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Merge branch 'fix-docs' of https://github.com/stash86/freqtrade into fix-docs

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This commit is contained in:
Stefano Ariestasia 2021-11-29 14:32:37 +09:00
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110
docs/plotting.md
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@ -164,16 +164,17 @@ The resulting plot will have the following elements:
An advanced plot configuration can be specified in the strategy in the `plot_config` parameter.
Additional features when using plot_config include:
Additional features when using `plot_config` include:
* Specify colors per indicator
* Specify additional subplots
* Specify indicator pairs to fill area in between
* Specify indicator pairs to fill area in between
The sample plot configuration below specifies fixed colors for the indicators. Otherwise, consecutive plots may produce different color schemes each time, making comparisons difficult.
It also allows multiple subplots to display both MACD and RSI at the same time.
Plot type can be configured using `type` key. Possible types are:
* `scatter` corresponding to `plotly.graph_objects.Scatter` class (default).
* `bar` corresponding to `plotly.graph_objects.Bar` class.
@ -182,40 +183,89 @@ Extra parameters to `plotly.graph_objects.*` constructor can be specified in `pl
Sample configuration with inline comments explaining the process:
``` python
plot_config = {
'main_plot': {
# Configuration for main plot indicators.
# Specifies `ema10` to be red, and `ema50` to be a shade of gray
'ema10': {'color': 'red'},
'ema50': {'color': '#CCCCCC'},
# By omitting color, a random color is selected.
'sar': {},
# fill area between senkou_a and senkou_b
'senkou_a': {
'color': 'green', #optional
'fill_to': 'senkou_b',
'fill_label': 'Ichimoku Cloud', #optional
'fill_color': 'rgba(255,76,46,0.2)', #optional
},
# plot senkou_b, too. Not only the area to it.
'senkou_b': {}
@property
def plot_config(self):
"""
There are a lot of solutions how to build the return dictionary.
The only important point is the return value.
Example:
plot_config = {'main_plot': {}, 'subplots': {}}
"""
plot_config = {}
plot_config['main_plot'] = {
# Configuration for main plot indicators.
# Assumes 2 parameters, emashort and emalong to be specified.
f'ema_{self.emashort.value}': {'color': 'red'},
f'ema_{self.emalong.value}': {'color': '#CCCCCC'},
# By omitting color, a random color is selected.
'sar': {},
# fill area between senkou_a and senkou_b
'senkou_a': {
'color': 'green', #optional
'fill_to': 'senkou_b',
'fill_label': 'Ichimoku Cloud', #optional
'fill_color': 'rgba(255,76,46,0.2)', #optional
},
'subplots': {
# Create subplot MACD
"MACD": {
'macd': {'color': 'blue', 'fill_to': 'macdhist'},
'macdsignal': {'color': 'orange'},
'macdhist': {'type': 'bar', 'plotly': {'opacity': 0.9}}
},
# Additional subplot RSI
"RSI": {
'rsi': {'color': 'red'}
}
# plot senkou_b, too. Not only the area to it.
'senkou_b': {}
}
plot_config['subplots'] = {
# Create subplot MACD
"MACD": {
'macd': {'color': 'blue', 'fill_to': 'macdhist'},
'macdsignal': {'color': 'orange'},
'macdhist': {'type': 'bar', 'plotly': {'opacity': 0.9}}
},
# Additional subplot RSI
"RSI": {
'rsi': {'color': 'red'}
}
}
return plot_config
```
??? Note "As attribute (former method)"
Assigning plot_config is also possible as Attribute (this used to be the default way).
This has the disadvantage that strategy parameters are not available, preventing certain configurations from working.
``` python
plot_config = {
'main_plot': {
# Configuration for main plot indicators.
# Specifies `ema10` to be red, and `ema50` to be a shade of gray
'ema10': {'color': 'red'},
'ema50': {'color': '#CCCCCC'},
# By omitting color, a random color is selected.
'sar': {},
# fill area between senkou_a and senkou_b
'senkou_a': {
'color': 'green', #optional
'fill_to': 'senkou_b',
'fill_label': 'Ichimoku Cloud', #optional
'fill_color': 'rgba(255,76,46,0.2)', #optional
},
# plot senkou_b, too. Not only the area to it.
'senkou_b': {}
},
'subplots': {
# Create subplot MACD
"MACD": {
'macd': {'color': 'blue', 'fill_to': 'macdhist'},
'macdsignal': {'color': 'orange'},
'macdhist': {'type': 'bar', 'plotly': {'opacity': 0.9}}
},
# Additional subplot RSI
"RSI": {
'rsi': {'color': 'red'}
}
}
}
```
!!! Note
The above configuration assumes that `ema10`, `ema50`, `senkou_a`, `senkou_b`,
`macd`, `macdsignal`, `macdhist` and `rsi` are columns in the DataFrame created by the strategy.

4
docs/strategy_analysis_example.md
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@ -50,7 +50,9 @@ candles.head()
```python
# Load strategy using values set above
from freqtrade.resolvers import StrategyResolver
from freqtrade.data.dataprovider import DataProvider
strategy = StrategyResolver.load_strategy(config)
strategy.dp = DataProvider(config, None, None)
# Generate buy/sell signals using strategy
df = strategy.analyze_ticker(candles, {'pair': pair})
@ -228,7 +230,7 @@ graph = generate_candlestick_graph(pair=pair,
# Show graph inline
# graph.show()
# Render graph in a separate window
# Render graph in a seperate window
graph.show(renderer="browser")
```

2
freqtrade/exchange/exchange.py
View File

@ -1294,7 +1294,7 @@ class Exchange:
cached_pairs = []
# Gather coroutines to run
for pair, timeframe in set(pair_list):
if ((pair, timeframe) not in self._klines
if ((pair, timeframe) not in self._klines or not cache
or self._now_is_time_to_refresh(pair, timeframe)):
if not since_ms and self.required_candle_call_count > 1:
# Multiple calls for one pair - to get more history

22
freqtrade/freqtradebot.py
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@ -466,8 +466,8 @@ class FreqtradeBot(LoggingMixin):
logger.info(f"Bids to asks delta for {pair} does not satisfy condition.")
return False
def execute_entry(self, pair: str, stake_amount: float, price: Optional[float] = None,
forcebuy: bool = False, buy_tag: Optional[str] = None) -> bool:
def execute_entry(self, pair: str, stake_amount: float, price: Optional[float] = None, *,
ordertype: Optional[str] = None, buy_tag: Optional[str] = None) -> bool:
"""
Executes a limit buy for the given pair
:param pair: pair for which we want to create a LIMIT_BUY
@ -510,10 +510,7 @@ class FreqtradeBot(LoggingMixin):
f"{stake_amount} ...")
amount = stake_amount / enter_limit_requested
order_type = self.strategy.order_types['buy']
if forcebuy:
# Forcebuy can define a different ordertype
order_type = self.strategy.order_types.get('forcebuy', order_type)
order_type = ordertype or self.strategy.order_types['buy']
if not strategy_safe_wrapper(self.strategy.confirm_trade_entry, default_retval=True)(
pair=pair, order_type=order_type, amount=amount, rate=enter_limit_requested,
@ -868,7 +865,7 @@ class FreqtradeBot(LoggingMixin):
logger.info(
f'Executing Sell for {trade.pair}. Reason: {should_sell.sell_type}. '
f'Tag: {exit_tag if exit_tag is not None else "None"}')
self.execute_trade_exit(trade, exit_rate, should_sell, exit_tag)
self.execute_trade_exit(trade, exit_rate, should_sell, exit_tag=exit_tag)
return True
return False
@ -1081,7 +1078,10 @@ class FreqtradeBot(LoggingMixin):
trade: Trade,
limit: float,
sell_reason: SellCheckTuple,
exit_tag: Optional[str] = None) -> bool:
*,
exit_tag: Optional[str] = None,
ordertype: Optional[str] = None,
) -> bool:
"""
Executes a trade exit for the given trade and limit
:param trade: Trade instance
@ -1119,14 +1119,10 @@ class FreqtradeBot(LoggingMixin):
except InvalidOrderException:
logger.exception(f"Could not cancel stoploss order {trade.stoploss_order_id}")
order_type = self.strategy.order_types[sell_type]
order_type = ordertype or self.strategy.order_types[sell_type]
if sell_reason.sell_type == SellType.EMERGENCY_SELL:
# Emergency sells (default to market!)
order_type = self.strategy.order_types.get("emergencysell", "market")
if sell_reason.sell_type == SellType.FORCE_SELL:
# Force sells (default to the sell_type defined in the strategy,
# but we allow this value to be changed)
order_type = self.strategy.order_types.get("forcesell", order_type)
amount = self._safe_exit_amount(trade.pair, trade.amount)
time_in_force = self.strategy.order_time_in_force['sell']

50
freqtrade/optimize/optimize_reports.py
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@ -46,20 +46,11 @@ def _get_line_floatfmt(stake_currency: str) -> List[str]:
'.2f', 'd', 's', 's']
def _get_line_header(first_column: str, stake_currency: str) -> List[str]:
def _get_line_header(first_column: str, stake_currency: str, direction: str = 'Buys') -> List[str]:
"""
Generate header lines (goes in line with _generate_result_line())
"""
return [first_column, 'Buys', 'Avg Profit %', 'Cum Profit %',
f'Tot Profit {stake_currency}', 'Tot Profit %', 'Avg Duration',
'Win Draw Loss Win%']
def _get_line_header_sell(first_column: str, stake_currency: str) -> List[str]:
"""
Generate header lines (goes in line with _generate_result_line())
"""
return [first_column, 'Sells', 'Avg Profit %', 'Cum Profit %',
return [first_column, direction, 'Avg Profit %', 'Cum Profit %',
f'Tot Profit {stake_currency}', 'Tot Profit %', 'Avg Duration',
'Win Draw Loss Win%']
@ -156,7 +147,7 @@ def generate_tag_metrics(tag_type: str,
if skip_nan and result['profit_abs'].isnull().all():
continue
tabular_data.append(_generate_tag_result_line(result, starting_balance, tag))
tabular_data.append(_generate_result_line(result, starting_balance, tag))
# Sort by total profit %:
tabular_data = sorted(tabular_data, key=lambda k: k['profit_total_abs'], reverse=True)
@ -168,39 +159,6 @@ def generate_tag_metrics(tag_type: str,
return []
def _generate_tag_result_line(result: DataFrame, starting_balance: int, first_column: str) -> Dict:
"""
Generate one result dict, with "first_column" as key.
"""
profit_sum = result['profit_ratio'].sum()
# (end-capital - starting capital) / starting capital
profit_total = result['profit_abs'].sum() / starting_balance
return {
'key': first_column,
'trades': len(result),
'profit_mean': result['profit_ratio'].mean() if len(result) > 0 else 0.0,
'profit_mean_pct': result['profit_ratio'].mean() * 100.0 if len(result) > 0 else 0.0,
'profit_sum': profit_sum,
'profit_sum_pct': round(profit_sum * 100.0, 2),
'profit_total_abs': result['profit_abs'].sum(),
'profit_total': profit_total,
'profit_total_pct': round(profit_total * 100.0, 2),
'duration_avg': str(timedelta(
minutes=round(result['trade_duration'].mean()))
) if not result.empty else '0:00',
# 'duration_max': str(timedelta(
# minutes=round(result['trade_duration'].max()))
# ) if not result.empty else '0:00',
# 'duration_min': str(timedelta(
# minutes=round(result['trade_duration'].min()))
# ) if not result.empty else '0:00',
'wins': len(result[result['profit_abs'] > 0]),
'draws': len(result[result['profit_abs'] == 0]),
'losses': len(result[result['profit_abs'] < 0]),
}
def generate_sell_reason_stats(max_open_trades: int, results: DataFrame) -> List[Dict]:
"""
Generate small table outlining Backtest results
@ -631,7 +589,7 @@ def text_table_tags(tag_type: str, tag_results: List[Dict[str, Any]], stake_curr
if(tag_type == "buy_tag"):
headers = _get_line_header("TAG", stake_currency)
else:
headers = _get_line_header_sell("TAG", stake_currency)
headers = _get_line_header("TAG", stake_currency, 'Sells')
floatfmt = _get_line_floatfmt(stake_currency)
output = [
[

23
freqtrade/rpc/api_server/api_schemas.py
View File

@ -1,4 +1,5 @@
from datetime import date, datetime
from enum import Enum
from typing import Any, Dict, List, Optional, Union
from pydantic import BaseModel
@ -131,13 +132,21 @@ class UnfilledTimeout(BaseModel):
exit_timeout_count: Optional[int]
class OrderTypeValues(Enum):
limit = 'limit'
market = 'market'
class Config:
use_enum_values = True
class OrderTypes(BaseModel):
buy: str
sell: str
emergencysell: Optional[str]
forcesell: Optional[str]
forcebuy: Optional[str]
stoploss: str
buy: OrderTypeValues
sell: OrderTypeValues
emergencysell: Optional[OrderTypeValues]
forcesell: Optional[OrderTypeValues]
forcebuy: Optional[OrderTypeValues]
stoploss: OrderTypeValues
stoploss_on_exchange: bool
stoploss_on_exchange_interval: Optional[int]
@ -274,10 +283,12 @@ class Logs(BaseModel):
class ForceBuyPayload(BaseModel):
pair: str
price: Optional[float]
ordertype: Optional[OrderTypeValues]
class ForceSellPayload(BaseModel):
tradeid: str
ordertype: Optional[OrderTypeValues]
class BlacklistPayload(BaseModel):

9
freqtrade/rpc/api_server/api_v1.py
View File

@ -29,7 +29,8 @@ logger = logging.getLogger(__name__)
# API version
# Pre-1.1, no version was provided
# Version increments should happen in "small" steps (1.1, 1.12, ...) unless big changes happen.
API_VERSION = 1.1
# 1.11: forcebuy and forcesell accept ordertype
API_VERSION = 1.11
# Public API, requires no auth.
router_public = APIRouter()
@ -129,7 +130,8 @@ def show_config(rpc: Optional[RPC] = Depends(get_rpc_optional), config=Depends(g
@router.post('/forcebuy', response_model=ForceBuyResponse, tags=['trading'])
def forcebuy(payload: ForceBuyPayload, rpc: RPC = Depends(get_rpc)):
trade = rpc._rpc_forcebuy(payload.pair, payload.price)
ordertype = payload.ordertype.value if payload.ordertype else None
trade = rpc._rpc_forcebuy(payload.pair, payload.price, ordertype)
if trade:
return ForceBuyResponse.parse_obj(trade.to_json())
@ -139,7 +141,8 @@ def forcebuy(payload: ForceBuyPayload, rpc: RPC = Depends(get_rpc)):
@router.post('/forcesell', response_model=ResultMsg, tags=['trading'])
def forcesell(payload: ForceSellPayload, rpc: RPC = Depends(get_rpc)):
return rpc._rpc_forcesell(payload.tradeid)
ordertype = payload.ordertype.value if payload.ordertype else None
return rpc._rpc_forcesell(payload.tradeid, ordertype)
@router.get('/blacklist', response_model=BlacklistResponse, tags=['info', 'pairlist'])

16
freqtrade/rpc/rpc.py
View File

@ -640,7 +640,7 @@ class RPC:
return {'status': 'No more buy will occur from now. Run /reload_config to reset.'}
def _rpc_forcesell(self, trade_id: str) -> Dict[str, str]:
def _rpc_forcesell(self, trade_id: str, ordertype: Optional[str] = None) -> Dict[str, str]:
"""
Handler for forcesell <id>.
Sells the given trade at current price
@ -664,7 +664,11 @@ class RPC:
current_rate = self._freqtrade.exchange.get_rate(
trade.pair, refresh=False, side="sell")
sell_reason = SellCheckTuple(sell_type=SellType.FORCE_SELL)
self._freqtrade.execute_trade_exit(trade, current_rate, sell_reason)
order_type = ordertype or self._freqtrade.strategy.order_types.get(
"forcesell", self._freqtrade.strategy.order_types["sell"])
self._freqtrade.execute_trade_exit(
trade, current_rate, sell_reason, ordertype=order_type)
# ---- EOF def _exec_forcesell ----
if self._freqtrade.state != State.RUNNING:
@ -692,7 +696,8 @@ class RPC:
self._freqtrade.wallets.update()
return {'result': f'Created sell order for trade {trade_id}.'}
def _rpc_forcebuy(self, pair: str, price: Optional[float]) -> Optional[Trade]:
def _rpc_forcebuy(self, pair: str, price: Optional[float],
order_type: Optional[str] = None) -> Optional[Trade]:
"""
Handler for forcebuy <asset> <price>
Buys a pair trade at the given or current price
@ -720,7 +725,10 @@ class RPC:
stakeamount = self._freqtrade.wallets.get_trade_stake_amount(pair)
# execute buy
if self._freqtrade.execute_entry(pair, stakeamount, price, forcebuy=True):
if not order_type:
order_type = self._freqtrade.strategy.order_types.get(
'forcebuy', self._freqtrade.strategy.order_types['buy'])
if self._freqtrade.execute_entry(pair, stakeamount, price, ordertype=order_type):
Trade.commit()
trade = Trade.get_trades([Trade.is_open.is_(True), Trade.pair == pair]).first()
return trade

1
freqtrade/templates/base_strategy.py.j2
View File

@ -87,6 +87,7 @@ class {{ strategy }}(IStrategy):
'sell': 'gtc'
}
{{ plot_config | indent(4) }}
def informative_pairs(self):
"""
Define additional, informative pair/interval combinations to be cached from the exchange.

2
freqtrade/templates/strategy_analysis_example.ipynb
View File

@ -79,7 +79,9 @@
"source": [
"# Load strategy using values set above\n",
"from freqtrade.resolvers import StrategyResolver\n",
"from freqtrade.data.dataprovider import DataProvider\n",
"strategy = StrategyResolver.load_strategy(config)\n",
"strategy.dp = DataProvider(config, None, None)\n",
"\n",
"# Generate buy/sell signals using strategy\n",
"df = strategy.analyze_ticker(candles, {'pair': pair})\n",

30
freqtrade/templates/subtemplates/plot_config_full.j2
View File

@ -1,18 +1,20 @@
plot_config = {
# Main plot indicators (Moving averages, ...)
'main_plot': {
'tema': {},
'sar': {'color': 'white'},
},
'subplots': {
# Subplots - each dict defines one additional plot
"MACD": {
'macd': {'color': 'blue'},
'macdsignal': {'color': 'orange'},
@property
def plot_config(self):
return {
# Main plot indicators (Moving averages, ...)
'main_plot': {
'tema': {},
'sar': {'color': 'white'},
},
"RSI": {
'rsi': {'color': 'red'},
'subplots': {
# Subplots - each dict defines one additional plot
"MACD": {
'macd': {'color': 'blue'},
'macdsignal': {'color': 'orange'},
},
"RSI": {
'rsi': {'color': 'red'},
}
}
}
}

9
tests/exchange/test_exchange.py
View File

@ -1667,12 +1667,21 @@ def test_refresh_latest_ohlcv(mocker, default_conf, caplog) -> None:
assert len(res) == len(pairs)
assert exchange._api_async.fetch_ohlcv.call_count == 0
exchange.required_candle_call_count = 1
assert log_has(f"Using cached candle (OHLCV) data for pair {pairs[0][0]}, "
f"timeframe {pairs[0][1]} ...",
caplog)
res = exchange.refresh_latest_ohlcv([('IOTA/ETH', '5m'), ('XRP/ETH', '5m'), ('XRP/ETH', '1d')],
cache=False)
assert len(res) == 3
assert exchange._api_async.fetch_ohlcv.call_count == 3
# Test the same again, should NOT return from cache!
exchange._api_async.fetch_ohlcv.reset_mock()
res = exchange.refresh_latest_ohlcv([('IOTA/ETH', '5m'), ('XRP/ETH', '5m'), ('XRP/ETH', '1d')],
cache=False)
assert len(res) == 3
assert exchange._api_async.fetch_ohlcv.call_count == 3
@pytest.mark.asyncio

2
tests/rpc/test_rpc.py
View File

@ -1093,7 +1093,7 @@ def test_rpcforcebuy(mocker, default_conf, ticker, fee, limit_buy_order_open) ->
with pytest.raises(RPCException, match=r'position for ETH/BTC already open - id: 1'):
rpc._rpc_forcebuy(pair, 0.0001)
pair = 'XRP/BTC'
trade = rpc._rpc_forcebuy(pair, 0.0001)
trade = rpc._rpc_forcebuy(pair, 0.0001, order_type='limit')
assert isinstance(trade, Trade)
assert trade.pair == pair
assert trade.open_rate == 0.0001

64
tests/rpc/test_rpc_telegram.py
View File

@ -24,6 +24,7 @@ from freqtrade.freqtradebot import FreqtradeBot
from freqtrade.loggers import setup_logging
from freqtrade.persistence import PairLocks, Trade
from freqtrade.rpc import RPC
from freqtrade.rpc.rpc import RPCException
from freqtrade.rpc.telegram import Telegram, authorized_only
from tests.conftest import (create_mock_trades, get_patched_freqtradebot, log_has, log_has_re,
patch_exchange, patch_get_signal, patch_whitelist)
@ -1186,8 +1187,8 @@ def test_forcebuy_no_pair(default_conf, update, mocker) -> None:
assert fbuy_mock.call_count == 1
def test_performance_handle(default_conf, update, ticker, fee,
limit_buy_order, limit_sell_order, mocker) -> None:
def test_telegram_performance_handle(default_conf, update, ticker, fee,
limit_buy_order, limit_sell_order, mocker) -> None:
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
@ -1216,8 +1217,8 @@ def test_performance_handle(default_conf, update, ticker, fee,
assert '<code>ETH/BTC\t0.00006217 BTC (6.20%) (1)</code>' in msg_mock.call_args_list[0][0][0]
def test_buy_tag_performance_handle(default_conf, update, ticker, fee,
limit_buy_order, limit_sell_order, mocker) -> None:
def test_telegram_buy_tag_performance_handle(default_conf, update, ticker, fee,
limit_buy_order, limit_sell_order, mocker) -> None:
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
fetch_ticker=ticker,
@ -1240,15 +1241,27 @@ def test_buy_tag_performance_handle(default_conf, update, ticker, fee,
trade.close_date = datetime.utcnow()
trade.is_open = False
telegram._buy_tag_performance(update=update, context=MagicMock())
context = MagicMock()
telegram._buy_tag_performance(update=update, context=context)
assert msg_mock.call_count == 1
assert 'Buy Tag Performance' in msg_mock.call_args_list[0][0][0]
assert '<code>TESTBUY\t0.00006217 BTC (6.20%) (1)</code>' in msg_mock.call_args_list[0][0][0]
context.args = [trade.pair]
telegram._buy_tag_performance(update=update, context=context)
assert msg_mock.call_count == 2
def test_sell_reason_performance_handle(default_conf, update, ticker, fee,
limit_buy_order, limit_sell_order, mocker) -> None:
msg_mock.reset_mock()
mocker.patch('freqtrade.rpc.rpc.RPC._rpc_buy_tag_performance',
side_effect=RPCException('Error'))
telegram._buy_tag_performance(update=update, context=MagicMock())
assert msg_mock.call_count == 1
assert "Error" in msg_mock.call_args_list[0][0][0]
def test_telegram_sell_reason_performance_handle(default_conf, update, ticker, fee,
limit_buy_order, limit_sell_order, mocker) -> None:
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
fetch_ticker=ticker,
@ -1271,15 +1284,27 @@ def test_sell_reason_performance_handle(default_conf, update, ticker, fee,
trade.close_date = datetime.utcnow()
trade.is_open = False
telegram._sell_reason_performance(update=update, context=MagicMock())
context = MagicMock()
telegram._sell_reason_performance(update=update, context=context)
assert msg_mock.call_count == 1
assert 'Sell Reason Performance' in msg_mock.call_args_list[0][0][0]
assert '<code>TESTSELL\t0.00006217 BTC (6.20%) (1)</code>' in msg_mock.call_args_list[0][0][0]
context.args = [trade.pair]
telegram._sell_reason_performance(update=update, context=context)
assert msg_mock.call_count == 2
msg_mock.reset_mock()
mocker.patch('freqtrade.rpc.rpc.RPC._rpc_sell_reason_performance',
side_effect=RPCException('Error'))
telegram._sell_reason_performance(update=update, context=MagicMock())
assert msg_mock.call_count == 1
assert "Error" in msg_mock.call_args_list[0][0][0]
def test_mix_tag_performance_handle(default_conf, update, ticker, fee,
limit_buy_order, limit_sell_order, mocker) -> None:
def test_telegram_mix_tag_performance_handle(default_conf, update, ticker, fee,
limit_buy_order, limit_sell_order, mocker) -> None:
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
fetch_ticker=ticker,
@ -1305,12 +1330,25 @@ def test_mix_tag_performance_handle(default_conf, update, ticker, fee,
trade.close_date = datetime.utcnow()
trade.is_open = False
telegram._mix_tag_performance(update=update, context=MagicMock())
context = MagicMock()
telegram._mix_tag_performance(update=update, context=context)
assert msg_mock.call_count == 1
assert 'Mix Tag Performance' in msg_mock.call_args_list[0][0][0]
assert ('<code>TESTBUY TESTSELL\t0.00006217 BTC (6.20%) (1)</code>'
in msg_mock.call_args_list[0][0][0])
context.args = [trade.pair]
telegram._mix_tag_performance(update=update, context=context)
assert msg_mock.call_count == 2
msg_mock.reset_mock()
mocker.patch('freqtrade.rpc.rpc.RPC._rpc_mix_tag_performance',
side_effect=RPCException('Error'))
telegram._mix_tag_performance(update=update, context=MagicMock())
assert msg_mock.call_count == 1
assert "Error" in msg_mock.call_args_list[0][0][0]
def test_count_handle(default_conf, update, ticker, fee, mocker) -> None:
mocker.patch.multiple(