi <= 40:
buy_increment = 0.5
elif rsi <= 70:
buy_increment = 0.2
else:
buy_increment = 0.1
cash = context.portfolio.cash
log.info('base currency available: {cash}'.format(cash=cash))
record(
price=price,
rsi=rsi,
)
orders = get_open_orders(context.asset)
if orders:
log.info('skipping bar until all open orders execute')
return
is_buy = False
cost_basis = None
if context.asset in context.portfolio.positions:
position = context.portfolio.positions[context.asset]
cost_basis = position.cost_basis
log.info(
'found {amount} positions with cost basis {cost_basis}'.format(
amount=position.amount,
cost_basis=cost_basis
)
)
if position.amount >= context.TARGET_POSITIONS:
log.info('reached positions target: {}'.format(position.amount))
return
if price < cost_basis:
is_buy = True
elif (position.amount > 0
and price > cost_basis * (1 + context.PROFIT_TARGET)):
profit = (price * position.amount) - (cost_basis * position.amount)
log.info('closing position, taking profit: {}'.format(profit))
order_target_percent(
asset=context.asset,
target=0,
limit_price=price * (1 - context.SLIPPAGE_ALLOWED),
)
else:
log.info('no buy or sell opportunity found')
else:
is_buy = True
if is_buy:
if buy_increment is None:
log.info('the rsi is too high to consider buying {}'.format(rsi))
return
if price * buy_increment > cash:
log.info('not enough base currency to consider buying')
return
log.info(
'buying position cheaper than cost basis {} < {}'.format(
price,
cost_basis
)
)
order(
asset=context.asset,
amount=buy_increment,
limit_price=price * (1 + context.SLIPPAGE_ALLOWED)
)
def handle_data(context, data):
log.info('handling bar {}'.format(data.current_dt))
# try:
_handle_data(context, data)
# except Exception as e:
# log.warn('aborting the bar on error {}'.format(e))
# context.errors.append(e)
log.info('completed bar {}, total execution errors {}'.format(
data.current_dt,
len(context.errors)
))
if len(context.errors) > 0:
log.info('the errors:\n{}'.format(context.errors))
def analyze(context, stats):
log.info('the daily stats:\n{}'.format(get_pretty_stats(stats)))
pass
if __name__ == '__main__':
run_algorithm(
capital_base=0.001,
initialize=initialize,
handle_data=handle_data,
analyze=analyze,
exchange_name='binance',
live=True,
algo_namespace=algo_namespace,
base_currency='btc',
simulate_orders=True,
)
+2 -2
View File
@@ -1,12 +1,12 @@
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from logbook import Logger
import matplotlib.pyplot as plt
from catalyst import run_algorithm
from catalyst.api import (record, symbol, order_target_percent,
get_open_orders)
from catalyst.exchange.stats_utils import extract_transactions
from catalyst.exchange.utils.stats_utils import extract_transactions
NAMESPACE = 'dual_moving_average'
log = Logger(NAMESPACE)
+21 -22
View File
@@ -12,8 +12,7 @@ from logbook import Logger
from catalyst import run_algorithm
from catalyst.api import symbol, record, order_target_percent, get_open_orders
from catalyst.exchange.stats_utils import extract_transactions
from catalyst.exchange.utils.stats_utils import extract_transactions
# We give a name to the algorithm which Catalyst will use to persist its state.
# In this example, Catalyst will create the `.catalyst/data/live_algos`
# directory. If we stop and start the algorithm, Catalyst will resume its
@@ -34,12 +33,12 @@ def initialize(context):
# parameters or values you're going to use.
# In our example, we're looking at Neo in Ether.
context.market = symbol('neo_eth')
context.market = symbol('eth_btc')
context.base_price = None
context.current_day = None
context.RSI_OVERSOLD = 30
context.RSI_OVERBOUGHT = 80
context.RSI_OVERSOLD = 50
context.RSI_OVERBOUGHT = 65
context.CANDLE_SIZE = '5T'
context.start_time = time.time()
@@ -245,9 +244,24 @@ def analyze(context=None, perf=None):
if __name__ == '__main__':
# The execution mode: backtest or live
MODE = 'backtest'
live = True
if MODE == 'backtest':
if live:
run_algorithm(
capital_base=0.03,
initialize=initialize,
handle_data=handle_data,
analyze=analyze,
exchange_name='poloniex',
live=True,
algo_namespace=NAMESPACE,
base_currency='btc',
live_graph=False,
simulate_orders=False,
stats_output=None,
)
else:
folder = os.path.join(
tempfile.gettempdir(), 'catalyst', NAMESPACE
)
@@ -272,18 +286,3 @@ if __name__ == '__main__':
output=out
)
log.info('saved perf stats: {}'.format(out))
elif MODE == 'live':
run_algorithm(
capital_base=0.05,
initialize=initialize,
handle_data=handle_data,
analyze=analyze,
exchange_name='binance',
live=True,
algo_namespace=NAMESPACE,
base_currency='eth',
live_graph=False,
simulate_orders=True,
stats_output=None
)
+39 -20
View File
@@ -1,23 +1,26 @@
import talib
import pandas as pd
import talib
from logbook import Logger, INFO
from catalyst import run_algorithm
from catalyst.api import symbol, record
from catalyst.exchange.stats_utils import get_pretty_stats, \
from catalyst.exchange.utils.stats_utils import get_pretty_stats, \
extract_transactions
log = Logger('simple_loop', level=INFO)
def initialize(context):
print('initializing')
log.info('initializing')
context.asset = symbol('eth_btc')
context.base_price = None
def handle_data(context, data):
print('handling bar: {}'.format(data.current_dt))
log.info('handling bar: {}'.format(data.current_dt))
price = data.current(context.asset, 'close')
print('got price {price}'.format(price=price))
log.info('got price {price}'.format(price=price))
prices = data.history(
context.asset,
@@ -26,10 +29,10 @@ def handle_data(context, data):
frequency='30T'
)
last_traded = prices.index[-1]
print('last candle date: {}'.format(last_traded))
log.info('last candle date: {}'.format(last_traded))
rsi = talib.RSI(prices.values, timeperiod=14)[-1]
print('got rsi: {}'.format(rsi))
log.info('got rsi: {}'.format(rsi))
# If base_price is not set, we use the current value. This is the
# price at the first bar which we reference to calculate price_change.
@@ -51,7 +54,7 @@ def handle_data(context, data):
def analyze(context, perf):
import matplotlib.pyplot as plt
print('the stats: {}'.format(get_pretty_stats(perf)))
log.info('the stats: {}'.format(get_pretty_stats(perf)))
# The base currency of the algo exchange
base_currency = context.exchanges.values()[0].base_currency.upper()
@@ -111,15 +114,31 @@ def analyze(context, perf):
if __name__ == '__main__':
run_algorithm(
capital_base=1,
initialize=initialize,
handle_data=handle_data,
analyze=None,
exchange_name='poloniex',
live=True,
algo_namespace='simple_loop',
base_currency='eth',
live_graph=False,
simulate_orders=True
)
mode = 'backtest'
if mode == 'backtest':
run_algorithm(
capital_base=1,
initialize=initialize,
handle_data=handle_data,
analyze=None,
exchange_name='poloniex',
algo_namespace='simple_loop',
base_currency='eth',
data_frequency='minute',
start=pd.to_datetime('2017-9-1', utc=True),
end=pd.to_datetime('2017-12-1', utc=True),
)
else:
run_algorithm(
capital_base=1,
initialize=initialize,
handle_data=handle_data,
analyze=None,
exchange_name='binance',
live=True,
algo_namespace='simple_loop',
base_currency='eth',
live_graph=False,
simulate_orders=True
)
+1 -1
View File
@@ -35,8 +35,8 @@ import numpy as np
import pandas as pd
from catalyst import run_algorithm
from catalyst.exchange.exchange_utils import get_exchange_symbols
from catalyst.api import (symbols, )
from catalyst.exchange.utils.exchange_utils import get_exchange_symbols
def initialize(context):
+1 -1
View File
@@ -23,7 +23,7 @@ from catalyst.api import (
order_target_percent,
symbol,
)
from catalyst.exchange.stats_utils import get_pretty_stats
from catalyst.exchange.utils.stats_utils import get_pretty_stats
algo_namespace = 'talib_sample'
log = Logger(algo_namespace)
@@ -1,99 +0,0 @@
from logbook import Logger
from catalyst.constants import LOG_LEVEL
log = Logger('AssetFinderExchange', level=LOG_LEVEL)
class AssetFinderExchange(object):
def __init__(self):
self._asset_cache = {}
@property
def sids(self):
"""
This seems to be used to pre-fetch assets.
I don't think that we need this for live-trading.
Leaving the list empty.
"""
return list()
def retrieve_all(self, sids, default_none=False):
"""
Retrieve all assets in `sids`.
Parameters
----------
sids : iterable of int
Assets to retrieve.
default_none : bool
If True, return None for failed lookups.
If False, raise `SidsNotFound`.
Returns
-------
assets : list[Asset or None]
A list of the same length as `sids` containing Assets (or Nones)
corresponding to the requested sids.
Raises
------
SidsNotFound
When a requested sid is not found and default_none=False.
"""
# for sid in sids:
# if sid in self._asset_cache:
# log.debug('got asset from cache: {}'.format(sid))
# else:
# log.debug('fetching asset: {}'.format(sid))
return list()
def lookup_symbol(self, symbol, exchange, data_frequency=None,
as_of_date=None, fuzzy=False):
"""Lookup an asset by symbol.
Parameters
----------
symbol : str
The ticker symbol to resolve.
as_of_date : datetime or None
Look up the last owner of this symbol as of this datetime.
If ``as_of_date`` is None, then this can only resolve the equity
if exactly one equity has ever owned the ticker.
fuzzy : bool, optional
Should fuzzy symbol matching be used? Fuzzy symbol matching
attempts to resolve differences in representations for
shareclasses. For example, some people may represent the ``A``
shareclass of ``BRK`` as ``BRK.A``, where others could write
``BRK_A``.
Returns
-------
equity : Asset
The equity that held ``symbol`` on the given ``as_of_date``, or the
only equity to hold ``symbol`` if ``as_of_date`` is None.
Raises
------
SymbolNotFound
Raised when no equity has ever held the given symbol.
MultipleSymbolsFound
Raised when no ``as_of_date`` is given and more than one equity
has held ``symbol``. This is also raised when ``fuzzy=True`` and
there are multiple candidates for the given ``symbol`` on the
``as_of_date``.
"""
log.debug('looking up symbol: {} {}'.format(symbol, exchange.name))
if data_frequency is not None:
key = ','.join([exchange.name, symbol, data_frequency])
else:
key = ','.join([exchange.name, symbol])
if key in self._asset_cache:
return self._asset_cache[key]
else:
asset = exchange.get_asset(symbol, data_frequency)
self._asset_cache[key] = asset
return asset
-709
View File
@@ -1,709 +0,0 @@
import base64
import datetime
import hashlib
import hmac
import json
import re
import time
import numpy as np
import pandas as pd
import pytz
import requests
import six
from catalyst.assets._assets import TradingPair
from logbook import Logger
from catalyst.constants import LOG_LEVEL
from catalyst.exchange.exchange import Exchange
from catalyst.exchange.exchange_bundle import ExchangeBundle
from catalyst.exchange.exchange_errors import (
ExchangeRequestError,
InvalidHistoryFrequencyError,
InvalidOrderStyle, OrderCancelError)
from catalyst.exchange.exchange_execution import ExchangeLimitOrder, \
ExchangeStopLimitOrder, ExchangeStopOrder
from catalyst.exchange.exchange_utils import get_exchange_symbols_filename, \
download_exchange_symbols, get_symbols_string
from catalyst.finance.order import Order, ORDER_STATUS
from catalyst.protocol import Account
# Trying to account for REST api instability
# https://stackoverflow.com/questions/15431044/can-i-set-max-retries-for-requests-request
from catalyst.utils.deprecate import deprecated
requests.adapters.DEFAULT_RETRIES = 20
BITFINEX_URL = 'https://api.bitfinex.com'
log = Logger('Bitfinex', level=LOG_LEVEL)
warning_logger = Logger('AlgoWarning')
@deprecated
class Bitfinex(Exchange):
def __init__(self, key, secret, base_currency, portfolio=None):
self.url = BITFINEX_URL
self.key = key
self.secret = secret.encode('UTF-8')
self.name = 'bitfinex'
self.color = 'green'
self.assets = dict()
self.load_assets()
self.local_assets = dict()
self.load_assets(is_local=True)
self.base_currency = base_currency
self._portfolio = portfolio
self.minute_writer = None
self.minute_reader = None
# The candle limit for each request
self.num_candles_limit = 1000
# Max is 90 but playing it safe
# https://www.bitfinex.com/posts/188
self.max_requests_per_minute = 80
self.request_cpt = dict()
self.bundle = ExchangeBundle(self.name)
def _request(self, operation, data, version='v1'):
payload_object = {
'request': '/{}/{}'.format(version, operation),
'nonce': '{0:f}'.format(time.time() * 1000000),
# convert to string
'options': {}
}
if data is None:
payload_dict = payload_object
else:
payload_dict = payload_object.copy()
payload_dict.update(data)
payload_json = json.dumps(payload_dict)
if six.PY3:
payload = base64.b64encode(bytes(payload_json, 'utf-8'))
else:
payload = base64.b64encode(payload_json)
m = hmac.new(self.secret, payload, hashlib.sha384)
m = m.hexdigest()
# headers
headers = {
'X-BFX-APIKEY': self.key,
'X-BFX-PAYLOAD': payload,
'X-BFX-SIGNATURE': m
}
if data is None:
request = requests.get(
'{url}/{version}/{operation}'.format(
url=self.url,
version=version,
operation=operation
), data={},
headers=headers)
else:
request = requests.post(
'{url}/{version}/{operation}'.format(
url=self.url,
version=version,
operation=operation
),
headers=headers)
return request
def _get_v2_symbol(self, asset):
pair = asset.symbol.split('_')
symbol = 't' + pair[0].upper() + pair[1].upper()
return symbol
def _get_v2_symbols(self, assets):
"""
Workaround to support Bitfinex v2
TODO: Might require a separate asset dictionary
:param assets:
:return:
"""
v2_symbols = []
for asset in assets:
v2_symbols.append(self._get_v2_symbol(asset))
return v2_symbols
def _create_order(self, order_status):
"""
Create a Catalyst order object from a Bitfinex order dictionary
:param order_status:
:return: Order
"""
if order_status['is_cancelled']:
status = ORDER_STATUS.CANCELLED
elif not order_status['is_live']:
log.info('found executed order {}'.format(order_status))
status = ORDER_STATUS.FILLED
else:
status = ORDER_STATUS.OPEN
amount = float(order_status['original_amount'])
filled = float(order_status['executed_amount'])
if order_status['side'] == 'sell':
amount = -amount
filled = -filled
price = float(order_status['price'])
order_type = order_status['type']
stop_price = None
limit_price = None
# TODO: is this comprehensive enough?
if order_type.endswith('limit'):
limit_price = price
elif order_type.endswith('stop'):
stop_price = price
executed_price = float(order_status['avg_execution_price'])
# TODO: bitfinex does not specify comission.
# I could calculate it but not sure if it's worth it.
commission = None
date = pd.Timestamp.utcfromtimestamp(float(order_status['timestamp']))
date = pytz.utc.localize(date)
order = Order(
dt=date,
asset=self.assets[order_status['symbol']],
amount=amount,
stop=stop_price,
limit=limit_price,
filled=filled,
id=str(order_status['id']),
commission=commission
)
order.status = status
return order, executed_price
def get_balances(self):
log.debug('retrieving wallets balances')
try:
self.ask_request()
response = self._request('balances', None)
balances = response.json()
except Exception as e:
raise ExchangeRequestError(error=e)
if 'message' in balances:
raise ExchangeRequestError(
error='unable to fetch balance {}'.format(balances['message'])
)
std_balances = dict()
for balance in balances:
currency = balance['currency'].lower()
std_balances[currency] = float(balance['available'])
return std_balances
@property
def account(self):
account = Account()
account.settled_cash = None
account.accrued_interest = None
account.buying_power = None
account.equity_with_loan = None
account.total_positions_value = None
account.total_positions_exposure = None
account.regt_equity = None
account.regt_margin = None
account.initial_margin_requirement = None
account.maintenance_margin_requirement = None
account.available_funds = None
account.excess_liquidity = None
account.cushion = None
account.day_trades_remaining = None
account.leverage = None
account.net_leverage = None
account.net_liquidation = None
return account
@property
def time_skew(self):
# TODO: research the time skew conditions
return pd.Timedelta('0s')
def get_account(self):
# TODO: fetch account data and keep in cache
return None
def get_candles(self, freq, assets, bar_count=None,
start_dt=None, end_dt=None):
"""
Retrieve OHLVC candles from Bitfinex
:param data_frequency:
:param assets:
:param bar_count:
:return:
Available Frequencies
---------------------
'1m', '5m', '15m', '30m', '1h', '3h', '6h', '12h', '1D', '7D', '14D',
'1M'
"""
log.debug(
'retrieving {bars} {freq} candles on {exchange} from '
'{end_dt} for markets {symbols}, '.format(
bars=bar_count,
freq=freq,
exchange=self.name,
end_dt=end_dt,
symbols=get_symbols_string(assets)
)
)
allowed_frequencies = ['1T', '5T', '15T', '30T', '60T', '180T',
'360T', '720T', '1D', '7D', '14D', '30D']
if freq not in allowed_frequencies:
raise InvalidHistoryFrequencyError(frequency=freq)
freq_match = re.match(r'([0-9].*)(T|H|D)', freq, re.M | re.I)
if freq_match:
number = int(freq_match.group(1))
unit = freq_match.group(2)
if unit == 'T':
if number in [60, 180, 360, 720]:
number = number / 60
converted_unit = 'h'
else:
converted_unit = 'm'
else:
converted_unit = unit
frequency = '{}{}'.format(number, converted_unit)
else:
raise InvalidHistoryFrequencyError(frequency=freq)
# Making sure that assets are iterable
asset_list = [assets] if isinstance(assets, TradingPair) else assets
ohlc_map = dict()
for asset in asset_list:
symbol = self._get_v2_symbol(asset)
url = '{url}/v2/candles/trade:{frequency}:{symbol}'.format(
url=self.url,
frequency=frequency,
symbol=symbol
)
if bar_count:
is_list = True
url += '/hist?limit={}'.format(int(bar_count))
def get_ms(date):
epoch = datetime.datetime.utcfromtimestamp(0)
epoch = epoch.replace(tzinfo=pytz.UTC)
return (date - epoch).total_seconds() * 1000.0
if start_dt is not None:
start_ms = get_ms(start_dt)
url += '&start={0:f}'.format(start_ms)
if end_dt is not None:
end_ms = get_ms(end_dt)
url += '&end={0:f}'.format(end_ms)
else:
is_list = False
url += '/last'
try:
self.ask_request()
response = requests.get(url)
except Exception as e:
raise ExchangeRequestError(error=e)
if 'error' in response.content:
raise ExchangeRequestError(
error='Unable to retrieve candles: {}'.format(
response.content)
)
candles = response.json()
def ohlc_from_candle(candle):
last_traded = pd.Timestamp.utcfromtimestamp(
candle[0] / 1000.0)
last_traded = last_traded.replace(tzinfo=pytz.UTC)
ohlc = dict(
open=np.float64(candle[1]),
high=np.float64(candle[3]),
low=np.float64(candle[4]),
close=np.float64(candle[2]),
volume=np.float64(candle[5]),
price=np.float64(candle[2]),
last_traded=last_traded
)
return ohlc
if is_list:
ohlc_bars = []
# We can to list candles from old to new
for candle in reversed(candles):
ohlc = ohlc_from_candle(candle)
ohlc_bars.append(ohlc)
ohlc_map[asset] = ohlc_bars
else:
ohlc = ohlc_from_candle(candles)
ohlc_map[asset] = ohlc
return ohlc_map[assets] \
if isinstance(assets, TradingPair) else ohlc_map
def create_order(self, asset, amount, is_buy, style):
"""
Creating order on the exchange.
:param asset:
:param amount:
:param is_buy:
:param style:
:return:
"""
exchange_symbol = self.get_symbol(asset)
if isinstance(style, ExchangeLimitOrder) \
or isinstance(style, ExchangeStopLimitOrder):
price = style.get_limit_price(is_buy)
order_type = 'limit'
elif isinstance(style, ExchangeStopOrder):
price = style.get_stop_price(is_buy)
order_type = 'stop'
else:
raise InvalidOrderStyle(exchange=self.name,
style=style.__class__.__name__)
req = dict(
symbol=exchange_symbol,
amount=str(float(abs(amount))),
price="{:.20f}".format(float(price)),
side='buy' if is_buy else 'sell',
type='exchange ' + order_type, # TODO: support margin trades
exchange=self.name,
is_hidden=False,
is_postonly=False,
use_all_available=0,
ocoorder=False,
buy_price_oco=0,
sell_price_oco=0
)
date = pd.Timestamp.utcnow()
try:
self.ask_request()
response = self._request('order/new', req)
order_status = response.json()
except Exception as e:
raise ExchangeRequestError(error=e)
if 'message' in order_status:
raise ExchangeRequestError(
error='unable to create Bitfinex order {}'.format(
order_status['message'])
)
order_id = str(order_status['id'])
order = Order(
dt=date,
asset=asset,
amount=amount,
stop=style.get_stop_price(is_buy),
limit=style.get_limit_price(is_buy),
id=order_id
)
return order
def get_open_orders(self, asset=None):
"""Retrieve all of the current open orders.
Parameters
----------
asset : Asset
If passed and not None, return only the open orders for the given
asset instead of all open orders.
Returns
-------
open_orders : dict[list[Order]] or list[Order]
If no asset is passed this will return a dict mapping Assets
to a list containing all the open orders for the asset.
If an asset is passed then this will return a list of the open
orders for this asset.
"""
try:
self.ask_request()
response = self._request('orders', None)
order_statuses = response.json()
except Exception as e:
raise ExchangeRequestError(error=e)
if 'message' in order_statuses:
raise ExchangeRequestError(
error='Unable to retrieve open orders: {}'.format(
order_statuses['message'])
)
orders = []
for order_status in order_statuses:
order, executed_price = self._create_order(order_status)
if asset is None or asset == order.sid:
orders.append(order)
return orders
def get_order(self, order_id):
"""Lookup an order based on the order id returned from one of the
order functions.
Parameters
----------
order_id : str
The unique identifier for the order.
Returns
-------
order : Order
The order object.
"""
try:
self.ask_request()
response = self._request(
'order/status', {'order_id': int(order_id)})
order_status = response.json()
except Exception as e:
raise ExchangeRequestError(error=e)
if 'message' in order_status:
raise ExchangeRequestError(
error='Unable to retrieve order status: {}'.format(
order_status['message'])
)
return self._create_order(order_status)
def cancel_order(self, order_param):
"""Cancel an open order.
Parameters
----------
order_param : str or Order
The order_id or order object to cancel.
"""
order_id = order_param.id \
if isinstance(order_param, Order) else order_param
try:
self.ask_request()
response = self._request('order/cancel', {'order_id': order_id})
status = response.json()
except Exception as e:
raise ExchangeRequestError(error=e)
if 'message' in status:
raise OrderCancelError(
order_id=order_id,
exchange=self.name,
error=status['message']
)
def tickers(self, assets):
"""
Fetch ticket data for assets
https://docs.bitfinex.com/v2/reference#rest-public-tickers
:param assets:
:return:
"""
symbols = self._get_v2_symbols(assets)
log.debug('fetching tickers {}'.format(symbols))
try:
self.ask_request()
response = requests.get(
'{url}/v2/tickers?symbols={symbols}'.format(
url=self.url,
symbols=','.join(symbols),
)
)
except Exception as e:
raise ExchangeRequestError(error=e)
if 'error' in response.content:
raise ExchangeRequestError(
error='Unable to retrieve tickers: {}'.format(
response.content)
)
try:
tickers = response.json()
except Exception as e:
raise ExchangeRequestError(error=e)
ticks = dict()
for index, ticker in enumerate(tickers):
if not len(ticker) == 11:
raise ExchangeRequestError(
error='Invalid ticker in response: {}'.format(ticker)
)
ticks[assets[index]] = dict(
timestamp=pd.Timestamp.utcnow(),
bid=ticker[1],
ask=ticker[3],
last_price=ticker[7],
low=ticker[10],
high=ticker[9],
volume=ticker[8],
)
log.debug('got tickers {}'.format(ticks))
return ticks
def generate_symbols_json(self, filename=None, source_dates=False):
symbol_map = {}
if not source_dates:
fn, r = download_exchange_symbols(self.name)
with open(fn) as data_file:
cached_symbols = json.load(data_file)
response = self._request('symbols', None)
for symbol in response.json():
if (source_dates):
start_date = self.get_symbol_start_date(symbol)
else:
try:
start_date = cached_symbols[symbol]['start_date']
except KeyError:
start_date = time.strftime('%Y-%m-%d')
try:
end_daily = cached_symbols[symbol]['end_daily']
except KeyError:
end_daily = 'N/A'
try:
end_minute = cached_symbols[symbol]['end_minute']
except KeyError:
end_minute = 'N/A'
symbol_map[symbol] = dict(
symbol=symbol[:-3] + '_' + symbol[-3:],
start_date=start_date,
end_daily=end_daily,
end_minute=end_minute,
)
if (filename is None):
filename = get_exchange_symbols_filename(self.name)
with open(filename, 'w') as f:
json.dump(symbol_map, f, sort_keys=True, indent=2,
separators=(',', ':'))
def get_symbol_start_date(self, symbol):
print(symbol)
symbol_v2 = 't' + symbol.upper()
"""
For each symbol we retrieve candles with Monhtly resolution
We get the first month, and query again with daily resolution
around that date, and we get the first date
"""
url = '{url}/v2/candles/trade:1M:{symbol}/hist'.format(
url=self.url,
symbol=symbol_v2
)
try:
self.ask_request()
response = requests.get(url)
except Exception as e:
raise ExchangeRequestError(error=e)
"""
If we don't get any data back for our monthly-resolution query
it means that symbol started trading less than a month ago, so
arbitrarily set the ref. date to 15 days ago to be safe with
+/- 31 days
"""
if (len(response.json())):
startmonth = response.json()[-1][0]
else:
startmonth = int((time.time() - 15 * 24 * 3600) * 1000)
"""
Query again with daily resolution setting the start and end around
the startmonth we got above. Avoid end dates greater than
now: time.time()
"""
url = ('{url}/v2/candles/trade:1D:{symbol}/hist?start={start}'
'&end={end}').format(
url=self.url,
symbol=symbol_v2,
start=startmonth - 3600 * 24 * 31 * 1000,
end=min(startmonth + 3600 * 24 * 31 * 1000,
int(time.time() * 1000)))
try:
self.ask_request()
response = requests.get(url)
except Exception as e:
raise ExchangeRequestError(error=e)
return time.strftime('%Y-%m-%d',
time.gmtime(int(response.json()[-1][0] / 1000)))
def get_orderbook(self, asset, order_type='all', limit=100):
exchange_symbol = asset.exchange_symbol
try:
self.ask_request()
# TODO: implement limit
response = self._request(
'book/{}'.format(exchange_symbol), None)
data = response.json()
except Exception as e:
raise ExchangeRequestError(error=e)
# TODO: filter by type
result = dict()
for order_type in data:
result[order_type] = []
for entry in data[order_type]:
result[order_type].append(dict(
rate=float(entry['price']),
quantity=float(entry['amount'])
))
return result
-127
View File
@@ -1,127 +0,0 @@
{
"neobtc": {
"symbol": "neo_btc",
"start_date": "2017-09-07",
"precision": 5
},
"neousd": {
"symbol": "neo_usd",
"start_date": "2017-09-07"
},
"neoeth": {
"symbol": "neo_eth",
"start_date": "2017-09-07"
},
"btcusd": {
"symbol": "btc_usd",
"start_date": "2010-01-01"
},
"bchusd": {
"symbol": "bch_usd",
"start_date": "2010-01-01"
},
"ltcusd": {
"symbol": "ltc_usd",
"start_date": "2010-01-01"
},
"ltcbtc": {
"symbol": "ltc_btc",
"start_date": "2010-01-01"
},
"ethusd": {
"symbol": "eth_usd",
"start_date": "2017-01-01"
},
"ethbtc": {
"symbol": "eth_btc",
"start_date": "2017-01-01"
},
"etcbtc": {
"symbol": "etc_btc",
"start_date": "2017-01-01"
},
"etcusd": {
"symbol": "etc_usd",
"start_date": "2017-01-01"
},
"rrtusd": {
"symbol": "rrt_usd",
"start_date": "2010-01-01"
},
"rrtbtc": {
"symbol": "rrt_btc",
"start_date": "2010-01-01"
},
"zecusd": {
"symbol": "zec_usd",
"start_date": "2010-01-01"
},
"zecbtc": {
"symbol": "zec_btc",
"start_date": "2010-01-01"
},
"xmrusd": {
"symbol": "xmr_usd",
"start_date": "2010-01-01"
},
"xmrbtc": {
"symbol": "xmr_btc",
"start_date": "2010-01-01"
},
"dshusd": {
"symbol": "dsh_usd",
"start_date": "2010-01-01"
},
"dshbtc": {
"symbol": "dsh_btc",
"start_date": "2010-01-01"
},
"bccbtc": {
"symbol": "bcc_btc",
"start_date": "2010-01-01"
},
"bcubtc": {
"symbol": "bcu_btc",
"start_date": "2010-01-01"
},
"bccusd": {
"symbol": "bcc_usd",
"start_date": "2010-01-01"
},
"bcuusd": {
"symbol": "bcu_usd",
"start_date": "2010-01-01"
},
"xrpusd": {
"symbol": "xrp_usd",
"start_date": "2010-01-01"
},
"xrpbtc": {
"symbol": "xrp_btc",
"start_date": "2010-01-01"
},
"iotusd": {
"symbol": "iot_usd",
"start_date": "2010-01-01"
},
"iotbtc": {
"symbol": "iot_btc",
"start_date": "2010-01-01"
},
"ioteth": {
"symbol": "iot_eth",
"start_date": "2010-01-01"
},
"eosusd": {
"symbol": "eos_usd",
"start_date": "2010-01-01"
},
"eosbtc": {
"symbol": "eos_btc",
"start_date": "2010-01-01"
},
"eoseth": {
"symbol": "eos_eth",
"start_date": "2010-01-01"
}
}
-417
View File
@@ -1,417 +0,0 @@
import json
import time
import pandas as pd
from catalyst.assets._assets import TradingPair
from logbook import Logger
from six.moves import urllib
from catalyst.constants import LOG_LEVEL
from catalyst.exchange.bittrex.bittrex_api import Bittrex_api
from catalyst.exchange.exchange import Exchange
from catalyst.exchange.exchange_bundle import ExchangeBundle
from catalyst.exchange.exchange_errors import InvalidHistoryFrequencyError, \
ExchangeRequestError, InvalidOrderStyle, OrderNotFound, OrderCancelError, \
CreateOrderError
from catalyst.exchange.exchange_utils import get_exchange_symbols_filename, \
download_exchange_symbols, get_symbols_string
from catalyst.finance.execution import LimitOrder, StopLimitOrder
from catalyst.finance.order import Order, ORDER_STATUS
# TODO: consider using this: https://github.com/mondeja/bittrex_v2
from catalyst.utils.deprecate import deprecated
log = Logger('Bittrex', level=LOG_LEVEL)
URL2 = 'https://bittrex.com/Api/v2.0'
@deprecated
class Bittrex(Exchange):
def __init__(self, key, secret, base_currency, portfolio=None):
self.api = Bittrex_api(key=key, secret=secret)
self.name = 'bittrex'
self.color = 'blue'
self.base_currency = base_currency
self._portfolio = portfolio
self.num_candles_limit = 2000
# Not sure what the rate limit is but trying to play it safe
# https://bitcoin.stackexchange.com/questions/53778/bittrex-api-rate-limit
self.max_requests_per_minute = 60
self.request_cpt = dict()
self.minute_writer = None
self.minute_reader = None
self.assets = dict()
self.load_assets()
self.local_assets = dict()
self.load_assets(is_local=True)
self.bundle = ExchangeBundle(self.name)
@property
def account(self):
pass
@property
def time_skew(self):
# TODO: research the time skew conditions
return pd.Timedelta('0s')
def sanitize_curency_symbol(self, exchange_symbol):
"""
Helper method used to build the universal pair.
Include any symbol mapping here if appropriate.
:param exchange_symbol:
:return universal_symbol:
"""
return exchange_symbol.lower()
def get_balances(self):
balances = self.api.getbalances()
try:
log.debug('retrieving wallet balances')
self.ask_request()
except Exception as e:
raise ExchangeRequestError(error=e)
std_balances = dict()
try:
for balance in balances:
currency = balance['Currency'].lower()
std_balances[currency] = balance['Available']
except TypeError:
raise ExchangeRequestError(error=balances)
return std_balances
def create_order(self, asset, amount, is_buy, style):
log.info('creating {} order'.format('buy' if is_buy else 'sell'))
exchange_symbol = self.get_symbol(asset)
if isinstance(style, LimitOrder) or isinstance(style, StopLimitOrder):
if isinstance(style, StopLimitOrder):
log.warn('{} will ignore the stop price'.format(self.name))
price = style.get_limit_price(is_buy)
try:
self.ask_request()
if is_buy:
order_status = self.api.buylimit(exchange_symbol, amount,
price)
else:
order_status = self.api.selllimit(exchange_symbol,
abs(amount), price)
except Exception as e:
raise ExchangeRequestError(error=e)
if 'uuid' in order_status:
order_id = order_status['uuid']
order = Order(
dt=pd.Timestamp.utcnow(),
asset=asset,
amount=amount,
stop=style.get_stop_price(is_buy),
limit=style.get_limit_price(is_buy),
id=order_id
)
return order
else:
if order_status == 'INSUFFICIENT_FUNDS':
log.warn('not enough funds to create order')
return None
elif order_status == 'DUST_TRADE_DISALLOWED_MIN_VALUE_50K_SAT':
log.warn('Your order is too small, order at least 50K'
' Satoshi')
return None
else:
raise CreateOrderError(
exchange=self.name,
error=order_status
)
else:
raise InvalidOrderStyle(exchange=self.name,
style=style.__class__.__name__)
def get_open_orders(self, asset):
symbol = self.get_symbol(asset)
try:
self.ask_request()
open_orders = self.api.getopenorders(symbol)
except Exception as e:
raise ExchangeRequestError(error=e)
orders = list()
for order_status in open_orders:
order = self._create_order(order_status)
orders.append(order)
return orders
def _create_order(self, order_status):
log.info(
'creating catalyst order from Bittrex {}'.format(order_status))
if order_status['CancelInitiated']:
status = ORDER_STATUS.CANCELLED
elif order_status['Closed'] is not None:
status = ORDER_STATUS.FILLED
else:
status = ORDER_STATUS.OPEN
date = pd.to_datetime(order_status['Opened'], utc=True)
amount = order_status['Quantity']
filled = amount - order_status['QuantityRemaining']
order = Order(
dt=date,
asset=self.assets[order_status['Exchange']],
amount=amount,
stop=None, # Not yet supported by Bittrex
limit=order_status['Limit'],
filled=filled,
id=order_status['OrderUuid'],
commission=order_status['CommissionPaid']
)
order.status = status
executed_price = order_status['PricePerUnit']
return order, executed_price
def get_order(self, order_id):
log.info('retrieving order {}'.format(order_id))
try:
self.ask_request()
order_status = self.api.getorder(order_id)
except Exception as e:
raise ExchangeRequestError(error=e)
if order_status is None:
raise OrderNotFound(order_id=order_id, exchange=self.name)
return self._create_order(order_status)
def cancel_order(self, order_param):
order_id = order_param.id \
if isinstance(order_param, Order) else order_param
log.info('cancelling order {}'.format(order_id))
try:
self.ask_request()
status = self.api.cancel(order_id)
except Exception as e:
raise ExchangeRequestError(error=e)
if 'message' in status:
raise OrderCancelError(
order_id=order_id,
exchange=self.name,
error=status['message']
)
def get_candles(self, freq, assets, bar_count=None,
start_dt=None, end_dt=None):
"""
Supported Intervals
-------------------
day, oneMin, fiveMin, thirtyMin, hour
:param freq:
:param assets:
:param bar_count:
:param start_dt
:param end_dt
:return:
"""
# TODO: this has no effect at the moment
if end_dt is None:
end_dt = pd.Timestamp.utcnow()
log.debug(
'retrieving {bars} {freq} candles on {exchange} from '
'{end_dt} for markets {symbols}, '.format(
bars=bar_count,
freq=freq,
exchange=self.name,
end_dt=end_dt,
symbols=get_symbols_string(assets)
)
)
if freq == '1T':
frequency = 'oneMin'
elif freq == '5T':
frequency = 'fiveMin'
elif freq == '30T':
frequency = 'thirtyMin'
elif freq == '60T':
frequency = 'hour'
elif freq == '1D':
frequency = 'day'
else:
raise InvalidHistoryFrequencyError(frequency=freq)
# Making sure that assets are iterable
asset_list = [assets] if isinstance(assets, TradingPair) else assets
for asset in asset_list:
end = int(time.mktime(end_dt.timetuple()))
url = '{url}/pub/market/GetTicks?marketName={symbol}' \
'&tickInterval={frequency}&_={end}'.format(
url=URL2,
symbol=self.get_symbol(asset),
frequency=frequency,
end=end, )
try:
data = json.loads(urllib.request.urlopen(url).read().decode())
except Exception as e:
raise ExchangeRequestError(error=e)
if data['message']:
raise ExchangeRequestError(
error='Unable to fetch candles {}'.format(data['message'])
)
candles = data['result']
def ohlc_from_candle(candle):
ohlc = dict(
open=candle['O'],
high=candle['H'],
low=candle['L'],
close=candle['C'],
volume=candle['V'],
price=candle['C'],
last_traded=pd.to_datetime(candle['T'], utc=True)
)
return ohlc
ordered_candles = list(reversed(candles))
ohlc_map = dict()
if bar_count is None:
ohlc_map[asset] = ohlc_from_candle(ordered_candles[0])
else:
# TODO: optimize
ohlc_bars = []
for candle in ordered_candles[:bar_count]:
ohlc = ohlc_from_candle(candle)
ohlc_bars.append(ohlc)
ohlc_map[asset] = ohlc_bars
return ohlc_map[assets] \
if isinstance(assets, TradingPair) else ohlc_map
def tickers(self, assets):
"""
As of v1.1, Bittrex only allows one ticker at the time.
So we have to make multiple calls to fetch multiple assets.
:param assets:
:return:
"""
log.info('retrieving tickers')
ticks = dict()
for asset in assets:
symbol = self.get_symbol(asset)
try:
self.ask_request()
ticker = self.api.getticker(symbol)
except Exception as e:
raise ExchangeRequestError(error=e)
# TODO: catch invalid ticker
ticks[asset] = dict(
timestamp=pd.Timestamp.utcnow(),
bid=ticker['Bid'],
ask=ticker['Ask'],
last_price=ticker['Last']
)
log.debug('got tickers {}'.format(ticks))
return ticks
def get_account(self):
log.info('retrieving account data')
pass
def generate_symbols_json(self, filename=None):
symbol_map = {}
fn, r = download_exchange_symbols(self.name)
with open(fn) as data_file:
cached_symbols = json.load(data_file)
markets = self.api.getmarkets()
for market in markets:
exchange_symbol = market['MarketName']
symbol = '{market}_{base}'.format(
market=self.sanitize_curency_symbol(market['MarketCurrency']),
base=self.sanitize_curency_symbol(market['BaseCurrency'])
)
try:
end_daily = cached_symbols[exchange_symbol]['end_daily']
except KeyError:
end_daily = 'N/A'
try:
end_minute = cached_symbols[exchange_symbol]['end_minute']
except KeyError:
end_minute = 'N/A'
symbol_map[exchange_symbol] = dict(
symbol=symbol,
start_date=pd.to_datetime(market['Created'],
utc=True).strftime("%Y-%m-%d"),
end_daily=end_daily,
end_minute=end_minute,
)
if (filename is None):
filename = get_exchange_symbols_filename(self.name)
with open(filename, 'w') as f:
json.dump(symbol_map, f, sort_keys=True, indent=2,
separators=(',', ':'))
def get_orderbook(self, asset, order_type='all', limit=100):
if order_type == 'all':
order_type = 'both'
elif order_type == 'bid':
order_type = 'buy'
elif order_type == 'ask':
order_type = 'sell'
else:
raise ValueError('invalid type')
exchange_symbol = asset.exchange_symbol
data = self.api.getorderbook(
market=exchange_symbol,
type=order_type,
depth=100
)
result = dict()
for exchange_type in data:
if exchange_type == 'buy':
order_type = 'bids'
elif exchange_type == 'sell':
order_type = 'asks'
result[order_type] = []
for entry in data[exchange_type]:
result[order_type].append(dict(
rate=entry['Rate'],
quantity=entry['Quantity']
))
return result
-132
View File
@@ -1,132 +0,0 @@
#!/usr/bin/env python
import json
import time
import hmac
import hashlib
import ssl
# Workaround for backwards compatibility
# https://stackoverflow.com/questions/3745771/urllib-request-in-python-2-7
from six.moves import urllib
urlopen = urllib.request.urlopen
class Bittrex_api(object):
def __init__(self, key, secret):
self.key = key
self.secret = secret
self.public = ['getmarkets', 'getcurrencies', 'getticker',
'getmarketsummaries', 'getmarketsummary',
'getorderbook', 'getmarkethistory']
self.market = ['buylimit', 'buymarket', 'selllimit', 'sellmarket',
'cancel', 'getopenorders']
self.account = ['getbalances', 'getbalance', 'getdepositaddress',
'withdraw', 'getorder', 'getorderhistory',
'getwithdrawalhistory', 'getdeposithistory']
def query(self, method, values={}):
if method in self.public:
url = 'https://bittrex.com/api/v1.1/public/'
elif method in self.market:
url = 'https://bittrex.com/api/v1.1/market/'
elif method in self.account:
url = 'https://bittrex.com/api/v1.1/account/'
else:
return 'Something went wrong, sorry.'
url += method + '?' + urllib.parse.urlencode(values)
if method not in self.public:
url += '&apikey=' + self.key
url += '&nonce=' + str(int(time.time()))
signature = hmac.new(self.secret.encode('utf-8'),
url.encode('utf-8'),
hashlib.sha512).hexdigest()
headers = {'apisign': signature}
else:
headers = {}
req = urllib.request.Request(url, headers=headers)
response = json.loads(urlopen(
req, context=ssl._create_unverified_context()).read())
if response["result"]:
return response["result"]
else:
return response["message"]
def getmarkets(self):
return self.query('getmarkets')
def getcurrencies(self):
return self.query('getcurrencies')
def getticker(self, market):
return self.query('getticker', {'market': market})
def getmarketsummaries(self):
return self.query('getmarketsummaries')
def getmarketsummary(self, market):
return self.query('getmarketsummary', {'market': market})
def getorderbook(self, market, type, depth=20):
return self.query('getorderbook',
{'market': market, 'type': type, 'depth': depth})
def getmarkethistory(self, market, count=20):
return self.query('getmarkethistory',
{'market': market, 'count': count})
def buylimit(self, market, quantity, rate):
return self.query('buylimit', {'market': market, 'quantity': quantity,
'rate': rate})
def buymarket(self, market, quantity):
return self.query('buymarket',
{'market': market, 'quantity': quantity})
def selllimit(self, market, quantity, rate):
return self.query('selllimit', {'market': market, 'quantity': quantity,
'rate': rate})
def sellmarket(self, market, quantity):
return self.query('sellmarket',
{'market': market, 'quantity': quantity})
def cancel(self, uuid):
return self.query('cancel', {'uuid': uuid})
def getopenorders(self, market):
return self.query('getopenorders', {'market': market})
def getbalances(self):
return self.query('getbalances')
def getbalance(self, currency):
return self.query('getbalance', {'currency': currency})
def getdepositaddress(self, currency):
return self.query('getdepositaddress', {'currency': currency})
def withdraw(self, currency, quantity, address):
return self.query('withdraw',
{'currency': currency, 'quantity': quantity,
'address': address})
def getorder(self, uuid):
return self.query('getorder', {'uuid': uuid})
def getorderhistory(self, market, count):
return self.query('getorderhistory',
{'market': market, 'count': count})
def getwithdrawalhistory(self, currency, count):
return self.query('getwithdrawalhistory',
{'currency': currency, 'count': count})
def getdeposithistory(self, currency, count):
return self.query('getdeposithistory',
{'currency': currency, 'count': count})
@@ -1,7 +0,0 @@
from catalyst.data.bundles import register
from catalyst.exchange.exchange_bundle import exchange_bundle
symbols = (
'neo_btc',
)
register('exchange_bitfinex', exchange_bundle('bitfinex', symbols))
+332 -104
View File
@@ -1,24 +1,27 @@
import json
import os
import re
from collections import defaultdict
import ccxt
import pandas as pd
import six
from catalyst.assets._assets import TradingPair
from ccxt import ExchangeNotAvailable, InvalidOrder
from logbook import Logger
from six import string_types
from catalyst.algorithm import MarketOrder
from catalyst.assets._assets import TradingPair
from catalyst.constants import LOG_LEVEL
from catalyst.exchange.exchange import Exchange
from catalyst.exchange.exchange_bundle import ExchangeBundle
from catalyst.exchange.exchange_errors import InvalidHistoryFrequencyError, \
ExchangeSymbolsNotFound, ExchangeRequestError, InvalidOrderStyle, \
ExchangeNotFoundError, CreateOrderError
ExchangeNotFoundError, CreateOrderError, InvalidHistoryTimeframeError
from catalyst.exchange.exchange_execution import ExchangeLimitOrder
from catalyst.exchange.exchange_utils import mixin_market_params, \
from_ms_timestamp, get_epoch
from catalyst.exchange.utils.exchange_utils import mixin_market_params, \
from_ms_timestamp, get_epoch, get_exchange_folder, get_catalyst_symbol, \
get_exchange_auth
from catalyst.finance.order import Order, ORDER_STATUS
log = Logger('CCXT', level=LOG_LEVEL)
@@ -58,26 +61,103 @@ class CCXT(Exchange):
self._symbol_maps = [None, None]
try:
markets_symbols = self.api.load_markets()
log.debug('the markets:\n{}'.format(markets_symbols))
except ExchangeNotAvailable as e:
raise ExchangeRequestError(error=e)
self.name = exchange_name
self.markets = self.api.fetch_markets()
self.load_assets()
self.base_currency = base_currency
self.transactions = defaultdict(list)
self.num_candles_limit = 2000
self.max_requests_per_minute = 60
self.low_balance_threshold = 0.1
self.request_cpt = dict()
self.bundle = ExchangeBundle(self.name)
self.markets = None
self._is_init = False
def init(self):
if self._is_init:
return
exchange_folder = get_exchange_folder(self.name)
filename = os.path.join(exchange_folder, 'cctx_markets.json')
if os.path.exists(filename):
timestamp = os.path.getmtime(filename)
dt = pd.to_datetime(timestamp, unit='s', utc=True)
if dt >= pd.Timestamp.utcnow().floor('1D'):
with open(filename) as f:
self.markets = json.load(f)
log.debug('loaded markets for {}'.format(self.name))
if self.markets is None:
try:
markets_symbols = self.api.load_markets()
log.debug(
'fetching {} markets:\n{}'.format(
self.name, markets_symbols
)
)
self.markets = self.api.fetch_markets()
with open(filename, 'w+') as f:
json.dump(self.markets, f, indent=4)
except ExchangeNotAvailable as e:
raise ExchangeRequestError(error=e)
self.load_assets()
self._is_init = True
@staticmethod
def find_exchanges(features=None, is_authenticated=False):
ccxt_features = []
if features is not None:
for feature in features:
if not feature.endswith('Bundle'):
ccxt_features.append(feature)
exchange_names = []
for exchange_name in ccxt.exchanges:
if is_authenticated:
exchange_auth = get_exchange_auth(exchange_name)
has_auth = (exchange_auth['key'] != ''
and exchange_auth['secret'] != '')
if not has_auth:
continue
log.debug('loading exchange: {}'.format(exchange_name))
exchange = getattr(ccxt, exchange_name)()
if ccxt_features is None:
has_feature = True
else:
try:
has_feature = all(
[exchange.has[feature] for feature in ccxt_features]
)
except Exception:
has_feature = False
if has_feature:
try:
log.info('initializing {}'.format(exchange_name))
exchange_names.append(exchange_name)
except Exception as e:
log.warn(
'unable to initialize exchange {}: {}'.format(
exchange_name, e
)
)
return exchange_names
def account(self):
return None
@@ -85,6 +165,30 @@ class CCXT(Exchange):
def time_skew(self):
return None
def get_candle_frequencies(self, data_frequency=None):
frequencies = []
try:
for timeframe in self.api.timeframes:
freq = CCXT.get_frequency(timeframe, raise_error=False)
# TODO: support all frequencies
if data_frequency == 'minute' and not freq.endswith('T'):
continue
elif data_frequency == 'daily' and not freq.endswith('D'):
continue
frequencies.append(freq)
except Exception as e:
log.warn(
'candle frequencies not available for exchange {}'.format(
self.name
)
)
return frequencies
def get_market(self, symbol):
"""
The CCXT market.
@@ -106,7 +210,7 @@ class CCXT(Exchange):
)
return market
def get_symbol(self, asset_or_symbol):
def get_symbol(self, asset_or_symbol, source='catalyst'):
"""
The CCXT symbol.
@@ -118,36 +222,109 @@ class CCXT(Exchange):
-------
"""
symbol = asset_or_symbol if isinstance(
asset_or_symbol, string_types
) else asset_or_symbol.symbol
parts = symbol.split('_')
return '{}/{}'.format(parts[0].upper(), parts[1].upper())
if source == 'ccxt':
if isinstance(asset_or_symbol, string_types):
parts = asset_or_symbol.split('/')
return '{}_{}'.format(parts[0].lower(), parts[1].lower())
def get_catalyst_symbol(self, market_or_symbol):
else:
return asset_or_symbol.symbol
else:
symbol = asset_or_symbol if isinstance(
asset_or_symbol, string_types
) else asset_or_symbol.symbol
parts = symbol.split('_')
return '{}/{}'.format(parts[0].upper(), parts[1].upper())
@staticmethod
def map_frequency(value, source='ccxt', raise_error=True):
"""
The Catalyst symbol.
Map a frequency value between CCXT and Catalyst
Parameters
----------
market_or_symbol
value: str
source: str
raise_error: bool
Returns
-------
Notes
-----
The Pandas offset aliases supported by Catalyst:
Alias Description
W weekly frequency
M month end frequency
D calendar day frequency
H hourly frequency
T, min minutely frequency
The CCXT timeframes:
'1m': '1minute',
'1h': '1hour',
'1d': '1day',
'1w': '1week',
'1M': '1month',
'1y': '1year',
"""
if isinstance(market_or_symbol, string_types):
parts = market_or_symbol.split('/')
return '{}_{}'.format(parts[0].lower(), parts[1].lower())
match = re.match(
r'([0-9].*)?(m|M|d|D|h|H|T|w|W|min)', value, re.M | re.I
)
if match:
candle_size = int(match.group(1)) \
if match.group(1) else 1
unit = match.group(2)
else:
return '{}_{}'.format(
market_or_symbol['base'].lower(),
market_or_symbol['quote'].lower(),
)
raise ValueError('Unable to parse frequency or timeframe')
def get_timeframe(self, freq):
if source == 'ccxt':
if unit == 'd':
result = '{}D'.format(candle_size)
elif unit == 'm':
result = '{}T'.format(candle_size)
elif unit == 'h':
result = '{}H'.format(candle_size)
elif unit == 'w':
result = '{}W'.format(candle_size)
elif unit == 'M':
result = '{}M'.format(candle_size)
elif raise_error:
raise InvalidHistoryTimeframeError(timeframe=value)
else:
if unit == 'D':
result = '{}d'.format(candle_size)
elif unit == 'min' or unit == 'T':
result = '{}m'.format(candle_size)
elif unit == 'H':
result = '{}h'.format(candle_size)
elif unit == 'W':
result = '{}w'.format(candle_size)
elif unit == 'M':
result = '{}M'.format(candle_size)
elif raise_error:
raise InvalidHistoryFrequencyError(frequency=value)
return result
@staticmethod
def get_timeframe(freq, raise_error=True):
"""
The CCXT timeframe from the Catalyst frequency.
@@ -161,26 +338,29 @@ class CCXT(Exchange):
str
"""
freq_match = re.match(r'([0-9].*)?(m|M|d|D|h|H|T)', freq, re.M | re.I)
if freq_match:
candle_size = int(freq_match.group(1)) \
if freq_match.group(1) else 1
return CCXT.map_frequency(
freq, source='catalyst', raise_error=raise_error
)
unit = freq_match.group(2)
@staticmethod
def get_frequency(timeframe, raise_error=True):
"""
Test Catalyst frequency from the CCXT timeframe
else:
raise InvalidHistoryFrequencyError(frequency=freq)
Catalyst uses the Pandas offset alias convention:
http://pandas.pydata.org/pandas-docs/stable/timeseries.html#offset-aliases
if unit.lower() == 'd':
timeframe = '{}d'.format(candle_size)
Parameters
----------
timeframe
elif unit.lower() == 'm' or unit == 'T':
timeframe = '{}m'.format(candle_size)
Returns
-------
elif unit.lower() == 'h' or unit == 'T':
timeframe = '{}h'.format(candle_size)
return timeframe
"""
return CCXT.map_frequency(
timeframe, source='ccxt', raise_error=raise_error
)
def get_candles(self, freq, assets, bar_count=None, start_dt=None,
end_dt=None):
@@ -189,7 +369,7 @@ class CCXT(Exchange):
assets = [assets]
symbols = self.get_symbols(assets)
timeframe = self.get_timeframe(freq)
timeframe = CCXT.get_timeframe(freq)
ms = None
if start_dt is not None:
@@ -198,30 +378,26 @@ class CCXT(Exchange):
candles = dict()
for asset in assets:
try:
ohlcvs = self.api.fetch_ohlcv(
symbol=symbols[0],
timeframe=timeframe,
since=ms,
limit=bar_count,
params={}
)
ohlcvs = self.api.fetch_ohlcv(
symbol=symbols[0],
timeframe=timeframe,
since=ms,
limit=bar_count,
params={}
)
candles[asset] = []
for ohlcv in ohlcvs:
candles[asset].append(dict(
last_traded=pd.to_datetime(
ohlcv[0], unit='ms', utc=True
),
open=ohlcv[1],
high=ohlcv[2],
low=ohlcv[3],
close=ohlcv[4],
volume=ohlcv[5]
))
except Exception as e:
raise ExchangeRequestError(error=e)
candles[asset] = []
for ohlcv in ohlcvs:
candles[asset].append(dict(
last_traded=pd.to_datetime(
ohlcv[0], unit='ms', utc=True
),
open=ohlcv[1],
high=ohlcv[2],
low=ohlcv[3],
close=ohlcv[4],
volume=ohlcv[5]
))
if is_single:
return six.next(six.itervalues(candles))
@@ -339,16 +515,21 @@ class CCXT(Exchange):
and asset_def['end_minute'] != 'N/A' else None
else:
params['symbol'] = self.get_catalyst_symbol(market)
params['symbol'] = get_catalyst_symbol(market)
# TODO: add as an optional column
params['leverage'] = 1.0
return TradingPair(**params)
def load_assets(self):
log.debug('loading assets for {}'.format(self.name))
self.assets = []
for market in self.markets:
if 'id' not in market:
log.warn('invalid market: {}'.format(market))
continue
asset_defs = self.get_asset_defs(market)
asset = None
@@ -399,21 +580,61 @@ class CCXT(Exchange):
The Catalyst order object
"""
if order_status['status'] == 'canceled':
order_id = order_status['id']
symbol = self.get_symbol(order_status['symbol'], source='ccxt')
asset = self.get_asset(symbol)
s = order_status['status']
amount = order_status['amount']
filled = order_status['filled']
if s == 'canceled' or (s == 'closed' and filled == 0):
status = ORDER_STATUS.CANCELLED
elif order_status['status'] == 'closed' and order_status['filled'] > 0:
log.debug('found executed order {}'.format(order_status))
elif s == 'closed' and filled > 0:
if filled < amount:
log.warn(
'order {id} is executed but only partially filled:'
' {filled} {symbol} out of {amount}'.format(
id=order_status['status'],
filled=order_status['filled'],
symbol=asset.symbol,
amount=order_status['amount'],
)
)
else:
log.info(
'order {id} executed in full: {filled} {symbol}'.format(
id=order_id,
filled=filled,
symbol=asset.symbol,
)
)
status = ORDER_STATUS.FILLED
elif order_status['status'] == 'open':
elif s == 'open':
status = ORDER_STATUS.OPEN
elif filled > 0:
log.info(
'order {id} partially filled: {filled} {symbol} out of '
'{amount}, waiting for complete execution'.format(
id=order_id,
filled=filled,
symbol=asset.symbol,
amount=amount,
)
)
status = ORDER_STATUS.OPEN
else:
raise ValueError('invalid state for order')
amount = order_status['amount']
filled = order_status['filled']
log.warn(
'invalid state {} for order {}'.format(
s, order_id
)
)
status = ORDER_STATUS.OPEN
if order_status['side'] == 'sell':
amount = -amount
@@ -423,25 +644,16 @@ class CCXT(Exchange):
order_type = order_status['type']
limit_price = price if order_type == 'limit' else None
stop_price = None # TODO: add support
executed_price = order_status['cost'] / order_status['amount']
commission = order_status['fee']
date = from_ms_timestamp(order_status['timestamp'])
# order_id = str(order_status['info']['clientOrderId'])
order_id = order_status['id']
# TODO: this won't work, redo the packages with a different key.
symbol = order_status['info']['symbol'] \
if 'symbol' in order_status['info'] \
else order_status['info']['Exchange']
order = Order(
dt=date,
asset=self.get_asset(symbol, is_exchange_symbol=True),
asset=asset,
amount=amount,
stop=stop_price,
stop=None,
limit=limit_price,
filled=filled,
id=order_id,
@@ -469,7 +681,6 @@ class CCXT(Exchange):
)
side = 'buy' if amount > 0 else 'sell'
if hasattr(self.api, 'amount_to_lots'):
adj_amount = self.api.amount_to_lots(
symbol=symbol,
@@ -583,10 +794,19 @@ class CCXT(Exchange):
"""
tickers = dict()
for asset in assets:
try:
ccxt_symbol = self.get_symbol(asset)
ticker = self.api.fetch_ticker(ccxt_symbol)
try:
for asset in assets:
symbol = self.get_symbol(asset)
# TODO: use fetch_tickers() for efficiency
# I tried using fetch_tickers() but noticed some
# inconsistencies, see issue:
# https://github.com/ccxt/ccxt/issues/870
ticker = self.api.fetch_ticker(symbol=symbol)
if not ticker:
log.warn('ticker not found for {} {}'.format(
self.name, symbol
))
continue
ticker['last_traded'] = from_ms_timestamp(ticker['timestamp'])
@@ -594,19 +814,27 @@ class CCXT(Exchange):
# TODO: any more exceptions?
ticker['last_price'] = ticker['last']
# Using the volume represented in the base currency
ticker['volume'] = ticker['baseVolume'] \
if 'baseVolume' in ticker else 0
if 'baseVolume' in ticker and ticker['baseVolume'] is not None:
# Using the volume represented in the base currency
ticker['volume'] = ticker['baseVolume']
elif 'info' in ticker and 'bidQty' in ticker['info'] \
and 'askQty' in ticker['info']:
ticker['volume'] = float(ticker['info']['bidQty']) + \
float(ticker['info']['askQty'])
else:
ticker['volume'] = 0
tickers[asset] = ticker
except ExchangeNotAvailable as e:
log.warn(
'unable to fetch ticker: {} {}'.format(
self.name, asset.symbol
)
except ExchangeNotAvailable as e:
log.warn(
'unable to fetch ticker: {} {}'.format(
self.name, asset.symbol
)
raise ExchangeRequestError(error=e)
)
raise ExchangeRequestError(error=e)
return tickers
+122 -37
View File
@@ -9,15 +9,16 @@ from logbook import Logger
from catalyst.constants import LOG_LEVEL
from catalyst.data.data_portal import BASE_FIELDS
from catalyst.exchange.bundle_utils import get_start_dt, \
get_delta, get_periods, get_periods_range
from catalyst.exchange.exchange_bundle import ExchangeBundle
from catalyst.exchange.exchange_errors import MismatchingBaseCurrencies, \
BaseCurrencyNotFoundError, SymbolNotFoundOnExchange, \
SymbolNotFoundOnExchange, \
PricingDataNotLoadedError, \
NoDataAvailableOnExchange, NoValueForField, LastCandleTooEarlyError
from catalyst.exchange.exchange_utils import get_exchange_symbols, \
get_frequency, resample_history_df
NoDataAvailableOnExchange, NoValueForField, LastCandleTooEarlyError, \
TickerNotFoundError, NotEnoughCashError
from catalyst.exchange.utils.bundle_utils import get_start_dt, \
get_delta, get_periods, get_periods_range
from catalyst.exchange.utils.exchange_utils import get_exchange_symbols, \
get_frequency, resample_history_df, has_bundle
log = Logger('Exchange', level=LOG_LEVEL)
@@ -38,6 +39,8 @@ class Exchange:
self.request_cpt = None
self.bundle = ExchangeBundle(self.name)
self.low_balance_threshold = None
@abstractproperty
def account(self):
pass
@@ -46,6 +49,9 @@ class Exchange:
def time_skew(self):
pass
def has_bundle(self, data_frequency):
return has_bundle(self.name, data_frequency)
def is_open(self, dt):
"""
Is the exchange open
@@ -148,7 +154,7 @@ class Exchange:
def get_assets(self, symbols=None, data_frequency=None,
is_exchange_symbol=False,
is_local=None):
is_local=None, quote_currency=None):
"""
The list of markets for the specified symbols.
@@ -172,6 +178,14 @@ class Exchange:
if symbols is None:
# Make a distinct list of all symbols
symbols = list(set([asset.symbol for asset in self.assets]))
if quote_currency is not None:
for symbol in symbols[:]:
suffix = '_{}'.format(quote_currency.lower())
if not symbol.endswith(suffix):
symbols.remove(symbol)
is_exchange_symbol = False
assets = []
@@ -235,10 +249,10 @@ class Exchange:
elif data_frequency is not None:
applies = (
(
data_frequency == 'minute' and a.end_minute is not None)
or (
data_frequency == 'daily' and a.end_daily is not None)
(
data_frequency == 'minute' and a.end_minute is not None)
or (
data_frequency == 'daily' and a.end_daily is not None)
)
else:
@@ -247,8 +261,16 @@ class Exchange:
# The symbol provided may use the Catalyst or the exchange
# convention
key = a.exchange_symbol if is_exchange_symbol else a.symbol
if not asset and key.lower() == symbol.lower() and applies:
asset = a
if not asset and key.lower() == symbol.lower():
if applies:
asset = a
else:
raise NoDataAvailableOnExchange(
symbol=key,
exchange=self.name,
data_frequency=data_frequency,
)
if asset is None:
supported_symbols = sorted([a.symbol for a in self.assets])
@@ -272,6 +294,16 @@ class Exchange:
self._symbol_maps[index] = symbol_map
return symbol_map
@abstractmethod
def init(self):
"""
Load the asset list from the network.
Returns
-------
"""
@abstractmethod
def load_assets(self, is_local=False):
"""
@@ -377,6 +409,7 @@ class Exchange:
return value
# TODO: replace with catalyst.exchange.exchange_utils.get_candles_df
def get_series_from_candles(self, candles, start_dt, end_dt,
data_frequency, field, previous_value=None):
"""
@@ -619,46 +652,98 @@ class Exchange:
return df
def calculate_totals(self, check_cash=False, positions=None):
def _check_low_balance(self, currency, balances, amount):
free = balances[currency]['free'] if currency in balances else 0.0
if free < amount:
return free, True
else:
return free, False
def sync_positions(self, positions, cash=None, check_balances=False):
"""
Update the portfolio cash and position balances based on the
latest ticker prices.
Parameters
----------
positions:
The positions to synchronize.
check_balances:
Check balances amounts against the exchange.
"""
log.debug('synchronizing portfolio with exchange {}'.format(self.name))
cash = None
if check_cash:
free_cash = 0.0
if check_balances:
log.debug('fetching {} balances'.format(self.name))
balances = self.get_balances()
cash = balances[self.base_currency]['free'] \
if self.base_currency in balances else None
if cash is None:
raise BaseCurrencyNotFoundError(
base_currency=self.base_currency,
exchange=self.name
log.debug(
'got free balances for {} currencies'.format(
len(balances)
)
log.debug('found base currency balance: {}'.format(cash))
)
if cash is not None:
free_cash, is_lower = self._check_low_balance(
currency=self.base_currency,
balances=balances,
amount=cash,
)
if is_lower:
raise NotEnoughCashError(
currency=self.base_currency,
exchange=self.name,
free=free_cash,
cash=cash,
)
positions_value = 0.0
if positions:
if positions is not None:
assets = set([position.asset for position in positions])
tickers = self.tickers(assets)
log.debug('got tickers for positions: {}'.format(tickers))
for asset in tickers:
for position in positions:
asset = position.asset
if asset not in tickers:
raise TickerNotFoundError(
symbol=asset.symbol,
exchange=self.name,
)
ticker = tickers[asset]
positions = [p for p in positions if p.asset == asset]
log.debug(
'updating {symbol} position, last traded on {dt} for '
'{price}{currency}'.format(
symbol=asset.symbol,
dt=ticker['last_traded'],
price=ticker['last_price'],
currency=asset.quote_currency,
)
)
position.last_sale_price = ticker['last_price']
position.last_sale_date = ticker['last_traded']
for position in positions:
position.last_sale_price = ticker['last_price']
position.last_sale_date = ticker['last_traded']
positions_value += \
position.amount * position.last_sale_price
positions_value += \
position.amount * position.last_sale_price
if check_balances:
free, is_lower = self._check_low_balance(
currency=asset.base_currency,
balances=balances,
amount=position.amount,
)
return cash, positions_value
if is_lower:
log.warn(
'detected lower balance for {} on {}: {} < {}, '
'updating position amount'.format(
asset.symbol, self.name, free, position.amount
)
)
position.amount = free
return free_cash, positions_value
def order(self, asset, amount, style):
"""Place an order.
+215 -157
View File
@@ -10,16 +10,17 @@
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import copy
import pickle
import signal
import sys
from datetime import timedelta
from os import listdir
from os.path import isfile, join
from time import sleep
import logbook
import pandas as pd
from redo import retry
import catalyst.protocol as zp
from catalyst.algorithm import TradingAlgorithm
@@ -27,21 +28,21 @@ from catalyst.constants import LOG_LEVEL
from catalyst.exchange.exchange_blotter import ExchangeBlotter
from catalyst.exchange.exchange_errors import (
ExchangeRequestError,
ExchangePortfolioDataError,
OrderTypeNotSupported, )
OrderTypeNotSupported)
from catalyst.exchange.exchange_execution import ExchangeLimitOrder
from catalyst.exchange.exchange_utils import (
from catalyst.exchange.live_graph_clock import LiveGraphClock
from catalyst.exchange.simple_clock import SimpleClock
from catalyst.exchange.utils.exchange_utils import (
save_algo_object,
get_algo_object,
get_algo_folder,
get_algo_df,
save_algo_df,
group_assets_by_exchange, )
from catalyst.exchange.live_graph_clock import LiveGraphClock
from catalyst.exchange.simple_clock import SimpleClock
from catalyst.exchange.stats_utils import get_pretty_stats, stats_to_s3, \
from catalyst.exchange.utils.stats_utils import get_pretty_stats, stats_to_s3, \
stats_to_algo_folder
from catalyst.finance.execution import MarketOrder
from catalyst.finance.performance import PerformanceTracker
from catalyst.finance.performance.period import calc_period_stats
from catalyst.gens.tradesimulation import AlgorithmSimulator
from catalyst.utils.api_support import api_method
@@ -70,12 +71,26 @@ class ExchangeTradingAlgorithmBase(TradingAlgorithm):
and self.sim_params.arena == 'backtest':
self.simulate_orders = True
# Operations with retry features
self.attempts = dict(
get_transactions_attempts=5,
order_attempts=5,
synchronize_portfolio_attempts=5,
get_order_attempts=5,
get_open_orders_attempts=5,
cancel_order_attempts=5,
get_spot_value_attempts=5,
get_history_window_attempts=5,
retry_sleeptime=5,
)
self.blotter = ExchangeBlotter(
data_frequency=self.data_frequency,
# Default to NeverCancel in catalyst
cancel_policy=self.cancel_policy,
simulate_orders=self.simulate_orders,
exchanges=self.exchanges
exchanges=self.exchanges,
attempts=self.attempts,
)
@staticmethod
@@ -218,28 +233,28 @@ class ExchangeTradingAlgorithmBase(TradingAlgorithm):
"""
tracker = self.perf_tracker
period = tracker.todays_performance
cum = tracker.cumulative_performance
pos_stats = period.position_tracker.stats()
period_stats = calc_period_stats(pos_stats, period.ending_cash)
pos_stats = cum.position_tracker.stats()
period_stats = calc_period_stats(pos_stats, cum.ending_cash)
stats = dict(
period_start=tracker.period_start,
period_end=tracker.period_end,
capital_base=tracker.capital_base,
progress=tracker.progress,
ending_value=period.ending_value,
ending_exposure=period.ending_exposure,
capital_used=period.cash_flow,
starting_value=period.starting_value,
starting_exposure=period.starting_exposure,
starting_cash=period.starting_cash,
ending_cash=period.ending_cash,
portfolio_value=period.ending_cash + period.ending_value,
pnl=period.pnl,
returns=period.returns,
period_open=period.period_open,
period_close=period.period_close,
ending_value=cum.ending_value,
ending_exposure=cum.ending_exposure,
capital_used=cum.cash_flow,
starting_value=cum.starting_value,
starting_exposure=cum.starting_exposure,
starting_cash=cum.starting_cash,
ending_cash=cum.ending_cash,
portfolio_value=cum.ending_cash + cum.ending_value,
pnl=cum.pnl,
returns=cum.returns,
period_open=start_dt,
period_close=end_dt,
gross_leverage=period_stats.gross_leverage,
net_leverage=period_stats.net_leverage,
short_exposure=pos_stats.short_exposure,
@@ -256,8 +271,9 @@ class ExchangeTradingAlgorithmBase(TradingAlgorithm):
# Merging latest recorded variables
stats.update(self.recorded_vars)
stats['positions'] = period.position_tracker.get_positions_list()
stats['positions'] = cum.position_tracker.get_positions_list()
period = tracker.todays_performance
# we want the key to be absent, not just empty
# Only include transactions for given dt
stats['transactions'] = []
@@ -276,6 +292,12 @@ class ExchangeTradingAlgorithmBase(TradingAlgorithm):
return stats
def run(self, data=None, overwrite_sim_params=True):
data.attempts = self.attempts
return super(ExchangeTradingAlgorithmBase, self).run(
data, overwrite_sim_params
)
class ExchangeTradingAlgorithmBacktest(ExchangeTradingAlgorithmBase):
def __init__(self, *args, **kwargs):
@@ -328,6 +350,7 @@ class ExchangeTradingAlgorithmLive(ExchangeTradingAlgorithmBase):
self.algo_namespace = kwargs.pop('algo_namespace', None)
self.live_graph = kwargs.pop('live_graph', None)
self.stats_output = kwargs.pop('stats_output', None)
self._analyze_live = kwargs.pop('analyze_live', None)
self._clock = None
self.frame_stats = list()
@@ -342,42 +365,30 @@ class ExchangeTradingAlgorithmLive(ExchangeTradingAlgorithmBase):
self.is_running = True
self.retry_check_open_orders = 5
self.retry_synchronize_portfolio = 5
self.retry_get_open_orders = 5
self.retry_order = 2
self.retry_delay = 5
self.stats_minutes = 1
self.stats_minutes = 10
self._last_orders = []
self.trading_client = None
super(ExchangeTradingAlgorithmLive, self).__init__(*args, **kwargs)
signal.signal(signal.SIGINT, self.signal_handler)
try:
signal.signal(signal.SIGINT, self.signal_handler)
except ValueError:
log.warn("Can't initialize signal handler inside another thread."
"Exit should be handled by the user.")
log.info('initialized trading algorithm in live mode')
def signal_handler(self, signal, frame):
"""
Handles the keyboard interruption signal.
Parameters
----------
signal
frame
Returns
-------
"""
def interrupt_algorithm(self):
self.is_running = False
if self._analyze is None:
log.info('Interruption signal detected {}, exiting the '
'algorithm'.format(signal))
log.info('Exiting the algorithm.')
else:
log.info('Interruption signal detected {}, calling `analyze()` '
'before exiting the algorithm'.format(signal))
log.info('Exiting the algorithm. Calling `analyze()` '
'before exiting the algorithm.')
algo_folder = get_algo_folder(self.algo_namespace)
folder = join(algo_folder, 'daily_perf')
@@ -395,6 +406,23 @@ class ExchangeTradingAlgorithmLive(ExchangeTradingAlgorithmBase):
sys.exit(0)
def signal_handler(self, signal, frame):
"""
Handles the keyboard interruption signal.
Parameters
----------
signal
frame
Returns
-------
"""
log.info('Interruption signal detected {}, exiting the '
'algorithm'.format(signal))
self.interrupt_algorithm()
@property
def clock(self):
if self._clock is None:
@@ -419,10 +447,11 @@ class ExchangeTradingAlgorithmLive(ExchangeTradingAlgorithmBase):
# TODO: should we apply time skew? not sure to understand the utility.
log.debug('creating clock')
if self.live_graph:
if self.live_graph or self._analyze_live is not None:
self._clock = LiveGraphClock(
self.sim_params.sessions,
context=self
context=self,
callback=self._analyze_live,
)
else:
self._clock = SimpleClock(
@@ -431,26 +460,52 @@ class ExchangeTradingAlgorithmLive(ExchangeTradingAlgorithmBase):
return self._clock
def _create_generator(self, sim_params):
def get_generator(self):
if self.trading_client is not None:
return self.trading_client.transform()
perf = None
if self.perf_tracker is None:
self.perf_tracker = get_algo_object(
algo_name=self.algo_namespace,
key='perf_tracker'
tracker = self.perf_tracker = PerformanceTracker(
sim_params=self.sim_params,
trading_calendar=self.trading_calendar,
env=self.trading_environment,
)
# Set the dt initially to the period start by forcing it to change.
self.on_dt_changed(self.sim_params.start_session)
# Unpacking the perf_tracker and positions if available
perf = get_algo_object(
algo_name=self.algo_namespace,
key='cumulative_performance',
)
if not self.initialized:
self.initialize(*self.initialize_args, **self.initialize_kwargs)
self.initialized = True
# Call the simulation trading algorithm for side-effects:
# it creates the perf tracker
TradingAlgorithm._create_generator(self, sim_params)
self.trading_client = ExchangeAlgorithmExecutor(
self,
sim_params,
self.data_portal,
self.clock,
self._create_benchmark_source(),
self.restrictions,
universe_func=self._calculate_universe
)
# TradingAlgorithm._create_generator(self, self.sim_params)
if perf is not None:
tracker.cumulative_performance = perf
period = self.perf_tracker.todays_performance
period.starting_cash = perf.ending_cash
period.starting_exposure = perf.ending_exposure
period.starting_value = perf.ending_value
period.position_tracker = perf.position_tracker
self.trading_client = ExchangeAlgorithmExecutor(
algo=self,
sim_params=self.sim_params,
data_portal=self.data_portal,
clock=self.clock,
benchmark_source=self._create_benchmark_source(),
restrictions=self.restrictions,
universe_func=self._calculate_universe,
)
return self.trading_client.transform()
def updated_portfolio(self):
@@ -459,7 +514,7 @@ class ExchangeTradingAlgorithmLive(ExchangeTradingAlgorithmBase):
def updated_account(self):
return self.perf_tracker.get_account(False)
def synchronize_portfolio(self, attempt_index=0):
def synchronize_portfolio(self):
"""
Synchronizes the portfolio tracked by the algorithm to refresh
its current value.
@@ -481,63 +536,51 @@ class ExchangeTradingAlgorithmLive(ExchangeTradingAlgorithmBase):
The total value of all tracked positions.
"""
check_balances = (not self.simulate_orders)
base_currency = None
tracker = self.perf_tracker.position_tracker
total_cash = 0.0
total_positions_value = 0.0
try:
# Position keys correspond to assets
positions = self.portfolio.positions
assets = list(positions)
exchange_assets = group_assets_by_exchange(assets)
for exchange_name in self.exchanges:
assets = exchange_assets[exchange_name] \
if exchange_name in exchange_assets else []
# Position keys correspond to assets
positions = self.portfolio.positions
assets = list(positions)
exchange_assets = group_assets_by_exchange(assets)
for exchange_name in self.exchanges:
assets = exchange_assets[exchange_name] \
if exchange_name in exchange_assets else []
exchange_positions = \
[positions[asset] for asset in assets]
check_cash = (not self.simulate_orders)
exchange = self.exchanges[exchange_name] # Type: Exchange
cash, positions_value = exchange.calculate_totals(
positions=exchange_positions,
check_cash=check_cash,
)
total_positions_value += positions_value
if cash is not None:
total_cash += cash
for position in exchange_positions:
tracker.update_position(
asset=position.asset,
last_sale_date=position.last_sale_date,
last_sale_price=position.last_sale_price
)
if cash is None:
total_cash = self.portfolio.cash
elif total_cash < self.portfolio.cash:
raise ValueError('Cash on exchanges is lower than the algo.')
return total_cash, total_positions_value
except ExchangeRequestError as e:
log.warn(
'update portfolio attempt {}: {}'.format(attempt_index, e)
exchange_positions = copy.deepcopy(
[positions[asset] for asset in assets if asset in positions]
)
if attempt_index < self.retry_synchronize_portfolio:
sleep(self.retry_delay)
return self.synchronize_portfolio(attempt_index + 1)
else:
raise ExchangePortfolioDataError(
data_type='update-portfolio',
attempts=attempt_index,
error=e
exchange = self.exchanges[exchange_name] # Type: Exchange
if base_currency is None:
base_currency = exchange.base_currency
cash, positions_value = exchange.sync_positions(
positions=exchange_positions,
check_balances=check_balances,
cash=self.portfolio.cash,
)
total_cash += cash
total_positions_value += positions_value
# Applying modifications to the original positions
for position in exchange_positions:
tracker.update_position(
asset=position.asset,
amount=position.amount,
last_sale_date=position.last_sale_date,
last_sale_price=position.last_sale_price,
)
if not check_balances:
total_cash = self.portfolio.cash
return total_cash, total_positions_value
def add_pnl_stats(self, period_stats):
"""
Save p&l stats.
@@ -632,13 +675,27 @@ class ExchangeTradingAlgorithmLive(ExchangeTradingAlgorithmBase):
if self.current_day is not None and today > self.current_day:
self.frame_stats = list()
new_transactions, new_commissions, closed_orders = \
self.blotter.get_transactions(data)
self.performance_needs_update = False
new_orders = self.perf_tracker.todays_performance.orders_by_id.keys()
if new_orders != self._last_orders:
self.performance_needs_update = True
if len(new_transactions) > 0:
self._last_orders = new_orders
if self.performance_needs_update:
self.perf_tracker.update_performance()
self.performance_needs_update = False
if self.portfolio_needs_update:
cash, positions_value = retry(
action=self.synchronize_portfolio,
attempts=self.attempts['synchronize_portfolio_attempts'],
sleeptime=self.attempts['retry_sleeptime'],
retry_exceptions=(ExchangeRequestError,),
cleanup=lambda: log.warn('Ordering again.')
)
self.portfolio_needs_update = False
cash, positions_value = self.synchronize_portfolio()
log.info(
'got totals from exchanges, cash: {} positions: {}'.format(
cash, positions_value
@@ -657,15 +714,11 @@ class ExchangeTradingAlgorithmLive(ExchangeTradingAlgorithmBase):
except Exception as e:
log.warn('unable to calculate performance: {}'.format(e))
# TODO: pickle does not seem to work in python 3
try:
save_algo_object(
algo_name=self.algo_namespace,
key='perf_tracker',
obj=self.perf_tracker
)
except Exception as e:
log.warn('unable to save minute perfs to disk: {}'.format(e))
save_algo_object(
algo_name=self.algo_namespace,
key='cumulative_performance',
obj=self.perf_tracker.cumulative_performance,
)
self.current_day = data.current_dt.floor('1D')
@@ -677,7 +730,8 @@ class ExchangeTradingAlgorithmLive(ExchangeTradingAlgorithmBase):
self.perf_tracker.update_performance()
frame_stats = self.prepare_period_stats(
data.current_dt, data.current_dt + timedelta(minutes=1))
data.current_dt, data.current_dt + timedelta(minutes=1)
)
# Saving the last hour in memory
self.frame_stats.append(frame_stats)
@@ -699,7 +753,7 @@ class ExchangeTradingAlgorithmLive(ExchangeTradingAlgorithmBase):
stats=get_pretty_stats(
stats=self.frame_stats,
recorded_cols=recorded_cols,
num_rows=self.stats_minutes
num_rows=self.stats_minutes,
)
))
@@ -751,33 +805,19 @@ class ExchangeTradingAlgorithmLive(ExchangeTradingAlgorithmBase):
def batch_market_order(self, share_counts):
raise NotImplementedError()
def _get_open_orders(self, asset=None, attempt_index=0):
try:
if asset:
exchange = self.exchanges[asset.exchange]
return exchange.get_open_orders(asset)
def _get_open_orders(self, asset=None):
if asset:
exchange = self.exchanges[asset.exchange]
return exchange.get_open_orders(asset)
else:
open_orders = []
for exchange_name in self.exchanges:
exchange = self.exchanges[exchange_name]
exchange_orders = exchange.get_open_orders()
open_orders.append(exchange_orders)
else:
open_orders = []
for exchange_name in self.exchanges:
exchange = self.exchanges[exchange_name]
exchange_orders = exchange.get_open_orders()
open_orders.append(exchange_orders)
return open_orders
except ExchangeRequestError as e:
log.warn(
'open orders attempt {}: {}'.format(attempt_index, e)
)
if attempt_index < self.retry_get_open_orders:
sleep(self.retry_delay)
return self._get_open_orders(asset, attempt_index + 1)
else:
raise ExchangePortfolioDataError(
data_type='open-orders',
attempts=attempt_index,
error=e
)
return open_orders
@error_keywords(sid='Keyword argument `sid` is no longer supported for '
'get_open_orders. Use `asset` instead.')
@@ -799,7 +839,13 @@ class ExchangeTradingAlgorithmLive(ExchangeTradingAlgorithmBase):
If an asset is passed then this will return a list of the open
orders for this asset.
"""
return self._get_open_orders(asset)
return retry(
action=self._get_open_orders,
attempts=self.attempts['get_open_orders_attempts'],
sleeptime=self.attempts['retry_sleeptime'],
retry_exceptions=(ExchangeRequestError,),
cleanup=lambda: log.warn('Fetching open orders again.'),
args=(asset,))
@api_method
def get_order(self, order_id, exchange_name):
@@ -819,7 +865,13 @@ class ExchangeTradingAlgorithmLive(ExchangeTradingAlgorithmBase):
The execution price per share of the order
"""
exchange = self.exchanges[exchange_name]
return exchange.get_order(order_id)
return retry(
action=exchange.get_order,
attempts=self.attempts['get_order_attempts'],
sleeptime=self.attempts['retry_sleeptime'],
retry_exceptions=(ExchangeRequestError,),
cleanup=lambda: log.warn('Fetching orders again.'),
args=(order_id,))
@api_method
def cancel_order(self, order_param, exchange_name):
@@ -836,4 +888,10 @@ class ExchangeTradingAlgorithmLive(ExchangeTradingAlgorithmBase):
if isinstance(order_param, zp.Order):
order_id = order_param.id
exchange.cancel_order(order_id)
retry(
action=exchange.cancel_order,
attempts=self.attempts['cancel_order_attempts'],
sleeptime=self.attempts['retry_sleeptime'],
retry_exceptions=(ExchangeRequestError,),
cleanup=lambda: log.warn('cancelling order again.'),
args=(order_id,))
+180
View File
@@ -0,0 +1,180 @@
import pandas as pd
from logbook import Logger
from catalyst.constants import LOG_LEVEL
from catalyst.exchange.utils.factory import find_exchanges
log = Logger('ExchangeAssetFinder', level=LOG_LEVEL)
class ExchangeAssetFinder(object):
def __init__(self, exchanges):
self.exchanges = exchanges
@property
def sids(self):
"""
This seems to be used to pre-fetch assets.
I don't think that we need this for live-trading.
Leaving the list empty.
"""
all_sids = []
for exchange_name in self.exchanges:
# This is what initializes each exchanges at the beginning
# of an algo
exchange = self.exchanges[exchange_name]
exchange.init()
all_sids += [asset.sid for asset in exchange.assets]
sids = list(set(all_sids))
return sids
def retrieve_asset(self, sid, default_none=False):
"""
Retrieve the first Asset found for a given sid.
"""
asset = None
for exchange_name in self.exchanges:
if asset is not None:
break
exchange = self.exchanges[exchange_name]
assets = [asset for asset in exchange.assets if asset.sid == sid]
if assets:
asset = assets[0]
return asset
def retrieve_all(self, sids, default_none=False):
"""
Retrieve all assets in `sids`.
Parameters
----------
sids : iterable of int
Assets to retrieve.
default_none : bool
If True, return None for failed lookups.
If False, raise `SidsNotFound`.
Returns
-------
assets : list[Asset or None]
A list of the same length as `sids` containing Assets (or Nones)
corresponding to the requested sids.
Raises
------
SidsNotFound
When a requested sid is not found and default_none=False.
"""
assets = []
for exchange_name in self.exchanges:
exchange = self.exchanges[exchange_name]
xas = [asset for asset in exchange.assets if asset.sid in sids]
assets += xas
return assets
def lookup_symbol(self, symbol, exchange, data_frequency=None,
as_of_date=None, fuzzy=False):
"""Lookup an asset by symbol.
Parameters
----------
symbol : str
The ticker symbol to resolve.
as_of_date : datetime or None
Look up the last owner of this symbol as of this datetime.
If ``as_of_date`` is None, then this can only resolve the equity
if exactly one equity has ever owned the ticker.
fuzzy : bool, optional
Should fuzzy symbol matching be used? Fuzzy symbol matching
attempts to resolve differences in representations for
shareclasses. For example, some people may represent the ``A``
shareclass of ``BRK`` as ``BRK.A``, where others could write
``BRK_A``.
Returns
-------
equity : Asset
The equity that held ``symbol`` on the given ``as_of_date``, or the
only equity to hold ``symbol`` if ``as_of_date`` is None.
Raises
------
SymbolNotFound
Raised when no equity has ever held the given symbol.
MultipleSymbolsFound
Raised when no ``as_of_date`` is given and more than one equity
has held ``symbol``. This is also raised when ``fuzzy=True`` and
there are multiple candidates for the given ``symbol`` on the
``as_of_date``.
"""
log.debug('looking up symbol: {} {}'.format(symbol, exchange.name))
return exchange.get_asset(symbol, data_frequency)
def lifetimes(self, dates, include_start_date):
"""
Compute a DataFrame representing asset lifetimes for the specified date
range.
Parameters
----------
dates : pd.DatetimeIndex
The dates for which to compute lifetimes.
include_start_date : bool
Whether or not to count the asset as alive on its start_date.
This is useful in a backtesting context where `lifetimes` is being
used to signify "do I have data for this asset as of the morning of
this date?" For many financial metrics, (e.g. daily close), data
isn't available for an asset until the end of the asset's first
day.
Returns
-------
lifetimes : pd.DataFrame
A frame of dtype bool with `dates` as index and an Int64Index of
assets as columns. The value at `lifetimes.loc[date, asset]` will
be True iff `asset` existed on `date`. If `include_start_date` is
False, then lifetimes.loc[date, asset] will be false when date ==
asset.start_date.
See Also
--------
numpy.putmask
catalyst.pipeline.engine.SimplePipelineEngine._compute_root_mask
"""
exchanges = find_exchanges(features=['minuteBundle'])
if not exchanges:
raise ValueError('exchange with minute bundles not found')
# TODO: find a way to support multiple exchanges
exchange = exchanges[0]
# Using a single exchange for now because are not unique for the
# same asset in different exchanges. I'd like to avoid binding
# pipeline to a single exchange.
exchange.init()
data = []
for dt in dates:
exists = []
for asset in exchange.assets:
if include_start_date:
condition = (asset.start_date <= dt < asset.end_minute)
else:
condition = (asset.start_date < dt < asset.end_minute)
exists.append(condition)
data.append(exists)
sids = [asset.sid for asset in exchange.assets]
df = pd.DataFrame(data, index=dates, columns=exchange.assets)
return df
+38 -61
View File
@@ -1,15 +1,13 @@
from time import sleep
import pandas as pd
from catalyst.assets._assets import TradingPair
from logbook import Logger
from redo import retry
from catalyst.constants import LOG_LEVEL
from catalyst.exchange.exchange_errors import ExchangeRequestError, \
ExchangePortfolioDataError, ExchangeTransactionError
from catalyst.exchange.exchange_errors import ExchangeRequestError
from catalyst.finance.blotter import Blotter
from catalyst.finance.commission import CommissionModel
from catalyst.finance.order import ORDER_STATUS, Order
from catalyst.finance.order import ORDER_STATUS
from catalyst.finance.slippage import SlippageModel
from catalyst.finance.transaction import create_transaction, Transaction
from catalyst.utils.input_validation import expect_types
@@ -60,12 +58,13 @@ class TradingPairFeeSchedule(CommissionModel):
maker = self.maker if self.maker is not None else asset.maker
taker = self.taker if self.taker is not None else asset.taker
multiplier = maker \
if ((order.amount > 0 and order.limit < transaction.price)
or (order.amount < 0 and order.limit > transaction.price)) \
and order.limit_reached else taker
multiplier = taker
if order.limit is not None:
multiplier = maker \
if ((order.amount > 0 and order.limit < transaction.price)
or (order.amount < 0 and order.limit > transaction.price)) \
and order.limit_reached else taker
# Assuming just the taker fee for now
fee = cost * multiplier
return fee
@@ -132,6 +131,7 @@ class TradingPairFixedSlippage(SlippageModel):
class ExchangeBlotter(Blotter):
def __init__(self, *args, **kwargs):
self.simulate_orders = kwargs.pop('simulate_orders', False)
self.attempts = kwargs.pop('attempts', False)
self.exchanges = kwargs.pop('exchanges', None)
if not self.exchanges:
@@ -151,31 +151,11 @@ class ExchangeBlotter(Blotter):
TradingPair: TradingPairFeeSchedule()
}
self.retry_delay = 5
self.retry_check_open_orders = 5
def exchange_order(self, asset, amount, style=None, attempt_index=0):
try:
exchange = self.exchanges[asset.exchange]
return exchange.order(
asset, amount, style
)
except ExchangeRequestError as e:
log.warn(
'order attempt {}: {}'.format(attempt_index, e)
)
if attempt_index < self.retry_order:
sleep(self.retry_delay)
return self.exchange_order(
asset, amount, style, attempt_index + 1
)
else:
raise ExchangeTransactionError(
transaction_type='order',
attempts=attempt_index,
error=e
)
def exchange_order(self, asset, amount, style=None):
exchange = self.exchanges[asset.exchange]
return exchange.order(
asset, amount, style
)
@expect_types(asset=TradingPair)
def order(self, asset, amount, style, order_id=None):
@@ -190,8 +170,13 @@ class ExchangeBlotter(Blotter):
)
else:
order = self.exchange_order(
asset, amount, style
order = retry(
action=self.exchange_order,
attempts=self.attempts['order_attempts'],
sleeptime=self.attempts['retry_sleeptime'],
retry_exceptions=(ExchangeRequestError,),
cleanup=lambda: log.warn('Ordering again.'),
args=(asset, amount, style),
)
self.open_orders[order.asset].append(order)
@@ -258,40 +243,32 @@ class ExchangeBlotter(Blotter):
)
)
def get_exchange_transactions(self, attempt_index=0):
def get_exchange_transactions(self):
closed_orders = []
transactions = []
commissions = []
try:
for order, txn in self.check_open_orders():
order.dt = txn.dt
for order, txn in self.check_open_orders():
order.dt = txn.dt
transactions.append(txn)
transactions.append(txn)
if not order.open:
closed_orders.append(order)
if not order.open:
closed_orders.append(order)
return transactions, commissions, closed_orders
except ExchangeRequestError as e:
log.warn(
'check open orders attempt {}: {}'.format(attempt_index, e)
)
if attempt_index < self.retry_check_open_orders:
sleep(self.retry_delay)
return self.get_exchange_transactions(attempt_index + 1)
else:
raise ExchangePortfolioDataError(
data_type='order-status',
attempts=attempt_index,
error=e
)
return transactions, commissions, closed_orders
def get_transactions(self, bar_data):
if self.simulate_orders:
return super(ExchangeBlotter, self).get_transactions(bar_data)
else:
return self.get_exchange_transactions()
return retry(
action=self.get_exchange_transactions,
attempts=self.attempts['get_transactions_attempts'],
sleeptime=self.attempts['retry_sleeptime'],
retry_exceptions=(ExchangeRequestError,),
cleanup=lambda: log.warn(
'Fetching exchange transactions again.'
)
)
+13 -11
View File
@@ -18,18 +18,18 @@ from catalyst.constants import DATE_TIME_FORMAT, AUTO_INGEST
from catalyst.constants import LOG_LEVEL
from catalyst.data.minute_bars import BcolzMinuteOverlappingData, \
BcolzMinuteBarMetadata
from catalyst.exchange.bundle_utils import range_in_bundle, \
get_bcolz_chunk, get_month_start_end, \
get_year_start_end, get_df_from_arrays, get_start_dt, get_period_label, \
get_delta, get_assets
from catalyst.exchange.exchange_bcolz import BcolzExchangeBarReader, \
BcolzExchangeBarWriter
from catalyst.exchange.exchange_errors import EmptyValuesInBundleError, \
TempBundleNotFoundError, \
NoDataAvailableOnExchange, \
PricingDataNotLoadedError, DataCorruptionError, PricingDataValueError
from catalyst.exchange.exchange_utils import get_exchange_folder, \
save_exchange_symbols, mixin_market_params
from catalyst.exchange.utils.bundle_utils import range_in_bundle, \
get_bcolz_chunk, get_month_start_end, \
get_year_start_end, get_df_from_arrays, get_start_dt, get_period_label, \
get_delta, get_assets
from catalyst.exchange.utils.exchange_utils import get_exchange_folder, \
save_exchange_symbols, mixin_market_params, get_catalyst_symbol
from catalyst.utils.cli import maybe_show_progress
from catalyst.utils.paths import ensure_directory
@@ -462,7 +462,7 @@ class ExchangeBundle:
(earliest_trade is not None and earliest_trade > start):
start = earliest_trade
if end is None or (last_entry is not None and end > last_entry):
if last_entry is not None and (end is None or end > last_entry):
end = last_entry.replace(minute=59, hour=23) \
if data_frequency == 'minute' else last_entry
@@ -668,7 +668,7 @@ class ExchangeBundle:
if self.exchange is None:
# Avoid circular dependencies
from catalyst.exchange.factory import get_exchange
from catalyst.exchange.utils.factory import get_exchange
self.exchange = get_exchange(self.exchange_name)
problems = []
@@ -681,6 +681,7 @@ class ExchangeBundle:
last_traded=np.object_,
open=np.float64,
high=np.float64,
low=np.float64,
close=np.float64,
volume=np.float64
),
@@ -730,7 +731,7 @@ class ExchangeBundle:
if data_frequency == 'minute' else asset_def['end_minute']
else:
params['symbol'] = self.exchange.get_catalyst_symbol(market)
params['symbol'] = get_catalyst_symbol(market)
params['end_daily'] = end_dt \
if data_frequency == 'daily' else 'N/A'
@@ -755,9 +756,10 @@ class ExchangeBundle:
)
for symbol in assets:
# here the symbol is the market['id']
asset = assets[symbol]
ohlcv_df = df.loc[
(df.index.get_level_values(0) == symbol)
(df.index.get_level_values(0) == asset.symbol)
] # type: pd.DataFrame
ohlcv_df.index = ohlcv_df.index.droplevel(0)
@@ -805,7 +807,7 @@ class ExchangeBundle:
else:
if self.exchange is None:
# Avoid circular dependencies
from catalyst.exchange.factory import get_exchange
from catalyst.exchange.utils.factory import get_exchange
self.exchange = get_exchange(self.exchange_name)
assets = get_assets(
+86 -115
View File
@@ -1,19 +1,18 @@
import abc
from time import sleep
import numpy as np
import pandas as pd
from catalyst.assets._assets import TradingPair
from logbook import Logger
from redo import retry
from catalyst.constants import LOG_LEVEL, AUTO_INGEST
from catalyst.data.data_portal import DataPortal
from catalyst.exchange.exchange_bundle import ExchangeBundle
from catalyst.exchange.exchange_errors import (
ExchangeRequestError,
ExchangeBarDataError,
PricingDataNotLoadedError)
from catalyst.exchange.exchange_utils import get_frequency, \
from catalyst.exchange.utils.exchange_utils import get_frequency, \
resample_history_df, group_assets_by_exchange
log = Logger('DataPortalExchange', level=LOG_LEVEL)
@@ -21,11 +20,11 @@ log = Logger('DataPortalExchange', level=LOG_LEVEL)
class DataPortalExchangeBase(DataPortal):
def __init__(self, *args, **kwargs):
# TODO: put somewhere accessible by each algo
self.retry_get_history_window = 5
self.retry_get_spot_value = 5
self.retry_delay = 5
self.attempts = dict(
get_spot_value_attempts=5,
get_history_window_attempts=5,
retry_sleeptime=5,
)
super(DataPortalExchangeBase, self).__init__(*args, **kwargs)
@@ -36,33 +35,14 @@ class DataPortalExchangeBase(DataPortal):
frequency,
field,
data_frequency,
ffill=True,
attempt_index=0):
try:
exchange_assets = group_assets_by_exchange(assets)
if len(exchange_assets) > 1:
df_list = []
for exchange_name in exchange_assets:
assets = exchange_assets[exchange_name]
ffill=True):
exchange_assets = group_assets_by_exchange(assets)
if len(exchange_assets) > 1:
df_list = []
for exchange_name in exchange_assets:
assets = exchange_assets[exchange_name]
df_exchange = self.get_exchange_history_window(
exchange_name,
assets,
end_dt,
bar_count,
frequency,
field,
data_frequency,
ffill)
df_list.append(df_exchange)
# Merging the values values of each exchange
return pd.concat(df_list)
else:
exchange_name = list(exchange_assets.keys())[0]
return self.get_exchange_history_window(
df_exchange = self.get_exchange_history_window(
exchange_name,
assets,
end_dt,
@@ -72,26 +52,22 @@ class DataPortalExchangeBase(DataPortal):
data_frequency,
ffill)
except ExchangeRequestError as e:
log.warn(
'get history attempt {}: {}'.format(attempt_index, e)
)
if attempt_index < self.retry_get_history_window:
sleep(self.retry_delay)
return self._get_history_window(assets,
end_dt,
bar_count,
frequency,
field,
data_frequency,
ffill,
attempt_index + 1)
else:
raise ExchangeBarDataError(
data_type='history',
attempts=attempt_index,
error=e
)
df_list.append(df_exchange)
# Merging the values values of each exchange
return pd.concat(df_list)
else:
exchange_name = list(exchange_assets.keys())[0]
return self.get_exchange_history_window(
exchange_name,
assets,
end_dt,
bar_count,
frequency,
field,
data_frequency,
ffill)
def get_history_window(self,
assets,
@@ -105,13 +81,19 @@ class DataPortalExchangeBase(DataPortal):
if field == 'price':
field = 'close'
return self._get_history_window(assets,
end_dt,
bar_count,
frequency,
field,
data_frequency,
ffill)
return retry(
action=self._get_history_window,
attempts=self.attempts['get_history_window_attempts'],
sleeptime=self.attempts['retry_sleeptime'],
retry_exceptions=(ExchangeRequestError,),
cleanup=lambda: log.warn('fetching history again.'),
args=(assets,
end_dt,
bar_count,
frequency,
field,
data_frequency,
ffill))
@abc.abstractmethod
def get_exchange_history_window(self,
@@ -125,69 +107,58 @@ class DataPortalExchangeBase(DataPortal):
ffill=True):
pass
def _get_spot_value(self, assets, field, dt, data_frequency,
attempt_index=0):
try:
if isinstance(assets, TradingPair):
spot_values = self.get_exchange_spot_value(
assets.exchange, [assets], field, dt, data_frequency)
def _get_spot_value(self, assets, field, dt, data_frequency):
if isinstance(assets, TradingPair):
spot_values = self.get_exchange_spot_value(
assets.exchange, [assets], field, dt, data_frequency)
if not spot_values:
return np.nan
if not spot_values:
return np.nan
return spot_values[0]
return spot_values[0]
else:
exchange_assets = dict()
for asset in assets:
if asset.exchange not in exchange_assets:
exchange_assets[asset.exchange] = list()
exchange_assets[asset.exchange].append(asset)
if len(list(exchange_assets.keys())) == 1:
exchange_name = list(exchange_assets.keys())[0]
return self.get_exchange_spot_value(
exchange_name, assets, field, dt, data_frequency)
else:
exchange_assets = dict()
for asset in assets:
if asset.exchange not in exchange_assets:
exchange_assets[asset.exchange] = list()
spot_values = []
for exchange_name in exchange_assets:
assets = exchange_assets[exchange_name]
exchange_spot_values = self.get_exchange_spot_value(
exchange_name,
assets,
field,
dt,
data_frequency
)
if len(assets) == 1:
spot_values.append(exchange_spot_values)
else:
spot_values += exchange_spot_values
exchange_assets[asset.exchange].append(asset)
if len(list(exchange_assets.keys())) == 1:
exchange_name = list(exchange_assets.keys())[0]
return self.get_exchange_spot_value(
exchange_name, assets, field, dt, data_frequency)
else:
spot_values = []
for exchange_name in exchange_assets:
assets = exchange_assets[exchange_name]
exchange_spot_values = self.get_exchange_spot_value(
exchange_name,
assets,
field,
dt,
data_frequency
)
if len(assets) == 1:
spot_values.append(exchange_spot_values)
else:
spot_values += exchange_spot_values
return spot_values
except ExchangeRequestError as e:
log.warn(
'get spot value attempt {}: {}'.format(attempt_index, e)
)
if attempt_index < self.retry_get_spot_value:
sleep(self.retry_delay)
return self._get_spot_value(assets, field, dt, data_frequency,
attempt_index + 1)
else:
raise ExchangeBarDataError(
data_type='spot',
attempts=attempt_index,
error=e
)
return spot_values
def get_spot_value(self, assets, field, dt, data_frequency):
if field == 'price':
field = 'close'
return self._get_spot_value(assets, field, dt, data_frequency)
return retry(
action=self._get_spot_value,
attempts=self.attempts['get_spot_value_attempts'],
sleeptime=self.attempts['retry_sleeptime'],
retry_exceptions=(ExchangeRequestError,),
cleanup=lambda: log.warn('fetching spot value again.'),
args=(assets, field, dt, data_frequency))
@abc.abstractmethod
def get_exchange_spot_value(self, exchange_name, assets, field, dt,
@@ -339,7 +310,7 @@ class DataPortalExchangeBacktest(DataPortalExchangeBase):
field=field,
data_frequency=adj_data_frequency,
algo_end_dt=self._last_available_session,
trailing_bar_count=trailing_bar_count
trailing_bar_count=trailing_bar_count,
)
df = resample_history_df(pd.DataFrame(series), freq, field)
+60 -14
View File
@@ -100,6 +100,12 @@ class InvalidHistoryFrequencyError(ZiplineError):
).strip()
class InvalidHistoryTimeframeError(ZiplineError):
msg = (
'CCXT timeframe {timeframe} not supported by the exchange.'
).strip()
class MismatchingFrequencyError(ZiplineError):
msg = (
'Bar aggregate frequency {frequency} not compatible with '
@@ -162,8 +168,8 @@ class SidHashError(ZiplineError):
class BaseCurrencyNotFoundError(ZiplineError):
msg = (
'Algorithm base currency {base_currency} not found in exchange '
'{exchange}.'
'Algorithm base currency {base_currency} not found in account '
'balances on {exchange}: {balances}'
).strip()
@@ -226,16 +232,20 @@ class PricingDataValueError(ZiplineError):
class DataCorruptionError(ZiplineError):
msg = ('Unable to validate data for {exchange} {symbols} in date range '
'[{start_dt} - {end_dt}]. The data is either corrupted or '
'unavailable. Please try deleting this bundle:'
'\n`catalyst clean-exchange -x {exchange}\n'
'Then, ingest the data again. Please contact the Catalyst team if '
'the issue persists.').strip()
msg = (
'Unable to validate data for {exchange} {symbols} in date range '
'[{start_dt} - {end_dt}]. The data is either corrupted or '
'unavailable. Please try deleting this bundle:'
'\n`catalyst clean-exchange -x {exchange}\n'
'Then, ingest the data again. Please contact the Catalyst team if '
'the issue persists.'
).strip()
class ApiCandlesError(ZiplineError):
msg = ('Unable to fetch candles from the remote API: {error}.').strip()
msg = (
'Unable to fetch candles from the remote API: {error}.'
).strip()
class NoDataAvailableOnExchange(ZiplineError):
@@ -248,13 +258,16 @@ class NoDataAvailableOnExchange(ZiplineError):
class NoValueForField(ZiplineError):
msg = ('Value not found for field: {field}.').strip()
msg = (
'Value not found for field: {field}.'
).strip()
class OrderTypeNotSupported(ZiplineError):
msg = (
'Order type `{order_type}` not currencly supported by Catalyst. '
'Please use `limit` or `market` orders only.').strip()
'Order type `{order_type}` not currency supported by Catalyst. '
'Please use `limit` or `market` orders only.'
).strip()
class NotEnoughCapitalError(ZiplineError):
@@ -262,10 +275,43 @@ class NotEnoughCapitalError(ZiplineError):
'Not enough capital on exchange {exchange} for trading. Each '
'exchange should contain at least as much {base_currency} '
'as the specified `capital_base`. The current balance {balance} is '
'lower than the `capital_base`: {capital_base}').strip()
'lower than the `capital_base`: {capital_base}'
).strip()
class NotEnoughCashError(ZiplineError):
msg = (
'Total {currency} amount on {exchange} is lower than the cash '
'reserved for this algo: {free} < {cash}. While trades can be made on '
'the exchange accounts outside of the algo, exchange must have enough '
'free {currency} to cover the algo cash.'
).strip()
class LastCandleTooEarlyError(ZiplineError):
msg = (
'The trade date of the last candle {last_traded} is before the '
'specified end date minus one candle {end_dt}. Please verify how '
'{exchange} calculates the start date of OHLCV candles.').strip()
'{exchange} calculates the start date of OHLCV candles.'
).strip()
class TickerNotFoundError(ZiplineError):
msg = (
'Unable to fetch ticker for {symbol} on {exchange}.'
).strip()
class BalanceNotFoundError(ZiplineError):
msg = (
'{currency} not found in account balance on {exchange}: {balances}.'
).strip()
class BalanceTooLowError(ZiplineError):
msg = (
'Balance for {currency} on {exchange} too low: {free} < {amount}. '
'Positions have likely been sold outside of this algorithm. Please '
'add positions to hold a free amount greater than {amount}, or clean '
'the state of this algo and restart.'
).strip()
@@ -0,0 +1,178 @@
# Copyright 2015 Quantopian, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from logbook import Logger
from numpy import (
iinfo,
uint32,
)
from catalyst.constants import LOG_LEVEL
from catalyst.data.us_equity_pricing import BcolzDailyBarReader
from catalyst.errors import NoFurtherDataError
from catalyst.exchange.utils.factory import get_exchange
from catalyst.lib.adjusted_array import AdjustedArray
from catalyst.pipeline.data import DataSet, Column
from catalyst.pipeline.loaders.base import PipelineLoader
from catalyst.utils.calendars import get_calendar
from catalyst.utils.numpy_utils import float64_dtype
UINT32_MAX = iinfo(uint32).max
log = Logger('ExchangePriceLoader', level=LOG_LEVEL)
class TradingPairPricing(DataSet):
"""
Dataset representing daily trading prices and volumes.
"""
open = Column(float64_dtype)
high = Column(float64_dtype)
low = Column(float64_dtype)
close = Column(float64_dtype)
volume = Column(float64_dtype)
class ExchangePricingLoader(PipelineLoader):
"""
PipelineLoader for Crypto Pricing data
Delegates loading of baselines and adjustments.
"""
def __init__(self, data_frequency):
cal = get_calendar('OPEN')
if data_frequency == 'daily':
reader = None
all_sessions = cal.all_sessions
elif data_frequency == 'minute':
reader = None
all_sessions = cal.all_minutes
else:
raise ValueError(
'Invalid data frequency: {}'.format(data_frequency)
)
self.data_frequency = data_frequency
self.raw_price_loader = reader
self._columns = TradingPairPricing.columns
self._all_sessions = all_sessions
@classmethod
def from_files(cls, pricing_path):
"""
Create a loader from a bcolz equity pricing dir and a SQLite
adjustments path.
Parameters
----------
pricing_path : str
Path to a bcolz directory written by a BcolzDailyBarWriter.
"""
return cls(
BcolzDailyBarReader(pricing_path),
)
def load_adjusted_array(self, columns, dates, assets, mask):
# load_adjusted_array is called with dates on which the user's algo
# will be shown data, which means we need to return the data that would
# be known at the start of each date. We assume that the latest data
# known on day N is the data from day (N - 1), so we shift all query
# dates back by a day.
start_date, end_date = _shift_dates(
self._all_sessions, dates[0], dates[-1], shift=1,
)
colnames = [c.name for c in columns]
if len(assets) == 0:
raise ValueError(
'Pipeline cannot load data with eligible assets.'
)
exchange_names = []
for asset in assets:
if asset.exchange not in exchange_names:
exchange_names.append(asset.exchange)
exchange = get_exchange(exchange_names[0])
reader = exchange.bundle.get_reader(self.data_frequency)
raw_arrays = reader.load_raw_arrays(
colnames,
start_date,
end_date,
assets,
)
out = {}
for c, c_raw in zip(columns, raw_arrays):
out[c] = AdjustedArray(
c_raw.astype(c.dtype),
mask,
{},
c.missing_value,
)
return out
@property
def columns(self):
return self._columns
def _shift_dates(dates, start_date, end_date, shift):
try:
start = dates.get_loc(start_date)
except KeyError:
if start_date < dates[0]:
raise NoFurtherDataError(
msg=(
"Pipeline Query requested data starting on {query_start}, "
"but first known date is {calendar_start}"
).format(
query_start=str(start_date),
calendar_start=str(dates[0]),
)
)
else:
raise ValueError("Query start %s not in calendar" % start_date)
# Make sure that shifting doesn't push us out of the calendar.
if start < shift:
raise NoFurtherDataError(
msg=(
"Pipeline Query requested data from {shift}"
" days before {query_start}, but first known date is only "
"{start} days earlier."
).format(shift=shift, query_start=start_date, start=start),
)
try:
end = dates.get_loc(end_date)
except KeyError:
if end_date > dates[-1]:
raise NoFurtherDataError(
msg=(
"Pipeline Query requesting data up to {query_end}, "
"but last known date is {calendar_end}"
).format(
query_end=end_date,
calendar_end=dates[-1],
)
)
else:
raise ValueError("Query end %s not in calendar" % end_date)
return dates[start - shift], dates[end - shift]
-34
View File
@@ -1,34 +0,0 @@
import os
from catalyst.exchange.ccxt.ccxt_exchange import CCXT
from catalyst.exchange.exchange_errors import ExchangeAuthEmpty
from catalyst.exchange.exchange_utils import get_exchange_auth, \
get_exchange_folder
def get_exchange(exchange_name, base_currency=None, must_authenticate=False):
exchange_auth = get_exchange_auth(exchange_name)
has_auth = (exchange_auth['key'] != '' and exchange_auth['secret'] != '')
if must_authenticate and not has_auth:
raise ExchangeAuthEmpty(
exchange=exchange_name.title(),
filename=os.path.join(
get_exchange_folder(exchange_name), 'auth.json'
)
)
return CCXT(
exchange_name=exchange_name,
key=exchange_auth['key'],
secret=exchange_auth['secret'],
base_currency=base_currency,
)
def get_exchanges(exchange_names):
exchanges = dict()
for exchange_name in exchange_names:
exchanges[exchange_name] = get_exchange(exchange_name)
return exchanges
+11 -169
View File
@@ -6,8 +6,7 @@ from catalyst.gens.sim_engine import (
from logbook import Logger
from catalyst.constants import LOG_LEVEL
from catalyst.exchange.exchange_errors import \
MismatchingBaseCurrenciesExchanges
from catalyst.exchange.utils.stats_utils import prepare_stats
log = Logger('LiveGraphClock', level=LOG_LEVEL)
@@ -38,177 +37,23 @@ class LiveGraphClock(object):
the exchange and the live trading machine's clock. It's not used currently.
"""
def __init__(self, sessions, context, time_skew=pd.Timedelta('0s')):
global mdates, plt # TODO: Could be cleaner
import matplotlib.dates as mdates
from matplotlib import pyplot as plt
from matplotlib import style
def __init__(self, sessions, context, callback=None,
time_skew=pd.Timedelta('0s')):
self.sessions = sessions
self.time_skew = time_skew
self._last_emit = None
self._before_trading_start_bar_yielded = True
self.context = context
self.fmt = mdates.DateFormatter('%Y-%m-%d %H:%M')
style.use('dark_background')
fig = plt.figure()
fig.canvas.set_window_title('Enigma Catalyst: {}'.format(
self.context.algo_namespace))
self.ax_pnl = fig.add_subplot(311)
self.ax_custom_signals = fig.add_subplot(312, sharex=self.ax_pnl)
self.ax_exposure = fig.add_subplot(313, sharex=self.ax_pnl)
if len(context.minute_stats) > 0:
self.draw_pnl()
self.draw_custom_signals()
self.draw_exposure()
# rotates and right aligns the x labels, and moves the bottom of the
# axes up to make room for them
fig.autofmt_xdate()
fig.subplots_adjust(hspace=0.5)
plt.tight_layout()
plt.ion()
plt.show()
def format_ax(self, ax):
"""
Trying to assign reasonable parameters to the time axis.
Parameters
----------
ax:
"""
# TODO: room for improvement
ax.xaxis.set_major_locator(mdates.DayLocator(interval=1))
ax.xaxis.set_major_formatter(self.fmt)
locator = mdates.HourLocator(interval=4)
locator.MAXTICKS = 5000
ax.xaxis.set_minor_locator(locator)
datemin = pd.Timestamp.utcnow()
ax.set_xlim(datemin)
ax.grid(True)
def set_legend(self, ax):
"""
Set legend on the chart.
Parameters
----------
ax
"""
ax.legend(loc='upper left', ncol=1, fontsize=10, numpoints=1)
def draw_pnl(self):
"""
Draw p&l line on the chart.
"""
ax = self.ax_pnl
df = self.context.pnl_stats
ax.clear()
ax.set_title('Performance')
ax.plot(df.index, df['performance'], '-',
color='green',
linewidth=1.0,
label='Performance'
)
def perc(val):
return '{:2f}'.format(val)
ax.format_ydata = perc
self.set_legend(ax)
self.format_ax(ax)
def draw_custom_signals(self):
"""
Draw custom signals on the chart.
"""
ax = self.ax_custom_signals
df = self.context.custom_signals_stats
colors = ['blue', 'green', 'red', 'black', 'orange', 'yellow', 'pink']
ax.clear()
ax.set_title('Custom Signals')
for index, column in enumerate(df.columns.values.tolist()):
ax.plot(df.index, df[column], '-',
color=colors[index],
linewidth=1.0,
label=column
)
self.set_legend(ax)
self.format_ax(ax)
def draw_exposure(self):
"""
Draw exposure line on the chart.
"""
ax = self.ax_exposure
context = self.context
df = context.exposure_stats
# TODO: list exchanges in graph
base_currency = None
positions = []
for exchange_name in context.exchanges:
exchange = context.exchanges[exchange_name]
if not base_currency:
base_currency = exchange.base_currency
elif base_currency != exchange.base_currency:
raise MismatchingBaseCurrenciesExchanges(
base_currency=base_currency,
exchange_name=exchange.name,
exchange_currency=exchange.base_currency
)
positions += exchange.portfolio.positions
ax.clear()
ax.set_title('Exposure')
ax.plot(df.index, df['base_currency'], '-',
color='green',
linewidth=1.0,
label='Base Currency: {}'.format(base_currency.upper())
)
symbols = []
for position in positions:
symbols.append(position.symbol)
ax.plot(df.index, df['long_exposure'], '-',
color='blue',
linewidth=1.0,
label='Long Exposure: {}'.format(', '.join(symbols).upper()))
self.set_legend(ax)
self.format_ax(ax)
self.callback = callback
def __iter__(self):
from matplotlib import pyplot as plt
yield pd.Timestamp.utcnow(), SESSION_START
while True:
current_time = pd.Timestamp.utcnow()
current_minute = current_time.floor('1 min')
current_minute = current_time.floor('1T')
if self._last_emit is None or current_minute > self._last_emit:
log.debug('emitting minutely bar: {}'.format(current_minute))
@@ -216,14 +61,11 @@ class LiveGraphClock(object):
self._last_emit = current_minute
yield current_minute, BAR
try:
self.draw_pnl()
self.draw_custom_signals()
self.draw_exposure()
plt.draw()
except Exception as e:
log.warn('Unable to update the graph: {}'.format(e))
recorded_cols = list(self.context.recorded_vars.keys())
df, _ = prepare_stats(
self.context.frame_stats, recorded_cols=recorded_cols
)
self.callback(self.context, df)
else:
# I can't use the "animate" reactive approach here because
-661
View File
@@ -1,661 +0,0 @@
import json
import time
from collections import defaultdict
import numpy as np
import pandas as pd
import pytz
from catalyst.assets._assets import TradingPair
from logbook import Logger
# import six
from six import iteritems
from catalyst.constants import LOG_LEVEL
# from websocket import create_connection
from catalyst.exchange.exchange import Exchange
from catalyst.exchange.exchange_bundle import ExchangeBundle
from catalyst.exchange.exchange_errors import (
ExchangeRequestError,
InvalidHistoryFrequencyError,
InvalidOrderStyle,
OrphanOrderError,
OrphanOrderReverseError)
from catalyst.exchange.exchange_execution import ExchangeLimitOrder, \
ExchangeStopLimitOrder
from catalyst.exchange.exchange_utils import get_exchange_symbols_filename, \
download_exchange_symbols, get_symbols_string
from catalyst.exchange.poloniex.poloniex_api import Poloniex_api
from catalyst.finance.order import Order, ORDER_STATUS
from catalyst.finance.transaction import Transaction
from catalyst.protocol import Account
from catalyst.utils.deprecate import deprecated
log = Logger('Poloniex', level=LOG_LEVEL)
@deprecated
class Poloniex(Exchange):
def __init__(self, key, secret, base_currency, portfolio=None):
self.api = Poloniex_api(key=key, secret=secret)
self.name = 'poloniex'
self.assets = dict()
self.load_assets()
self.local_assets = dict()
self.load_assets(is_local=True)
self.base_currency = base_currency
self._portfolio = portfolio
self.minute_writer = None
self.minute_reader = None
self.transactions = defaultdict(list)
self.num_candles_limit = 2000
self.max_requests_per_minute = 60
self.request_cpt = dict()
self.bundle = ExchangeBundle(self.name)
def sanitize_curency_symbol(self, exchange_symbol):
"""
Helper method used to build the universal pair.
Include any symbol mapping here if appropriate.
:param exchange_symbol:
:return universal_symbol:
"""
return exchange_symbol.lower()
def _create_order(self, order_status):
"""
Create a Catalyst order object from the Exchange order dictionary
:param order_status:
:return: Order
"""
# if order_status['is_cancelled']:
# status = ORDER_STATUS.CANCELLED
# elif not order_status['is_live']:
# log.info('found executed order {}'.format(order_status))
# status = ORDER_STATUS.FILLED
# else:
status = ORDER_STATUS.OPEN
amount = float(order_status['amount'])
# filled = float(order_status['executed_amount'])
filled = None
if order_status['type'] == 'sell':
amount = -amount
# filled = -filled
price = float(order_status['rate'])
stop_price = None
limit_price = None
# TODO: is this comprehensive enough?
# if order_type.endswith('limit'):
# limit_price = price
# elif order_type.endswith('stop'):
# stop_price = price
# executed_price = float(order_status['avg_execution_price'])
executed_price = price
# TODO: Set Poloniex comission
commission = None
# date=pd.Timestamp.utcfromtimestamp(float(order_status['timestamp']))
# date=pytz.utc.localize(date)
date = None
order = Order(
dt=date,
asset=self.assets[order_status['symbol']],
# No such field in Poloniex
amount=amount,
stop=stop_price,
limit=limit_price,
filled=filled,
id=str(order_status['orderNumber']),
commission=commission
)
order.status = status
return order, executed_price
def get_balances(self):
balances = self.api.returnbalances()
try:
log.debug('retrieving wallets balances')
except Exception as e:
log.debug(e)
raise ExchangeRequestError(error=e)
if 'error' in balances:
raise ExchangeRequestError(
error='unable to fetch balance {}'.format(balances['error'])
)
std_balances = dict()
for (key, value) in iteritems(balances):
currency = key.lower()
std_balances[currency] = float(value)
return std_balances
@property
def account(self):
account = Account()
account.settled_cash = None
account.accrued_interest = None
account.buying_power = None
account.equity_with_loan = None
account.total_positions_value = None
account.total_positions_exposure = None
account.regt_equity = None
account.regt_margin = None
account.initial_margin_requirement = None
account.maintenance_margin_requirement = None
account.available_funds = None
account.excess_liquidity = None
account.cushion = None
account.day_trades_remaining = None
account.leverage = None
account.net_leverage = None
account.net_liquidation = None
return account
@property
def time_skew(self):
# TODO: research the time skew conditions
return pd.Timedelta('0s')
def get_account(self):
# TODO: fetch account data and keep in cache
return None
def get_candles(self, freq, assets, bar_count=None,
start_dt=None, end_dt=None):
"""
Retrieve OHLVC candles from Poloniex
:param freq:
:param assets:
:param bar_count:
:return:
Available Frequencies
---------------------
'5m', '15m', '30m', '2h', '4h', '1D'
"""
if end_dt is None:
end_dt = pd.Timestamp.utcnow()
log.debug(
'retrieving {bars} {freq} candles on {exchange} from '
'{end_dt} for markets {symbols}, '.format(
bars=bar_count,
freq=freq,
exchange=self.name,
end_dt=end_dt,
symbols=get_symbols_string(assets)
)
)
if freq == '1T' and (bar_count == 1 or bar_count is None):
# TODO: use the order book instead
# We use the 5m to fetch the last bar
frequency = 300
elif freq == '5T':
frequency = 300
elif freq == '15T':
frequency = 900
elif freq == '30T':
frequency = 1800
elif freq == '120T':
frequency = 7200
elif freq == '240T':
frequency = 14400
elif freq == '1D':
frequency = 86400
else:
# Poloniex does not offer 1m data candles
# It is likely to error out there frequently
raise InvalidHistoryFrequencyError(frequency=freq)
# Making sure that assets are iterable
asset_list = [assets] if isinstance(assets, TradingPair) else assets
ohlc_map = dict()
for asset in asset_list:
delta = end_dt - pd.to_datetime('1970-1-1', utc=True)
end = int(delta.total_seconds())
if bar_count is None:
start = end - 2 * frequency
else:
start = end - bar_count * frequency
try:
response = self.api.returnchartdata(
self.get_symbol(asset), frequency, start, end
)
except Exception as e:
raise ExchangeRequestError(error=e)
if 'error' in response:
raise ExchangeRequestError(
error='Unable to retrieve candles: {}'.format(
response.content)
)
def ohlc_from_candle(candle):
last_traded = pd.Timestamp.utcfromtimestamp(candle['date'])
last_traded = last_traded.replace(tzinfo=pytz.UTC)
ohlc = dict(
open=np.float64(candle['open']),
high=np.float64(candle['high']),
low=np.float64(candle['low']),
close=np.float64(candle['close']),
volume=np.float64(candle['volume']),
price=np.float64(candle['close']),
last_traded=last_traded
)
return ohlc
if bar_count is None:
ohlc_map[asset] = ohlc_from_candle(response[0])
else:
ohlc_bars = []
for candle in response:
ohlc = ohlc_from_candle(candle)
ohlc_bars.append(ohlc)
ohlc_map[asset] = ohlc_bars
return ohlc_map[assets] \
if isinstance(assets, TradingPair) else ohlc_map
def create_order(self, asset, amount, is_buy, style):
"""
Creating order on the exchange.
:param asset:
:param amount:
:param is_buy:
:param style:
:return:
"""
exchange_symbol = self.get_symbol(asset)
if (isinstance(style, ExchangeLimitOrder)
or isinstance(style, ExchangeStopLimitOrder)):
if isinstance(style, ExchangeStopLimitOrder):
log.warn('{} will ignore the stop price'.format(self.name))
price = style.get_limit_price(is_buy)
try:
if (is_buy):
response = self.api.buy(exchange_symbol, amount, price)
else:
response = self.api.sell(exchange_symbol, -amount, price)
except Exception as e:
raise ExchangeRequestError(error=e)
date = pd.Timestamp.utcnow()
if ('orderNumber' in response):
order_id = str(response['orderNumber'])
order = Order(
dt=date,
asset=asset,
amount=amount,
stop=style.get_stop_price(is_buy),
limit=style.get_limit_price(is_buy),
id=order_id
)
return order
else:
log.warn(
'{} order failed: {}'.format('buy' if is_buy else 'sell',
response['error']))
return None
else:
raise InvalidOrderStyle(exchange=self.name,
style=style.__class__.__name__)
def get_open_orders(self, asset='all'):
"""Retrieve all of the current open orders.
Parameters
----------
asset : Asset
If passed and not 'all', return only the open orders for the given
asset instead of all open orders.
Returns
-------
open_orders : dict[list[Order]] or list[Order]
If 'all' is passed this will return a dict mapping Assets
to a list containing all the open orders for the asset.
If an asset is passed then this will return a list of the open
orders for this asset.
"""
return self.portfolio.open_orders
"""
TODO: Why going to the exchange if we already have this info locally?
And why creating all these Orders if we later discard them?
"""
try:
if (asset == 'all'):
response = self.api.returnopenorders('all')
else:
response = self.api.returnopenorders(self.get_symbol(asset))
except Exception as e:
raise ExchangeRequestError(error=e)
if 'error' in response:
raise ExchangeRequestError(
error='Unable to retrieve open orders: {}'.format(
response['message'])
)
print(self.portfolio.open_orders)
# TODO: Need to handle openOrders for 'all'
orders = list()
for order_status in response:
# will Throw error b/c Polo doesn't track order['symbol']
order, executed_price = self._create_order(order_status)
if asset is None or asset == order.sid:
orders.append(order)
return orders
def get_order(self, order_id):
"""Lookup an order based on the order id returned from one of the
order functions.
Parameters
----------
order_id : str
The unique identifier for the order.
Returns
-------
order : Order
The order object.
"""
try:
order = self._portfolio.open_orders[order_id]
except Exception as e:
raise OrphanOrderError(order_id=order_id, exchange=self.name)
return order
# TODO: Need to decide whether we fetch orders locally or from exchnage
# The code below is ignored
try:
response = self.api.returnopenorders(self.get_symbol(order.sid))
except Exception as e:
raise ExchangeRequestError(error=e)
for o in response:
if (int(o['orderNumber']) == int(order_id)):
return order
return None
def cancel_order(self, order_param):
"""Cancel an open order.
Parameters
----------
order_param : str or Order
The order_id or order object to cancel.
"""
if (isinstance(order_param, Order)):
order = order_param
else:
order = self._portfolio.open_orders[order_param]
try:
response = self.api.cancelorder(order.id)
except Exception as e:
raise ExchangeRequestError(error=e)
if 'error' in response:
log.info(
'Unable to cancel order {order_id} on exchange {exchange} '
'{error}.'.format(
order_id=order.id,
exchange=self.name,
error=response['error']
))
# raise OrderCancelError(
# order_id=order.id,
# exchange=self.name,
# error=response['error']
# )
self.portfolio.remove_order(order)
def tickers(self, assets):
"""
Fetch ticket data for assets
https://docs.bitfinex.com/v2/reference#rest-public-tickers
:param assets:
:return:
"""
symbols = self.get_symbols(assets)
log.debug('fetching tickers {}'.format(symbols))
try:
response = self.api.returnticker()
except Exception as e:
raise ExchangeRequestError(error=e)
if 'error' in response:
raise ExchangeRequestError(
error='Unable to retrieve tickers: {}'.format(
response['error'])
)
ticks = dict()
for index, symbol in enumerate(symbols):
ticks[assets[index]] = dict(
timestamp=pd.Timestamp.utcnow(),
bid=float(response[symbol]['highestBid']),
ask=float(response[symbol]['lowestAsk']),
last_price=float(response[symbol]['last']),
low=float(response[symbol]['lowestAsk']),
# TODO: Polo does not provide low
high=float(response[symbol]['highestBid']),
# TODO: Polo does not provide high
volume=float(response[symbol]['baseVolume']),
)
log.debug('got tickers {}'.format(ticks))
return ticks
def generate_symbols_json(self, filename=None, source_dates=False):
symbol_map = {}
if not source_dates:
fn, r = download_exchange_symbols(self.name)
with open(fn) as data_file:
cached_symbols = json.load(data_file)
response = self.api.returnticker()
for exchange_symbol in response:
base, market = self.sanitize_curency_symbol(exchange_symbol).split(
'_')
symbol = '{market}_{base}'.format(market=market, base=base)
if (source_dates):
start_date = self.get_symbol_start_date(exchange_symbol)
else:
try:
start_date = cached_symbols[exchange_symbol]['start_date']
except KeyError:
start_date = time.strftime('%Y-%m-%d')
try:
end_daily = cached_symbols[exchange_symbol]['end_daily']
except KeyError:
end_daily = 'N/A'
try:
end_minute = cached_symbols[exchange_symbol]['end_minute']
except KeyError:
end_minute = 'N/A'
symbol_map[exchange_symbol] = dict(
symbol=symbol,
start_date=start_date,
end_daily=end_daily,
end_minute=end_minute,
)
if (filename is None):
filename = get_exchange_symbols_filename(self.name)
with open(filename, 'w') as f:
json.dump(symbol_map, f, sort_keys=True, indent=2,
separators=(',', ':'))
def get_symbol_start_date(self, symbol):
try:
r = self.api.returnchartdata(symbol, 86400, pd.to_datetime(
'2010-1-1').value // 10 ** 9)
except Exception as e:
raise ExchangeRequestError(error=e)
return time.strftime('%Y-%m-%d', time.gmtime(int(r[0]['date'])))
def check_open_orders(self):
"""
Need to override this function for Poloniex:
Loop through the list of open orders in the Portfolio object.
Check if any transactions have been executed:
If so, create a transaction and apply to the Portfolio.
Check if the order is still open:
If not, remove it from open orders
:return:
transactions: Transaction[]
"""
transactions = list()
if self.portfolio.open_orders:
for order_id in list(self.portfolio.open_orders):
order = self._portfolio.open_orders[order_id]
log.debug('found open order: {}'.format(order_id))
try:
order_open = self.get_order(order_id)
except Exception as e:
raise ExchangeRequestError(error=e)
if (order_open):
delta = pd.Timestamp.utcnow() - order.dt
log.info(
'order {order_id} still open after {delta}'.format(
order_id=order_id,
delta=delta)
)
try:
response = self.api.returnordertrades(order_id)
except Exception as e:
raise ExchangeRequestError(error=e)
if ('error' in response):
if (not order_open):
raise OrphanOrderReverseError(order_id=order_id,
exchange=self.name)
else:
for tx in response:
"""
We maintain a list of dictionaries of transactions that
correspond to partially filled orders, indexed by
order_id. Every time we query executed transactions
from the exchange, we check if we had that transaction
for that order already. If not, we process it.
When an order if fully filled, we flush the dict of
transactions associated with that order.
"""
if (not filter(
lambda item: item['order_id'] == tx['tradeID'],
self.transactions[order_id])):
log.debug(
'Got new transaction for order {}: amount {}, '
'price {}'.format(
order_id, tx['amount'], tx['rate']))
tx['amount'] = float(tx['amount'])
if (tx['type'] == 'sell'):
tx['amount'] = -tx['amount']
transaction = Transaction(
asset=order.asset,
amount=tx['amount'],
dt=pd.to_datetime(tx['date'], utc=True),
price=float(tx['rate']),
order_id=tx['tradeID'],
# it's a misnomer, but keep for compatibility
commission=float(tx['fee'])
)
self.transactions[order_id].append(transaction)
self.portfolio.execute_transaction(transaction)
transactions.append(transaction)
if (not order_open):
"""
Since transactions have been executed individually
the only thing left to do is remove them from list
of open_orders
"""
del self.portfolio.open_orders[order_id]
del self.transactions[order_id]
return transactions
def get_orderbook(self, asset, order_type='all'):
exchange_symbol = asset.exchange_symbol
data = self.api.returnOrderBook(market=exchange_symbol)
result = dict()
for order_type in data:
# TODO: filter by type
if order_type != 'asks' and order_type != 'bids':
continue
result[order_type] = []
for entry in data[order_type]:
if len(entry) == 2:
result[order_type].append(
dict(
rate=float(entry[0]),
quantity=float(entry[1])
)
)
return result
-212
View File
@@ -1,212 +0,0 @@
#!/usr/bin/env python
import json
import time
import hmac
import hashlib
import ssl
from six.moves import urllib
# Workaround for backwards compatibility
# https://stackoverflow.com/questions/3745771/urllib-request-in-python-2-7
urlopen = urllib.request.urlopen
class Poloniex_api(object):
def __init__(self, key, secret):
self.key = key
self.secret = secret
self.max_requests_per_second = 6
self.request_cpt = dict()
self.public = ['returnTicker', 'return24Volume', 'returnOrderBook',
'returnTradeHistory', 'returnChartData',
'returnCurrencies', 'returnLoanOrders']
self.trading = ['returnBalances', 'returnCompleteBalances',
'returnDepositAddresses',
'generateNewAddress', 'returnDepositsWithdrawals',
'returnOpenOrders',
'returnTradeHistory', 'returnOrderTrades',
'buy', 'sell', 'cancelOrder', 'moveOrder',
'withdraw', 'returnFeeInfo',
'returnAvailableAccountBalances',
'returnTradableBalances', 'transferBalance',
'returnMarginAccountSummary', 'marginBuy',
'marginSell',
'getMarginPosition', 'closeMarginPosition',
'createLoanOffer',
'cancelLoanOffer', 'returnOpenLoanOffers',
'returnActiveLoans',
'returnLendingHistory', 'toggleAutoRenew']
def ask_request(self):
"""
Asks permission to issue a request to the exchange.
The primary purpose is to avoid hitting rate limits.
The application will pause if the maximum requests per minute
permitted by the exchange is exceeded.
:return boolean:
"""
now = time.time()
if not self.request_cpt:
self.request_cpt = dict()
self.request_cpt[now] = 0
return True
cpt_date = list(self.request_cpt.keys())[0]
cpt = self.request_cpt[cpt_date]
if now > cpt_date + 1:
self.request_cpt = dict()
self.request_cpt[now] = 0
return True
if cpt >= self.max_requests_per_second:
time.sleep(1)
now = time.time()
self.request_cpt = dict()
self.request_cpt[now] = 0
return True
else:
self.request_cpt[cpt_date] += 1
def query(self, method, req={}):
if method in self.public:
url = 'https://poloniex.com/public?command=' + method + '&' + \
urllib.parse.urlencode(req)
headers = {}
post_data = None
elif method in self.trading:
url = 'https://poloniex.com/tradingApi'
req['command'] = method
req['nonce'] = int(time.time() * 1000)
post_data = urllib.parse.urlencode(req)
signature = hmac.new(self.secret.encode('utf-8'),
post_data.encode('utf-8'),
hashlib.sha512).hexdigest()
headers = {'Sign': signature, 'Key': self.key}
post_data = post_data.encode('utf-8')
else:
raise ValueError(
'Method "' + method + '" not found in neither the Public API '
'or Trading API endpoints'
)
self.ask_request()
req = urllib.request.Request(
url,
data=post_data,
headers=headers,
)
resource = urlopen(req, context=ssl._create_unverified_context())
content = resource.read().decode('utf-8')
return json.loads(content)
def returnticker(self):
return self.query('returnTicker', {})
def return24volume(self):
return self.query('return24Volume', {})
def returnOrderBook(self, market='all'):
return self.query('returnOrderBook', {'currencyPair': market})
def returntradehistory(self, market, start=None, end=None):
if (start is not None and end is not None):
return self.query('returntradehistory',
{'currencyPair': market, 'start': start,
'end': end})
else:
return self.query('returntradehistory', {'currencyPair': market})
def returnchartdata(self, market, period, start, end=9999999999):
return self.query('returnChartData',
{'currencyPair': market, 'period': period,
'start': start, 'end': end})
def returncurrencies(self):
return self.query('returnCurrencies', {})
def returnloadorders(self, market):
return self.query('returnLoanOrders', {'currency': market})
def returnbalances(self):
return self.query('returnBalances')
def returncompletebalances(self, account):
if (account):
return self.query('returnCompleteBalances', {'account': account})
else:
return self.query('returnCompleteBalances')
def returndepositaddresses(self):
return self.query('returnDepositAddresses')
def generatenewaddress(self, currency):
return self.query('generateNewAddress', {'currency': currency})
def returnDepositsWithdrawals(self, start, end):
return self.query('returnDepositsWithdrawals',
{'start': start, 'end': end})
def returnopenorders(self, market):
return self.query('returnOpenOrders', {'currencyPair': market})
def returnordertrades(self, ordernumber):
return self.query('returnOrderTrades', {'orderNumber': ordernumber})
def buy(self, market, amount, rate, fillorkill=0, immediateorcancel=0,
postonly=0):
if (fillorkill):
return self.query('buy', {'currencyPair': market, 'rate': rate,
'amount': amount,
'fillOrKill': fillorkill, })
elif (immediateorcancel):
return self.query('buy', {'currencyPair': market, 'rate': rate,
'amount': amount,
'immediateOrCancel': immediateorcancel})
elif (postonly):
return self.query('buy', {'currencyPair': market, 'rate': rate,
'amount': amount,
'postOnly': postonly, })
else:
return self.query('buy', {'currencyPair': market, 'rate': rate,
'amount': amount, })
def sell(self, market, amount, rate, fillorkill=0, immediateorcancel=0,
postonly=0):
if (fillorkill):
return self.query('sell', {'currencyPair': market, 'rate': rate,
'amount': amount,
'fillOrKill': fillorkill, })
elif (immediateorcancel):
return self.query('sell', {'currencyPair': market, 'rate': rate,
'amount': amount,
'immediateOrCancel': immediateorcancel})
elif (postonly):
return self.query('sell', {'currencyPair': market, 'rate': rate,
'amount': amount,
'postOnly': postonly, })
else:
return self.query('sell', {'currencyPair': market, 'rate': rate,
'amount': amount, })
def cancelorder(self, ordernumber):
return self.query('cancelOrder', {'orderNumber': ordernumber})
def withdraw(self, currency, quantity, address):
return self.query('withdraw',
{'currency': currency, 'amount': quantity,
'address': address})
def returnfeeinfo(self):
return self.query('returnFeeInfo')
@@ -8,7 +8,7 @@ import pandas as pd
import pytz
from catalyst.data.bundles.core import download_without_progress
from catalyst.exchange.exchange_utils import get_exchange_bundles_folder
from catalyst.exchange.utils.exchange_utils import get_exchange_bundles_folder
EXCHANGE_NAMES = ['bitfinex', 'bittrex', 'poloniex']
API_URL = 'http://data.enigma.co/api/v1'
@@ -14,6 +14,8 @@ from six.moves.urllib import request
from catalyst.constants import DATE_FORMAT, SYMBOLS_URL
from catalyst.exchange.exchange_errors import ExchangeSymbolsNotFound, \
InvalidHistoryFrequencyError, InvalidHistoryFrequencyAlias
from catalyst.exchange.utils.serialization_utils import ExchangeJSONEncoder, \
ExchangeJSONDecoder
from catalyst.utils.paths import data_root, ensure_directory, \
last_modified_time
@@ -62,6 +64,13 @@ def get_exchange_folder(exchange_name, environ=None):
return exchange_folder
def is_blacklist(exchange_name, environ=None):
exchange_folder = get_exchange_folder(exchange_name, environ)
filename = os.path.join(exchange_folder, 'blacklist.txt')
return os.path.exists(filename)
def get_exchange_symbols_filename(exchange_name, is_local=False, environ=None):
"""
The absolute path of the exchange's symbol.json file.
@@ -101,20 +110,6 @@ def download_exchange_symbols(exchange_name, environ=None):
return response
def symbols_parser(asset_def):
for key, value in asset_def.items():
match = isinstance(value, string_types) \
and re.search(r'(\d{4}-\d{2}-\d{2})', value)
if match:
try:
asset_def[key] = pd.to_datetime(value, utc=True)
except ValueError:
pass
return asset_def
def get_exchange_symbols(exchange_name, is_local=False, environ=None):
"""
The de-serialized content of the exchange's symbols.json.
@@ -134,13 +129,13 @@ def get_exchange_symbols(exchange_name, is_local=False, environ=None):
if not is_local and (not os.path.isfile(filename) or pd.Timedelta(
pd.Timestamp('now', tz='UTC') - last_modified_time(
filename)).days > 1):
filename)).days > 1):
download_exchange_symbols(exchange_name, environ)
if os.path.isfile(filename):
with open(filename) as data_file:
try:
data = json.load(data_file, object_hook=symbols_parser)
data = json.load(data_file, cls=ExchangeJSONDecoder)
return data
except ValueError:
@@ -266,7 +261,7 @@ def get_algo_folder(algo_name, environ=None):
return algo_folder
def get_algo_object(algo_name, key, environ=None, rel_path=None):
def get_algo_object(algo_name, key, environ=None, rel_path=None, how='pickle'):
"""
The de-serialized object of the algo name and key.
@@ -290,19 +285,25 @@ def get_algo_object(algo_name, key, environ=None, rel_path=None):
if rel_path is not None:
folder = os.path.join(folder, rel_path)
filename = os.path.join(folder, key + '.p')
name = '{}.p'.format(key) if how == 'pickle' else '{}.json'.format(key)
filename = os.path.join(folder, name)
if os.path.isfile(filename):
try:
if how == 'pickle':
with open(filename, 'rb') as handle:
return pickle.load(handle)
except Exception:
return None
else:
with open(filename) as data_file:
data = json.load(data_file, cls=ExchangeJSONDecoder)
return data
else:
return None
def save_algo_object(algo_name, key, obj, environ=None, rel_path=None):
def save_algo_object(algo_name, key, obj, environ=None, rel_path=None,
how='pickle'):
"""
Serialize and save an object by algo name and key.
@@ -321,10 +322,15 @@ def save_algo_object(algo_name, key, obj, environ=None, rel_path=None):
folder = os.path.join(folder, rel_path)
ensure_directory(folder)
filename = os.path.join(folder, key + '.p')
if how == 'json':
filename = os.path.join(folder, '{}.json'.format(key))
with open(filename, 'wt') as handle:
json.dump(obj, handle, indent=4, cls=ExchangeJSONEncoder)
with open(filename, 'wb') as handle:
pickle.dump(obj, handle, protocol=pickle.HIGHEST_PROTOCOL)
else:
filename = os.path.join(folder, '{}.p'.format(key))
with open(filename, 'wb') as handle:
pickle.dump(obj, handle, protocol=pickle.HIGHEST_PROTOCOL)
def get_algo_df(algo_name, key, environ=None, rel_path=None):
@@ -428,6 +434,15 @@ def get_exchange_bundles_folder(exchange_name, environ=None):
return temp_bundles
def has_bundle(exchange_name, data_frequency, environ=None):
exchange_folder = get_exchange_folder(exchange_name, environ)
folder_name = '{}_bundle'.format(data_frequency.lower())
folder = os.path.join(exchange_folder, folder_name)
return os.path.isdir(folder)
def symbols_serial(obj):
"""
JSON serializer for objects not serializable by default json code
@@ -531,6 +546,11 @@ def get_frequency(freq, data_frequency):
else:
raise InvalidHistoryFrequencyError(frequency=freq)
# TODO: some exchanges support H and W frequencies but not bundles
# Find a way to pass-through these parameters to exchanges
# but resample from minute or daily in backtest mode
# see catalyst/exchange/ccxt/ccxt_exchange.py:242 for mapping between
# Pandas offet aliases (used by Catalyst) and the CCXT timeframes
if unit.lower() == 'd':
alias = '{}D'.format(candle_size)
@@ -646,3 +666,70 @@ def group_assets_by_exchange(assets):
exchange_assets[asset.exchange].append(asset)
return exchange_assets
def get_catalyst_symbol(market_or_symbol):
"""
The Catalyst symbol.
Parameters
----------
market_or_symbol
Returns
-------
"""
if isinstance(market_or_symbol, string_types):
parts = market_or_symbol.split('/')
return '{}_{}'.format(parts[0].lower(), parts[1].lower())
else:
return '{}_{}'.format(
market_or_symbol['base'].lower(),
market_or_symbol['quote'].lower(),
)
def save_asset_data(folder, df, decimals=8):
symbols = df.index.get_level_values('symbol')
for symbol in symbols:
symbol_df = df.loc[(symbols == symbol)] # Type: pd.DataFrame
filename = os.path.join(folder, '{}.csv'.format(symbol))
if os.path.exists(filename):
print_headers = False
else:
print_headers = True
with open(filename, 'a') as f:
symbol_df.to_csv(
path_or_buf=f,
header=print_headers,
float_format='%.{}f'.format(decimals),
)
def get_candles_df(candles, field, freq, bar_count, end_dt,
previous_value=None):
all_series = dict()
for asset in candles:
periods = pd.date_range(end=end_dt, periods=bar_count, freq=freq)
dates = [candle['last_traded'] for candle in candles[asset]]
values = [candle[field] for candle in candles[asset]]
series = pd.Series(values, index=dates)
series = series.reindex(
periods,
method='ffill',
fill_value=previous_value,
)
series.sort_index(inplace=True)
all_series[asset] = series
df = pd.DataFrame(all_series)
df.dropna(inplace=True)
return df
+98
View File
@@ -0,0 +1,98 @@
import os
from logbook import Logger
from catalyst.constants import LOG_LEVEL
from catalyst.exchange.ccxt.ccxt_exchange import CCXT
from catalyst.exchange.exchange import Exchange
from catalyst.exchange.exchange_errors import ExchangeAuthEmpty
from catalyst.exchange.utils.exchange_utils import get_exchange_auth, \
get_exchange_folder, is_blacklist
log = Logger('factory', level=LOG_LEVEL)
exchange_cache = dict()
def get_exchange(exchange_name, base_currency=None, must_authenticate=False,
skip_init=False):
key = (exchange_name, base_currency)
if key in exchange_cache:
return exchange_cache[key]
exchange_auth = get_exchange_auth(exchange_name)
has_auth = (exchange_auth['key'] != '' and exchange_auth['secret'] != '')
if must_authenticate and not has_auth:
raise ExchangeAuthEmpty(
exchange=exchange_name.title(),
filename=os.path.join(
get_exchange_folder(exchange_name), 'auth.json'
)
)
exchange = CCXT(
exchange_name=exchange_name,
key=exchange_auth['key'],
secret=exchange_auth['secret'],
base_currency=base_currency,
)
exchange_cache[key] = exchange
if not skip_init:
exchange.init()
return exchange
def get_exchanges(exchange_names):
exchanges = dict()
for exchange_name in exchange_names:
exchanges[exchange_name] = get_exchange(exchange_name)
return exchanges
def find_exchanges(features=None, skip_blacklist=True, is_authenticated=False,
base_currency=None):
"""
Find exchanges filtered by a list of feature.
Parameters
----------
features: str
The list of features.
skip_blacklist: bool
is_authenticated: bool
base_currency: bool
Returns
-------
list[Exchange]
"""
exchange_names = CCXT.find_exchanges(features, is_authenticated)
exchanges = []
for exchange_name in exchange_names:
if skip_blacklist and is_blacklist(exchange_name):
continue
exchange = get_exchange(
exchange_name=exchange_name,
skip_init=True,
base_currency=base_currency,
)
if features is not None:
if 'dailyBundle' in features \
and not exchange.has_bundle('daily'):
continue
elif 'minuteBundle' in features \
and not exchange.has_bundle('minute'):
continue
exchanges.append(exchange)
return exchanges
+131
View File
@@ -0,0 +1,131 @@
import matplotlib.dates as mdates
import pandas as pd
from catalyst.exchange.exchange_errors import \
MismatchingBaseCurrenciesExchanges
fmt = mdates.DateFormatter('%Y-%m-%d %H:%M')
def format_ax(ax):
"""
Trying to assign reasonable parameters to the time axis.
Parameters
----------
ax:
"""
# TODO: room for improvement
ax.xaxis.set_major_locator(mdates.DayLocator(interval=1))
ax.xaxis.set_major_formatter(fmt)
locator = mdates.HourLocator(interval=4)
locator.MAXTICKS = 5000
ax.xaxis.set_minor_locator(locator)
datemin = pd.Timestamp.utcnow()
ax.set_xlim(datemin)
ax.grid(True)
def set_legend(ax):
"""
Set legend on the chart.
Parameters
----------
ax
"""
ax.legend(loc='upper left', ncol=1, fontsize=10, numpoints=1)
def draw_pnl(ax, df):
"""
Draw p&l line on the chart.
"""
ax.clear()
ax.set_title('Performance')
index = df.index.unique()
dt = index.get_level_values(level=0)
pnl = index.get_level_values(level=4)
ax.plot(
dt, pnl, '-',
color='green',
linewidth=1.0,
label='Performance'
)
def perc(val):
return '{:2f}'.format(val)
ax.format_ydata = perc
set_legend(ax)
format_ax(ax)
def draw_custom_signals(ax, df):
"""
Draw custom signals on the chart.
"""
colors = ['blue', 'green', 'red', 'black', 'orange', 'yellow', 'pink']
ax.clear()
ax.set_title('Custom Signals')
for index, column in enumerate(df.columns.values.tolist()):
ax.plot(df.index, df[column], '-',
color=colors[index],
linewidth=1.0,
label=column
)
set_legend(ax)
format_ax(ax)
def draw_exposure(ax, df, context):
"""
Draw exposure line on the chart.
"""
# TODO: list exchanges in graph
base_currency = None
positions = []
for exchange_name in context.exchanges:
exchange = context.exchanges[exchange_name]
if not base_currency:
base_currency = exchange.base_currency
elif base_currency != exchange.base_currency:
raise MismatchingBaseCurrenciesExchanges(
base_currency=base_currency,
exchange_name=exchange.name,
exchange_currency=exchange.base_currency
)
positions += exchange.portfolio.positions
ax.clear()
ax.set_title('Exposure')
ax.plot(df.index, df['base_currency'], '-',
color='green',
linewidth=1.0,
label='Base Currency: {}'.format(base_currency.upper())
)
symbols = []
for position in positions:
symbols.append(position.symbol)
ax.plot(df.index, df['long_exposure'], '-',
color='blue',
linewidth=1.0,
label='Long Exposure: {}'.format(', '.join(symbols).upper()))
set_legend(ax)
format_ax(ax)
@@ -0,0 +1,70 @@
import json
import re
from json import JSONEncoder
import pandas as pd
from six import string_types
from catalyst.constants import DATE_TIME_FORMAT
class ExchangeJSONEncoder(json.JSONEncoder):
def default(self, obj):
if isinstance(obj, pd.Timestamp):
return obj.strftime(DATE_TIME_FORMAT)
# Let the base class default method raise the TypeError
return JSONEncoder.default(self, obj)
class ExchangeJSONDecoder(json.JSONDecoder):
def __init__(self, *args, **kwargs):
json.JSONDecoder.__init__(
self, object_hook=self.object_hook, *args, **kwargs
)
def recursive_iter(self, obj):
if isinstance(obj, dict):
for key, value in obj.items():
match = isinstance(value, string_types) and re.search(
r'(\d{4}-\d{2}-\d{2}).*', value
)
if match:
try:
obj[key] = pd.to_datetime(value, utc=True)
except ValueError:
pass
elif any(isinstance(obj, t) for t in (list, tuple)):
for item in obj:
self.recursive_iter(item)
def object_hook(self, obj):
self.recursive_iter(obj)
return obj
def portfolio_to_dict(portfolio):
positions = []
for asset in portfolio.positions:
p = portfolio.positions[asset] # Type: Position
position = dict(
symbol=asset.symbol,
exchange=asset.exchange,
amount=p.amount,
cost_basis=p.cost_basis,
last_sale_price=p.last_sale_price,
last_sale_date=p.last_sale_date,
)
positions.append(position)
portfolio_dict = vars(portfolio)
portfolio_dict['positions'] = positions
return portfolio_dict
def portfolio_from_dict(self, portfolio_data):
from catalyst.protocol import Portfolio
return Portfolio()
@@ -1,18 +1,19 @@
import csv
import numbers
import copy
import numpy as np
import csv
import json
import numbers
import os
import pandas as pd
import boto3
import time
import numpy as np
import pandas as pd
from catalyst.assets._assets import TradingPair
from catalyst.exchange.exchange_utils import get_algo_folder
from catalyst.exchange.utils.exchange_utils import get_algo_folder
from catalyst.utils.paths import data_root, ensure_directory
s3 = boto3.resource('s3')
s3_conn = []
mailgun = []
def trend_direction(series):
@@ -195,6 +196,9 @@ def prepare_stats(stats, recorded_cols=list()):
if recorded_cols is not None:
for column in recorded_cols[:]:
value = row_data[column]
if isinstance(value, pd.Series):
value = value.to_dict()
if type(value) is dict:
for asset in value:
if not isinstance(asset, TradingPair):
@@ -278,21 +282,17 @@ def get_pretty_stats(stats, recorded_cols=None, num_rows=10):
if isinstance(stats, pd.DataFrame):
stats = stats.T.to_dict().values()
df, columns = prepare_stats(stats, recorded_cols=recorded_cols)
display_stats = stats[-num_rows:] if len(stats) > num_rows else stats
df, columns = prepare_stats(
display_stats, recorded_cols=recorded_cols
)
pd.set_option('display.expand_frame_repr', False)
pd.set_option('precision', 8)
pd.set_option('display.width', 1000)
pd.set_option('display.max_colwidth', 1000)
formatters = {
'returns': lambda returns: "{0:.4f}".format(returns),
}
return df.tail(num_rows).to_string(
columns=columns,
formatters=formatters
)
return df.to_string(columns=columns)
def get_csv_stats(stats, recorded_cols=None):
@@ -338,6 +338,12 @@ def stats_to_s3(uri, stats, algo_namespace, recorded_cols=None,
-------
"""
if not s3_conn:
import boto3
s3_conn.append(boto3.resource('s3'))
s3 = s3_conn[0]
if bytes_to_write is None:
bytes_to_write = get_csv_stats(stats, recorded_cols=recorded_cols)
@@ -352,6 +358,35 @@ def stats_to_s3(uri, stats, algo_namespace, recorded_cols=None,
obj.put(Body=bytes_to_write)
def email_error(algo_name, dt, e, environ=None):
import requests
import traceback
if not mailgun:
root = data_root(environ)
filename = os.path.join(root, 'mailgun.json')
if not os.path.exists(filename):
raise ValueError(
'mailgun.json not found in the catalyst data folder'
)
with open(filename) as data_file:
mailgun.append(json.load(data_file))
mg = mailgun[0]
return requests.post(
mg['url'],
auth=("api", mg['api']),
data={
"from": mg['from'],
"to": mg['to'],
"subject": 'Error: {}'.format(algo_name),
"text": '{}\n\n{}\n{}'.format(
dt, e, traceback.format_exc()
)})
def stats_to_algo_folder(stats, algo_namespace, recorded_cols=None):
"""
Saves the performance stats to the algo local folder.
@@ -372,7 +407,10 @@ def stats_to_algo_folder(stats, algo_namespace, recorded_cols=None):
timestr = time.strftime('%Y%m%d')
folder = get_algo_folder(algo_namespace)
filename = os.path.join(folder, '{}-{}.csv'.format(timestr, 'frames'))
stats_folder = os.path.join(folder, 'stats')
ensure_directory(stats_folder)
filename = os.path.join(stats_folder, '{}.csv'.format(timestr))
with open(filename, 'wb') as handle:
handle.write(bytes_to_write)
+83
View File
@@ -0,0 +1,83 @@
import os
import random
import tempfile
from catalyst.assets._assets import TradingPair
from catalyst.exchange.utils.exchange_utils import get_exchange_folder
from catalyst.exchange.utils.factory import find_exchanges
from catalyst.utils.paths import ensure_directory
def handle_exchange_error(exchange, e):
try:
message = '{}: {}'.format(
e.__class__, e.message.decode('ascii', 'ignore')
)
except Exception:
message = 'unexpected error'
folder = get_exchange_folder(exchange.name)
filename = os.path.join(folder, 'blacklist.txt')
with open(filename, 'wt') as handle:
handle.write(message)
def select_random_exchanges(population=3, features=None,
is_authenticated=False, base_currency=None):
all_exchanges = find_exchanges(
features=features,
is_authenticated=is_authenticated,
base_currency=base_currency,
)
if population is not None:
if len(all_exchanges) < population:
population = len(all_exchanges)
exchanges = random.sample(all_exchanges, population)
else:
exchanges = all_exchanges
return exchanges
def select_random_assets(all_assets, population=3):
assets = random.sample(all_assets, population)
return assets
def output_df(df, assets, name=None):
"""
Outputs a price DataFrame to a temp folder.
Parameters
----------
df: pd.DataFrame
assets
name
Returns
-------
"""
if isinstance(assets, TradingPair):
exchange_folder = assets.exchange
asset_folder = assets.symbol
else:
exchange_folder = ','.join([asset.exchange for asset in assets])
asset_folder = ','.join([asset.symbol for asset in assets])
folder = os.path.join(
tempfile.gettempdir(), 'catalyst', exchange_folder, asset_folder
)
ensure_directory(folder)
if name is None:
name = 'output'
path = os.path.join(folder, '{}.csv'.format(name))
df.to_csv(path)
return path
-142
View File
@@ -1,142 +0,0 @@
import os
import tempfile
import pandas as pd
import six
from catalyst.assets._assets import TradingPair, get_calendar
from logbook import Logger
from pandas.util.testing import assert_frame_equal
from catalyst.constants import LOG_LEVEL
from catalyst.exchange.asset_finder_exchange import AssetFinderExchange
from catalyst.exchange.exchange_data_portal import DataPortalExchangeBacktest
from catalyst.exchange.factory import get_exchanges
from catalyst.utils.paths import ensure_directory
log = Logger('Validator', level=LOG_LEVEL)
def output_df(df, assets, name=None):
"""
Outputs a price DataFrame to a temp folder.
Parameters
----------
df: pd.DataFrame
assets
name
Returns
-------
"""
if isinstance(assets, TradingPair):
exchange_folder = assets.exchange
asset_folder = assets.symbol
else:
exchange_folder = ','.join([asset.exchange for asset in assets])
asset_folder = ','.join([asset.symbol for asset in assets])
folder = os.path.join(
tempfile.gettempdir(), 'catalyst', exchange_folder, asset_folder
)
ensure_directory(folder)
if name is None:
name = 'output'
path = os.path.join(folder, '{}.csv'.format(name))
df.to_csv(path)
return path
class Validator(object):
def __init__(self, data_portal):
self.data_portal = data_portal
def compare_bundle_with_exchange(self, exchange, assets, end_dt, bar_count,
sample_minutes):
"""
Creates DataFrames from the bundle and exchange for the specified
data set.
Parameters
----------
exchange: Exchange
assets
end_dt
bar_count
sample_minutes
Returns
-------
"""
freq = '{}T'.format(sample_minutes)
log.info('creating data sample from bundle')
df1 = self.data_portal.get_history_window(
assets=assets,
end_dt=end_dt,
bar_count=bar_count,
frequency=freq,
field='close',
data_frequency='minute'
)
path = output_df(df1, assets, '{}_resampled'.format(freq))
log.info('saved resampled bundle candles: {}\n{}'.format(
path, df1.tail(10))
)
log.info('creating data sample from exchange api')
candles = exchange.get_candles(
end_dt=end_dt,
freq='{}T'.format(sample_minutes),
assets=assets,
bar_count=bar_count
)
series = dict()
for asset in assets:
series[asset] = pd.Series(
data=[candle['close'] for candle in candles[asset]],
index=[candle['last_traded'] for candle in candles[asset]]
)
df2 = pd.DataFrame(series)
path = output_df(df2, assets, '{}_api'.format(freq))
log.info('saved exchange api candles: {}\n{}'.format(
path, df2.tail(10))
)
try:
assert_frame_equal(df1, df2)
return True
except:
log.warn('differences found in dataframes')
return False
if __name__ == '__main__':
exchanges = get_exchanges(['poloniex'])
exchange = six.next(six.itervalues(exchanges))
assets = exchange.get_assets(symbols=['eth_btc'])
open_calendar = get_calendar('OPEN')
asset_finder = AssetFinderExchange()
data_portal = DataPortalExchangeBacktest(
exchanges=exchanges,
asset_finder=asset_finder,
trading_calendar=open_calendar,
first_trading_day=None # will set dynamically based on assets
)
validator = Validator(data_portal=data_portal)
validator.compare_bundle_with_exchange(
exchange=exchange,
assets=assets,
end_dt=pd.to_datetime('2017-11-10 1:00', utc=True),
bar_count=200,
sample_minutes=30
)
+39 -16
View File
@@ -27,15 +27,15 @@ from .risk import (
choose_treasury
)
from empyrical import (
from catalyst.patches.stats import (
alpha_beta_aligned,
annual_volatility,
cum_returns,
downside_risk,
information_ratio,
max_drawdown,
sharpe_ratio,
sortino_ratio,
cum_returns,
)
import warnings
from catalyst.constants import LOG_LEVEL
@@ -161,9 +161,13 @@ class RiskMetricsCumulative(object):
if len(self.algorithm_returns) == 1:
self.algorithm_returns = np.append(0.0, self.algorithm_returns)
self.algorithm_cumulative_returns[dt_loc] = cum_returns(
self.algorithm_returns
)[-1]
try:
self.algorithm_cumulative_returns[dt_loc] = cum_returns(
self.algorithm_returns
)[-1]
except Exception as e:
log.debug('unable to calculate cum returns: {}'.format(e))
self.algorithm_cumulative_returns[dt_loc] = np.nan
algo_cumulative_returns_to_date = \
self.algorithm_cumulative_returns[:dt_loc + 1]
@@ -196,8 +200,11 @@ class RiskMetricsCumulative(object):
self.benchmark_cumulative_returns[dt_loc] = cum_returns(
self.benchmark_returns
)[-1]
except Exception:
self.benchmark_cumulative_returns[dt_loc] = 0
except Exception as e:
log.debug(
'unable to calculate benchmark cum returns: {}'.format(e)
)
self.benchmark_cumulative_returns[dt_loc] = np.nan
benchmark_cumulative_returns_to_date = \
self.benchmark_cumulative_returns[:dt_loc + 1]
@@ -269,9 +276,16 @@ algorithm_returns ({algo_count}) in range {start} : {end} on {dt}"
self.sharpe[dt_loc] = sharpe_ratio(
self.algorithm_returns,
)
self.downside_risk[dt_loc] = downside_risk(
self.algorithm_returns
)
try:
self.downside_risk[dt_loc] = downside_risk(
self.algorithm_returns
)
except Exception as e:
log.debug(
'unable to calculate downside risk returns: {}'.format(e)
)
self.downside_risk[dt_loc] = np.nan
try:
risk = self.downside_risk[dt_loc]
@@ -279,17 +293,26 @@ algorithm_returns ({algo_count}) in range {start} : {end} on {dt}"
self.algorithm_returns,
_downside_risk=risk
)
except Exception:
# TODO: what causes it to error out?
self.sortino[dt_loc] = 0
except Exception as e:
log.debug(
'unable to calculate benchmark cum returns: {}'.format(e)
)
self.sortino[dt_loc] = np.nan
self.information[dt_loc] = information_ratio(
self.algorithm_returns,
self.benchmark_returns,
)
self.max_drawdown = max_drawdown(
self.algorithm_returns
)
try:
self.max_drawdown = max_drawdown(
self.algorithm_returns
)
except Exception as e:
log.debug(
'unable to calculate max drawdown: {}'.format(e)
)
self.max_drawdown = np.nan
self.max_drawdowns[dt_loc] = self.max_drawdown
self.max_leverage = self.calculate_max_leverage()
self.max_leverages[dt_loc] = self.max_leverage
File diff suppressed because it is too large Load Diff
+8 -4
View File
@@ -7,6 +7,7 @@ from abc import (
)
from uuid import uuid4
import six
from six import (
iteritems,
with_metaclass,
@@ -33,7 +34,6 @@ from catalyst.utils.sharedoc import copydoc
class PipelineEngine(with_metaclass(ABCMeta)):
@abstractmethod
def run_pipeline(self, pipeline, start_date, end_date):
"""
@@ -118,6 +118,7 @@ class ExplodingPipelineEngine(PipelineEngine):
"""
A PipelineEngine that doesn't do anything.
"""
def run_pipeline(self, pipeline, start_date, end_date):
raise NoEngineRegistered(
"Attempted to run a pipeline but no pipeline "
@@ -484,8 +485,10 @@ class SimplePipelineEngine(PipelineEngine):
)
if isinstance(term, LoadableTerm):
term_key = loader_group_key(term)
# TODO: temp workaround
to_load = sorted(
loader_groups[loader_group_key(term)],
six.next(six.itervalues(loader_groups)),
key=lambda t: t.dataset
)
loader = get_loader(term)
@@ -565,9 +568,10 @@ class SimplePipelineEngine(PipelineEngine):
index=MultiIndex.from_arrays([empty_dates, empty_assets]),
)
resolved_assets = array(self._finder.retrieve_all(assets))
# TODO: not sure what's wrong with the resolved_assets
# resolved_assets = array(self._finder.retrieve_all(assets))
dates_kept = repeat_last_axis(dates.values, len(assets))[mask]
assets_kept = repeat_first_axis(resolved_assets, len(dates))[mask]
assets_kept = repeat_first_axis(assets, len(dates))[mask]
final_columns = {}
for name in data:
+52
View File
@@ -0,0 +1,52 @@
from catalyst import run_algorithm
from catalyst.api import order, record, symbol
import pandas as pd
from catalyst.exchange.utils.stats_utils import get_pretty_stats
def initialize(context):
context.assets = [symbol('eth_btc'), symbol('eth_usdt')]
def handle_data(context, data):
order(context.assets[0], 1)
prices = data.current(context.assets, 'price')
record(price=prices)
pass
def analyze(context, perf):
stats = get_pretty_stats(perf)
print(stats)
pass
if __name__ == '__main__':
live = True
if live:
run_algorithm(
capital_base=0.01,
initialize=initialize,
handle_data=handle_data,
exchange_name='poloniex',
algo_namespace='buy_btc_polo_jh',
base_currency='btc',
analyze=analyze,
live=True,
simulate_orders=True,
)
else:
run_algorithm(
capital_base=1000,
data_frequency='daily',
initialize=initialize,
handle_data=handle_data,
exchange_name='poloniex',
algo_namespace='buy_btc_polo_jh',
base_currency='usd',
analyze=analyze,
start=pd.to_datetime('2017-01-01', utc=True),
end=pd.to_datetime('2017-12-25', utc=True),
)
+28
View File
@@ -0,0 +1,28 @@
from catalyst.api import symbol
from catalyst.utils.run_algo import run_algorithm
def initialize(context):
context.asset = symbol('bcc_usdt')
def handle_data(context, data):
data.history(context.asset, ['close'], bar_count=100, frequency='5T')
def analyze(context=None, results=None):
pass
if __name__ == '__main__':
run_algorithm(
capital_base=100,
initialize=initialize,
handle_data=handle_data,
analyze=analyze,
exchange_name='bittrex',
algo_namespace="bittrex_is_broken",
base_currency='usdt',
data_frequency='minute',
simulate_orders=True,
live=True)
+272 -215
View File
@@ -12,7 +12,9 @@ from logbook import Logger
from catalyst.data.bundles import load
from catalyst.data.data_portal import DataPortal
from catalyst.exchange.factory import get_exchange
from catalyst.exchange.exchange_pricing_loader import ExchangePricingLoader, \
TradingPairPricing
from catalyst.exchange.utils.factory import get_exchange
try:
from pygments import highlight
@@ -37,7 +39,7 @@ from catalyst.exchange.exchange_algorithm import (
)
from catalyst.exchange.exchange_data_portal import DataPortalExchangeLive, \
DataPortalExchangeBacktest
from catalyst.exchange.asset_finder_exchange import AssetFinderExchange
from catalyst.exchange.exchange_asset_finder import ExchangeAssetFinder
from catalyst.exchange.exchange_errors import (
ExchangeRequestError, ExchangeRequestErrorTooManyAttempts,
BaseCurrencyNotFoundError, NotEnoughCapitalError)
@@ -68,35 +70,7 @@ class _RunAlgoError(click.ClickException, ValueError):
return self.pyfunc_msg
def _run(handle_data,
initialize,
before_trading_start,
analyze,
algofile,
algotext,
defines,
data_frequency,
capital_base,
data,
bundle,
bundle_timestamp,
start,
end,
output,
print_algo,
local_namespace,
environ,
live,
exchange,
algo_namespace,
base_currency,
live_graph,
simulate_orders,
stats_output):
"""Run a backtest for the given algorithm.
This is shared between the cli and :func:`catalyst.run_algo`.
"""
def _build_namespace(algotext, local_namespace, defines):
if algotext is not None:
if local_namespace:
ip = get_ipython() # noqa
@@ -110,164 +84,197 @@ def _run(handle_data,
except ValueError:
raise ValueError(
'invalid define %r, should be of the form name=value' %
assign,
)
assign)
try:
# evaluate in the same namespace so names may refer to
# eachother
namespace[name] = eval(value, namespace)
except Exception as e:
raise ValueError(
'failed to execute definition for name %r: %s' % (name, e),
)
'failed to execute definition for name %r: %s' % (name, e))
elif defines:
raise _RunAlgoError(
'cannot pass define without `algotext`',
"cannot pass '-D' / '--define' without '-t' / '--algotext'",
)
"cannot pass '-D' / '--define' without '-t' / '--algotext'")
else:
namespace = {}
if algofile is not None:
algotext = algofile.read()
if print_algo:
if PYGMENTS:
highlight(
algotext,
PythonLexer(),
TerminalFormatter(),
outfile=sys.stdout,
)
else:
click.echo(algotext)
return namespace
mode = 'paper-trading' if simulate_orders else 'live-trading' \
if live else 'backtest'
log.info('running algo in {mode} mode'.format(mode=mode))
def _mode(simulate_orders, live):
if not live:
return 'backtest'
elif simulate_orders:
return 'paper-trading'
else:
return 'live-trading'
def _build_exchanges_dict(exchange, live, simulate_orders, base_currency):
exchange_name = exchange
if exchange_name is None:
raise ValueError('Please specify at least one exchange.')
exchange_list = [x.strip().lower() for x in exchange.split(',')]
exchanges = dict()
for exchange_name in exchange_list:
exchanges[exchange_name] = get_exchange(
exchange_name=exchange_name,
exchanges = {exchange_name: get_exchange(
exchange_name=exchange_name,
base_currency=base_currency,
must_authenticate=(live and not simulate_orders))
for exchange_name in exchange_list}
return exchanges
def _pretty_print_code(algotext):
if PYGMENTS:
highlight(
algotext,
PythonLexer(),
TerminalFormatter(),
outfile=sys.stdout)
else:
click.echo(algotext)
def _choose_loader(data_frequency, column):
bound_cols = TradingPairPricing.columns
if column in bound_cols:
return ExchangePricingLoader(data_frequency)
raise ValueError(
"No PipelineLoader registered for column %s." % column)
def _get_live_time_range():
start = pd.Timestamp.utcnow()
# TODO: fix the end data.
end = start + timedelta(hours=8760)
return start, end
def _data_for_live_trading(sim_params, exchanges, env, open_calendar):
data = DataPortalExchangeLive(
exchanges=exchanges,
asset_finder=env.asset_finder,
trading_calendar=open_calendar,
first_trading_day=pd.to_datetime('today', utc=True))
return data
# TODO use proper retry here
def _fetch_capital_base(base_currency, exchange_name, exchange,
attempt_index=0):
"""
Fetch the base currency amount required to bootstrap
the algorithm against the exchange.
The algorithm cannot continue without this value.
:param exchange: the targeted exchange
:param attempt_index:
:return capital_base: the amount of base currency available for
trading
"""
try:
log.debug('retrieving capital base in {} to bootstrap '
'exchange {}'.format(base_currency, exchange_name))
balances = exchange.get_balances()
except ExchangeRequestError as e:
if attempt_index < 20:
log.warn(
'could not retrieve balances on {}: {}'.format(
exchange.name, e))
sleep(5)
return _fetch_capital_base(base_currency, exchange_name, exchange,
attempt_index + 1)
else:
raise ExchangeRequestErrorTooManyAttempts(
attempts=attempt_index,
error=e)
if base_currency in balances:
base_currency_available = balances[base_currency]['free']
log.info(
'base currency available in the account: {} {}'.format(
base_currency_available, base_currency))
return base_currency_available
else:
raise BaseCurrencyNotFoundError(
base_currency=base_currency,
must_authenticate=(live and not simulate_orders),
)
exchange=exchange_name)
open_calendar = get_calendar('OPEN')
env = TradingEnvironment(
load=partial(
load_crypto_market_data,
environ=environ,
start_dt=start,
end_dt=end
),
environ=environ,
exchange_tz='UTC',
asset_db_path=None # We don't need an asset db, we have exchanges
)
env.asset_finder = AssetFinderExchange()
choose_loader = None # TODO: use the DataPortal in the algo class for this
def _algorithm_class_for_live(algo_namespace, live_graph, stats_output,
analyze_live, base_currency, simulate_orders,
exchanges, capital_base):
if not simulate_orders:
for exchange_name in exchanges:
exchange = exchanges[exchange_name]
balance = _fetch_capital_base(base_currency, exchange_name,
exchange)
if live:
start = pd.Timestamp.utcnow()
# TODO: fix the end data.
end = start + timedelta(hours=8760)
data = DataPortalExchangeLive(
exchanges=exchanges,
asset_finder=env.asset_finder,
trading_calendar=open_calendar,
first_trading_day=pd.to_datetime('today', utc=True)
)
def fetch_capital_base(exchange, attempt_index=0):
"""
Fetch the base currency amount required to bootstrap
the algorithm against the exchange.
The algorithm cannot continue without this value.
:param exchange: the targeted exchange
:param attempt_index:
:return capital_base: the amount of base currency available for
trading
"""
try:
log.debug('retrieving capital base in {} to bootstrap '
'exchange {}'.format(base_currency, exchange_name))
balances = exchange.get_balances()
except ExchangeRequestError as e:
if attempt_index < 20:
log.warn(
'could not retrieve balances on {}: {}'.format(
exchange.name, e
)
)
sleep(5)
return fetch_capital_base(exchange, attempt_index + 1)
else:
raise ExchangeRequestErrorTooManyAttempts(
attempts=attempt_index,
error=e
)
if base_currency in balances:
base_currency_available = balances[base_currency]['free']
log.info(
'base currency available in the account: {} {}'.format(
base_currency_available, base_currency
)
)
return base_currency_available
else:
raise BaseCurrencyNotFoundError(
if balance < capital_base:
raise NotEnoughCapitalError(
exchange=exchange_name,
base_currency=base_currency,
exchange=exchange_name
)
balance=balance,
capital_base=capital_base)
if not simulate_orders:
for exchange_name in exchanges:
exchange = exchanges[exchange_name]
balance = fetch_capital_base(exchange)
algorithm_class = partial(
ExchangeTradingAlgorithmLive,
exchanges=exchanges,
algo_namespace=algo_namespace,
live_graph=live_graph,
simulate_orders=simulate_orders,
stats_output=stats_output,
analyze_live=analyze_live,)
if balance < capital_base:
raise NotEnoughCapitalError(
exchange=exchange_name,
base_currency=base_currency,
balance=balance,
capital_base=capital_base,
)
return algorithm_class
sim_params = create_simulation_parameters(
start=start,
end=end,
capital_base=capital_base,
emission_rate='minute',
data_frequency='minute'
)
# TODO: use the constructor instead
sim_params._arena = 'live'
def _bundle_trading_environment(bundle_data, environ):
prefix, connstr = re.split(
r'sqlite:///',
str(bundle_data.asset_finder.engine.url),
maxsplit=1)
if prefix:
raise ValueError(
"invalid url %r, must begin with 'sqlite:///'" %
str(bundle_data.asset_finder.engine.url))
algorithm_class = partial(
ExchangeTradingAlgorithmLive,
exchanges=exchanges,
algo_namespace=algo_namespace,
live_graph=live_graph,
simulate_orders=simulate_orders,
stats_output=stats_output,
)
elif exchanges:
return TradingEnvironment(asset_db_path=connstr, environ=environ)
def _build_live_algo_and_data(sim_params, exchanges, env, open_calendar,
simulate_orders, algo_namespace, capital_base,
live_graph, stats_output, analyze_live,
base_currency, namespace, choose_loader,
algorithm_class_kwargs):
sim_params._arena = 'live' # TODO: use the constructor instead
data = _data_for_live_trading(sim_params, exchanges, env, open_calendar)
algorithm_class = _algorithm_class_for_live(
algo_namespace, live_graph, stats_output, analyze_live,
base_currency, simulate_orders, exchanges, capital_base)
return data, algorithm_class(
namespace=namespace,
env=env,
get_pipeline_loader=choose_loader,
sim_params=sim_params,
**algorithm_class_kwargs)
def _build_backtest_algo_and_data(
exchanges, bundle, env, environ, bundle_timestamp, open_calendar,
start, end, namespace, choose_loader, sim_params,
algorithm_class_kwargs):
if exchanges:
# Removed the existing Poloniex fork to keep things simple
# We can add back the complexity if required.
@@ -281,41 +288,19 @@ def _run(handle_data,
asset_finder=None,
trading_calendar=open_calendar,
first_trading_day=start,
last_available_session=end
)
sim_params = create_simulation_parameters(
start=start,
end=end,
capital_base=capital_base,
data_frequency=data_frequency,
emission_rate=data_frequency,
)
last_available_session=end)
algorithm_class = partial(
ExchangeTradingAlgorithmBacktest,
exchanges=exchanges
)
exchanges=exchanges)
elif bundle is not None:
bundle_data = load(
bundle,
environ,
bundle_timestamp,
)
# TODO This branch should probably be removed or fixed: it doesn't even
# build `algorithm_class`, so it will break when trying to instantiate
# it.
bundle_data = load(bundle, environ, bundle_timestamp)
prefix, connstr = re.split(
r'sqlite:///',
str(bundle_data.asset_finder.engine.url),
maxsplit=1,
)
if prefix:
raise ValueError(
"invalid url %r, must begin with 'sqlite:///'" %
str(bundle_data.asset_finder.engine.url),
)
env = _bundle_trading_environment(bundle_data, environ)
env = TradingEnvironment(asset_db_path=connstr, environ=environ)
first_trading_day = \
bundle_data.equity_minute_bar_reader.first_trading_day
@@ -324,27 +309,103 @@ def _run(handle_data,
first_trading_day=first_trading_day,
equity_minute_reader=bundle_data.equity_minute_bar_reader,
equity_daily_reader=bundle_data.equity_daily_bar_reader,
adjustment_reader=bundle_data.adjustment_reader,
)
adjustment_reader=bundle_data.adjustment_reader)
perf = algorithm_class(
return data, algorithm_class(
namespace=namespace,
env=env,
get_pipeline_loader=choose_loader,
sim_params=sim_params,
**{
'initialize': initialize,
'handle_data': handle_data,
'before_trading_start': before_trading_start,
'analyze': analyze,
} if algotext is None else {
'algo_filename': getattr(algofile, 'name', '<algorithm>'),
'script': algotext,
}
).run(
**algorithm_class_kwargs)
def _build_algo_and_data(handle_data, initialize, before_trading_start,
analyze, algofile, algotext, defines, data_frequency,
capital_base, data, bundle, bundle_timestamp, start,
end, output, print_algo, local_namespace, environ,
live, exchange, algo_namespace, base_currency,
live_graph, analyze_live, simulate_orders,
stats_output):
namespace = _build_namespace(algotext, local_namespace, defines)
if algotext is not None:
algotext = algofile.read()
if print_algo:
_pretty_print_code(algotext)
mode = _mode(simulate_orders, live)
log.info('running algo in {mode} mode'.format(mode=mode))
exchanges = _build_exchanges_dict(exchange, live, simulate_orders,
base_currency)
open_calendar = get_calendar('OPEN')
env = TradingEnvironment(
load=partial(load_crypto_market_data, environ=environ, start_dt=start,
end_dt=end),
environ=environ,
exchange_tz='UTC',
asset_db_path=None) # We don't need an asset db, we have exchanges
env.asset_finder = ExchangeAssetFinder(exchanges=exchanges)
choose_loader = partial(_choose_loader, data_frequency)
if live:
start, end = _get_live_time_range()
data_frequency = 'minute' # TODO double check if this is the desired behavior
sim_params = create_simulation_parameters(
start=start,
end=end,
capital_base=capital_base,
emission_rate=data_frequency,
data_frequency=data_frequency)
if algotext is None:
algorithm_class_kwargs = {'initialize': initialize,
'handle_data': handle_data,
'before_trading_start': before_trading_start,
'analyze': analyze}
else:
algorithm_class_kwargs = {'algo_filename': getattr(algofile, 'name',
'<algorithm>'),
'script': algotext}
if live:
return _build_live_algo_and_data(
sim_params, exchanges, env, open_calendar, simulate_orders,
algo_namespace, capital_base, live_graph, stats_output,
analyze_live, base_currency, namespace, choose_loader,
algorithm_class_kwargs)
else:
return _build_backtest_algo_and_data(
exchanges, bundle, env, environ, bundle_timestamp, open_calendar,
start, end, namespace, choose_loader, sim_params,
algorithm_class_kwargs)
def _run(handle_data, initialize, before_trading_start, analyze, algofile,
algotext, defines, data_frequency, capital_base, data, bundle,
bundle_timestamp, start, end, output, print_algo, local_namespace,
environ, live, exchange, algo_namespace, base_currency, live_graph,
analyze_live, simulate_orders, stats_output):
"""Run an algorithm in backtest,
paper-trading or live-trading mode.
This is shared between the cli and :func:`catalyst.run_algo`.
"""
data, algorithm = _build_algo_and_data(
handle_data, initialize, before_trading_start, analyze, algofile,
algotext, defines, data_frequency, capital_base, data, bundle,
bundle_timestamp, start, end, output, print_algo, local_namespace,
environ, live, exchange, algo_namespace, base_currency, live_graph,
analyze_live, simulate_orders, stats_output)
perf = algorithm.run(
data,
overwrite_sim_params=False,
)
overwrite_sim_params=False)
if output == '-':
click.echo(str(perf))
@@ -401,8 +462,7 @@ def load_extensions(default, extensions, strict, environ, reload=False):
# without `strict` we should just log the failure
warnings.warn(
'Failed to load extension: %r\n%s' % (ext, e),
stacklevel=2
)
stacklevel=2)
else:
_loaded_extensions.add(ext)
@@ -427,6 +487,7 @@ def run_algorithm(initialize,
base_currency=None,
algo_namespace=None,
live_graph=False,
analyze_live=None,
simulate_orders=True,
stats_output=None,
output=os.devnull):
@@ -500,8 +561,7 @@ def run_algorithm(initialize,
catalyst.data.bundles.bundles : The available data bundles.
"""
load_extensions(
default_extension, extensions, strict_extensions, environ
)
default_extension, extensions, strict_extensions, environ)
if capital_base is None:
raise ValueError(
@@ -509,8 +569,7 @@ def run_algorithm(initialize,
'amount of base currency available for trading. For example, '
'if the `capital_base` is 5ETH, the '
'`order_target_percent(asset, 1)` command will order 5ETH worth '
'of the specified asset.'
)
'of the specified asset.')
# I'm not sure that we need this since the modified DataPortal
# does not require extensions to be explicitly loaded.
@@ -528,13 +587,11 @@ def run_algorithm(initialize,
elif len(non_none_data) != 1:
raise ValueError(
'must specify one of `data`, `data_portal`, or `bundle`,'
' got: %r' % non_none_data,
)
' got: %r' % non_none_data)
elif 'bundle' not in non_none_data and bundle_timestamp is not None:
raise ValueError(
'cannot specify `bundle_timestamp` without passing `bundle`',
)
'cannot specify `bundle_timestamp` without passing `bundle`')
return _run(
handle_data=handle_data,
initialize=initialize,
@@ -559,6 +616,6 @@ def run_algorithm(initialize,
algo_namespace=algo_namespace,
base_currency=base_currency,
live_graph=live_graph,
analyze_live=analyze_live,
simulate_orders=simulate_orders,
stats_output=stats_output
)
stats_output=stats_output)
+36
View File
@@ -15,6 +15,9 @@ as an alternative installation method for MacOS and Linux, you can install
Catalyst directly with ``pip`` (we recommend in combination with a virtual
environemnt). See :ref:`Installing with pip <pip>`.
Alternatively you can install Catalyst using ``pipenv`` which is a mix of pip
and virtualenv. See :ref:`Installing with pipenv <pipenv>`.
Regardless of the method, each operating system (OS), has its own
prerequisites, make sure to review the corresponding sections for your system:
:ref:`Linux <linux>`, :ref:`MacOS <macos>` and :ref:`Windows <windows>`.
@@ -293,6 +296,39 @@ Troubleshooting ``pip`` Install
sudo apt-get install python-dev
.. _pipenv:
Installing with ``pipenv``
-------------------------
Installing Catalyst via ``pipenv`` is perhaps easier that installing it via
``pip`` itself but you need to install ``pipenv`` first via ``pip``.
.. code-block:: bash
$ pip install pipenv
Once ``pipenv`` is installed you can proceed by creating a project folder and
installing Catalyst on that project automagically as follows:
.. code-block:: bash
$ mkdir project
$ cd project
$ pipenv --two
$ pipenv install enigma-catalyst matplotlib
Until now the workflow compared to ``pip`` is almost identical, the difference
is that you don't need to load manually any virtualenv however you need to use
the `pipenv run` prefix to run the `catalyst` command as follows:
.. code-block:: bash
$ pipenv run catalyst --version
If you want to know more about ``pipenv`` go to the `pipenv github repo`_
.. _`pipenv github repo`: https://github.com/pypa/pipenv
.. _linux:
+28 -11
View File
@@ -2,23 +2,31 @@
Release Notes
=============
Version 0.3.10
Version 0.4.1
^^^^^^^^^^^^^
**Release Date**: 2017-01-03
Bug Fixes
~~~~~~~~~
- Fixed cash synchronization issue (:issue:`133`)
- Fixed positions synchronization issue (:issue:`132`)
- Patched empyrical to resolve a np.log1p issue (:issue:`126`)
- Fixed a paper trading issue (:issue:`124`)
- Fixed a commission issue (:issue:`104`)
- Fixed a poloniex specific issue in live trading (:issue:`103`)
Build
~~~~~
- Caching CCXT market info to limit round-trips (:issue:`99`)
- Tentative support for Pipeline (:issue:`96`)
Version 0.4.0
^^^^^^^^^^^^^
**Release Date**: 2017-12-12
Bug Fixes
~~~~~~~~~
- Fixed issue with fetching assets with daily frequency
Version 0.3.10
^^^^^^^^^^^^^
**Release Date**: 2017-11-28
Bug Fixes
~~~~~~~~~
- Fixed issue with fetching assets with daily frequency
- Changed Poloniex interface (should solve :issue:`95` and :issue:`94`)
- Solved issue with overriding commission and slippage (:issue:`87`)
- Fixed inefficiency with Bittrex current prices (:issue:`76`)
@@ -30,6 +38,15 @@ Build
- More granular commissions (:issue:`82`)
- Added market orders in live mode (:issue:`81`)
Version 0.3.10
^^^^^^^^^^^^^
**Release Date**: 2017-11-28
Bug Fixes
~~~~~~~~~
- Fixed issue with fetching assets with daily frequency
Version 0.3.9
^^^^^^^^^^^^^
**Release Date**: 2017-11-28
+88
View File
@@ -0,0 +1,88 @@
==========
Unit Tests
==========
Exchanges
~~~~~~~~~
Markets
-------
Sample:
All markets in 3 random exchanges
Test:
Fetch all TradingPair instances
Assert:
No error
Current Ticker
------------------
Sample:
3 random markets in each of the 3 random exchanges
Test:
Fetch current price and volume
Assert:
Not null and no error
Historical Price Data
---------------------
Sample:
- 3 random markets for each of the 3 random exchanges supporting historical data
- For each market, randomly select one supported frequency
Test:
Fetch historical data for each market using the selected frequency
Assert:
- No error and not blank
- Date of each candle is consistent with the Catalyst desired pattern,
- All candle start at fix intervals
- Last candle partial and forward looking from the end date
Authentication and Orders
-------------------------
Sample:
1 random market for each of 3 random authenticated exchanges
Test:
- Create one limit order randomly buying or selling at least 10% out from the current price
- Retrieve the open order from the exchange
- Cancel the open order
Assert:
No error
Bundles
~~~~~~~
Validate Bundle Data
--------------------
Sample:
- 3 random market in bundles for exchanges supporting historical data
- For each market, randomly selected data range available in the exchange historical data
Test:
- Clean the target exchange bundle
- Ingest the selected market data for the selected data range
- Retrieve the bundle data into a dataframe
- Retrieve the equivalent OHLCV data from the exchange into a dataframe
Assert:
Matching data for the bundle and exchange
Algo Stats
----------
Sample:
- 2 sample algorithms with built-in stats calculator
- 2 KPIs both calculated by each algo and by Catalyst
Test:
- Run each algorithm
- Compare the results of the two methods or calculating stats
Assert:
- Matching stats
CSV Ingestion
-------------
Sample:
3 random CSV files containing price data
Test:
- Ingest each CSV files
- Validate with the exchange like in the 'Validate Bundle Data' test
Assert:
Matching data between the bundle and the exchange
+2 -1
View File
@@ -20,7 +20,7 @@ dependencies:
- bcolz==0.12.1
- bottleneck==1.2.1
- chardet==3.0.4
- ccxt==1.10.319
- ccxt==1.10.283
- click==6.7
- contextlib2==0.5.5
- cycler==0.10.0
@@ -45,6 +45,7 @@ dependencies:
- python-dateutil==2.6.1
- python-editor==1.0.3
- pytz==2017.2
- redo==1.6
- requests==2.18.4
- requests-file==1.4.2
- requests-ftp==0.3.1
+1
View File
@@ -83,3 +83,4 @@ tables==3.3.0
#Catalyst dependencies
ccxt==1.10.283
boto3==1.4.8
redo==1.6
+6 -7
View File
@@ -1,15 +1,14 @@
import shutil
import random
import shutil
import tempfile
import pandas as pd
from catalyst.exchange.exchange_bundle import ExchangeBundle
import pandas as pd
from nose.tools import assert_equals
from catalyst.exchange.exchange_bcolz import BcolzExchangeBarWriter, \
BcolzExchangeBarReader
from catalyst.exchange.bundle_utils import get_df_from_arrays
from nose.tools import assert_equals
from catalyst.exchange.exchange_bundle import ExchangeBundle
from catalyst.exchange.utils.bundle_utils import get_df_from_arrays
class TestBcolzWriter(object):
-78
View File
@@ -1,78 +0,0 @@
from logbook import Logger
from base import BaseExchangeTestCase
from catalyst.exchange.bitfinex.bitfinex import Bitfinex
from catalyst.exchange.exchange_utils import get_exchange_auth
from catalyst.finance.execution import (LimitOrder)
from catalyst.utils.deprecate import deprecated
log = Logger('test_bitfinex')
@deprecated
class TestBitfinex(BaseExchangeTestCase):
@classmethod
def setup(self):
log.info('creating bitfinex object')
auth = get_exchange_auth('bitfinex')
self.exchange = Bitfinex(
key=auth['key'],
secret=auth['secret'],
base_currency='usd'
)
def test_order(self):
log.info('creating order')
asset = self.exchange.get_asset('eth_usd')
order_id = self.exchange.order(
asset=asset,
style=LimitOrder(limit_price=200),
limit_price=200,
amount=0.5,
stop_price=None
)
log.info('order created {}'.format(order_id))
pass
def test_open_orders(self):
log.info('retrieving open orders')
# orders = self.exchange.get_open_orders()
pass
def test_get_order(self):
log.info('retrieving order')
pass
def test_cancel_order(self):
log.info('cancel order')
pass
def test_get_candles(self):
log.info('retrieving candles')
# ohlcv_neo = self.exchange.get_candles(
# freq='1T',
# assets=self.exchange.get_asset('neo_btc'))
pass
def test_tickers(self):
log.info('retrieving tickers')
# tickers = self.exchange.tickers([
# self.exchange.get_asset('eth_btc'),
# self.exchange.get_asset('etc_btc')
# ])
pass
def test_get_account(self):
log.info('retrieving account data')
pass
def test_get_balances(self):
log.info('testing exchange balances')
# balances = self.exchange.get_balances()
pass
def test_orderbook(self):
log.info('testing order book for bitfinex')
# asset = self.exchange.get_asset('eth_btc')
# orderbook = self.exchange.get_orderbook(asset)
pass
-95
View File
@@ -1,95 +0,0 @@
# import pandas as pd
from catalyst.exchange.bittrex.bittrex import Bittrex
from catalyst.finance.order import Order
from base import BaseExchangeTestCase
from logbook import Logger
from catalyst.exchange.exchange_utils import get_exchange_auth
from catalyst.utils.deprecate import deprecated
log = Logger('test_bittrex')
@deprecated
class TestBittrex(BaseExchangeTestCase):
@classmethod
def setup(self):
auth = get_exchange_auth('bittrex')
self.exchange = Bittrex(
key=auth['key'],
secret=auth['secret'],
base_currency=None,
portfolio=None
)
def test_order(self):
log.info('creating order')
asset = self.exchange.get_asset('neo_btc')
order_id = self.exchange.order(
asset=asset,
limit_price=0.0005,
amount=1,
)
log.info('order created {}'.format(order_id))
assert order_id is not None
pass
def test_open_orders(self):
log.info('retrieving open orders')
# asset = self.exchange.get_asset('neo_btc')
# orders = self.exchange.get_open_orders(asset)
pass
def test_get_order(self):
log.info('retrieving order')
order = self.exchange.get_order(
u'2c584020-9caf-4af5-bde0-332c0bba17e2')
assert isinstance(order, Order)
pass
def test_cancel_order(self, ):
log.info('cancel order')
self.exchange.cancel_order(u'dc7bcca2-5219-4145-8848-8a593d2a72f9')
pass
def test_get_candles(self):
log.info('retrieving candles')
# ohlcv_neo = self.exchange.get_candles(
# freq='5T',
# assets=self.exchange.get_asset('neo_btc'),
# bar_count=20,
# end_dt=pd.to_datetime('2017-10-20', utc=True)
# )
# ohlcv_neo_ubq = self.exchange.get_candles(
# freq='1D',
# assets=[
# self.exchange.get_asset('neo_btc'),
# self.exchange.get_asset('ubq_btc')
# ],
# bar_count=14,
# end_dt=pd.to_datetime('2017-10-20', utc=True)
# )
pass
def test_tickers(self):
log.info('retrieving tickers')
tickers = self.exchange.tickers([
self.exchange.get_asset('eth_btc'),
self.exchange.get_asset('etc_btc')
])
assert len(tickers) == 2
pass
def test_get_balances(self):
log.info('testing wallet balances')
# balances = self.exchange.get_balances()
pass
def test_get_account(self):
log.info('testing account data')
pass
def test_orderbook(self):
log.info('testing order book for bittrex')
# asset = self.exchange.get_asset('eth_btc')
# orderbook = self.exchange.get_orderbook(asset)
pass
+5 -5
View File
@@ -5,15 +5,15 @@ from logging import getLogger
import pandas as pd
from catalyst.exchange.bundle_utils import get_bcolz_chunk, \
get_start_dt, get_df_from_arrays
from catalyst.exchange.exchange_bcolz import BcolzExchangeBarReader, \
BcolzExchangeBarWriter
from catalyst.exchange.exchange_bundle import ExchangeBundle, \
BUNDLE_NAME_TEMPLATE
from catalyst.exchange.exchange_utils import get_exchange_folder
from catalyst.exchange.factory import get_exchange
from catalyst.exchange.stats_utils import df_to_string
from catalyst.exchange.utils.bundle_utils import get_bcolz_chunk, \
get_start_dt, get_df_from_arrays
from catalyst.exchange.utils.exchange_utils import get_exchange_folder
from catalyst.exchange.utils.factory import get_exchange
from catalyst.exchange.utils.stats_utils import df_to_string
from catalyst.utils.paths import ensure_directory
log = getLogger('test_exchange_bundle')
+10 -8
View File
@@ -1,10 +1,11 @@
import pandas as pd
from logbook import Logger
from base import BaseExchangeTestCase
from base import BaseExchangeTestCase
from catalyst.exchange.ccxt.ccxt_exchange import CCXT
from catalyst.exchange.exchange_execution import ExchangeLimitOrder
from catalyst.exchange.utils.exchange_utils import get_exchange_auth
from catalyst.finance.order import Order
from catalyst.exchange.exchange_utils import get_exchange_auth
log = Logger('test_ccxt')
@@ -12,22 +13,22 @@ log = Logger('test_ccxt')
class TestCCXT(BaseExchangeTestCase):
@classmethod
def setup(self):
exchange_name = 'gdax'
exchange_name = 'binance'
auth = get_exchange_auth(exchange_name)
self.exchange = CCXT(
exchange_name=exchange_name,
key=auth['key'],
secret=auth['secret'],
base_currency='eth',
portfolio=None
)
self.exchange.init()
def test_order(self):
log.info('creating order')
asset = self.exchange.get_asset('neo_eth')
order_id = self.exchange.order(
asset=asset,
limit_price=0.07,
style=ExchangeLimitOrder(limit_price=0.7),
amount=1,
)
log.info('order created {}'.format(order_id))
@@ -68,9 +69,10 @@ class TestCCXT(BaseExchangeTestCase):
def test_tickers(self):
log.info('retrieving tickers')
tickers = self.exchange.tickers([
self.exchange.get_asset('eth_btc'),
])
assets = [
self.exchange.get_asset('eng_eth'),
]
tickers = self.exchange.tickers(assets)
assert len(tickers) == 1
pass
+4 -4
View File
@@ -2,13 +2,13 @@ import pandas as pd
from logbook import Logger
from catalyst import get_calendar
from catalyst.exchange.asset_finder_exchange import AssetFinderExchange
from catalyst.exchange.exchange_asset_finder import ExchangeAssetFinder
from catalyst.exchange.exchange_data_portal import (
DataPortalExchangeBacktest,
DataPortalExchangeLive
)
from catalyst.exchange.exchange_utils import get_common_assets
from catalyst.exchange.factory import get_exchanges
from catalyst.exchange.utils.exchange_utils import get_common_assets
from catalyst.exchange.utils.factory import get_exchanges
from test_utils import rnd_history_date_days, rnd_bar_count
log = Logger('test_bitfinex')
@@ -20,7 +20,7 @@ class TestExchangeDataPortal:
log.info('creating bitfinex exchange')
exchanges = get_exchanges(['bitfinex', 'bittrex', 'poloniex'])
open_calendar = get_calendar('OPEN')
asset_finder = AssetFinderExchange()
asset_finder = ExchangeAssetFinder()
self.data_portal_live = DataPortalExchangeLive(
exchanges=exchanges,
-96
View File
@@ -1,96 +0,0 @@
from catalyst.exchange.poloniex.poloniex import Poloniex
from catalyst.finance.order import Order
from base import BaseExchangeTestCase
from logbook import Logger
from catalyst.exchange.exchange_utils import get_exchange_auth
import pandas as pd
from catalyst.utils.deprecate import deprecated
from test_utils import output_df
log = Logger('test_poloniex')
@deprecated
class TestPoloniex(BaseExchangeTestCase):
@classmethod
def setup(self):
print ('creating poloniex object')
auth = get_exchange_auth('poloniex')
self.exchange = Poloniex(
key=auth['key'],
secret=auth['secret'],
base_currency='btc'
)
def test_order(self):
log.info('creating order')
asset = self.exchange.get_asset('neos_btc')
order_id = self.exchange.order(
asset=asset,
limit_price=0.0005,
amount=1,
)
log.info('order created {}'.format(order_id))
assert order_id is not None
pass
def test_open_orders(self):
log.info('retrieving open orders')
# asset = self.exchange.get_asset('neos_btc')
# orders = self.exchange.get_open_orders(asset)
pass
def test_get_order(self):
log.info('retrieving order')
order = self.exchange.get_order(
u'2c584020-9caf-4af5-bde0-332c0bba17e2')
assert isinstance(order, Order)
pass
def test_cancel_order(self, ):
log.info('cancel order')
self.exchange.cancel_order(u'dc7bcca2-5219-4145-8848-8a593d2a72f9')
pass
def test_get_candles(self):
log.info('retrieving candles')
assets = self.exchange.get_asset('eth_btc')
ohlcv = self.exchange.get_candles(
# end_dt=pd.to_datetime('2017-11-01', utc=True),
end_dt=None,
freq='5T',
assets=assets,
bar_count=200
)
df = pd.DataFrame(ohlcv)
df.set_index('last_traded', drop=True, inplace=True)
log.info(df.tail(25))
path = output_df(df, assets, '5min_candles')
log.info('saved candles: {}'.format(path))
pass
def test_tickers(self):
log.info('retrieving tickers')
tickers = self.exchange.tickers([
self.exchange.get_asset('eth_btc'),
self.exchange.get_asset('etc_btc')
])
assert len(tickers) == 2
pass
def test_get_balances(self):
log.info('testing wallet balances')
# balances = self.exchange.get_balances()
pass
def test_get_account(self):
log.info('testing account data')
pass
def test_orderbook(self):
log.info('testing order book for poloniex')
# asset = self.exchange.get_asset('eth_btc')
# orderbook = self.exchange.get_orderbook(asset)
pass
+7 -6
View File
@@ -1,17 +1,18 @@
import os
import importlib
import os
import pandas as pd
import matplotlib
import matplotlib.pyplot as plt
from matplotlib.finance import candlestick2_ohlc
# from matplotlib.finance import volume_overlay
import matplotlib.ticker as ticker
import pandas as pd
from matplotlib.finance import candlestick2_ohlc
from catalyst.exchange.exchange_bundle import ExchangeBundle
from catalyst.exchange.exchange_bcolz import BcolzExchangeBarReader
from catalyst.exchange.bundle_utils import get_df_from_arrays, get_bcolz_chunk
from catalyst.exchange.factory import get_exchange
from catalyst.exchange.exchange_bundle import ExchangeBundle
from catalyst.exchange.utils.bundle_utils import get_df_from_arrays, \
get_bcolz_chunk
from catalyst.exchange.utils.factory import get_exchange
EXCHANGE_NAMES = ['bitfinex', 'bittrex', 'poloniex']
exchanges = dict((e, getattr(importlib.import_module(
+145
View File
@@ -0,0 +1,145 @@
import random
import pandas as pd
from logbook import Logger
from pandas.util.testing import assert_frame_equal
from catalyst import get_calendar
from catalyst.exchange.exchange_asset_finder import ExchangeAssetFinder
from catalyst.exchange.exchange_data_portal import DataPortalExchangeBacktest
from catalyst.exchange.utils.exchange_utils import get_candles_df
from catalyst.exchange.utils.factory import get_exchange
from catalyst.exchange.utils.test_utils import output_df, \
select_random_assets
log = Logger('TestSuiteExchange')
pd.set_option('display.expand_frame_repr', False)
pd.set_option('precision', 8)
pd.set_option('display.width', 1000)
pd.set_option('display.max_colwidth', 1000)
class TestSuiteBundle:
@staticmethod
def get_data_portal(exchange_names):
open_calendar = get_calendar('OPEN')
asset_finder = ExchangeAssetFinder()
data_portal = DataPortalExchangeBacktest(
exchange_names=exchange_names,
asset_finder=asset_finder,
trading_calendar=open_calendar,
first_trading_day=None # will set dynamically based on assets
)
return data_portal
def compare_bundle_with_exchange(self, exchange, assets, end_dt, bar_count,
freq, data_frequency, data_portal):
"""
Creates DataFrames from the bundle and exchange for the specified
data set.
Parameters
----------
exchange: Exchange
assets
end_dt
bar_count
sample_minutes
Returns
-------
"""
data = dict()
log.info('creating data sample from bundle')
data['bundle'] = data_portal.get_history_window(
assets=assets,
end_dt=end_dt,
bar_count=bar_count,
frequency=freq,
field='close',
data_frequency=data_frequency,
)
log.info('bundle data:\n{}'.format(
data['bundle'].tail(10))
)
log.info('creating data sample from exchange api')
candles = exchange.get_candles(
end_dt=end_dt,
freq=freq,
assets=assets,
bar_count=bar_count,
)
data['exchange'] = get_candles_df(
candles=candles,
field='close',
freq=freq,
bar_count=bar_count,
end_dt=end_dt,
)
log.info('exchange data:\n{}'.format(
data['exchange'].tail(10))
)
for source in data:
df = data[source]
path = output_df(df, assets, '{}_{}'.format(freq, source))
log.info('saved {}:\n{}'.format(source, path))
assert_frame_equal(
right=data['bundle'],
left=data['exchange'],
check_less_precise=True,
)
def test_validate_bundles(self):
# exchange_population = 3
asset_population = 3
data_frequency = random.choice(['minute', 'daily'])
# bundle = 'dailyBundle' if data_frequency
# == 'daily' else 'minuteBundle'
# exchanges = select_random_exchanges(
# population=exchange_population,
# features=[bundle],
# ) # Type: list[Exchange]
exchanges = [get_exchange('bitfinex', skip_init=True)]
data_portal = TestSuiteBundle.get_data_portal(
[exchange.name for exchange in exchanges]
)
for exchange in exchanges:
exchange.init()
frequencies = exchange.get_candle_frequencies(data_frequency)
freq = random.sample(frequencies, 1)[0]
bar_count = random.randint(1, 10)
assets = select_random_assets(
exchange.assets, asset_population
)
end_dt = None
for asset in assets:
attribute = 'end_{}'.format(data_frequency)
asset_end_dt = getattr(asset, attribute)
if end_dt is None or asset_end_dt < end_dt:
end_dt = asset_end_dt
dt_range = pd.date_range(
end=end_dt, periods=bar_count, freq=freq
)
self.compare_bundle_with_exchange(
exchange=exchange,
assets=assets,
end_dt=dt_range[-1],
bar_count=bar_count,
freq=freq,
data_frequency=data_frequency,
data_portal=data_portal,
)
pass
+189
View File
@@ -0,0 +1,189 @@
import json
import os
import random
from logging import Logger
from time import sleep
import pandas as pd
from catalyst.exchange.exchange_errors import ExchangeRequestError
from catalyst.exchange.exchange_execution import ExchangeLimitOrder
from catalyst.exchange.utils.exchange_utils import get_exchange_folder
from catalyst.exchange.utils.test_utils import select_random_exchanges, \
handle_exchange_error, select_random_assets
log = Logger('TestSuiteExchange')
class TestSuiteExchange:
def _test_markets_exchange(self, exchange, attempts=0):
assets = None
try:
exchange.init()
# Verify that the assets and markets are populated
if not exchange.markets:
raise ValueError(
'no markets found'
)
if not exchange.assets:
raise ValueError(
'no assets derived from markets'
)
assets = exchange.assets
except ExchangeRequestError as e:
sleep(5)
if attempts > 5:
handle_exchange_error(exchange, e)
else:
print(
're-trying an exchange request {} {}'.format(
exchange.name, attempts
)
)
self._test_markets_exchange(exchange, attempts + 1)
except Exception as e:
handle_exchange_error(exchange, e)
return assets
def test_markets(self):
population = 3
results = dict()
exchanges = select_random_exchanges(population) # Type: list[Exchange]
for exchange in exchanges:
assets = self._test_markets_exchange(exchange)
if assets is not None:
results[exchange.name] = len(assets)
folder = get_exchange_folder(exchange.name)
filename = os.path.join(folder, 'whitelist.json')
symbols = [asset.symbol for asset in assets]
with open(filename, 'wt') as handle:
json.dump(symbols, handle, indent=4)
series = pd.Series(results)
print('the tested markets\n{}'.format(series))
if population is not None:
assert (len(results) == population)
pass
def test_tickers(self):
exchange_population = 3
asset_population = 3
exchanges = select_random_exchanges(
exchange_population,
features=['fetchTickers'],
) # Type: list[Exchange]
for exchange in exchanges:
exchange.init()
if exchange.assets and len(exchange.assets) >= asset_population:
assets = select_random_assets(
exchange.assets, asset_population
)
tickers = exchange.tickers(assets)
assert len(tickers) == asset_population
else:
print(
'skipping exchange without assets {}'.format(exchange.name)
)
exchange_population -= 1
pass
def test_candles(self):
exchange_population = 3
asset_population = 3
exchanges = select_random_exchanges(
population=exchange_population,
features=['fetchOHLCV'],
) # Type: list[Exchange]
for exchange in exchanges:
exchange.init()
if exchange.assets and len(exchange.assets) >= asset_population:
frequencies = exchange.get_candle_frequencies()
freq = random.sample(frequencies, 1)[0]
bar_count = random.randint(1, 10)
end_dt = pd.Timestamp.utcnow().floor('1T')
dt_range = pd.date_range(
end=end_dt, periods=bar_count, freq=freq
)
assets = select_random_assets(
exchange.assets, asset_population
)
candles = exchange.get_candles(
freq=freq,
assets=assets,
bar_count=bar_count,
start_dt=dt_range[0],
end_dt=dt_range[-1],
)
assert len(candles) == asset_population
else:
print(
'skipping exchange without assets {}'.format(exchange.name)
)
exchange_population -= 1
pass
def test_orders(self):
population = 3
quote_currency = 'eth'
order_amount = 0.1
exchanges = select_random_exchanges(
population=population,
features=['fetchOrder'],
is_authenticated=True,
base_currency=quote_currency,
) # Type: list[Exchange]
for exchange in exchanges:
exchange.init()
assets = exchange.get_assets(quote_currency=quote_currency)
asset = select_random_assets(assets, 1)[0]
assert asset
tickers = exchange.tickers([asset])
price = tickers[asset]['last_price']
amount = order_amount / price
limit_price = price * 0.8
style = ExchangeLimitOrder(limit_price=limit_price)
order = exchange.order(
asset=asset,
amount=amount,
style=style,
)
sleep(1)
open_order, _ = exchange.get_order(order.id, asset)
assert open_order.status == 0
exchange.cancel_order(open_order, asset)
sleep(1)
canceled_order, _ = exchange.get_order(open_order.id, asset)
assert canceled_order.status == 2
pass