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

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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. 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 colors per indicator
* Specify additional subplots * 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. 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. 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: Plot type can be configured using `type` key. Possible types are:
* `scatter` corresponding to `plotly.graph_objects.Scatter` class (default). * `scatter` corresponding to `plotly.graph_objects.Scatter` class (default).
* `bar` corresponding to `plotly.graph_objects.Bar` class. * `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: Sample configuration with inline comments explaining the process:
``` python ``` python
plot_config = { @property
'main_plot': { def plot_config(self):
# Configuration for main plot indicators. """
# Specifies `ema10` to be red, and `ema50` to be a shade of gray There are a lot of solutions how to build the return dictionary.
'ema10': {'color': 'red'}, The only important point is the return value.
'ema50': {'color': '#CCCCCC'}, Example:
# By omitting color, a random color is selected. plot_config = {'main_plot': {}, 'subplots': {}}
'sar': {},
# fill area between senkou_a and senkou_b """
'senkou_a': { plot_config = {}
'color': 'green', #optional plot_config['main_plot'] = {
'fill_to': 'senkou_b', # Configuration for main plot indicators.
'fill_label': 'Ichimoku Cloud', #optional # Assumes 2 parameters, emashort and emalong to be specified.
'fill_color': 'rgba(255,76,46,0.2)', #optional f'ema_{self.emashort.value}': {'color': 'red'},
}, f'ema_{self.emalong.value}': {'color': '#CCCCCC'},
# plot senkou_b, too. Not only the area to it. # By omitting color, a random color is selected.
'senkou_b': {} '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': { # plot senkou_b, too. Not only the area to it.
# Create subplot MACD 'senkou_b': {}
"MACD": { }
'macd': {'color': 'blue', 'fill_to': 'macdhist'}, plot_config['subplots'] = {
'macdsignal': {'color': 'orange'}, # Create subplot MACD
'macdhist': {'type': 'bar', 'plotly': {'opacity': 0.9}} "MACD": {
}, 'macd': {'color': 'blue', 'fill_to': 'macdhist'},
# Additional subplot RSI 'macdsignal': {'color': 'orange'},
"RSI": { 'macdhist': {'type': 'bar', 'plotly': {'opacity': 0.9}}
'rsi': {'color': 'red'} },
} # 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 !!! Note
The above configuration assumes that `ema10`, `ema50`, `senkou_a`, `senkou_b`, 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. `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 ```python
# Load strategy using values set above # Load strategy using values set above
from freqtrade.resolvers import StrategyResolver from freqtrade.resolvers import StrategyResolver
from freqtrade.data.dataprovider import DataProvider
strategy = StrategyResolver.load_strategy(config) strategy = StrategyResolver.load_strategy(config)
strategy.dp = DataProvider(config, None, None)
# Generate buy/sell signals using strategy # Generate buy/sell signals using strategy
df = strategy.analyze_ticker(candles, {'pair': pair}) df = strategy.analyze_ticker(candles, {'pair': pair})
@ -228,7 +230,7 @@ graph = generate_candlestick_graph(pair=pair,
# Show graph inline # Show graph inline
# graph.show() # graph.show()
# Render graph in a separate window # Render graph in a seperate window
graph.show(renderer="browser") graph.show(renderer="browser")
``` ```

2
freqtrade/exchange/exchange.py
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@ -1294,7 +1294,7 @@ class Exchange:
cached_pairs = [] cached_pairs = []
# Gather coroutines to run # Gather coroutines to run
for pair, timeframe in set(pair_list): 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)): or self._now_is_time_to_refresh(pair, timeframe)):
if not since_ms and self.required_candle_call_count > 1: if not since_ms and self.required_candle_call_count > 1:
# Multiple calls for one pair - to get more history # 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.") logger.info(f"Bids to asks delta for {pair} does not satisfy condition.")
return False return False
def execute_entry(self, pair: str, stake_amount: float, price: Optional[float] = None, def execute_entry(self, pair: str, stake_amount: float, price: Optional[float] = None, *,
forcebuy: bool = False, buy_tag: Optional[str] = None) -> bool: ordertype: Optional[str] = None, buy_tag: Optional[str] = None) -> bool:
""" """
Executes a limit buy for the given pair Executes a limit buy for the given pair
:param pair: pair for which we want to create a LIMIT_BUY :param pair: pair for which we want to create a LIMIT_BUY
@ -510,10 +510,7 @@ class FreqtradeBot(LoggingMixin):
f"{stake_amount} ...") f"{stake_amount} ...")
amount = stake_amount / enter_limit_requested amount = stake_amount / enter_limit_requested
order_type = self.strategy.order_types['buy'] order_type = ordertype or self.strategy.order_types['buy']
if forcebuy:
# Forcebuy can define a different ordertype
order_type = self.strategy.order_types.get('forcebuy', order_type)
if not strategy_safe_wrapper(self.strategy.confirm_trade_entry, default_retval=True)( 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, pair=pair, order_type=order_type, amount=amount, rate=enter_limit_requested,
@ -868,7 +865,7 @@ class FreqtradeBot(LoggingMixin):
logger.info( logger.info(
f'Executing Sell for {trade.pair}. Reason: {should_sell.sell_type}. ' f'Executing Sell for {trade.pair}. Reason: {should_sell.sell_type}. '
f'Tag: {exit_tag if exit_tag is not None else "None"}') 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 True
return False return False
@ -1081,7 +1078,10 @@ class FreqtradeBot(LoggingMixin):
trade: Trade, trade: Trade,
limit: float, limit: float,
sell_reason: SellCheckTuple, 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 Executes a trade exit for the given trade and limit
:param trade: Trade instance :param trade: Trade instance
@ -1119,14 +1119,10 @@ class FreqtradeBot(LoggingMixin):
except InvalidOrderException: except InvalidOrderException:
logger.exception(f"Could not cancel stoploss order {trade.stoploss_order_id}") 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: if sell_reason.sell_type == SellType.EMERGENCY_SELL:
# Emergency sells (default to market!) # Emergency sells (default to market!)
order_type = self.strategy.order_types.get("emergencysell", "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) amount = self._safe_exit_amount(trade.pair, trade.amount)
time_in_force = self.strategy.order_time_in_force['sell'] 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'] '.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()) Generate header lines (goes in line with _generate_result_line())
""" """
return [first_column, 'Buys', '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%']
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 %',
f'Tot Profit {stake_currency}', 'Tot Profit %', 'Avg Duration', f'Tot Profit {stake_currency}', 'Tot Profit %', 'Avg Duration',
'Win Draw Loss Win%'] 'Win Draw Loss Win%']
@ -156,7 +147,7 @@ def generate_tag_metrics(tag_type: str,
if skip_nan and result['profit_abs'].isnull().all(): if skip_nan and result['profit_abs'].isnull().all():
continue 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 %: # Sort by total profit %:
tabular_data = sorted(tabular_data, key=lambda k: k['profit_total_abs'], reverse=True) 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 [] 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]: def generate_sell_reason_stats(max_open_trades: int, results: DataFrame) -> List[Dict]:
""" """
Generate small table outlining Backtest results 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"): if(tag_type == "buy_tag"):
headers = _get_line_header("TAG", stake_currency) headers = _get_line_header("TAG", stake_currency)
else: else:
headers = _get_line_header_sell("TAG", stake_currency) headers = _get_line_header("TAG", stake_currency, 'Sells')
floatfmt = _get_line_floatfmt(stake_currency) floatfmt = _get_line_floatfmt(stake_currency)
output = [ output = [
[ [

23
freqtrade/rpc/api_server/api_schemas.py
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@ -1,4 +1,5 @@
from datetime import date, datetime from datetime import date, datetime
from enum import Enum
from typing import Any, Dict, List, Optional, Union from typing import Any, Dict, List, Optional, Union
from pydantic import BaseModel from pydantic import BaseModel
@ -131,13 +132,21 @@ class UnfilledTimeout(BaseModel):
exit_timeout_count: Optional[int] exit_timeout_count: Optional[int]
class OrderTypeValues(Enum):
limit = 'limit'
market = 'market'
class Config:
use_enum_values = True
class OrderTypes(BaseModel): class OrderTypes(BaseModel):
buy: str buy: OrderTypeValues
sell: str sell: OrderTypeValues
emergencysell: Optional[str] emergencysell: Optional[OrderTypeValues]
forcesell: Optional[str] forcesell: Optional[OrderTypeValues]
forcebuy: Optional[str] forcebuy: Optional[OrderTypeValues]
stoploss: str stoploss: OrderTypeValues
stoploss_on_exchange: bool stoploss_on_exchange: bool
stoploss_on_exchange_interval: Optional[int] stoploss_on_exchange_interval: Optional[int]
@ -274,10 +283,12 @@ class Logs(BaseModel):
class ForceBuyPayload(BaseModel): class ForceBuyPayload(BaseModel):
pair: str pair: str
price: Optional[float] price: Optional[float]
ordertype: Optional[OrderTypeValues]
class ForceSellPayload(BaseModel): class ForceSellPayload(BaseModel):
tradeid: str tradeid: str
ordertype: Optional[OrderTypeValues]
class BlacklistPayload(BaseModel): class BlacklistPayload(BaseModel):

9
freqtrade/rpc/api_server/api_v1.py
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@ -29,7 +29,8 @@ logger = logging.getLogger(__name__)
# API version # API version
# Pre-1.1, no version was provided # Pre-1.1, no version was provided
# Version increments should happen in "small" steps (1.1, 1.12, ...) unless big changes happen. # 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. # Public API, requires no auth.
router_public = APIRouter() 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']) @router.post('/forcebuy', response_model=ForceBuyResponse, tags=['trading'])
def forcebuy(payload: ForceBuyPayload, rpc: RPC = Depends(get_rpc)): 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: if trade:
return ForceBuyResponse.parse_obj(trade.to_json()) 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']) @router.post('/forcesell', response_model=ResultMsg, tags=['trading'])
def forcesell(payload: ForceSellPayload, rpc: RPC = Depends(get_rpc)): 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']) @router.get('/blacklist', response_model=BlacklistResponse, tags=['info', 'pairlist'])

16
freqtrade/rpc/rpc.py
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@ -640,7 +640,7 @@ class RPC:
return {'status': 'No more buy will occur from now. Run /reload_config to reset.'} 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>. Handler for forcesell <id>.
Sells the given trade at current price Sells the given trade at current price
@ -664,7 +664,11 @@ class RPC:
current_rate = self._freqtrade.exchange.get_rate( current_rate = self._freqtrade.exchange.get_rate(
trade.pair, refresh=False, side="sell") trade.pair, refresh=False, side="sell")
sell_reason = SellCheckTuple(sell_type=SellType.FORCE_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 ---- # ---- EOF def _exec_forcesell ----
if self._freqtrade.state != State.RUNNING: if self._freqtrade.state != State.RUNNING:
@ -692,7 +696,8 @@ class RPC:
self._freqtrade.wallets.update() self._freqtrade.wallets.update()
return {'result': f'Created sell order for trade {trade_id}.'} 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> Handler for forcebuy <asset> <price>
Buys a pair trade at the given or current 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) stakeamount = self._freqtrade.wallets.get_trade_stake_amount(pair)
# execute buy # 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.commit()
trade = Trade.get_trades([Trade.is_open.is_(True), Trade.pair == pair]).first() trade = Trade.get_trades([Trade.is_open.is_(True), Trade.pair == pair]).first()
return trade return trade

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

@ -87,6 +87,7 @@ class {{ strategy }}(IStrategy):
'sell': 'gtc' 'sell': 'gtc'
} }
{{ plot_config | indent(4) }} {{ plot_config | indent(4) }}
def informative_pairs(self): def informative_pairs(self):
""" """
Define additional, informative pair/interval combinations to be cached from the exchange. 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": [ "source": [
"# Load strategy using values set above\n", "# Load strategy using values set above\n",
"from freqtrade.resolvers import StrategyResolver\n", "from freqtrade.resolvers import StrategyResolver\n",
"from freqtrade.data.dataprovider import DataProvider\n",
"strategy = StrategyResolver.load_strategy(config)\n", "strategy = StrategyResolver.load_strategy(config)\n",
"strategy.dp = DataProvider(config, None, None)\n",
"\n", "\n",
"# Generate buy/sell signals using strategy\n", "# Generate buy/sell signals using strategy\n",
"df = strategy.analyze_ticker(candles, {'pair': pair})\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 = { @property
# Main plot indicators (Moving averages, ...) def plot_config(self):
'main_plot': { return {
'tema': {}, # Main plot indicators (Moving averages, ...)
'sar': {'color': 'white'}, 'main_plot': {
}, 'tema': {},
'subplots': { 'sar': {'color': 'white'},
# Subplots - each dict defines one additional plot
"MACD": {
'macd': {'color': 'blue'},
'macdsignal': {'color': 'orange'},
}, },
"RSI": { 'subplots': {
'rsi': {'color': 'red'}, # 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 len(res) == len(pairs)
assert exchange._api_async.fetch_ohlcv.call_count == 0 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]}, " assert log_has(f"Using cached candle (OHLCV) data for pair {pairs[0][0]}, "
f"timeframe {pairs[0][1]} ...", f"timeframe {pairs[0][1]} ...",
caplog) caplog)
res = exchange.refresh_latest_ohlcv([('IOTA/ETH', '5m'), ('XRP/ETH', '5m'), ('XRP/ETH', '1d')], res = exchange.refresh_latest_ohlcv([('IOTA/ETH', '5m'), ('XRP/ETH', '5m'), ('XRP/ETH', '1d')],
cache=False) cache=False)
assert len(res) == 3 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 @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'): with pytest.raises(RPCException, match=r'position for ETH/BTC already open - id: 1'):
rpc._rpc_forcebuy(pair, 0.0001) rpc._rpc_forcebuy(pair, 0.0001)
pair = 'XRP/BTC' 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 isinstance(trade, Trade)
assert trade.pair == pair assert trade.pair == pair
assert trade.open_rate == 0.0001 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.loggers import setup_logging
from freqtrade.persistence import PairLocks, Trade from freqtrade.persistence import PairLocks, Trade
from freqtrade.rpc import RPC from freqtrade.rpc import RPC
from freqtrade.rpc.rpc import RPCException
from freqtrade.rpc.telegram import Telegram, authorized_only from freqtrade.rpc.telegram import Telegram, authorized_only
from tests.conftest import (create_mock_trades, get_patched_freqtradebot, log_has, log_has_re, from tests.conftest import (create_mock_trades, get_patched_freqtradebot, log_has, log_has_re,
patch_exchange, patch_get_signal, patch_whitelist) 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 assert fbuy_mock.call_count == 1
def test_performance_handle(default_conf, update, ticker, fee, def test_telegram_performance_handle(default_conf, update, ticker, fee,
limit_buy_order, limit_sell_order, mocker) -> None: limit_buy_order, limit_sell_order, mocker) -> None:
mocker.patch.multiple( mocker.patch.multiple(
'freqtrade.exchange.Exchange', '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] 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, def test_telegram_buy_tag_performance_handle(default_conf, update, ticker, fee,
limit_buy_order, limit_sell_order, mocker) -> None: limit_buy_order, limit_sell_order, mocker) -> None:
mocker.patch.multiple( mocker.patch.multiple(
'freqtrade.exchange.Exchange', 'freqtrade.exchange.Exchange',
fetch_ticker=ticker, fetch_ticker=ticker,
@ -1240,15 +1241,27 @@ def test_buy_tag_performance_handle(default_conf, update, ticker, fee,
trade.close_date = datetime.utcnow() trade.close_date = datetime.utcnow()
trade.is_open = False trade.is_open = False
context = MagicMock()
telegram._buy_tag_performance(update=update, context=MagicMock()) telegram._buy_tag_performance(update=update, context=context)
assert msg_mock.call_count == 1 assert msg_mock.call_count == 1
assert 'Buy Tag Performance' in msg_mock.call_args_list[0][0][0] 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] 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, msg_mock.reset_mock()
limit_buy_order, limit_sell_order, mocker) -> None: 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( mocker.patch.multiple(
'freqtrade.exchange.Exchange', 'freqtrade.exchange.Exchange',
fetch_ticker=ticker, fetch_ticker=ticker,
@ -1271,15 +1284,27 @@ def test_sell_reason_performance_handle(default_conf, update, ticker, fee,
trade.close_date = datetime.utcnow() trade.close_date = datetime.utcnow()
trade.is_open = False trade.is_open = False
context = MagicMock()
telegram._sell_reason_performance(update=update, context=MagicMock()) telegram._sell_reason_performance(update=update, context=context)
assert msg_mock.call_count == 1 assert msg_mock.call_count == 1
assert 'Sell Reason Performance' in msg_mock.call_args_list[0][0][0] 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] 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, def test_telegram_mix_tag_performance_handle(default_conf, update, ticker, fee,
limit_buy_order, limit_sell_order, mocker) -> None: limit_buy_order, limit_sell_order, mocker) -> None:
mocker.patch.multiple( mocker.patch.multiple(
'freqtrade.exchange.Exchange', 'freqtrade.exchange.Exchange',
fetch_ticker=ticker, fetch_ticker=ticker,
@ -1305,12 +1330,25 @@ def test_mix_tag_performance_handle(default_conf, update, ticker, fee,
trade.close_date = datetime.utcnow() trade.close_date = datetime.utcnow()
trade.is_open = False 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 msg_mock.call_count == 1
assert 'Mix Tag Performance' in msg_mock.call_args_list[0][0][0] assert 'Mix Tag Performance' in msg_mock.call_args_list[0][0][0]
assert ('<code>TESTBUY TESTSELL\t0.00006217 BTC (6.20%) (1)</code>' assert ('<code>TESTBUY TESTSELL\t0.00006217 BTC (6.20%) (1)</code>'
in msg_mock.call_args_list[0][0][0]) 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: def test_count_handle(default_conf, update, ticker, fee, mocker) -> None:
mocker.patch.multiple( mocker.patch.multiple(