Fix the fee calculation, backtesting, and hyperopt fee calculation and avg_profit

This commit is contained in:
Gerald Lonlas 2017-12-18 21:58:02 -08:00
commit d258118b0a
14 changed files with 94 additions and 59 deletions

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@ -1,4 +1,4 @@
sudo: false sudo: true
os: os:
- linux - linux
language: python language: python
@ -11,9 +11,7 @@ addons:
- libdw-dev - libdw-dev
- binutils-dev - binutils-dev
install: install:
- wget http://prdownloads.sourceforge.net/ta-lib/ta-lib-0.4.0-src.tar.gz - ./install_ta-lib.sh
- tar zxvf ta-lib-0.4.0-src.tar.gz
- cd ta-lib && ./configure && sudo make && sudo make install && cd ..
- export LD_LIBRARY_PATH=/usr/local/lib:$LD_LIBRARY_PATH - export LD_LIBRARY_PATH=/usr/local/lib:$LD_LIBRARY_PATH
- pip install flake8 coveralls - pip install flake8 coveralls
- pip install -r requirements.txt - pip install -r requirements.txt
@ -27,11 +25,13 @@ jobs:
- script: - script:
- cp config.json.example config.json - cp config.json.example config.json
- python freqtrade/main.py hyperopt -e 5 - python freqtrade/main.py hyperopt -e 5
- script: flake8 freqtrade
after_success: after_success:
- flake8 freqtrade && coveralls - coveralls
notifications: notifications:
slack: slack:
secure: 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 secure: bKLXmOrx8e2aPZl7W8DA5BdPAXWGpI5UzST33oc1G/thegXcDVmHBTJrBs4sZak6bgAclQQrdZIsRd2eFYzHLalJEaw6pk7hoAw8SvLnZO0ZurWboz7qg2+aZZXfK4eKl/VUe4sM9M4e/qxjkK+yWG7Marg69c4v1ypF7ezUi1fPYILYw8u0paaiX0N5UX8XNlXy+PBlga2MxDjUY70MuajSZhPsY2pDUvYnMY1D/7XN3cFW0g+3O8zXjF0IF4q1Z/1ASQe+eYjKwPQacE+O8KDD+ZJYoTOFBAPllrtpO1jnOPFjNGf3JIbVMZw4bFjIL0mSQaiSUaUErbU3sFZ5Or79rF93XZ81V7uEZ55vD8KMfR2CB1cQJcZcj0v50BxLo0InkFqa0Y8Nra3sbpV4fV5Oe8pDmomPJrNFJnX6ULQhQ1gTCe0M5beKgVms5SITEpt4/Y0CmLUr6iHDT0CUiyMIRWAXdIgbGh1jfaWOMksybeRevlgDsIsNBjXmYI1Sw2ZZR2Eo2u4R6zyfyjOMLwYJ3vgq9IrACv2w5nmf0+oguMWHf6iWi2hiOqhlAN1W74+3HsYQcqnuM3LGOmuCnPprV1oGBqkPXjIFGpy21gNx4vHfO1noLUyJnMnlu2L7SSuN1CdLsnjJ1hVjpJjPfqB4nn8g12x87TqM1bOm+3Q=
cache: cache:
directories: directories:
- $HOME/.cache/pip - $HOME/.cache/pip
- ta-lib

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@ -50,8 +50,8 @@ class Bittrex(Exchange):
@property @property
def fee(self) -> float: def fee(self) -> float:
# See https://bittrex.com/fees # 0.25 %: See https://bittrex.com/fees
return 0.0025 #0.25% return 0.0025
def buy(self, pair: str, rate: float, amount: float) -> str: def buy(self, pair: str, rate: float, amount: float) -> str:
data = _API.buy_limit(pair.replace('_', '-'), amount, rate) data = _API.buy_limit(pair.replace('_', '-'), amount, rate)

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@ -168,8 +168,8 @@ def build_subcommands(parser: argparse.ArgumentParser) -> None:
) )
backtesting_cmd.add_argument( backtesting_cmd.add_argument(
'-r', '--refresh-pairs-cached', '-r', '--refresh-pairs-cached',
help='refresh the pairs files in tests/testdata with the latest data from Bittrex. Use it if you want to \ help='refresh the pairs files in tests/testdata with the latest data from Bittrex. \
run your backtesting with up-to-date data.', Use it if you want to run your backtesting with up-to-date data.',
action='store_true', action='store_true',
dest='refresh_pairs', dest='refresh_pairs',
) )

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@ -13,7 +13,8 @@ from freqtrade.analyze import populate_indicators, parse_ticker_dataframe
logger = logging.getLogger(__name__) logger = logging.getLogger(__name__)
def load_data(pairs: List[str], ticker_interval: int = 5, refresh_pairs: Optional[bool] = False) -> Dict[str, List]: def load_data(pairs: List[str], ticker_interval: int = 5,
refresh_pairs: Optional[bool] = False) -> Dict[str, List]:
""" """
Loads ticker history data for the given parameters Loads ticker history data for the given parameters
:param ticker_interval: ticker interval in minutes :param ticker_interval: ticker interval in minutes
@ -61,10 +62,10 @@ def download_pairs(pairs: List[str]) -> bool:
"""For each pairs passed in parameters, download 1 and 5 ticker intervals""" """For each pairs passed in parameters, download 1 and 5 ticker intervals"""
for pair in pairs: for pair in pairs:
try: try:
for interval in [1,5]: for interval in [1, 5]:
download_backtesting_testdata(pair=pair, interval=interval) download_backtesting_testdata(pair=pair, interval=interval)
except BaseException: except BaseException:
logger.info('Impossible to download the pair: "{pair}", Interval: {interval} min'.format( logger.info('Failed to download the pair: "{pair}", Interval: {interval} min'.format(
pair=pair, pair=pair,
interval=interval, interval=interval,
)) ))
@ -103,7 +104,7 @@ def download_backtesting_testdata(pair: str, interval: int = 5) -> bool:
logger.debug("Current Start: None") logger.debug("Current Start: None")
logger.debug("Current End: None") logger.debug("Current End: None")
new_data = get_ticker_history(pair = pair, tick_interval = int(interval)) new_data = get_ticker_history(pair=pair, tick_interval=int(interval))
for row in new_data: for row in new_data:
if row not in data: if row not in data:
data.append(row) data.append(row)

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@ -48,8 +48,8 @@ def generate_text_table(
tabular_data.append([ tabular_data.append([
pair, pair,
len(result.index), len(result.index),
'{:.2f}%'.format(result.profit.mean() * 100.0), '{:.2f}%'.format(result.profit_percent.mean() * 100.0),
'{:.08f} {}'.format(result.profit.sum(), stake_currency), '{:.08f} {}'.format(result.profit_BTC.sum(), stake_currency),
'{:.2f}'.format(result.duration.mean() * ticker_interval), '{:.2f}'.format(result.duration.mean() * ticker_interval),
]) ])
@ -57,8 +57,8 @@ def generate_text_table(
tabular_data.append([ tabular_data.append([
'TOTAL', 'TOTAL',
len(results.index), len(results.index),
'{:.2f}%'.format(results.profit.mean() * 100.0), '{:.2f}%'.format(results.profit_percent.mean() * 100.0),
'{:.08f} {}'.format(results.profit.sum(), stake_currency), '{:.08f} {}'.format(results.profit_BTC.sum(), stake_currency),
'{:.2f}'.format(results.duration.mean() * ticker_interval), '{:.2f}'.format(results.duration.mean() * ticker_interval),
]) ])
return tabulate(tabular_data, headers=headers) return tabulate(tabular_data, headers=headers)
@ -98,7 +98,8 @@ def backtest(config: Dict, processed: Dict[str, DataFrame],
trade = Trade( trade = Trade(
open_rate=row.close, open_rate=row.close,
open_date=row.date, open_date=row.date,
amount=config['stake_amount'], stake_amount=config['stake_amount'],
amount=config['stake_amount'] / row.open,
fee=exchange.get_fee() fee=exchange.get_fee()
) )
@ -109,12 +110,20 @@ def backtest(config: Dict, processed: Dict[str, DataFrame],
trade_count_lock[row2.date] = trade_count_lock.get(row2.date, 0) + 1 trade_count_lock[row2.date] = trade_count_lock.get(row2.date, 0) + 1
if min_roi_reached(trade, row2.close, row2.date) or row2.sell == 1: if min_roi_reached(trade, row2.close, row2.date) or row2.sell == 1:
current_profit = trade.calc_profit_percent(row2.close) current_profit_percent = trade.calc_profit_percent(rate=row2.close)
current_profit_BTC = trade.calc_profit(rate=row2.close)
lock_pair_until = row2.Index lock_pair_until = row2.Index
trades.append((pair, current_profit, row2.Index - row.Index)) trades.append(
(
pair,
current_profit_percent,
current_profit_BTC,
row2.Index - row.Index
)
)
break break
labels = ['currency', 'profit', 'duration'] labels = ['currency', 'profit_percent', 'profit_BTC', 'duration']
return DataFrame.from_records(trades, columns=labels) return DataFrame.from_records(trades, columns=labels)
@ -140,7 +149,8 @@ def start(args):
data[pair] = exchange.get_ticker_history(pair, args.ticker_interval) data[pair] = exchange.get_ticker_history(pair, args.ticker_interval)
else: else:
logger.info('Using local backtesting data (using whitelist in given config) ...') logger.info('Using local backtesting data (using whitelist in given config) ...')
data = load_data(pairs=pairs, ticker_interval=args.ticker_interval, refresh_pairs=args.refresh_pairs) data = load_data(pairs=pairs, ticker_interval=args.ticker_interval,
refresh_pairs=args.refresh_pairs)
logger.info('Using stake_currency: %s ...', config['stake_currency']) logger.info('Using stake_currency: %s ...', config['stake_currency'])
logger.info('Using stake_amount: %s ...', config['stake_amount']) logger.info('Using stake_amount: %s ...', config['stake_amount'])

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@ -131,7 +131,7 @@ def optimizer(params):
result = format_results(results) result = format_results(results)
total_profit = results.profit.sum() * 1000 total_profit = results.profit_percent.sum() * 1000
trade_count = len(results.index) trade_count = len(results.index)
trade_loss = 1 - 0.35 * exp(-(trade_count - TARGET_TRADES) ** 2 / 10 ** 5.2) trade_loss = 1 - 0.35 * exp(-(trade_count - TARGET_TRADES) ** 2 / 10 ** 5.2)
@ -144,13 +144,13 @@ def optimizer(params):
'total_profit': total_profit, 'total_profit': total_profit,
'trade_loss': trade_loss, 'trade_loss': trade_loss,
'profit_loss': profit_loss, 'profit_loss': profit_loss,
'avg_profit': results.profit.mean() * 100.0, 'avg_profit': results.profit_percent.mean() * 100.0,
'avg_duration': results.duration.mean() * 5, 'avg_duration': results.duration.mean() * 5,
'current_tries': _CURRENT_TRIES, 'current_tries': _CURRENT_TRIES,
'total_tries': TOTAL_TRIES, 'total_tries': TOTAL_TRIES,
'result': result, 'result': result,
'results': results 'results': results
} }
# logger.info('{:5d}/{}: {}'.format(_CURRENT_TRIES, TOTAL_TRIES, result)) # logger.info('{:5d}/{}: {}'.format(_CURRENT_TRIES, TOTAL_TRIES, result))
log_results(result_data) log_results(result_data)
@ -166,10 +166,10 @@ def format_results(results: DataFrame):
return ('Made {:6d} buys. Average profit {: 5.2f}%. ' return ('Made {:6d} buys. Average profit {: 5.2f}%. '
'Total profit was {: 7.3f}. Average duration {:5.1f} mins.').format( 'Total profit was {: 7.3f}. Average duration {:5.1f} mins.').format(
len(results.index), len(results.index),
results.profit.mean() * 100.0, results.profit_percent.mean() * 100.0,
results.profit.sum(), results.profit_BTC.sum(),
results.duration.mean() * 5, results.duration.mean() * 5,
) )
def buy_strategy_generator(params): def buy_strategy_generator(params):
@ -232,7 +232,8 @@ def start(args):
logger.info('Using config: %s ...', args.config) logger.info('Using config: %s ...', args.config)
config = load_config(args.config) config = load_config(args.config)
pairs = config['exchange']['pair_whitelist'] pairs = config['exchange']['pair_whitelist']
PROCESSED = optimize.preprocess(optimize.load_data(pairs=pairs, ticker_interval=args.ticker_interval)) PROCESSED = optimize.preprocess(optimize.load_data(
pairs=pairs, ticker_interval=args.ticker_interval))
if args.mongodb: if args.mongodb:
logger.info('Using mongodb ...') logger.info('Using mongodb ...')

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@ -121,7 +121,9 @@ class Trade(_DECL_BASE):
self self
) )
def calc_open_trade_price(self, fee: Optional[float] = None) -> float: def calc_open_trade_price(
self,
fee: Optional[float] = None) -> float:
""" """
Calculate the open_rate in BTC Calculate the open_rate in BTC
:param fee: fee to use on the open rate (optional). :param fee: fee to use on the open rate (optional).
@ -134,7 +136,10 @@ class Trade(_DECL_BASE):
fees = buy_trade * Decimal(fee or self.fee) fees = buy_trade * Decimal(fee or self.fee)
return float(buy_trade + fees) return float(buy_trade + fees)
def calc_close_trade_price(self, rate: Optional[float] = None, fee: Optional[float] = None) -> float: def calc_close_trade_price(
self,
rate: Optional[float] = None,
fee: Optional[float] = None) -> float:
""" """
Calculate the close_rate in BTC Calculate the close_rate in BTC
:param fee: fee to use on the close rate (optional). :param fee: fee to use on the close rate (optional).
@ -152,7 +157,10 @@ class Trade(_DECL_BASE):
fees = sell_trade * Decimal(fee or self.fee) fees = sell_trade * Decimal(fee or self.fee)
return float(sell_trade - fees) return float(sell_trade - fees)
def calc_profit(self, rate: Optional[float] = None, fee: Optional[float] = None) -> float: def calc_profit(
self,
rate: Optional[float] = None,
fee: Optional[float] = None) -> float:
""" """
Calculate the profit in BTC between Close and Open trade Calculate the profit in BTC between Close and Open trade
:param fee: fee to use on the close rate (optional). :param fee: fee to use on the close rate (optional).
@ -168,7 +176,10 @@ class Trade(_DECL_BASE):
) )
return float("{0:.8f}".format(close_trade_price - open_trade_price)) return float("{0:.8f}".format(close_trade_price - open_trade_price))
def calc_profit_percent(self, rate: Optional[float] = None, fee: Optional[float] = None) -> float: def calc_profit_percent(
self,
rate: Optional[float] = None,
fee: Optional[float] = None) -> float:
""" """
Calculates the profit in percentage (including fee). Calculates the profit in percentage (including fee).
:param rate: rate to compare with (optional). :param rate: rate to compare with (optional).

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@ -232,8 +232,8 @@ def _daily(bot: Bot, update: Update) -> None:
for day in range(0, timescale): for day in range(0, timescale):
# need to query between day+1 and day-1 # need to query between day+1 and day-1
nextdate = date.fromordinal(today-day+1) nextdate = date.fromordinal(today - day + 1)
prevdate = date.fromordinal(today-day-1) prevdate = date.fromordinal(today - day - 1)
trades = Trade.query \ trades = Trade.query \
.filter(Trade.is_open.is_(False)) \ .filter(Trade.is_open.is_(False)) \
.filter(between(Trade.close_date, prevdate, nextdate)) \ .filter(between(Trade.close_date, prevdate, nextdate)) \

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@ -66,6 +66,7 @@ def ticker():
'last': 0.00001098, 'last': 0.00001098,
}) })
@pytest.fixture @pytest.fixture
def ticker_sell_up(): def ticker_sell_up():
return MagicMock(return_value={ return MagicMock(return_value={
@ -74,6 +75,7 @@ def ticker_sell_up():
'last': 0.00001172, 'last': 0.00001172,
}) })
@pytest.fixture @pytest.fixture
def ticker_sell_down(): def ticker_sell_down():
return MagicMock(return_value={ return MagicMock(return_value={
@ -82,6 +84,7 @@ def ticker_sell_down():
'last': 0.00001044, 'last': 0.00001044,
}) })
@pytest.fixture @pytest.fixture
def health(): def health():
return MagicMock(return_value=[{ return MagicMock(return_value=[{
@ -143,7 +146,7 @@ def limit_sell_order():
@pytest.fixture @pytest.fixture
def ticker_history(): def ticker_history():
return [ return [
{ {
"O": 8.794e-05, "O": 8.794e-05,
"H": 8.948e-05, "H": 8.948e-05,
"L": 8.794e-05, "L": 8.794e-05,
@ -152,7 +155,7 @@ def ticker_history():
"T": "2017-11-26T08:50:00", "T": "2017-11-26T08:50:00",
"BV": 0.0877869 "BV": 0.0877869
}, },
{ {
"O": 8.88e-05, "O": 8.88e-05,
"H": 8.942e-05, "H": 8.942e-05,
"L": 8.88e-05, "L": 8.88e-05,
@ -161,7 +164,7 @@ def ticker_history():
"T": "2017-11-26T08:55:00", "T": "2017-11-26T08:55:00",
"BV": 0.05874751 "BV": 0.05874751
}, },
{ {
"O": 8.891e-05, "O": 8.891e-05,
"H": 8.893e-05, "H": 8.893e-05,
"L": 8.875e-05, "L": 8.875e-05,

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@ -1,15 +1,11 @@
# pragma pylint: disable=missing-docstring,W0212 # pragma pylint: disable=missing-docstring,W0212
from unittest.mock import MagicMock
from freqtrade import exchange, optimize from freqtrade import exchange, optimize
from freqtrade.exchange import Bittrex from freqtrade.exchange import Bittrex
from freqtrade.optimize.backtesting import backtest from freqtrade.optimize.backtesting import backtest
from freqtrade.optimize.__init__ import testdata_path, download_pairs, download_backtesting_testdata from freqtrade.optimize.__init__ import testdata_path, download_pairs, download_backtesting_testdata
import os import os
import pytest
def test_backtest(default_conf, mocker): def test_backtest(default_conf, mocker):
mocker.patch.dict('freqtrade.main._CONF', default_conf) mocker.patch.dict('freqtrade.main._CONF', default_conf)
@ -30,6 +26,7 @@ def test_1min_ticker_interval(default_conf, mocker):
results = backtest(default_conf, optimize.preprocess(data), 1, True) results = backtest(default_conf, optimize.preprocess(data), 1, True)
assert len(results) > 0 assert len(results) > 0
def test_backtest_with_new_pair(default_conf, ticker_history, mocker): def test_backtest_with_new_pair(default_conf, ticker_history, mocker):
mocker.patch('freqtrade.optimize.get_ticker_history', return_value=ticker_history) mocker.patch('freqtrade.optimize.get_ticker_history', return_value=ticker_history)
mocker.patch.dict('freqtrade.main._CONF', default_conf) mocker.patch.dict('freqtrade.main._CONF', default_conf)
@ -59,7 +56,7 @@ def test_download_pairs(default_conf, ticker_history, mocker):
file2_1 = 'freqtrade/tests/testdata/BTC_CFI-1.json' file2_1 = 'freqtrade/tests/testdata/BTC_CFI-1.json'
file2_5 = 'freqtrade/tests/testdata/BTC_CFI-5.json' file2_5 = 'freqtrade/tests/testdata/BTC_CFI-5.json'
assert download_pairs(pairs = ['BTC-MEME', 'BTC-CFI']) is True assert download_pairs(pairs=['BTC-MEME', 'BTC-CFI']) is True
assert os.path.isfile(file1_1) is True assert os.path.isfile(file1_1) is True
assert os.path.isfile(file1_5) is True assert os.path.isfile(file1_5) is True
@ -87,7 +84,7 @@ def test_download_backtesting_testdata(default_conf, ticker_history, mocker):
# Download a 1 min ticker file # Download a 1 min ticker file
file1 = 'freqtrade/tests/testdata/BTC_XEL-1.json' file1 = 'freqtrade/tests/testdata/BTC_XEL-1.json'
download_backtesting_testdata(pair = "BTC-XEL", interval = 1) download_backtesting_testdata(pair="BTC-XEL", interval=1)
assert os.path.isfile(file1) is True assert os.path.isfile(file1) is True
if os.path.isfile(file1): if os.path.isfile(file1):
@ -95,7 +92,7 @@ def test_download_backtesting_testdata(default_conf, ticker_history, mocker):
# Download a 5 min ticker file # Download a 5 min ticker file
file2 = 'freqtrade/tests/testdata/BTC_STORJ-5.json' file2 = 'freqtrade/tests/testdata/BTC_STORJ-5.json'
download_backtesting_testdata(pair = "BTC-STORJ", interval = 5) download_backtesting_testdata(pair="BTC-STORJ", interval=5)
assert os.path.isfile(file2) is True assert os.path.isfile(file2) is True
if os.path.isfile(file2): if os.path.isfile(file2):

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@ -10,17 +10,23 @@ def test_update_with_bittrex(limit_buy_order, limit_sell_order):
On this test we will buy and sell a crypto currency. On this test we will buy and sell a crypto currency.
Buy Buy
- Buy: 90.99181073 Crypto at 0.00001099 BTC (90.99181073*0.00001099 = 0.0009999 BTC) - Buy: 90.99181073 Crypto at 0.00001099 BTC
(90.99181073*0.00001099 = 0.0009999 BTC)
- Buying fee: 0.25% - Buying fee: 0.25%
- Total cost of buy trade: 0.001002500 BTC ((90.99181073*0.00001099) + ((90.99181073*0.00001099)*0.0025)) - Total cost of buy trade: 0.001002500 BTC
((90.99181073*0.00001099) + ((90.99181073*0.00001099)*0.0025))
Sell Sell
- Sell: 90.99181073 Crypto at 0.00001173 BTC (90.99181073*0.00001173 = 0,00106733394 BTC) - Sell: 90.99181073 Crypto at 0.00001173 BTC
(90.99181073*0.00001173 = 0,00106733394 BTC)
- Selling fee: 0.25% - Selling fee: 0.25%
- Total cost of sell trade: 0.001064666 BTC ((90.99181073*0.00001173) - ((90.99181073*0.00001173)*0.0025)) - Total cost of sell trade: 0.001064666 BTC
((90.99181073*0.00001173) - ((90.99181073*0.00001173)*0.0025))
Profit/Loss: +0.000062166 BTC (Sell:0.001064666 - Buy:0.001002500) Profit/Loss: +0.000062166 BTC
Profit/Loss percentage: 0.0620 ((0.001064666/0.001002500)-1 = 6.20%) (Sell:0.001064666 - Buy:0.001002500)
Profit/Loss percentage: 0.0620
((0.001064666/0.001002500)-1 = 6.20%)
:param limit_buy_order: :param limit_buy_order:
:param limit_sell_order: :param limit_sell_order:

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@ -1,6 +1,6 @@
# pragma pylint: disable=missing-docstring, too-many-arguments, too-many-ancestors, C0103 # pragma pylint: disable=missing-docstring, too-many-arguments, too-many-ancestors, C0103
import re import re
from datetime import datetime, date from datetime import datetime
from random import randint from random import randint
from unittest.mock import MagicMock from unittest.mock import MagicMock
@ -151,7 +151,8 @@ def test_status_table_handle(default_conf, update, ticker, mocker):
assert msg_mock.call_count == 1 assert msg_mock.call_count == 1
def test_profit_handle(default_conf, update, ticker, ticker_sell_up, limit_buy_order, limit_sell_order, mocker): def test_profit_handle(
default_conf, update, ticker, ticker_sell_up, limit_buy_order, limit_sell_order, mocker):
mocker.patch.dict('freqtrade.main._CONF', default_conf) mocker.patch.dict('freqtrade.main._CONF', default_conf)
mocker.patch('freqtrade.main.get_signal', side_effect=lambda s, t: True) mocker.patch('freqtrade.main.get_signal', side_effect=lambda s, t: True)
msg_mock = MagicMock() msg_mock = MagicMock()
@ -246,7 +247,7 @@ def test_forcesell_down_handle(default_conf, update, ticker, ticker_sell_down, m
# Create some test data # Create some test data
create_trade(0.001) create_trade(0.001)
## Decrease the price and sell it # Decrease the price and sell it
mocker.patch.multiple('freqtrade.main.exchange', mocker.patch.multiple('freqtrade.main.exchange',
validate_pairs=MagicMock(), validate_pairs=MagicMock(),
get_ticker=ticker_sell_down) get_ticker=ticker_sell_down)
@ -383,7 +384,6 @@ def test_performance_handle(
assert '<code>BTC_ETH\t6.20%</code>' in msg_mock.call_args_list[0][0][0] assert '<code>BTC_ETH\t6.20%</code>' in msg_mock.call_args_list[0][0][0]
def test_daily_handle( def test_daily_handle(
default_conf, update, ticker, limit_buy_order, limit_sell_order, mocker): default_conf, update, ticker, limit_buy_order, limit_sell_order, mocker):
mocker.patch.dict('freqtrade.main._CONF', default_conf) mocker.patch.dict('freqtrade.main._CONF', default_conf)

8
install_ta-lib.sh Executable file
View File

@ -0,0 +1,8 @@
if [ ! -f "ta-lib/CHANGELOG.TXT" ]; then
curl -O http://prdownloads.sourceforge.net/ta-lib/ta-lib-0.4.0-src.tar.gz
tar zxvf ta-lib-0.4.0-src.tar.gz
cd ta-lib && ./configure && make && sudo make install && cd ..
else
echo "TA-lib already installed, skipping download and build."
cd ta-lib && sudo make install && cd ..
fi

View File

@ -3,7 +3,6 @@
import matplotlib # Install PYQT5 manually if you want to test this helper function import matplotlib # Install PYQT5 manually if you want to test this helper function
matplotlib.use("Qt5Agg") matplotlib.use("Qt5Agg")
import matplotlib.pyplot as plt import matplotlib.pyplot as plt
from freqtrade import exchange, analyze from freqtrade import exchange, analyze
@ -52,4 +51,3 @@ def plot_analyzed_dataframe(pair: str) -> None:
if __name__ == '__main__': if __name__ == '__main__':
plot_analyzed_dataframe('BTC_ETH') plot_analyzed_dataframe('BTC_ETH')