mirror of
https://github.com/wassname/catalyst.git
synced 2026-07-03 06:34:39 +08:00
Merge branch 'develop'
This commit is contained in:
fredfortier
@@ -1,173 +0,0 @@
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import talib
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from logbook import Logger
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import pandas as pd
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from catalyst.api import (
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order,
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order_target_percent,
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symbol,
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record,
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get_open_orders,
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)
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from catalyst.exchange.stats_utils import get_pretty_stats
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from catalyst.utils.run_algo import run_algorithm
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algo_namespace = 'buy_low_sell_high_neo'
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log = Logger(algo_namespace)
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def initialize(context):
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log.info('initializing algo')
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context.asset = symbol('neo_btc', 'bitfinex')
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context.TARGET_POSITIONS = 50000
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context.PROFIT_TARGET = 0.1
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context.SLIPPAGE_ALLOWED = 0.02
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context.retry_check_open_orders = 10
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context.retry_update_portfolio = 10
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context.retry_order = 5
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context.errors = []
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pass
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def _handle_data(context, data):
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price = data.current(context.asset, 'close')
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log.info('got price {price}'.format(price=price))
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if price is None:
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log.warn('no pricing data')
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return
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prices = data.history(
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context.asset,
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fields='price',
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bar_count=1,
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frequency='1m'
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)
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rsi = talib.RSI(prices.values, timeperiod=14)[-1]
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log.info('got rsi: {}'.format(rsi))
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# Buying more when RSI is low, this should lower our cost basis
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if rsi <= 30:
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buy_increment = 1
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elif rsi <= 40:
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buy_increment = 0.5
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elif rsi <= 70:
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buy_increment = 0.1
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else:
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buy_increment = None
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cash = context.portfolio.cash
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log.info('base currency available: {cash}'.format(cash=cash))
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record(price=price)
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orders = get_open_orders(context.asset)
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if len(orders) > 0:
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log.info('skipping bar until all open orders execute')
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return
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is_buy = False
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cost_basis = None
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if context.asset in context.portfolio.positions:
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position = context.portfolio.positions[context.asset]
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cost_basis = position.cost_basis
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log.info(
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'found {amount} positions with cost basis {cost_basis}'.format(
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amount=position.amount,
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cost_basis=cost_basis
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)
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)
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if position.amount >= context.TARGET_POSITIONS:
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log.info('reached positions target: {}'.format(position.amount))
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return
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if price < cost_basis:
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is_buy = True
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elif position.amount > 0 and \
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price > cost_basis * (1 + context.PROFIT_TARGET):
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profit = (price * position.amount) - (cost_basis * position.amount)
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log.info('closing position, taking profit: {}'.format(profit))
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order_target_percent(
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asset=context.asset,
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target=0,
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limit_price=price * (1 - context.SLIPPAGE_ALLOWED),
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)
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else:
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log.info('no buy or sell opportunity found')
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else:
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is_buy = True
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if is_buy:
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if buy_increment is None:
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return
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if price * buy_increment > cash:
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log.info('not enough base currency to consider buying')
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return
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log.info(
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'buying position cheaper than cost basis {} < {}'.format(
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price,
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cost_basis
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)
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)
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limit_price = price * (1 + context.SLIPPAGE_ALLOWED)
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order(
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asset=context.asset,
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amount=buy_increment,
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limit_price=limit_price
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)
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pass
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def handle_data(context, data):
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log.info('handling bar {}'.format(data.current_dt))
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# try:
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_handle_data(context, data)
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# except Exception as e:
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# log.warn('aborting the bar on error {}'.format(e))
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# context.errors.append(e)
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log.info('completed bar {}, total execution errors {}'.format(
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data.current_dt,
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len(context.errors)
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))
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if len(context.errors) > 0:
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log.info('the errors:\n{}'.format(context.errors))
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def analyze(context, stats):
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log.info('the daily stats:\n{}'.format(get_pretty_stats(stats)))
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pass
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# run_algorithm(
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# initialize=initialize,
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# handle_data=handle_data,
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# analyze=analyze,
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# exchange_name='bitfinex',
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# live=True,
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# algo_namespace=algo_namespace,
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# base_currency='btc',
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# live_graph=False
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# )
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# Backtest
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run_algorithm(
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capital_base=250,
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data_frequency='minute',
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initialize=initialize,
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handle_data=handle_data,
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analyze=analyze,
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exchange_name='bitfinex',
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algo_namespace=algo_namespace,
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base_currency='btc'
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)
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@@ -50,4 +50,3 @@ run_algorithm(
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# algo_namespace='simple_loop',
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# base_currency='eth',
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# live_graph=False
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# )
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@@ -1,7 +1,7 @@
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import json
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import time
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import pandas as pd
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import time
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from catalyst.assets._assets import TradingPair
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from logbook import Logger
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from six.moves import urllib
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@@ -223,6 +223,9 @@ def get_month_start_end(dt, first_day=None, last_day=None):
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dt.year, dt.month, month_range[1], 23, 59, 0, 0
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), utc=True)
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if month_end > pd.Timestamp.utcnow():
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month_end = pd.Timestamp.utcnow().floor('1D')
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return month_start, month_end
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@@ -247,6 +250,9 @@ def get_year_start_end(dt, first_day=None, last_day=None):
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year_end = last_day if last_day \
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else pd.to_datetime(date(dt.year, 12, 31), utc=True)
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if year_end > pd.Timestamp.utcnow():
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year_end = pd.Timestamp.utcnow().floor('1D')
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return year_start, year_end
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@@ -294,24 +300,17 @@ def range_in_bundle(asset, start_dt, end_dt, reader):
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"""
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has_data = True
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if has_data and reader is not None:
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dates = [start_dt, end_dt]
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while dates and has_data:
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try:
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start_close = \
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reader.get_value(asset.sid, start_dt, 'close')
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dt = dates.pop(0)
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close = reader.get_value(asset.sid, dt, 'close')
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if np.isnan(start_close):
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if np.isnan(close):
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has_data = False
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else:
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end_close = reader.get_value(asset.sid, end_dt, 'close')
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if np.isnan(end_close):
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has_data = False
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except Exception as e:
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has_data = False
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else:
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has_data = False
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return has_data
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@@ -1,4 +1,30 @@
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import os
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import shutil
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from itertools import chain
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import pandas as pd
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from catalyst.assets._assets import TradingPair
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from logbook import Logger
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from pandas.tslib import Timestamp
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from pytz import UTC
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from six import itervalues
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from catalyst import get_calendar
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from catalyst.constants import LOG_LEVEL
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from catalyst.data.minute_bars import BcolzMinuteOverlappingData, \
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BcolzMinuteBarMetadata
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from catalyst.exchange.bundle_utils import range_in_bundle, \
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get_bcolz_chunk, get_delta, get_month_start_end, \
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get_year_start_end, get_df_from_arrays, get_start_dt, get_period_label
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from catalyst.exchange.exchange_bcolz import BcolzExchangeBarReader, \
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BcolzExchangeBarWriter
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from catalyst.exchange.exchange_errors import EmptyValuesInBundleError, \
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TempBundleNotFoundError, \
|
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NoDataAvailableOnExchange, \
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PricingDataNotLoadedError
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from catalyst.exchange.exchange_utils import get_exchange_folder
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from catalyst.utils.cli import maybe_show_progress
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from catalyst.utils.paths import ensure_directory
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import os
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import shutil
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from itertools import chain
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@@ -303,7 +329,7 @@ class ExchangeBundle:
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:return:
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"""
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# Download and extract the bundle
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path = get_bcolz_chunk(
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exchange_name=self.exchange.name,
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symbol=asset.symbol,
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@@ -313,6 +339,14 @@ class ExchangeBundle:
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reader = self.get_reader(data_frequency, path=path)
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if reader is None:
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try:
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log.warn('the reader is unable to use bundle: {}, '
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'deleting it.'.format(path))
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shutil.rmtree(path)
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except Exception as e:
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log.warn('unable to remove temp bundle: {}'.format(e))
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raise TempBundleNotFoundError(path=path)
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start_dt = reader.first_trading_day
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@@ -335,7 +369,7 @@ class ExchangeBundle:
|
||||
))
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|
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if not arrays:
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return path
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return reader._rootdir
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periods = self.get_calendar_periods_range(
|
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start_dt, end_dt, data_frequency
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@@ -351,11 +385,12 @@ class ExchangeBundle:
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|
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if cleanup:
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log.debug(
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'removing bundle folder following ingestion: {}'.format(path)
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'removing bundle folder following ingestion: {}'.format(
|
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reader._rootdir)
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)
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shutil.rmtree(path)
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shutil.rmtree(reader._rootdir)
|
||||
|
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return path
|
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return reader._rootdir
|
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|
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def get_adj_dates(self, start, end, assets, data_frequency):
|
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"""
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@@ -402,8 +437,8 @@ class ExchangeBundle:
|
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|
||||
if end is None or start is None or start >= end:
|
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raise NoDataAvailableOnExchange(
|
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exchange=asset.exchange.title(),
|
||||
symbol=[asset.symbol],
|
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exchange=[asset.exchange for asset in assets],
|
||||
symbol=[asset.symbol for asset in assets],
|
||||
data_frequency=data_frequency,
|
||||
)
|
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|
||||
@@ -429,9 +464,7 @@ class ExchangeBundle:
|
||||
get_start_end = get_month_start_end \
|
||||
if data_frequency == 'minute' else get_year_start_end
|
||||
|
||||
start_dt, _ = get_start_end(start_dt)
|
||||
_, end_dt = get_start_end(end_dt)
|
||||
|
||||
# Get a reader for the main bundle to verify if data exists
|
||||
reader = self.get_reader(data_frequency)
|
||||
|
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chunks = dict()
|
||||
@@ -462,7 +495,6 @@ class ExchangeBundle:
|
||||
|
||||
chunks[asset] = []
|
||||
for index, dt in enumerate(dates):
|
||||
|
||||
period_start, period_end = get_start_end(
|
||||
dt=dt,
|
||||
first_day=dt if index == 0 else None,
|
||||
@@ -481,17 +513,17 @@ class ExchangeBundle:
|
||||
asset, range_start, period_end, reader
|
||||
)
|
||||
if not has_data:
|
||||
chunks[asset].append(
|
||||
dict(
|
||||
asset=asset,
|
||||
period_start=period_start,
|
||||
period_end=period_end,
|
||||
period=get_period_label(dt, data_frequency)
|
||||
)
|
||||
period = get_period_label(dt, data_frequency)
|
||||
chunk = dict(
|
||||
asset=asset,
|
||||
period=period,
|
||||
)
|
||||
chunks[asset].append(chunk)
|
||||
|
||||
# We sort the chunks by end date to ingest most recent data first
|
||||
chunks[asset].sort(key=lambda chunk: chunk['period_end'])
|
||||
chunks[asset].sort(
|
||||
key=lambda chunk: pd.to_datetime(chunk['period'])
|
||||
)
|
||||
|
||||
return chunks
|
||||
|
||||
@@ -503,20 +535,26 @@ class ExchangeBundle:
|
||||
Parameters
|
||||
----------
|
||||
assets: list[TradingPair]
|
||||
data_frequency: str
|
||||
start_dt: datetime
|
||||
end_dt: datetime
|
||||
show_progress: bool
|
||||
asset_chunks: bool
|
||||
|
||||
"""
|
||||
|
||||
if start_dt is None:
|
||||
start_dt = self.calendar.first_session
|
||||
|
||||
if end_dt is None:
|
||||
end_dt = pd.Timestamp.utcnow()
|
||||
|
||||
start_dt, end_dt = self.get_adj_dates(
|
||||
start_dt, end_dt, assets, data_frequency
|
||||
)
|
||||
get_start_end = get_month_start_end \
|
||||
if data_frequency == 'minute' else get_year_start_end
|
||||
|
||||
# Assign the first and last day of the period
|
||||
start_dt, _ = get_start_end(start_dt)
|
||||
_, end_dt = get_start_end(end_dt)
|
||||
|
||||
chunks = self.prepare_chunks(
|
||||
assets=assets,
|
||||
data_frequency=data_frequency,
|
||||
@@ -524,19 +562,9 @@ class ExchangeBundle:
|
||||
end_dt=end_dt
|
||||
)
|
||||
|
||||
# Since chunks are either monthly or yearly, it is possible that
|
||||
# our ingestion data range is greater than specified. We adjust
|
||||
# the boundaries to ensure that the writer can write all data.
|
||||
all_chunks = list(chain.from_iterable(itervalues(chunks)))
|
||||
for chunk in all_chunks:
|
||||
if chunk['period_start'] < start_dt:
|
||||
start_dt = chunk['period_start']
|
||||
|
||||
if chunk['period_end'] > end_dt:
|
||||
end_dt = chunk['period_end']
|
||||
|
||||
# This is the common writer for the entire exchange bundle
|
||||
# we want to give an end_date far in time
|
||||
writer = self.get_writer(start_dt, end_dt, data_frequency)
|
||||
|
||||
if asset_chunks:
|
||||
for asset in chunks:
|
||||
with maybe_show_progress(
|
||||
@@ -558,6 +586,12 @@ class ExchangeBundle:
|
||||
cleanup=True
|
||||
)
|
||||
else:
|
||||
all_chunks = list(chain.from_iterable(itervalues(chunks)))
|
||||
|
||||
# We sort the chunks by end date to ingest most recent data first
|
||||
all_chunks.sort(
|
||||
key=lambda chunk: pd.to_datetime(chunk['period'])
|
||||
)
|
||||
with maybe_show_progress(
|
||||
all_chunks,
|
||||
show_progress,
|
||||
@@ -597,15 +631,15 @@ class ExchangeBundle:
|
||||
|
||||
for frequency in data_frequency.split(','):
|
||||
self.ingest_assets(assets, frequency, start, end,
|
||||
show_progress)
|
||||
show_progress, True)
|
||||
|
||||
def get_history_window_series_and_load(self,
|
||||
assets, # type: List[TradingPair]
|
||||
end_dt, # type: Timestamp
|
||||
bar_count, # type: int
|
||||
field, # type: str
|
||||
data_frequency, # type: str
|
||||
algo_end_dt=None # type: Timestamp
|
||||
assets,
|
||||
end_dt,
|
||||
bar_count,
|
||||
field,
|
||||
data_frequency,
|
||||
algo_end_dt=None
|
||||
):
|
||||
"""
|
||||
Retrieve price data history, ingest missing data.
|
||||
@@ -663,13 +697,12 @@ class ExchangeBundle:
|
||||
return series
|
||||
|
||||
def get_spot_values(self,
|
||||
assets, # type: List[TradingPair]
|
||||
field, # type: str
|
||||
dt, # type: Timestamp
|
||||
data_frequency, # type: str
|
||||
reset_reader=False # type: bool
|
||||
assets,
|
||||
field,
|
||||
dt,
|
||||
data_frequency,
|
||||
reset_reader=False
|
||||
):
|
||||
# type: (...) -> List[float]
|
||||
"""
|
||||
The spot values for the gives assets, field and date. Reads from
|
||||
the exchange data bundle.
|
||||
@@ -788,6 +821,14 @@ class ExchangeBundle:
|
||||
return series
|
||||
|
||||
def clean(self, data_frequency):
|
||||
"""
|
||||
Removing the bundle data from the catalyst folder.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
data_frequency: str
|
||||
|
||||
"""
|
||||
log.debug('cleaning exchange {}, frequency {}'.format(
|
||||
self.exchange.name, data_frequency
|
||||
))
|
||||
|
||||
@@ -284,13 +284,12 @@ def save_algo_df(algo_name, key, df, environ=None, rel_path=None):
|
||||
----------
|
||||
algo_name: str
|
||||
key: str
|
||||
df: DataFrame
|
||||
df: pd.DataFrame
|
||||
environ:
|
||||
rel_path: str
|
||||
|
||||
"""
|
||||
folder = get_algo_folder(algo_name, environ)
|
||||
|
||||
if rel_path is not None:
|
||||
folder = os.path.join(folder, rel_path)
|
||||
ensure_directory(folder)
|
||||
|
||||
@@ -1,4 +1,3 @@
|
||||
import calendar
|
||||
import json
|
||||
import json
|
||||
import time
|
||||
|
||||
@@ -2,24 +2,46 @@
|
||||
Release Notes
|
||||
=============
|
||||
|
||||
Version 0.3.4
|
||||
Version 0.3.5
|
||||
^^^^^^^^^^^^^
|
||||
**Release Date**: 2017-10-31
|
||||
**Release Date**: 2017-11-2
|
||||
|
||||
Bug Fixes
|
||||
~~~~~~~~~
|
||||
|
||||
- Fixed issue with auto-ingestion of minute data
|
||||
- Added workaround for: KeyError: Timestamp error (:issue:`53`)
|
||||
|
||||
Version 0.3.4
|
||||
^^^^^^^^^^^^^
|
||||
**Release Date**: 2017-11-2
|
||||
|
||||
Bug Fixes
|
||||
~~~~~~~~~
|
||||
|
||||
- Fixed issue with auto-ingestion of minute data (:issue:`47`)
|
||||
- Fixed issue with sell orders in backtesting
|
||||
- Fixed data frequency issues with data.history() in backtesting
|
||||
- Fixed an issue with can_trade()
|
||||
|
||||
- Reduced the commission and slippage values to account for lower volume transactions
|
||||
|
||||
Build
|
||||
~~~~~
|
||||
|
||||
- Added more unit tests
|
||||
|
||||
Documentation
|
||||
~~~~~~~~~~~~~
|
||||
|
||||
- Improved installation notes for Windows C++ compiler and Conda
|
||||
- Addition of `Jupyter Notebook guide <https://enigmampc.github.io/catalyst/jupyter.html>`_
|
||||
- Addition of `Live Trading page <https://enigmampc.github.io/catalyst/live-trading.html>`_
|
||||
- Addition of `Videos page <https://enigmampc.github.io/catalyst/videos.html>`_
|
||||
- Addition of `Resources page <https://enigmampc.github.io/catalyst/resources.html>`_
|
||||
- Addition of `Development Guidelines <https://enigmampc.github.io/catalyst/development-guidelines.html>`_
|
||||
- Addition of `Release Notes <https://enigmampc.github.io/catalyst/releases.html>`_
|
||||
- Updated code docstrings
|
||||
|
||||
|
||||
Version 0.3.3
|
||||
^^^^^^^^^^^^^
|
||||
**Release Date**: 2017-10-26
|
||||
|
||||
@@ -1,14 +1,13 @@
|
||||
import hashlib
|
||||
import os
|
||||
import tempfile
|
||||
from logging import getLogger
|
||||
|
||||
import os
|
||||
import pandas as pd
|
||||
|
||||
from catalyst import get_calendar
|
||||
from catalyst.exchange.bundle_utils import get_bcolz_chunk, \
|
||||
get_periods_range, get_start_dt, get_month_start_end, get_df_from_arrays, \
|
||||
get_year_start_end
|
||||
get_start_dt, get_df_from_arrays
|
||||
from catalyst.exchange.exchange_bcolz import BcolzExchangeBarReader, \
|
||||
BcolzExchangeBarWriter
|
||||
from catalyst.exchange.exchange_bundle import ExchangeBundle, \
|
||||
@@ -122,18 +121,20 @@ class TestExchangeBundle:
|
||||
pass
|
||||
|
||||
def test_ingest_daily(self):
|
||||
# exchange_name = 'bitfinex'
|
||||
# data_frequency = 'daily'
|
||||
# include_symbols = 'neo_btc,bch_btc,eth_btc'
|
||||
|
||||
exchange_name = 'poloniex'
|
||||
exchange_name = 'bitfinex'
|
||||
data_frequency = 'daily'
|
||||
include_symbols = 'eth_btc'
|
||||
include_symbols = 'btc_usd'
|
||||
|
||||
start = pd.to_datetime('2017-1-1', utc=True)
|
||||
end = pd.to_datetime('2017-10-16', utc=True)
|
||||
periods = get_periods_range(start, end, data_frequency)
|
||||
# exchange_name = 'poloniex'
|
||||
# data_frequency = 'daily'
|
||||
# include_symbols = 'eth_btc'
|
||||
|
||||
# start = pd.to_datetime('2017-1-1', utc=True)
|
||||
# end = pd.to_datetime('2017-10-16', utc=True)
|
||||
# periods = get_periods_range(start, end, data_frequency)
|
||||
|
||||
start = None
|
||||
end = None
|
||||
exchange = get_exchange(exchange_name)
|
||||
exchange_bundle = ExchangeBundle(exchange)
|
||||
|
||||
@@ -153,12 +154,18 @@ class TestExchangeBundle:
|
||||
assets.append(exchange.get_asset(pair_symbol))
|
||||
|
||||
reader = exchange_bundle.get_reader(data_frequency)
|
||||
start_dt = reader.first_trading_day
|
||||
end_dt = reader.last_available_dt
|
||||
|
||||
if data_frequency == 'daily':
|
||||
end_dt = end_dt - pd.Timedelta(hours=23, minutes=59)
|
||||
|
||||
for asset in assets:
|
||||
arrays = reader.load_raw_arrays(
|
||||
sids=[asset.sid],
|
||||
fields=['close'],
|
||||
start_dt=start,
|
||||
end_dt=end
|
||||
start_dt=start_dt,
|
||||
end_dt=end_dt
|
||||
)
|
||||
print('found {} rows for {} ingestion\n{}'.format(
|
||||
len(arrays[0]), asset.symbol, arrays[0])
|
||||
@@ -430,14 +437,30 @@ class TestExchangeBundle:
|
||||
print('\n' + df_to_string(df))
|
||||
pass
|
||||
|
||||
def bundle_to_csv(self):
|
||||
def main_bundle_to_csv(self):
|
||||
exchange_name = 'bitfinex'
|
||||
data_frequency = 'daily'
|
||||
period = '2016'
|
||||
data_frequency = 'minute'
|
||||
|
||||
exchange = get_exchange(exchange_name)
|
||||
bundle = ExchangeBundle(exchange)
|
||||
asset = exchange.get_asset('eth_btc')
|
||||
asset = exchange.get_asset('neo_usd')
|
||||
|
||||
self._bundle_to_csv(
|
||||
asset=asset,
|
||||
exchange=exchange,
|
||||
data_frequency=data_frequency,
|
||||
filename='{}_{}_{}'.format(
|
||||
exchange_name, data_frequency, asset.symbol
|
||||
)
|
||||
)
|
||||
|
||||
def bundle_to_csv(self):
|
||||
exchange_name = 'bitfinex'
|
||||
data_frequency = 'minute'
|
||||
period = '2017-10'
|
||||
symbol = 'neo_btc'
|
||||
|
||||
exchange = get_exchange(exchange_name)
|
||||
asset = exchange.get_asset(symbol)
|
||||
|
||||
path = get_bcolz_chunk(
|
||||
exchange_name=exchange.name,
|
||||
@@ -445,7 +468,20 @@ class TestExchangeBundle:
|
||||
data_frequency=data_frequency,
|
||||
period=period
|
||||
)
|
||||
self._bundle_to_csv(
|
||||
asset=asset,
|
||||
exchange=exchange,
|
||||
data_frequency=data_frequency,
|
||||
path=path,
|
||||
filename=period
|
||||
)
|
||||
pass
|
||||
|
||||
def _bundle_to_csv(self, asset, exchange, data_frequency, filename,
|
||||
path=None):
|
||||
bundle = ExchangeBundle(exchange)
|
||||
reader = bundle.get_reader(data_frequency, path=path)
|
||||
|
||||
start_dt = reader.first_trading_day
|
||||
end_dt = reader.last_available_dt
|
||||
|
||||
@@ -475,7 +511,7 @@ class TestExchangeBundle:
|
||||
)
|
||||
ensure_directory(folder)
|
||||
|
||||
path = os.path.join(folder, period + '.csv')
|
||||
path = os.path.join(folder, filename + '.csv')
|
||||
|
||||
log.info('creating csv file: {}'.format(path))
|
||||
print('HEAD\n{}'.format(df.head(10)))
|
||||
|
||||
Reference in New Issue
Block a user