Merge branch 'develop' into pr/imxuwang/3799

This commit is contained in:
Matthias 2020-11-19 13:18:03 +01:00
commit 7a8b274a44
54 changed files with 772 additions and 511 deletions

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@ -7,8 +7,8 @@ services:
dockerfile: ".devcontainer/Dockerfile"
volumes:
# Allow git usage within container
- "/home/${USER}/.ssh:/home/ftuser/.ssh:ro"
- "/home/${USER}/.gitconfig:/home/ftuser/.gitconfig:ro"
- "${HOME}/.ssh:/home/ftuser/.ssh:ro"
- "${HOME}/.gitconfig:/home/ftuser/.gitconfig:ro"
- ..:/freqtrade:cached
# Persist bash-history
- freqtrade-vscode-server:/home/ftuser/.vscode-server

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@ -59,8 +59,8 @@ Mandatory parameters are marked as **Required**, which means that they are requi
| `trailing_stop_positive` | Changes stoploss once profit has been reached. More details in the [stoploss documentation](stoploss.md#trailing-stop-loss-custom-positive-loss). [Strategy Override](#parameters-in-the-strategy). <br> **Datatype:** Float
| `trailing_stop_positive_offset` | Offset on when to apply `trailing_stop_positive`. Percentage value which should be positive. More details in the [stoploss documentation](stoploss.md#trailing-stop-loss-only-once-the-trade-has-reached-a-certain-offset). [Strategy Override](#parameters-in-the-strategy). <br>*Defaults to `0.0` (no offset).* <br> **Datatype:** Float
| `trailing_only_offset_is_reached` | Only apply trailing stoploss when the offset is reached. [stoploss documentation](stoploss.md). [Strategy Override](#parameters-in-the-strategy). <br>*Defaults to `false`.* <br> **Datatype:** Boolean
| `unfilledtimeout.buy` | **Required.** How long (in minutes) the bot will wait for an unfilled buy order to complete, after which the order will be cancelled. [Strategy Override](#parameters-in-the-strategy).<br> **Datatype:** Integer
| `unfilledtimeout.sell` | **Required.** How long (in minutes) the bot will wait for an unfilled sell order to complete, after which the order will be cancelled. [Strategy Override](#parameters-in-the-strategy).<br> **Datatype:** Integer
| `unfilledtimeout.buy` | **Required.** How long (in minutes) the bot will wait for an unfilled buy order to complete, after which the order will be cancelled and repeated at current (new) price, as long as there is a signal. [Strategy Override](#parameters-in-the-strategy).<br> **Datatype:** Integer
| `unfilledtimeout.sell` | **Required.** How long (in minutes) the bot will wait for an unfilled sell order to complete, after which the order will be cancelled and repeated at current (new) price, as long as there is a signal. [Strategy Override](#parameters-in-the-strategy).<br> **Datatype:** Integer
| `bid_strategy.price_side` | Select the side of the spread the bot should look at to get the buy rate. [More information below](#buy-price-side).<br> *Defaults to `bid`.* <br> **Datatype:** String (either `ask` or `bid`).
| `bid_strategy.ask_last_balance` | **Required.** Set the bidding price. More information [below](#buy-price-without-orderbook-enabled).
| `bid_strategy.use_order_book` | Enable buying using the rates in [Order Book Bids](#buy-price-with-orderbook-enabled). <br> **Datatype:** Boolean

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@ -1,3 +1,3 @@
mkdocs-material==6.1.0
mkdocs-material==6.1.5
mdx_truly_sane_lists==1.2
pymdown-extensions==8.0.1

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@ -704,7 +704,7 @@ To verify if a pair is currently locked, use `self.is_pair_locked(pair)`.
Locked pairs will always be rounded up to the next candle. So assuming a `5m` timeframe, a lock with `until` set to 10:18 will lock the pair until the candle from 10:15-10:20 will be finished.
!!! Warning
Locking pairs is not functioning during backtesting.
Locking pairs is not available during backtesting.
#### Pair locking example

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@ -35,12 +35,30 @@ Copy the API Token (`22222222:APITOKEN` in the above example) and keep use it fo
Don't forget to start the conversation with your bot, by clicking `/START` button
### 2. Get your user id
### 2. Telegram user_id
#### Get your user id
Talk to the [userinfobot](https://telegram.me/userinfobot)
Get your "Id", you will use it for the config parameter `chat_id`.
#### Use Group id
You can use bots in telegram groups by just adding them to the group. You can find the group id by first adding a [RawDataBot](https://telegram.me/rawdatabot) to your group. The Group id is shown as id in the `"chat"` section, which the RawDataBot will send to you:
``` json
"chat":{
"id":-1001332619709
}
```
For the Freqtrade configuration, you can then use the the full value (including `-` if it's there) as string:
```json
"chat_id": "-1001332619709"
```
## Control telegram noise
Freqtrade provides means to control the verbosity of your telegram bot.

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@ -32,7 +32,7 @@ python -m venv .env
.env\Scripts\activate.ps1
# optionally install ta-lib from wheel
# Eventually adjust the below filename to match the downloaded wheel
pip install build_helpes/TA_Lib0.4.19cp38cp38win_amd64.whl
pip install build_helpers/TA_Lib-0.4.19-cp38-cp38-win_amd64.whl
pip install -r requirements.txt
pip install -e .
freqtrade
@ -50,8 +50,8 @@ freqtrade
error: Microsoft Visual C++ 14.0 is required. Get it with "Microsoft Visual C++ Build Tools": http://landinghub.visualstudio.com/visual-cpp-build-tools
```
Unfortunately, many packages requiring compilation don't provide a pre-build wheel. It is therefore mandatory to have a C/C++ compiler installed and available for your python environment to use.
Unfortunately, many packages requiring compilation don't provide a pre-built wheel. It is therefore mandatory to have a C/C++ compiler installed and available for your python environment to use.
The easiest way is to download install Microsoft Visual Studio Community [here](https://visualstudio.microsoft.com/downloads/) and make sure to install "Common Tools for Visual C++" to enable building c code on Windows. Unfortunately, this is a heavy download / dependency (~4Gb) so you might want to consider WSL or [docker](docker.md) first.
The easiest way is to download install Microsoft Visual Studio Community [here](https://visualstudio.microsoft.com/downloads/) and make sure to install "Common Tools for Visual C++" to enable building C code on Windows. Unfortunately, this is a heavy download / dependency (~4Gb) so you might want to consider WSL or [docker](docker.md) first.
---

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@ -4,6 +4,7 @@ Definition of cli arguments used in arguments.py
from argparse import ArgumentTypeError
from freqtrade import __version__, constants
from freqtrade.constants import HYPEROPT_LOSS_BUILTIN
def check_int_positive(value: str) -> int:
@ -257,8 +258,7 @@ AVAILABLE_CLI_OPTIONS = {
help='Specify the class name of the hyperopt loss function class (IHyperOptLoss). '
'Different functions can generate completely different results, '
'since the target for optimization is different. Built-in Hyperopt-loss-functions are: '
'ShortTradeDurHyperOptLoss, OnlyProfitHyperOptLoss, SharpeHyperOptLoss, '
'SharpeHyperOptLossDaily, SortinoHyperOptLoss, SortinoHyperOptLossDaily.',
f'{", ".join(HYPEROPT_LOSS_BUILTIN)}',
metavar='NAME',
),
"hyperoptexportfilename": Arg(
@ -354,13 +354,11 @@ AVAILABLE_CLI_OPTIONS = {
'--data-format-ohlcv',
help='Storage format for downloaded candle (OHLCV) data. (default: `%(default)s`).',
choices=constants.AVAILABLE_DATAHANDLERS,
default='json'
),
"dataformat_trades": Arg(
'--data-format-trades',
help='Storage format for downloaded trades data. (default: `%(default)s`).',
choices=constants.AVAILABLE_DATAHANDLERS,
default='jsongz'
),
"exchange": Arg(
'--exchange',

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@ -1,10 +1,9 @@
import logging
import sys
from collections import defaultdict
from datetime import datetime, timedelta
from typing import Any, Dict, List
import arrow
from freqtrade.configuration import TimeRange, setup_utils_configuration
from freqtrade.data.converter import convert_ohlcv_format, convert_trades_format
from freqtrade.data.history import (convert_trades_to_ohlcv, refresh_backtest_ohlcv_data,
@ -29,12 +28,15 @@ def start_download_data(args: Dict[str, Any]) -> None:
"You can only specify one or the other.")
timerange = TimeRange()
if 'days' in config:
time_since = arrow.utcnow().shift(days=-config['days']).strftime("%Y%m%d")
time_since = (datetime.now() - timedelta(days=config['days'])).strftime("%Y%m%d")
timerange = TimeRange.parse_timerange(f'{time_since}-')
if 'timerange' in config:
timerange = timerange.parse_timerange(config['timerange'])
# Remove stake-currency to skip checks which are not relevant for datadownload
config['stake_currency'] = ''
if 'pairs' not in config:
raise OperationalException(
"Downloading data requires a list of pairs. "

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@ -133,7 +133,7 @@ def start_new_hyperopt(args: Dict[str, Any]) -> None:
if new_path.exists():
raise OperationalException(f"`{new_path}` already exists. "
"Please choose another Strategy Name.")
"Please choose another Hyperopt Name.")
deploy_new_hyperopt(args['hyperopt'], new_path, args['template'])
else:
raise OperationalException("`new-hyperopt` requires --hyperopt to be set.")

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@ -52,11 +52,11 @@ class TimeRange:
:return: None (Modifies the object in place)
"""
if (not self.starttype or (startup_candles
and min_date.timestamp >= self.startts)):
and min_date.int_timestamp >= self.startts)):
# If no startts was defined, or backtest-data starts at the defined backtest-date
logger.warning("Moving start-date by %s candles to account for startup time.",
startup_candles)
self.startts = (min_date.timestamp + timeframe_secs * startup_candles)
self.startts = (min_date.int_timestamp + timeframe_secs * startup_candles)
self.starttype = 'date'
@staticmethod
@ -89,7 +89,7 @@ class TimeRange:
if stype[0]:
starts = rvals[index]
if stype[0] == 'date' and len(starts) == 8:
start = arrow.get(starts, 'YYYYMMDD').timestamp
start = arrow.get(starts, 'YYYYMMDD').int_timestamp
elif len(starts) == 13:
start = int(starts) // 1000
else:
@ -98,7 +98,7 @@ class TimeRange:
if stype[1]:
stops = rvals[index]
if stype[1] == 'date' and len(stops) == 8:
stop = arrow.get(stops, 'YYYYMMDD').timestamp
stop = arrow.get(stops, 'YYYYMMDD').int_timestamp
elif len(stops) == 13:
stop = int(stops) // 1000
else:

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@ -20,6 +20,9 @@ REQUIRED_ORDERTYPES = ['buy', 'sell', 'stoploss', 'stoploss_on_exchange']
ORDERBOOK_SIDES = ['ask', 'bid']
ORDERTYPE_POSSIBILITIES = ['limit', 'market']
ORDERTIF_POSSIBILITIES = ['gtc', 'fok', 'ioc']
HYPEROPT_LOSS_BUILTIN = ['ShortTradeDurHyperOptLoss', 'OnlyProfitHyperOptLoss',
'SharpeHyperOptLoss', 'SharpeHyperOptLossDaily',
'SortinoHyperOptLoss', 'SortinoHyperOptLossDaily']
AVAILABLE_PAIRLISTS = ['StaticPairList', 'VolumePairList',
'AgeFilter', 'PrecisionFilter', 'PriceFilter',
'ShuffleFilter', 'SpreadFilter']

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@ -8,7 +8,6 @@ import logging
from datetime import datetime, timezone
from typing import Any, Dict, List, Optional, Tuple
from arrow import Arrow
from pandas import DataFrame
from freqtrade.constants import ListPairsWithTimeframes, PairWithTimeframe
@ -38,7 +37,7 @@ class DataProvider:
:param timeframe: Timeframe to get data for
:param dataframe: analyzed dataframe
"""
self.__cached_pairs[(pair, timeframe)] = (dataframe, Arrow.utcnow().datetime)
self.__cached_pairs[(pair, timeframe)] = (dataframe, datetime.now(timezone.utc))
def add_pairlisthandler(self, pairlists) -> None:
"""
@ -88,7 +87,8 @@ class DataProvider:
"""
return load_pair_history(pair=pair,
timeframe=timeframe or self._config['timeframe'],
datadir=self._config['datadir']
datadir=self._config['datadir'],
data_format=self._config.get('dataformat_ohlcv', 'json')
)
def get_pair_dataframe(self, pair: str, timeframe: str = None) -> DataFrame:

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@ -3,6 +3,7 @@ import re
from pathlib import Path
from typing import List, Optional
import numpy as np
import pandas as pd
from freqtrade import misc
@ -175,7 +176,8 @@ class HDF5DataHandler(IDataHandler):
if timerange.stoptype == 'date':
where.append(f"timestamp < {timerange.stopts * 1e3}")
trades = pd.read_hdf(filename, key=key, mode="r", where=where)
trades: pd.DataFrame = pd.read_hdf(filename, key=key, mode="r", where=where)
trades[['id', 'type']] = trades[['id', 'type']].replace({np.nan: None})
return trades.values.tolist()
def trades_purge(self, pair: str) -> bool:

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@ -87,7 +87,7 @@ class Edge:
heartbeat = self.edge_config.get('process_throttle_secs')
if (self._last_updated > 0) and (
self._last_updated + heartbeat > arrow.utcnow().timestamp):
self._last_updated + heartbeat > arrow.utcnow().int_timestamp):
return False
data: Dict[str, Any] = {}
@ -146,7 +146,7 @@ class Edge:
# Fill missing, calculable columns, profit, duration , abs etc.
trades_df = self._fill_calculable_fields(DataFrame(trades))
self._cached_pairs = self._process_expectancy(trades_df)
self._last_updated = arrow.utcnow().timestamp
self._last_updated = arrow.utcnow().int_timestamp
return True

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@ -282,7 +282,7 @@ class Exchange:
asyncio.get_event_loop().run_until_complete(
self._api_async.load_markets(reload=reload))
except ccxt.BaseError as e:
except (asyncio.TimeoutError, ccxt.BaseError) as e:
logger.warning('Could not load async markets. Reason: %s', e)
return
@ -291,7 +291,7 @@ class Exchange:
try:
self._api.load_markets()
self._load_async_markets()
self._last_markets_refresh = arrow.utcnow().timestamp
self._last_markets_refresh = arrow.utcnow().int_timestamp
except ccxt.BaseError as e:
logger.warning('Unable to initialize markets. Reason: %s', e)
@ -300,14 +300,14 @@ class Exchange:
# Check whether markets have to be reloaded
if (self._last_markets_refresh > 0) and (
self._last_markets_refresh + self.markets_refresh_interval
> arrow.utcnow().timestamp):
> arrow.utcnow().int_timestamp):
return None
logger.debug("Performing scheduled market reload..")
try:
self._api.load_markets(reload=True)
# Also reload async markets to avoid issues with newly listed pairs
self._load_async_markets(reload=True)
self._last_markets_refresh = arrow.utcnow().timestamp
self._last_markets_refresh = arrow.utcnow().int_timestamp
except ccxt.BaseError:
logger.exception("Could not reload markets.")
@ -501,7 +501,7 @@ class Exchange:
'side': side,
'remaining': _amount,
'datetime': arrow.utcnow().isoformat(),
'timestamp': int(arrow.utcnow().timestamp * 1000),
'timestamp': int(arrow.utcnow().int_timestamp * 1000),
'status': "closed" if ordertype == "market" else "open",
'fee': None,
'info': {}
@ -687,6 +687,9 @@ class Exchange:
async def _async_get_historic_ohlcv(self, pair: str,
timeframe: str,
since_ms: int) -> List:
"""
Download historic ohlcv
"""
one_call = timeframe_to_msecs(timeframe) * self._ohlcv_candle_limit
logger.debug(
@ -696,15 +699,20 @@ class Exchange:
)
input_coroutines = [self._async_get_candle_history(
pair, timeframe, since) for since in
range(since_ms, arrow.utcnow().timestamp * 1000, one_call)]
range(since_ms, arrow.utcnow().int_timestamp * 1000, one_call)]
results = await asyncio.gather(*input_coroutines, return_exceptions=True)
# Combine gathered results
data: List = []
for p, timeframe, res in results:
for res in results:
if isinstance(res, Exception):
logger.warning("Async code raised an exception: %s", res.__class__.__name__)
continue
# Deconstruct tuple if it's not an exception
p, _, new_data = res
if p == pair:
data.extend(res)
data.extend(new_data)
# Sort data again after extending the result - above calls return in "async order"
data = sorted(data, key=lambda x: x[0])
logger.info("Downloaded data for %s with length %s.", pair, len(data))
@ -741,9 +749,8 @@ class Exchange:
if isinstance(res, Exception):
logger.warning("Async code raised an exception: %s", res.__class__.__name__)
continue
pair = res[0]
timeframe = res[1]
ticks = res[2]
# Deconstruct tuple (has 3 elements)
pair, timeframe, ticks = res
# keeping last candle time as last refreshed time of the pair
if ticks:
self._pairs_last_refresh_time[(pair, timeframe)] = ticks[-1][0] // 1000
@ -759,7 +766,7 @@ class Exchange:
interval_in_sec = timeframe_to_seconds(timeframe)
return not ((self._pairs_last_refresh_time.get((pair, timeframe), 0)
+ interval_in_sec) >= arrow.utcnow().timestamp)
+ interval_in_sec) >= arrow.utcnow().int_timestamp)
@retrier_async
async def _async_get_candle_history(self, pair: str, timeframe: str,

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@ -4,7 +4,7 @@ Freqtrade is the main module of this bot. It contains the class Freqtrade()
import copy
import logging
import traceback
from datetime import datetime
from datetime import datetime, timezone
from math import isclose
from threading import Lock
from typing import Any, Dict, List, Optional
@ -19,10 +19,10 @@ from freqtrade.data.dataprovider import DataProvider
from freqtrade.edge import Edge
from freqtrade.exceptions import (DependencyException, ExchangeError, InsufficientFundsError,
InvalidOrderException, PricingError)
from freqtrade.exchange import timeframe_to_minutes, timeframe_to_next_date
from freqtrade.exchange import timeframe_to_minutes
from freqtrade.misc import safe_value_fallback, safe_value_fallback2
from freqtrade.pairlist.pairlistmanager import PairListManager
from freqtrade.persistence import Order, Trade, cleanup_db, init_db
from freqtrade.persistence import Order, PairLocks, Trade, cleanup_db, init_db
from freqtrade.resolvers import ExchangeResolver, StrategyResolver
from freqtrade.rpc import RPCManager, RPCMessageType
from freqtrade.state import State
@ -72,6 +72,8 @@ class FreqtradeBot:
self.wallets = Wallets(self.config, self.exchange)
PairLocks.timeframe = self.config['timeframe']
self.pairlists = PairListManager(self.exchange, self.config)
self.dataprovider = DataProvider(self.config, self.exchange, self.pairlists)
@ -345,27 +347,27 @@ class FreqtradeBot:
whitelist = copy.deepcopy(self.active_pair_whitelist)
if not whitelist:
logger.info("Active pair whitelist is empty.")
else:
# Remove pairs for currently opened trades from the whitelist
for trade in Trade.get_open_trades():
if trade.pair in whitelist:
whitelist.remove(trade.pair)
logger.debug('Ignoring %s in pair whitelist', trade.pair)
return trades_created
# Remove pairs for currently opened trades from the whitelist
for trade in Trade.get_open_trades():
if trade.pair in whitelist:
whitelist.remove(trade.pair)
logger.debug('Ignoring %s in pair whitelist', trade.pair)
if not whitelist:
logger.info("No currency pair in active pair whitelist, "
"but checking to sell open trades.")
else:
# Create entity and execute trade for each pair from whitelist
for pair in whitelist:
try:
trades_created += self.create_trade(pair)
except DependencyException as exception:
logger.warning('Unable to create trade for %s: %s', pair, exception)
if not whitelist:
logger.info("No currency pair in active pair whitelist, "
"but checking to sell open trades.")
return trades_created
# Create entity and execute trade for each pair from whitelist
for pair in whitelist:
try:
trades_created += self.create_trade(pair)
except DependencyException as exception:
logger.warning('Unable to create trade for %s: %s', pair, exception)
if not trades_created:
logger.debug("Found no buy signals for whitelisted currencies. "
"Trying again...")
if not trades_created:
logger.debug("Found no buy signals for whitelisted currencies. "
"Trying again...")
return trades_created
@ -937,7 +939,7 @@ class FreqtradeBot:
self.update_trade_state(trade, trade.stoploss_order_id, stoploss_order,
stoploss_order=True)
# Lock pair for one candle to prevent immediate rebuys
self.strategy.lock_pair(trade.pair, timeframe_to_next_date(self.config['timeframe']),
self.strategy.lock_pair(trade.pair, datetime.now(timezone.utc),
reason='Auto lock')
self._notify_sell(trade, "stoploss")
return True
@ -1264,7 +1266,7 @@ class FreqtradeBot:
Trade.session.flush()
# Lock pair for one candle to prevent immediate rebuys
self.strategy.lock_pair(trade.pair, timeframe_to_next_date(self.config['timeframe']),
self.strategy.lock_pair(trade.pair, datetime.now(timezone.utc),
reason='Auto lock')
self._notify_sell(trade, order_type)

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@ -340,7 +340,7 @@ class Backtesting:
# max_open_trades must be respected
# don't open on the last row
if ((position_stacking or len(open_trades[pair]) == 0)
and max_open_trades > 0 and open_trade_count_start < max_open_trades
and (max_open_trades <= 0 or open_trade_count_start < max_open_trades)
and tmp != end_date
and row[BUY_IDX] == 1 and row[SELL_IDX] != 1):
# Enter trade

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@ -268,9 +268,9 @@ def generate_backtest_stats(btdata: Dict[str, DataFrame],
'profit_total': results['profit_percent'].sum(),
'profit_total_abs': results['profit_abs'].sum(),
'backtest_start': min_date.datetime,
'backtest_start_ts': min_date.timestamp * 1000,
'backtest_start_ts': min_date.int_timestamp * 1000,
'backtest_end': max_date.datetime,
'backtest_end_ts': max_date.timestamp * 1000,
'backtest_end_ts': max_date.int_timestamp * 1000,
'backtest_days': backtest_days,
'trades_per_day': round(len(results) / backtest_days, 2) if backtest_days > 0 else 0,

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@ -1,4 +1,4 @@
# flake8: noqa: F401
from freqtrade.persistence.models import (Order, PairLock, Trade, clean_dry_run_db, cleanup_db,
init_db)
from freqtrade.persistence.models import Order, Trade, clean_dry_run_db, cleanup_db, init_db
from freqtrade.persistence.pairlock_middleware import PairLocks

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@ -270,7 +270,6 @@ class Trade(_DECL_BASE):
'amount_requested': round(self.amount_requested, 8) if self.amount_requested else None,
'stake_amount': round(self.stake_amount, 8),
'strategy': self.strategy,
'ticker_interval': self.timeframe, # DEPRECATED
'timeframe': self.timeframe,
'fee_open': self.fee_open,
@ -295,12 +294,16 @@ class Trade(_DECL_BASE):
tzinfo=timezone.utc).timestamp() * 1000) if self.close_date else None,
'close_rate': self.close_rate,
'close_rate_requested': self.close_rate_requested,
'close_profit': self.close_profit,
'close_profit_abs': self.close_profit_abs,
'close_profit': self.close_profit, # Deprecated
'close_profit_pct': round(self.close_profit * 100, 2) if self.close_profit else None,
'close_profit_abs': self.close_profit_abs, # Deprecated
'profit_ratio': self.close_profit,
'profit_pct': round(self.close_profit * 100, 2) if self.close_profit else None,
'profit_abs': self.close_profit_abs,
'sell_reason': self.sell_reason,
'sell_order_status': self.sell_order_status,
'stop_loss': self.stop_loss, # Deprecated - should not be used
'stop_loss_abs': self.stop_loss,
'stop_loss_ratio': self.stop_loss_pct if self.stop_loss_pct else None,
'stop_loss_pct': (self.stop_loss_pct * 100) if self.stop_loss_pct else None,
@ -309,7 +312,6 @@ class Trade(_DECL_BASE):
if self.stoploss_last_update else None),
'stoploss_last_update_timestamp': int(self.stoploss_last_update.replace(
tzinfo=timezone.utc).timestamp() * 1000) if self.stoploss_last_update else None,
'initial_stop_loss': self.initial_stop_loss, # Deprecated - should not be used
'initial_stop_loss_abs': self.initial_stop_loss,
'initial_stop_loss_ratio': (self.initial_stop_loss_pct
if self.initial_stop_loss_pct else None),
@ -684,70 +686,21 @@ class PairLock(_DECL_BASE):
f'lock_end_time={lock_end_time})')
@staticmethod
def lock_pair(pair: str, until: datetime, reason: str = None) -> None:
lock = PairLock(
pair=pair,
lock_time=datetime.now(timezone.utc),
lock_end_time=until,
reason=reason,
active=True
)
PairLock.session.add(lock)
PairLock.session.flush()
@staticmethod
def get_pair_locks(pair: Optional[str], now: Optional[datetime] = None) -> List['PairLock']:
def query_pair_locks(pair: Optional[str], now: datetime) -> Query:
"""
Get all locks for this pair
:param pair: Pair to check for. Returns all current locks if pair is empty
:param now: Datetime object (generated via datetime.now(timezone.utc)).
defaults to datetime.utcnow()
"""
if not now:
now = datetime.now(timezone.utc)
filters = [func.datetime(PairLock.lock_end_time) >= now,
filters = [PairLock.lock_end_time > now,
# Only active locks
PairLock.active.is_(True), ]
if pair:
filters.append(PairLock.pair == pair)
return PairLock.query.filter(
*filters
).all()
@staticmethod
def unlock_pair(pair: str, now: Optional[datetime] = None) -> None:
"""
Release all locks for this pair.
:param pair: Pair to unlock
:param now: Datetime object (generated via datetime.now(timezone.utc)).
defaults to datetime.utcnow()
"""
if not now:
now = datetime.now(timezone.utc)
logger.info(f"Releasing all locks for {pair}.")
locks = PairLock.get_pair_locks(pair, now)
for lock in locks:
lock.active = False
PairLock.session.flush()
@staticmethod
def is_pair_locked(pair: str, now: Optional[datetime] = None) -> bool:
"""
:param pair: Pair to check for
:param now: Datetime object (generated via datetime.now(timezone.utc)).
defaults to datetime.utcnow()
"""
if not now:
now = datetime.now(timezone.utc)
return PairLock.query.filter(
PairLock.pair == pair,
func.datetime(PairLock.lock_end_time) >= now,
# Only active locks
PairLock.active.is_(True),
).first() is not None
)
def to_json(self) -> Dict[str, Any]:
return {

View File

@ -0,0 +1,99 @@
import logging
from datetime import datetime, timezone
from typing import List, Optional
from freqtrade.exchange import timeframe_to_next_date
from freqtrade.persistence.models import PairLock
logger = logging.getLogger(__name__)
class PairLocks():
"""
Pairlocks middleware class
Abstracts the database layer away so it becomes optional - which will be necessary to support
backtesting and hyperopt in the future.
"""
use_db = True
locks: List[PairLock] = []
timeframe: str = ''
@staticmethod
def lock_pair(pair: str, until: datetime, reason: str = None) -> None:
lock = PairLock(
pair=pair,
lock_time=datetime.now(timezone.utc),
lock_end_time=timeframe_to_next_date(PairLocks.timeframe, until),
reason=reason,
active=True
)
if PairLocks.use_db:
PairLock.session.add(lock)
PairLock.session.flush()
else:
PairLocks.locks.append(lock)
@staticmethod
def get_pair_locks(pair: Optional[str], now: Optional[datetime] = None) -> List[PairLock]:
"""
Get all currently active locks for this pair
:param pair: Pair to check for. Returns all current locks if pair is empty
:param now: Datetime object (generated via datetime.now(timezone.utc)).
defaults to datetime.now(timezone.utc)
"""
if not now:
now = datetime.now(timezone.utc)
if PairLocks.use_db:
return PairLock.query_pair_locks(pair, now).all()
else:
locks = [lock for lock in PairLocks.locks if (
lock.lock_end_time >= now
and lock.active is True
and (pair is None or lock.pair == pair)
)]
return locks
@staticmethod
def unlock_pair(pair: str, now: Optional[datetime] = None) -> None:
"""
Release all locks for this pair.
:param pair: Pair to unlock
:param now: Datetime object (generated via datetime.now(timezone.utc)).
defaults to datetime.now(timezone.utc)
"""
if not now:
now = datetime.now(timezone.utc)
logger.info(f"Releasing all locks for {pair}.")
locks = PairLocks.get_pair_locks(pair, now)
for lock in locks:
lock.active = False
if PairLocks.use_db:
PairLock.session.flush()
@staticmethod
def is_global_lock(now: Optional[datetime] = None) -> bool:
"""
:param now: Datetime object (generated via datetime.now(timezone.utc)).
defaults to datetime.now(timezone.utc)
"""
if not now:
now = datetime.now(timezone.utc)
return len(PairLocks.get_pair_locks('*', now)) > 0
@staticmethod
def is_pair_locked(pair: str, now: Optional[datetime] = None) -> bool:
"""
:param pair: Pair to check for
:param now: Datetime object (generated via datetime.now(timezone.utc)).
defaults to datetime.now(timezone.utc)
"""
if not now:
now = datetime.now(timezone.utc)
return len(PairLocks.get_pair_locks(pair, now)) > 0 or PairLocks.is_global_lock(now)

View File

@ -9,9 +9,9 @@ from freqtrade.data.btanalysis import (calculate_max_drawdown, combine_dataframe
create_cum_profit, extract_trades_of_period, load_trades)
from freqtrade.data.converter import trim_dataframe
from freqtrade.data.dataprovider import DataProvider
from freqtrade.data.history import load_data
from freqtrade.data.history import get_timerange, load_data
from freqtrade.exceptions import OperationalException
from freqtrade.exchange import timeframe_to_prev_date
from freqtrade.exchange import timeframe_to_prev_date, timeframe_to_seconds
from freqtrade.misc import pair_to_filename
from freqtrade.resolvers import ExchangeResolver, StrategyResolver
from freqtrade.strategy import IStrategy
@ -29,7 +29,7 @@ except ImportError:
exit(1)
def init_plotscript(config):
def init_plotscript(config, startup_candles: int = 0):
"""
Initialize objects needed for plotting
:return: Dict with candle (OHLCV) data, trades and pairs
@ -48,9 +48,16 @@ def init_plotscript(config):
pairs=pairs,
timeframe=config.get('timeframe', '5m'),
timerange=timerange,
startup_candles=startup_candles,
data_format=config.get('dataformat_ohlcv', 'json'),
)
if startup_candles:
min_date, max_date = get_timerange(data)
logger.info(f"Loading data from {min_date} to {max_date}")
timerange.adjust_start_if_necessary(timeframe_to_seconds(config.get('timeframe', '5m')),
startup_candles, min_date)
no_trades = False
filename = config.get('exportfilename')
if config.get('no_trades', False):
@ -72,6 +79,7 @@ def init_plotscript(config):
return {"ohlcv": data,
"trades": trades,
"pairs": pairs,
"timerange": timerange,
}
@ -474,7 +482,8 @@ def load_and_plot_trades(config: Dict[str, Any]):
exchange = ExchangeResolver.load_exchange(config['exchange']['name'], config)
IStrategy.dp = DataProvider(config, exchange)
plot_elements = init_plotscript(config)
plot_elements = init_plotscript(config, strategy.startup_candle_count)
timerange = plot_elements['timerange']
trades = plot_elements['trades']
pair_counter = 0
for pair, data in plot_elements["ohlcv"].items():
@ -482,6 +491,7 @@ def load_and_plot_trades(config: Dict[str, Any]):
logger.info("analyse pair %s", pair)
df_analyzed = strategy.analyze_ticker(data, {'pair': pair})
df_analyzed = trim_dataframe(df_analyzed, timerange)
trades_pair = trades.loc[trades['pair'] == pair]
trades_pair = extract_trades_of_period(df_analyzed, trades_pair)

View File

@ -7,7 +7,7 @@ import logging
from pathlib import Path
from typing import Dict
from freqtrade.constants import USERPATH_HYPEROPTS
from freqtrade.constants import HYPEROPT_LOSS_BUILTIN, USERPATH_HYPEROPTS
from freqtrade.exceptions import OperationalException
from freqtrade.optimize.hyperopt_interface import IHyperOpt
from freqtrade.optimize.hyperopt_loss_interface import IHyperOptLoss
@ -72,8 +72,11 @@ class HyperOptLossResolver(IResolver):
hyperoptloss_name = config.get('hyperopt_loss')
if not hyperoptloss_name:
raise OperationalException("No Hyperopt loss set. Please use `--hyperopt-loss` to "
"specify the Hyperopt-Loss class to use.")
raise OperationalException(
"No Hyperopt loss set. Please use `--hyperopt-loss` to "
"specify the Hyperopt-Loss class to use.\n"
f"Built-in Hyperopt-loss-functions are: {', '.join(HYPEROPT_LOSS_BUILTIN)}"
)
hyperoptloss = HyperOptLossResolver.load_object(hyperoptloss_name,
config, kwargs={},
extra_dir=config.get('hyperopt_path'))

View File

@ -329,7 +329,7 @@ class ApiServer(RPC):
"""
Prints the bot's version
"""
return jsonify(self._rpc_show_config(self._config))
return jsonify(RPC._rpc_show_config(self._config, self._freqtrade.state))
@require_login
@rpc_catch_errors

View File

@ -19,7 +19,7 @@ from freqtrade.exceptions import ExchangeError, PricingError
from freqtrade.exchange import timeframe_to_minutes, timeframe_to_msecs
from freqtrade.loggers import bufferHandler
from freqtrade.misc import shorten_date
from freqtrade.persistence import PairLock, Trade
from freqtrade.persistence import PairLocks, Trade
from freqtrade.rpc.fiat_convert import CryptoToFiatConverter
from freqtrade.state import State
from freqtrade.strategy.interface import SellType
@ -93,7 +93,8 @@ class RPC:
def send_msg(self, msg: Dict[str, str]) -> None:
""" Sends a message to all registered rpc modules """
def _rpc_show_config(self, config) -> Dict[str, Any]:
@staticmethod
def _rpc_show_config(config, botstate: State) -> Dict[str, Any]:
"""
Return a dict of config options.
Explicitly does NOT return the full config to avoid leakage of sensitive
@ -104,22 +105,24 @@ class RPC:
'stake_currency': config['stake_currency'],
'stake_amount': config['stake_amount'],
'max_open_trades': config['max_open_trades'],
'minimal_roi': config['minimal_roi'].copy(),
'stoploss': config['stoploss'],
'trailing_stop': config['trailing_stop'],
'minimal_roi': config['minimal_roi'].copy() if 'minimal_roi' in config else {},
'stoploss': config.get('stoploss'),
'trailing_stop': config.get('trailing_stop'),
'trailing_stop_positive': config.get('trailing_stop_positive'),
'trailing_stop_positive_offset': config.get('trailing_stop_positive_offset'),
'trailing_only_offset_is_reached': config.get('trailing_only_offset_is_reached'),
'ticker_interval': config['timeframe'], # DEPRECATED
'timeframe': config['timeframe'],
'timeframe_ms': timeframe_to_msecs(config['timeframe']),
'timeframe_min': timeframe_to_minutes(config['timeframe']),
'timeframe': config.get('timeframe'),
'timeframe_ms': timeframe_to_msecs(config['timeframe']
) if 'timeframe' in config else '',
'timeframe_min': timeframe_to_minutes(config['timeframe']
) if 'timeframe' in config else '',
'exchange': config['exchange']['name'],
'strategy': config['strategy'],
'forcebuy_enabled': config.get('forcebuy_enable', False),
'ask_strategy': config.get('ask_strategy', {}),
'bid_strategy': config.get('bid_strategy', {}),
'state': str(self._freqtrade.state) if self._freqtrade else '',
'state': str(botstate),
'runmode': config['runmode'].value
}
return val
@ -152,17 +155,18 @@ class RPC:
stoploss_current_dist = trade.stop_loss - current_rate
stoploss_current_dist_ratio = stoploss_current_dist / current_rate
fmt_close_profit = (f'{round(trade.close_profit * 100, 2):.2f}%'
if trade.close_profit is not None else None)
trade_dict = trade.to_json()
trade_dict.update(dict(
base_currency=self._freqtrade.config['stake_currency'],
close_profit=trade.close_profit if trade.close_profit is not None else None,
close_profit_pct=fmt_close_profit,
current_rate=current_rate,
current_profit=current_profit,
current_profit_pct=round(current_profit * 100, 2),
current_profit_abs=current_profit_abs,
current_profit=current_profit, # Deprectated
current_profit_pct=round(current_profit * 100, 2), # Deprectated
current_profit_abs=current_profit_abs, # Deprectated
profit_ratio=current_profit,
profit_pct=round(current_profit * 100, 2),
profit_abs=current_profit_abs,
stoploss_current_dist=stoploss_current_dist,
stoploss_current_dist_ratio=round(stoploss_current_dist_ratio, 8),
stoploss_current_dist_pct=round(stoploss_current_dist_ratio * 100, 2),
@ -601,10 +605,8 @@ class RPC:
def _rpc_locks(self) -> Dict[str, Any]:
""" Returns the current locks"""
if self._freqtrade.state != State.RUNNING:
raise RPCException('trader is not running')
locks = PairLock.get_pair_locks(None)
locks = PairLocks.get_pair_locks(None)
return {
'lock_count': len(locks),
'locks': [lock.to_json() for lock in locks]

View File

@ -248,18 +248,17 @@ class Telegram(RPC):
"*Open Rate:* `{open_rate:.8f}`",
"*Close Rate:* `{close_rate}`" if r['close_rate'] else "",
"*Current Rate:* `{current_rate:.8f}`",
("*Close Profit:* `{close_profit_pct}`"
if r['close_profit_pct'] is not None else ""),
"*Current Profit:* `{current_profit_pct:.2f}%`",
("*Current Profit:* " if r['is_open'] else "*Close Profit: *")
+ "`{profit_pct:.2f}%`",
]
if (r['stop_loss'] != r['initial_stop_loss']
if (r['stop_loss_abs'] != r['initial_stop_loss_abs']
and r['initial_stop_loss_pct'] is not None):
# Adding initial stoploss only if it is different from stoploss
lines.append("*Initial Stoploss:* `{initial_stop_loss:.8f}` "
lines.append("*Initial Stoploss:* `{initial_stop_loss_abs:.8f}` "
"`({initial_stop_loss_pct:.2f}%)`")
# Adding stoploss and stoploss percentage only if it is not None
lines.append("*Stoploss:* `{stop_loss:.8f}` " +
lines.append("*Stoploss:* `{stop_loss_abs:.8f}` " +
("`({stop_loss_pct:.2f}%)`" if r['stop_loss_pct'] else ""))
lines.append("*Stoploss distance:* `{stoploss_current_dist:.8f}` "
"`({stoploss_current_dist_pct:.2f}%)`")
@ -833,7 +832,8 @@ class Telegram(RPC):
:param update: message update
:return: None
"""
val = self._rpc_show_config(self._freqtrade.config)
val = RPC._rpc_show_config(self._freqtrade.config, self._freqtrade.state)
if val['trailing_stop']:
sl_info = (
f"*Initial Stoploss:* `{val['stoploss']}`\n"

View File

@ -17,7 +17,7 @@ from freqtrade.data.dataprovider import DataProvider
from freqtrade.exceptions import OperationalException, StrategyError
from freqtrade.exchange import timeframe_to_minutes
from freqtrade.exchange.exchange import timeframe_to_next_date
from freqtrade.persistence import PairLock, Trade
from freqtrade.persistence import PairLocks, Trade
from freqtrade.strategy.strategy_wrapper import strategy_safe_wrapper
from freqtrade.wallets import Wallets
@ -288,7 +288,7 @@ class IStrategy(ABC):
Needs to be timezone aware `datetime.now(timezone.utc)`
:param reason: Optional string explaining why the pair was locked.
"""
PairLock.lock_pair(pair, until, reason)
PairLocks.lock_pair(pair, until, reason)
def unlock_pair(self, pair: str) -> None:
"""
@ -297,7 +297,7 @@ class IStrategy(ABC):
manually from within the strategy, to allow an easy way to unlock pairs.
:param pair: Unlock pair to allow trading again
"""
PairLock.unlock_pair(pair, datetime.now(timezone.utc))
PairLocks.unlock_pair(pair, datetime.now(timezone.utc))
def is_pair_locked(self, pair: str, candle_date: datetime = None) -> bool:
"""
@ -312,10 +312,10 @@ class IStrategy(ABC):
if not candle_date:
# Simple call ...
return PairLock.is_pair_locked(pair, candle_date)
return PairLocks.is_pair_locked(pair, candle_date)
else:
lock_time = timeframe_to_next_date(self.timeframe, candle_date)
return PairLock.is_pair_locked(pair, lock_time)
return PairLocks.is_pair_locked(pair, lock_time)
def analyze_ticker(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""

View File

@ -63,7 +63,7 @@ class {{ strategy }}(IStrategy):
ignore_roi_if_buy_signal = False
# Number of candles the strategy requires before producing valid signals
startup_candle_count: int = 20
startup_candle_count: int = 30
# Optional order type mapping.
order_types = {

View File

@ -64,7 +64,7 @@ class SampleStrategy(IStrategy):
ignore_roi_if_buy_signal = False
# Number of candles the strategy requires before producing valid signals
startup_candle_count: int = 20
startup_candle_count: int = 30
# Optional order type mapping.
order_types = {

View File

@ -108,13 +108,13 @@ class Wallets:
for trading operations, the latest balance is needed.
:param require_update: Allow skipping an update if balances were recently refreshed
"""
if (require_update or (self._last_wallet_refresh + 3600 < arrow.utcnow().timestamp)):
if (require_update or (self._last_wallet_refresh + 3600 < arrow.utcnow().int_timestamp)):
if self._config['dry_run']:
self._update_dry()
else:
self._update_live()
logger.info('Wallets synced.')
self._last_wallet_refresh = arrow.utcnow().timestamp
self._last_wallet_refresh = arrow.utcnow().int_timestamp
def get_all_balances(self) -> Dict[str, Any]:
return self._wallets

View File

@ -8,7 +8,7 @@ flake8==3.8.4
flake8-type-annotations==0.1.0
flake8-tidy-imports==4.1.0
mypy==0.790
pytest==6.1.1
pytest==6.1.2
pytest-asyncio==0.14.0
pytest-cov==2.10.1
pytest-mock==3.3.1

View File

@ -2,7 +2,7 @@
-r requirements.txt
# Required for hyperopt
scipy==1.5.3
scipy==1.5.4
scikit-learn==0.23.2
scikit-optimize==0.8.1
filelock==3.0.12

View File

@ -1,5 +1,5 @@
# Include all requirements to run the bot.
-r requirements.txt
plotly==4.11.0
plotly==4.12.0

View File

@ -1,15 +1,14 @@
numpy==1.19.2
pandas==1.1.3
numpy==1.19.4
pandas==1.1.4
ccxt==1.36.66
multidict==4.7.6
aiohttp==3.6.3
ccxt==1.37.69
aiohttp==3.7.2
SQLAlchemy==1.3.20
python-telegram-bot==13.0
arrow==0.17.0
cachetools==4.1.1
requests==2.24.0
urllib3==1.25.10
requests==2.25.0
urllib3==1.26.2
wrapt==1.12.1
jsonschema==3.2.0
TA-Lib==0.4.19
@ -23,18 +22,18 @@ blosc==1.9.2
py_find_1st==1.1.4
# Load ticker files 30% faster
python-rapidjson==0.9.1
python-rapidjson==0.9.3
# Notify systemd
sdnotify==0.3.2
# Api server
flask==1.1.2
flask-jwt-extended==3.24.1
flask-jwt-extended==3.25.0
flask-cors==3.0.9
# Support for colorized terminal output
colorama==0.4.4
# Building config files interactively
questionary==1.7.0
questionary==1.8.0
prompt-toolkit==3.0.8

View File

@ -69,7 +69,7 @@ setup(name='freqtrade',
'ccxt>=1.24.96',
'SQLAlchemy',
'python-telegram-bot',
'arrow',
'arrow>=0.17.0',
'cachetools',
'requests',
'urllib3',

View File

@ -435,6 +435,16 @@ def test_list_markets(mocker, markets, capsys):
assert re.search(r"^BLK/BTC$", captured.out, re.MULTILINE)
assert re.search(r"^LTC/USD$", captured.out, re.MULTILINE)
mocker.patch('freqtrade.exchange.Exchange.markets', PropertyMock(side_effect=ValueError))
# Test --one-column
args = [
"list-markets",
'--config', 'config.json.example',
"--one-column"
]
with pytest.raises(OperationalException, match=r"Cannot get markets.*"):
start_list_markets(get_args(args), False)
def test_create_datadir_failed(caplog):
@ -476,6 +486,12 @@ def test_start_new_strategy(mocker, caplog):
assert "CoolNewStrategy" in wt_mock.call_args_list[0][0][0]
assert log_has_re("Writing strategy to .*", caplog)
mocker.patch('freqtrade.commands.deploy_commands.setup_utils_configuration')
mocker.patch.object(Path, "exists", MagicMock(return_value=True))
with pytest.raises(OperationalException,
match=r".* already exists. Please choose another Strategy Name\."):
start_new_strategy(get_args(args))
def test_start_new_strategy_DefaultStrat(mocker, caplog):
args = [
@ -512,6 +528,12 @@ def test_start_new_hyperopt(mocker, caplog):
assert "CoolNewhyperopt" in wt_mock.call_args_list[0][0][0]
assert log_has_re("Writing hyperopt to .*", caplog)
mocker.patch('freqtrade.commands.deploy_commands.setup_utils_configuration')
mocker.patch.object(Path, "exists", MagicMock(return_value=True))
with pytest.raises(OperationalException,
match=r".* already exists. Please choose another Hyperopt Name\."):
start_new_hyperopt(get_args(args))
def test_start_new_hyperopt_DefaultHyperopt(mocker, caplog):
args = [
@ -579,7 +601,7 @@ def test_download_data_timerange(mocker, caplog, markets):
start_download_data(get_args(args))
assert dl_mock.call_count == 1
# 20days ago
days_ago = arrow.get(arrow.utcnow().shift(days=-20).date()).timestamp
days_ago = arrow.get(arrow.utcnow().shift(days=-20).date()).int_timestamp
assert dl_mock.call_args_list[0][1]['timerange'].startts == days_ago
dl_mock.reset_mock()
@ -592,7 +614,8 @@ def test_download_data_timerange(mocker, caplog, markets):
start_download_data(get_args(args))
assert dl_mock.call_count == 1
assert dl_mock.call_args_list[0][1]['timerange'].startts == arrow.Arrow(2020, 1, 1).timestamp
assert dl_mock.call_args_list[0][1]['timerange'].startts == arrow.Arrow(
2020, 1, 1).int_timestamp
def test_download_data_no_markets(mocker, caplog):
@ -695,6 +718,7 @@ def test_start_list_strategies(mocker, caplog, capsys):
"list-strategies",
"--strategy-path",
str(Path(__file__).parent.parent / "strategy" / "strats"),
'--no-color',
]
pargs = get_args(args)
# pargs['config'] = None
@ -769,6 +793,25 @@ def test_start_test_pairlist(mocker, caplog, tickers, default_conf, capsys):
assert re.match(r"Pairs for .*", captured.out)
assert re.match("['ETH/BTC', 'TKN/BTC', 'BLK/BTC', 'LTC/BTC', 'XRP/BTC']", captured.out)
args = [
'test-pairlist',
'-c', 'config.json.example',
'--one-column',
]
start_test_pairlist(get_args(args))
captured = capsys.readouterr()
assert re.match(r"ETH/BTC\nTKN/BTC\nBLK/BTC\nLTC/BTC\nXRP/BTC\n", captured.out)
args = [
'test-pairlist',
'-c', 'config.json.example',
'--print-json',
]
start_test_pairlist(get_args(args))
captured = capsys.readouterr()
assert re.match(r'Pairs for BTC: \n\["ETH/BTC","TKN/BTC","BLK/BTC","LTC/BTC","XRP/BTC"\]\n',
captured.out)
def test_hyperopt_list(mocker, capsys, caplog, hyperopt_results):
mocker.patch(

View File

@ -792,7 +792,7 @@ def limit_buy_order_open():
'side': 'buy',
'symbol': 'mocked',
'datetime': arrow.utcnow().isoformat(),
'timestamp': arrow.utcnow().timestamp,
'timestamp': arrow.utcnow().int_timestamp,
'price': 0.00001099,
'amount': 90.99181073,
'filled': 0.0,
@ -911,7 +911,7 @@ def limit_buy_order_canceled_empty(request):
'info': {},
'id': '1234512345',
'clientOrderId': None,
'timestamp': arrow.utcnow().shift(minutes=-601).timestamp,
'timestamp': arrow.utcnow().shift(minutes=-601).int_timestamp,
'datetime': arrow.utcnow().shift(minutes=-601).isoformat(),
'lastTradeTimestamp': None,
'symbol': 'LTC/USDT',
@ -932,7 +932,7 @@ def limit_buy_order_canceled_empty(request):
'info': {},
'id': 'AZNPFF-4AC4N-7MKTAT',
'clientOrderId': None,
'timestamp': arrow.utcnow().shift(minutes=-601).timestamp,
'timestamp': arrow.utcnow().shift(minutes=-601).int_timestamp,
'datetime': arrow.utcnow().shift(minutes=-601).isoformat(),
'lastTradeTimestamp': None,
'status': 'canceled',
@ -953,7 +953,7 @@ def limit_buy_order_canceled_empty(request):
'info': {},
'id': '1234512345',
'clientOrderId': 'alb1234123',
'timestamp': arrow.utcnow().shift(minutes=-601).timestamp,
'timestamp': arrow.utcnow().shift(minutes=-601).int_timestamp,
'datetime': arrow.utcnow().shift(minutes=-601).isoformat(),
'lastTradeTimestamp': None,
'symbol': 'LTC/USDT',
@ -974,7 +974,7 @@ def limit_buy_order_canceled_empty(request):
'info': {},
'id': '1234512345',
'clientOrderId': 'alb1234123',
'timestamp': arrow.utcnow().shift(minutes=-601).timestamp,
'timestamp': arrow.utcnow().shift(minutes=-601).int_timestamp,
'datetime': arrow.utcnow().shift(minutes=-601).isoformat(),
'lastTradeTimestamp': None,
'symbol': 'LTC/USDT',
@ -1000,7 +1000,7 @@ def limit_sell_order_open():
'side': 'sell',
'pair': 'mocked',
'datetime': arrow.utcnow().isoformat(),
'timestamp': arrow.utcnow().timestamp,
'timestamp': arrow.utcnow().int_timestamp,
'price': 0.00001173,
'amount': 90.99181073,
'filled': 0.0,

View File

@ -52,6 +52,31 @@ def test_historic_ohlcv(mocker, default_conf, ohlcv_history):
assert historymock.call_args_list[0][1]["timeframe"] == "5m"
def test_historic_ohlcv_dataformat(mocker, default_conf, ohlcv_history):
hdf5loadmock = MagicMock(return_value=ohlcv_history)
jsonloadmock = MagicMock(return_value=ohlcv_history)
mocker.patch("freqtrade.data.history.hdf5datahandler.HDF5DataHandler._ohlcv_load", hdf5loadmock)
mocker.patch("freqtrade.data.history.jsondatahandler.JsonDataHandler._ohlcv_load", jsonloadmock)
default_conf["runmode"] = RunMode.BACKTEST
exchange = get_patched_exchange(mocker, default_conf)
dp = DataProvider(default_conf, exchange)
data = dp.historic_ohlcv("UNITTEST/BTC", "5m")
assert isinstance(data, DataFrame)
hdf5loadmock.assert_not_called()
jsonloadmock.assert_called_once()
# Swiching to dataformat hdf5
hdf5loadmock.reset_mock()
jsonloadmock.reset_mock()
default_conf["dataformat_ohlcv"] = "hdf5"
dp = DataProvider(default_conf, exchange)
data = dp.historic_ohlcv("UNITTEST/BTC", "5m")
assert isinstance(data, DataFrame)
hdf5loadmock.assert_called_once()
jsonloadmock.assert_not_called()
def test_get_pair_dataframe(mocker, default_conf, ohlcv_history):
default_conf["runmode"] = RunMode.DRY_RUN
timeframe = default_conf["timeframe"]

View File

@ -323,7 +323,7 @@ def test_load_partial_missing(testdatadir, caplog) -> None:
start = arrow.get('2018-01-01T00:00:00')
end = arrow.get('2018-01-11T00:00:00')
data = load_data(testdatadir, '5m', ['UNITTEST/BTC'], startup_candles=20,
timerange=TimeRange('date', 'date', start.timestamp, end.timestamp))
timerange=TimeRange('date', 'date', start.int_timestamp, end.int_timestamp))
assert log_has(
'Using indicator startup period: 20 ...', caplog
)
@ -339,7 +339,7 @@ def test_load_partial_missing(testdatadir, caplog) -> None:
start = arrow.get('2018-01-10T00:00:00')
end = arrow.get('2018-02-20T00:00:00')
data = load_data(datadir=testdatadir, timeframe='5m', pairs=['UNITTEST/BTC'],
timerange=TimeRange('date', 'date', start.timestamp, end.timestamp))
timerange=TimeRange('date', 'date', start.int_timestamp, end.int_timestamp))
# timedifference in 5 minutes
td = ((end - start).total_seconds() // 60 // 5) + 1
assert td != len(data['UNITTEST/BTC'])
@ -724,6 +724,8 @@ def test_hdf5datahandler_trades_load(testdatadir):
trades2 = dh._trades_load('XRP/ETH', timerange)
assert len(trades) > len(trades2)
# Check that ID is None (If it's nan, it's wrong)
assert trades2[0][2] is None
# unfiltered load has trades before starttime
assert len([t for t in trades if t[0] < timerange.startts * 1000]) >= 0

View File

@ -50,7 +50,7 @@ def _build_dataframe(buy_ohlc_sell_matrice):
'date': tests_start_time.shift(
minutes=(
ohlc[0] *
timeframe_in_minute)).timestamp *
timeframe_in_minute)).int_timestamp *
1000,
'buy': ohlc[1],
'open': ohlc[2],
@ -71,7 +71,7 @@ def _build_dataframe(buy_ohlc_sell_matrice):
def _time_on_candle(number):
return np.datetime64(tests_start_time.shift(
minutes=(number * timeframe_in_minute)).timestamp * 1000, 'ms')
minutes=(number * timeframe_in_minute)).int_timestamp * 1000, 'ms')
# End helper functions
@ -251,7 +251,7 @@ def test_edge_heartbeat_calculate(mocker, edge_conf):
heartbeat = edge_conf['edge']['process_throttle_secs']
# should not recalculate if heartbeat not reached
edge._last_updated = arrow.utcnow().timestamp - heartbeat + 1
edge._last_updated = arrow.utcnow().int_timestamp - heartbeat + 1
assert edge.calculate() is False
@ -263,7 +263,7 @@ def mocked_load_data(datadir, pairs=[], timeframe='0m',
NEOBTC = [
[
tests_start_time.shift(minutes=(x * timeframe_in_minute)).timestamp * 1000,
tests_start_time.shift(minutes=(x * timeframe_in_minute)).int_timestamp * 1000,
math.sin(x * hz) / 1000 + base,
math.sin(x * hz) / 1000 + base + 0.0001,
math.sin(x * hz) / 1000 + base - 0.0001,
@ -275,7 +275,7 @@ def mocked_load_data(datadir, pairs=[], timeframe='0m',
base = 0.002
LTCBTC = [
[
tests_start_time.shift(minutes=(x * timeframe_in_minute)).timestamp * 1000,
tests_start_time.shift(minutes=(x * timeframe_in_minute)).int_timestamp * 1000,
math.sin(x * hz) / 1000 + base,
math.sin(x * hz) / 1000 + base + 0.0001,
math.sin(x * hz) / 1000 + base - 0.0001,
@ -299,7 +299,7 @@ def test_edge_process_downloaded_data(mocker, edge_conf):
assert edge.calculate()
assert len(edge._cached_pairs) == 2
assert edge._last_updated <= arrow.utcnow().timestamp + 2
assert edge._last_updated <= arrow.utcnow().int_timestamp + 2
def test_edge_process_no_data(mocker, edge_conf, caplog):

View File

@ -1,6 +1,6 @@
import copy
import logging
from datetime import datetime, timezone
from datetime import datetime, timedelta, timezone
from random import randint
from unittest.mock import MagicMock, Mock, PropertyMock, patch
@ -393,7 +393,7 @@ def test_reload_markets(default_conf, mocker, caplog):
exchange = get_patched_exchange(mocker, default_conf, api_mock, id="binance",
mock_markets=False)
exchange._load_async_markets = MagicMock()
exchange._last_markets_refresh = arrow.utcnow().timestamp
exchange._last_markets_refresh = arrow.utcnow().int_timestamp
updated_markets = {'ETH/BTC': {}, "LTC/BTC": {}}
assert exchange.markets == initial_markets
@ -404,7 +404,7 @@ def test_reload_markets(default_conf, mocker, caplog):
assert exchange._load_async_markets.call_count == 0
# more than 10 minutes have passed, reload is executed
exchange._last_markets_refresh = arrow.utcnow().timestamp - 15 * 60
exchange._last_markets_refresh = arrow.utcnow().int_timestamp - 15 * 60
exchange.reload_markets()
assert exchange.markets == updated_markets
assert exchange._load_async_markets.call_count == 1
@ -1272,7 +1272,7 @@ def test_get_historic_ohlcv(default_conf, mocker, caplog, exchange_name):
exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
ohlcv = [
[
arrow.utcnow().timestamp * 1000, # unix timestamp ms
arrow.utcnow().int_timestamp * 1000, # unix timestamp ms
1, # open
2, # high
3, # low
@ -1289,17 +1289,28 @@ def test_get_historic_ohlcv(default_conf, mocker, caplog, exchange_name):
# one_call calculation * 1.8 should do 2 calls
since = 5 * 60 * exchange._ft_has['ohlcv_candle_limit'] * 1.8
ret = exchange.get_historic_ohlcv(pair, "5m", int((arrow.utcnow().timestamp - since) * 1000))
ret = exchange.get_historic_ohlcv(pair, "5m", int((
arrow.utcnow().int_timestamp - since) * 1000))
assert exchange._async_get_candle_history.call_count == 2
# Returns twice the above OHLCV data
assert len(ret) == 2
caplog.clear()
async def mock_get_candle_hist_error(pair, *args, **kwargs):
raise TimeoutError()
exchange._async_get_candle_history = MagicMock(side_effect=mock_get_candle_hist_error)
ret = exchange.get_historic_ohlcv(pair, "5m", int(
(arrow.utcnow().int_timestamp - since) * 1000))
assert log_has_re(r"Async code raised an exception: .*", caplog)
def test_refresh_latest_ohlcv(mocker, default_conf, caplog) -> None:
ohlcv = [
[
(arrow.utcnow().timestamp - 1) * 1000, # unix timestamp ms
(arrow.utcnow().int_timestamp - 1) * 1000, # unix timestamp ms
1, # open
2, # high
3, # low
@ -1307,7 +1318,7 @@ def test_refresh_latest_ohlcv(mocker, default_conf, caplog) -> None:
5, # volume (in quote currency)
],
[
arrow.utcnow().timestamp * 1000, # unix timestamp ms
arrow.utcnow().int_timestamp * 1000, # unix timestamp ms
3, # open
1, # high
4, # low
@ -1353,7 +1364,7 @@ def test_refresh_latest_ohlcv(mocker, default_conf, caplog) -> None:
async def test__async_get_candle_history(default_conf, mocker, caplog, exchange_name):
ohlcv = [
[
arrow.utcnow().timestamp * 1000, # unix timestamp ms
arrow.utcnow().int_timestamp * 1000, # unix timestamp ms
1, # open
2, # high
3, # low
@ -1388,14 +1399,14 @@ async def test__async_get_candle_history(default_conf, mocker, caplog, exchange_
api_mock.fetch_ohlcv = MagicMock(side_effect=ccxt.BaseError("Unknown error"))
exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
await exchange._async_get_candle_history(pair, "5m",
(arrow.utcnow().timestamp - 2000) * 1000)
(arrow.utcnow().int_timestamp - 2000) * 1000)
with pytest.raises(OperationalException, match=r'Exchange.* does not support fetching '
r'historical candle \(OHLCV\) data\..*'):
api_mock.fetch_ohlcv = MagicMock(side_effect=ccxt.NotSupported("Not supported"))
exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
await exchange._async_get_candle_history(pair, "5m",
(arrow.utcnow().timestamp - 2000) * 1000)
(arrow.utcnow().int_timestamp - 2000) * 1000)
@pytest.mark.asyncio
@ -1641,13 +1652,13 @@ async def test__async_fetch_trades(default_conf, mocker, caplog, exchange_name,
with pytest.raises(OperationalException, match=r'Could not fetch trade data*'):
api_mock.fetch_trades = MagicMock(side_effect=ccxt.BaseError("Unknown error"))
exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
await exchange._async_fetch_trades(pair, since=(arrow.utcnow().timestamp - 2000) * 1000)
await exchange._async_fetch_trades(pair, since=(arrow.utcnow().int_timestamp - 2000) * 1000)
with pytest.raises(OperationalException, match=r'Exchange.* does not support fetching '
r'historical trade data\..*'):
api_mock.fetch_trades = MagicMock(side_effect=ccxt.NotSupported("Not supported"))
exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
await exchange._async_fetch_trades(pair, since=(arrow.utcnow().timestamp - 2000) * 1000)
await exchange._async_fetch_trades(pair, since=(arrow.utcnow().int_timestamp - 2000) * 1000)
@pytest.mark.asyncio
@ -2291,6 +2302,9 @@ def test_timeframe_to_next_date():
date = datetime.now(tz=timezone.utc)
assert timeframe_to_next_date("5m") > date
date = datetime(2019, 8, 12, 13, 30, 0, tzinfo=timezone.utc)
assert timeframe_to_next_date("5m", date) == date + timedelta(minutes=5)
@pytest.mark.parametrize("market_symbol,base,quote,exchange,add_dict,expected_result", [
("BTC/USDT", 'BTC', 'USDT', "binance", {}, True),

View File

@ -0,0 +1,51 @@
from copy import deepcopy
from datetime import datetime
from pathlib import Path
import pandas as pd
import pytest
from freqtrade.optimize.hyperopt import Hyperopt
from freqtrade.strategy.interface import SellType
from tests.conftest import patch_exchange
@pytest.fixture(scope='function')
def hyperopt_conf(default_conf):
hyperconf = deepcopy(default_conf)
hyperconf.update({
'hyperopt': 'DefaultHyperOpt',
'hyperopt_loss': 'ShortTradeDurHyperOptLoss',
'hyperopt_path': str(Path(__file__).parent / 'hyperopts'),
'epochs': 1,
'timerange': None,
'spaces': ['default'],
'hyperopt_jobs': 1,
})
return hyperconf
@pytest.fixture(scope='function')
def hyperopt(hyperopt_conf, mocker):
patch_exchange(mocker)
return Hyperopt(hyperopt_conf)
@pytest.fixture(scope='function')
def hyperopt_results():
return pd.DataFrame(
{
'pair': ['ETH/BTC', 'ETH/BTC', 'ETH/BTC'],
'profit_percent': [-0.1, 0.2, 0.3],
'profit_abs': [-0.2, 0.4, 0.6],
'trade_duration': [10, 30, 10],
'sell_reason': [SellType.STOP_LOSS, SellType.ROI, SellType.ROI],
'close_date':
[
datetime(2019, 1, 1, 9, 26, 3, 478039),
datetime(2019, 2, 1, 9, 26, 3, 478039),
datetime(2019, 3, 1, 9, 26, 3, 478039)
]
}
)

View File

@ -2,7 +2,6 @@
import locale
import logging
import re
from copy import deepcopy
from datetime import datetime
from pathlib import Path
from typing import Dict, List
@ -17,58 +16,15 @@ from freqtrade import constants
from freqtrade.commands.optimize_commands import setup_optimize_configuration, start_hyperopt
from freqtrade.data.history import load_data
from freqtrade.exceptions import DependencyException, OperationalException
from freqtrade.optimize.default_hyperopt_loss import ShortTradeDurHyperOptLoss
from freqtrade.optimize.hyperopt import Hyperopt
from freqtrade.resolvers.hyperopt_resolver import HyperOptLossResolver, HyperOptResolver
from freqtrade.resolvers.hyperopt_resolver import HyperOptResolver
from freqtrade.state import RunMode
from freqtrade.strategy.interface import SellType
from tests.conftest import (get_args, log_has, log_has_re, patch_exchange,
patched_configuration_load_config_file)
from .hyperopts.default_hyperopt import DefaultHyperOpt
@pytest.fixture(scope='function')
def hyperopt_conf(default_conf):
hyperconf = deepcopy(default_conf)
hyperconf.update({
'hyperopt': 'DefaultHyperOpt',
'hyperopt_loss': 'ShortTradeDurHyperOptLoss',
'hyperopt_path': str(Path(__file__).parent / 'hyperopts'),
'epochs': 1,
'timerange': None,
'spaces': ['default'],
'hyperopt_jobs': 1,
})
return hyperconf
@pytest.fixture(scope='function')
def hyperopt(hyperopt_conf, mocker):
patch_exchange(mocker)
return Hyperopt(hyperopt_conf)
@pytest.fixture(scope='function')
def hyperopt_results():
return pd.DataFrame(
{
'pair': ['ETH/BTC', 'ETH/BTC', 'ETH/BTC'],
'profit_percent': [-0.1, 0.2, 0.3],
'profit_abs': [-0.2, 0.4, 0.6],
'trade_duration': [10, 30, 10],
'sell_reason': [SellType.STOP_LOSS, SellType.ROI, SellType.ROI],
'close_date':
[
datetime(2019, 1, 1, 9, 26, 3, 478039),
datetime(2019, 2, 1, 9, 26, 3, 478039),
datetime(2019, 3, 1, 9, 26, 3, 478039)
]
}
)
# Functions for recurrent object patching
def create_results(mocker, hyperopt, testdatadir) -> List[Dict]:
"""
@ -230,32 +186,6 @@ def test_hyperoptresolver_noname(default_conf):
HyperOptResolver.load_hyperopt(default_conf)
def test_hyperoptlossresolver_noname(default_conf):
with pytest.raises(OperationalException,
match="No Hyperopt loss set. Please use `--hyperopt-loss` to specify "
"the Hyperopt-Loss class to use."):
HyperOptLossResolver.load_hyperoptloss(default_conf)
def test_hyperoptlossresolver(mocker, default_conf) -> None:
hl = ShortTradeDurHyperOptLoss
mocker.patch(
'freqtrade.resolvers.hyperopt_resolver.HyperOptLossResolver.load_object',
MagicMock(return_value=hl)
)
default_conf.update({'hyperopt_loss': 'SharpeHyperOptLossDaily'})
x = HyperOptLossResolver.load_hyperoptloss(default_conf)
assert hasattr(x, "hyperopt_loss_function")
def test_hyperoptlossresolver_wrongname(default_conf) -> None:
default_conf.update({'hyperopt_loss': "NonExistingLossClass"})
with pytest.raises(OperationalException, match=r'Impossible to load HyperoptLoss.*'):
HyperOptLossResolver.load_hyperoptloss(default_conf)
def test_start_not_installed(mocker, default_conf, import_fails) -> None:
start_mock = MagicMock()
patched_configuration_load_config_file(mocker, default_conf)
@ -269,7 +199,8 @@ def test_start_not_installed(mocker, default_conf, import_fails) -> None:
'--hyperopt', 'DefaultHyperOpt',
'--hyperopt-path',
str(Path(__file__).parent / "hyperopts"),
'--epochs', '5'
'--epochs', '5',
'--hyperopt-loss', 'SharpeHyperOptLossDaily',
]
pargs = get_args(args)
@ -337,137 +268,6 @@ def test_start_filelock(mocker, hyperopt_conf, caplog) -> None:
assert log_has("Another running instance of freqtrade Hyperopt detected.", caplog)
def test_loss_calculation_prefer_correct_trade_count(hyperopt_conf, hyperopt_results) -> None:
hl = HyperOptLossResolver.load_hyperoptloss(hyperopt_conf)
correct = hl.hyperopt_loss_function(hyperopt_results, 600,
datetime(2019, 1, 1), datetime(2019, 5, 1))
over = hl.hyperopt_loss_function(hyperopt_results, 600 + 100,
datetime(2019, 1, 1), datetime(2019, 5, 1))
under = hl.hyperopt_loss_function(hyperopt_results, 600 - 100,
datetime(2019, 1, 1), datetime(2019, 5, 1))
assert over > correct
assert under > correct
def test_loss_calculation_prefer_shorter_trades(hyperopt_conf, hyperopt_results) -> None:
resultsb = hyperopt_results.copy()
resultsb.loc[1, 'trade_duration'] = 20
hl = HyperOptLossResolver.load_hyperoptloss(hyperopt_conf)
longer = hl.hyperopt_loss_function(hyperopt_results, 100,
datetime(2019, 1, 1), datetime(2019, 5, 1))
shorter = hl.hyperopt_loss_function(resultsb, 100,
datetime(2019, 1, 1), datetime(2019, 5, 1))
assert shorter < longer
def test_loss_calculation_has_limited_profit(hyperopt_conf, hyperopt_results) -> None:
results_over = hyperopt_results.copy()
results_over['profit_percent'] = hyperopt_results['profit_percent'] * 2
results_under = hyperopt_results.copy()
results_under['profit_percent'] = hyperopt_results['profit_percent'] / 2
hl = HyperOptLossResolver.load_hyperoptloss(hyperopt_conf)
correct = hl.hyperopt_loss_function(hyperopt_results, 600,
datetime(2019, 1, 1), datetime(2019, 5, 1))
over = hl.hyperopt_loss_function(results_over, 600,
datetime(2019, 1, 1), datetime(2019, 5, 1))
under = hl.hyperopt_loss_function(results_under, 600,
datetime(2019, 1, 1), datetime(2019, 5, 1))
assert over < correct
assert under > correct
def test_sharpe_loss_prefers_higher_profits(default_conf, hyperopt_results) -> None:
results_over = hyperopt_results.copy()
results_over['profit_percent'] = hyperopt_results['profit_percent'] * 2
results_under = hyperopt_results.copy()
results_under['profit_percent'] = hyperopt_results['profit_percent'] / 2
default_conf.update({'hyperopt_loss': 'SharpeHyperOptLossDaily'})
hl = HyperOptLossResolver.load_hyperoptloss(default_conf)
correct = hl.hyperopt_loss_function(hyperopt_results, len(hyperopt_results),
datetime(2019, 1, 1), datetime(2019, 5, 1))
over = hl.hyperopt_loss_function(results_over, len(hyperopt_results),
datetime(2019, 1, 1), datetime(2019, 5, 1))
under = hl.hyperopt_loss_function(results_under, len(hyperopt_results),
datetime(2019, 1, 1), datetime(2019, 5, 1))
assert over < correct
assert under > correct
def test_sharpe_loss_daily_prefers_higher_profits(default_conf, hyperopt_results) -> None:
results_over = hyperopt_results.copy()
results_over['profit_percent'] = hyperopt_results['profit_percent'] * 2
results_under = hyperopt_results.copy()
results_under['profit_percent'] = hyperopt_results['profit_percent'] / 2
default_conf.update({'hyperopt_loss': 'SharpeHyperOptLossDaily'})
hl = HyperOptLossResolver.load_hyperoptloss(default_conf)
correct = hl.hyperopt_loss_function(hyperopt_results, len(hyperopt_results),
datetime(2019, 1, 1), datetime(2019, 5, 1))
over = hl.hyperopt_loss_function(results_over, len(hyperopt_results),
datetime(2019, 1, 1), datetime(2019, 5, 1))
under = hl.hyperopt_loss_function(results_under, len(hyperopt_results),
datetime(2019, 1, 1), datetime(2019, 5, 1))
assert over < correct
assert under > correct
def test_sortino_loss_prefers_higher_profits(default_conf, hyperopt_results) -> None:
results_over = hyperopt_results.copy()
results_over['profit_percent'] = hyperopt_results['profit_percent'] * 2
results_under = hyperopt_results.copy()
results_under['profit_percent'] = hyperopt_results['profit_percent'] / 2
default_conf.update({'hyperopt_loss': 'SortinoHyperOptLoss'})
hl = HyperOptLossResolver.load_hyperoptloss(default_conf)
correct = hl.hyperopt_loss_function(hyperopt_results, len(hyperopt_results),
datetime(2019, 1, 1), datetime(2019, 5, 1))
over = hl.hyperopt_loss_function(results_over, len(hyperopt_results),
datetime(2019, 1, 1), datetime(2019, 5, 1))
under = hl.hyperopt_loss_function(results_under, len(hyperopt_results),
datetime(2019, 1, 1), datetime(2019, 5, 1))
assert over < correct
assert under > correct
def test_sortino_loss_daily_prefers_higher_profits(default_conf, hyperopt_results) -> None:
results_over = hyperopt_results.copy()
results_over['profit_percent'] = hyperopt_results['profit_percent'] * 2
results_under = hyperopt_results.copy()
results_under['profit_percent'] = hyperopt_results['profit_percent'] / 2
default_conf.update({'hyperopt_loss': 'SortinoHyperOptLossDaily'})
hl = HyperOptLossResolver.load_hyperoptloss(default_conf)
correct = hl.hyperopt_loss_function(hyperopt_results, len(hyperopt_results),
datetime(2019, 1, 1), datetime(2019, 5, 1))
over = hl.hyperopt_loss_function(results_over, len(hyperopt_results),
datetime(2019, 1, 1), datetime(2019, 5, 1))
under = hl.hyperopt_loss_function(results_under, len(hyperopt_results),
datetime(2019, 1, 1), datetime(2019, 5, 1))
assert over < correct
assert under > correct
def test_onlyprofit_loss_prefers_higher_profits(default_conf, hyperopt_results) -> None:
results_over = hyperopt_results.copy()
results_over['profit_percent'] = hyperopt_results['profit_percent'] * 2
results_under = hyperopt_results.copy()
results_under['profit_percent'] = hyperopt_results['profit_percent'] / 2
default_conf.update({'hyperopt_loss': 'OnlyProfitHyperOptLoss'})
hl = HyperOptLossResolver.load_hyperoptloss(default_conf)
correct = hl.hyperopt_loss_function(hyperopt_results, len(hyperopt_results),
datetime(2019, 1, 1), datetime(2019, 5, 1))
over = hl.hyperopt_loss_function(results_over, len(hyperopt_results),
datetime(2019, 1, 1), datetime(2019, 5, 1))
under = hl.hyperopt_loss_function(results_under, len(hyperopt_results),
datetime(2019, 1, 1), datetime(2019, 5, 1))
assert over < correct
assert under > correct
def test_log_results_if_loss_improves(hyperopt, capsys) -> None:
hyperopt.current_best_loss = 2
hyperopt.total_epochs = 2

View File

@ -0,0 +1,165 @@
from datetime import datetime
from unittest.mock import MagicMock
import pytest
from freqtrade.exceptions import OperationalException
from freqtrade.optimize.default_hyperopt_loss import ShortTradeDurHyperOptLoss
from freqtrade.resolvers.hyperopt_resolver import HyperOptLossResolver
def test_hyperoptlossresolver_noname(default_conf):
with pytest.raises(OperationalException,
match="No Hyperopt loss set. Please use `--hyperopt-loss` to specify "
"the Hyperopt-Loss class to use."):
HyperOptLossResolver.load_hyperoptloss(default_conf)
def test_hyperoptlossresolver(mocker, default_conf) -> None:
hl = ShortTradeDurHyperOptLoss
mocker.patch(
'freqtrade.resolvers.hyperopt_resolver.HyperOptLossResolver.load_object',
MagicMock(return_value=hl)
)
default_conf.update({'hyperopt_loss': 'SharpeHyperOptLossDaily'})
x = HyperOptLossResolver.load_hyperoptloss(default_conf)
assert hasattr(x, "hyperopt_loss_function")
def test_hyperoptlossresolver_wrongname(default_conf) -> None:
default_conf.update({'hyperopt_loss': "NonExistingLossClass"})
with pytest.raises(OperationalException, match=r'Impossible to load HyperoptLoss.*'):
HyperOptLossResolver.load_hyperoptloss(default_conf)
def test_loss_calculation_prefer_correct_trade_count(hyperopt_conf, hyperopt_results) -> None:
hl = HyperOptLossResolver.load_hyperoptloss(hyperopt_conf)
correct = hl.hyperopt_loss_function(hyperopt_results, 600,
datetime(2019, 1, 1), datetime(2019, 5, 1))
over = hl.hyperopt_loss_function(hyperopt_results, 600 + 100,
datetime(2019, 1, 1), datetime(2019, 5, 1))
under = hl.hyperopt_loss_function(hyperopt_results, 600 - 100,
datetime(2019, 1, 1), datetime(2019, 5, 1))
assert over > correct
assert under > correct
def test_loss_calculation_prefer_shorter_trades(hyperopt_conf, hyperopt_results) -> None:
resultsb = hyperopt_results.copy()
resultsb.loc[1, 'trade_duration'] = 20
hl = HyperOptLossResolver.load_hyperoptloss(hyperopt_conf)
longer = hl.hyperopt_loss_function(hyperopt_results, 100,
datetime(2019, 1, 1), datetime(2019, 5, 1))
shorter = hl.hyperopt_loss_function(resultsb, 100,
datetime(2019, 1, 1), datetime(2019, 5, 1))
assert shorter < longer
def test_loss_calculation_has_limited_profit(hyperopt_conf, hyperopt_results) -> None:
results_over = hyperopt_results.copy()
results_over['profit_percent'] = hyperopt_results['profit_percent'] * 2
results_under = hyperopt_results.copy()
results_under['profit_percent'] = hyperopt_results['profit_percent'] / 2
hl = HyperOptLossResolver.load_hyperoptloss(hyperopt_conf)
correct = hl.hyperopt_loss_function(hyperopt_results, 600,
datetime(2019, 1, 1), datetime(2019, 5, 1))
over = hl.hyperopt_loss_function(results_over, 600,
datetime(2019, 1, 1), datetime(2019, 5, 1))
under = hl.hyperopt_loss_function(results_under, 600,
datetime(2019, 1, 1), datetime(2019, 5, 1))
assert over < correct
assert under > correct
def test_sharpe_loss_prefers_higher_profits(default_conf, hyperopt_results) -> None:
results_over = hyperopt_results.copy()
results_over['profit_percent'] = hyperopt_results['profit_percent'] * 2
results_under = hyperopt_results.copy()
results_under['profit_percent'] = hyperopt_results['profit_percent'] / 2
default_conf.update({'hyperopt_loss': 'SharpeHyperOptLoss'})
hl = HyperOptLossResolver.load_hyperoptloss(default_conf)
correct = hl.hyperopt_loss_function(hyperopt_results, len(hyperopt_results),
datetime(2019, 1, 1), datetime(2019, 5, 1))
over = hl.hyperopt_loss_function(results_over, len(hyperopt_results),
datetime(2019, 1, 1), datetime(2019, 5, 1))
under = hl.hyperopt_loss_function(results_under, len(hyperopt_results),
datetime(2019, 1, 1), datetime(2019, 5, 1))
assert over < correct
assert under > correct
def test_sharpe_loss_daily_prefers_higher_profits(default_conf, hyperopt_results) -> None:
results_over = hyperopt_results.copy()
results_over['profit_percent'] = hyperopt_results['profit_percent'] * 2
results_under = hyperopt_results.copy()
results_under['profit_percent'] = hyperopt_results['profit_percent'] / 2
default_conf.update({'hyperopt_loss': 'SharpeHyperOptLossDaily'})
hl = HyperOptLossResolver.load_hyperoptloss(default_conf)
correct = hl.hyperopt_loss_function(hyperopt_results, len(hyperopt_results),
datetime(2019, 1, 1), datetime(2019, 5, 1))
over = hl.hyperopt_loss_function(results_over, len(hyperopt_results),
datetime(2019, 1, 1), datetime(2019, 5, 1))
under = hl.hyperopt_loss_function(results_under, len(hyperopt_results),
datetime(2019, 1, 1), datetime(2019, 5, 1))
assert over < correct
assert under > correct
def test_sortino_loss_prefers_higher_profits(default_conf, hyperopt_results) -> None:
results_over = hyperopt_results.copy()
results_over['profit_percent'] = hyperopt_results['profit_percent'] * 2
results_under = hyperopt_results.copy()
results_under['profit_percent'] = hyperopt_results['profit_percent'] / 2
default_conf.update({'hyperopt_loss': 'SortinoHyperOptLoss'})
hl = HyperOptLossResolver.load_hyperoptloss(default_conf)
correct = hl.hyperopt_loss_function(hyperopt_results, len(hyperopt_results),
datetime(2019, 1, 1), datetime(2019, 5, 1))
over = hl.hyperopt_loss_function(results_over, len(hyperopt_results),
datetime(2019, 1, 1), datetime(2019, 5, 1))
under = hl.hyperopt_loss_function(results_under, len(hyperopt_results),
datetime(2019, 1, 1), datetime(2019, 5, 1))
assert over < correct
assert under > correct
def test_sortino_loss_daily_prefers_higher_profits(default_conf, hyperopt_results) -> None:
results_over = hyperopt_results.copy()
results_over['profit_percent'] = hyperopt_results['profit_percent'] * 2
results_under = hyperopt_results.copy()
results_under['profit_percent'] = hyperopt_results['profit_percent'] / 2
default_conf.update({'hyperopt_loss': 'SortinoHyperOptLossDaily'})
hl = HyperOptLossResolver.load_hyperoptloss(default_conf)
correct = hl.hyperopt_loss_function(hyperopt_results, len(hyperopt_results),
datetime(2019, 1, 1), datetime(2019, 5, 1))
over = hl.hyperopt_loss_function(results_over, len(hyperopt_results),
datetime(2019, 1, 1), datetime(2019, 5, 1))
under = hl.hyperopt_loss_function(results_under, len(hyperopt_results),
datetime(2019, 1, 1), datetime(2019, 5, 1))
assert over < correct
assert under > correct
def test_onlyprofit_loss_prefers_higher_profits(default_conf, hyperopt_results) -> None:
results_over = hyperopt_results.copy()
results_over['profit_percent'] = hyperopt_results['profit_percent'] * 2
results_under = hyperopt_results.copy()
results_under['profit_percent'] = hyperopt_results['profit_percent'] / 2
default_conf.update({'hyperopt_loss': 'OnlyProfitHyperOptLoss'})
hl = HyperOptLossResolver.load_hyperoptloss(default_conf)
correct = hl.hyperopt_loss_function(hyperopt_results, len(hyperopt_results),
datetime(2019, 1, 1), datetime(2019, 5, 1))
over = hl.hyperopt_loss_function(results_over, len(hyperopt_results),
datetime(2019, 1, 1), datetime(2019, 5, 1))
under = hl.hyperopt_loss_function(results_under, len(hyperopt_results),
datetime(2019, 1, 1), datetime(2019, 5, 1))
assert over < correct
assert under > correct

View File

@ -0,0 +1,82 @@
from datetime import datetime, timedelta, timezone
import arrow
import pytest
from freqtrade.persistence import PairLocks
from freqtrade.persistence.models import PairLock
@pytest.mark.parametrize('use_db', (False, True))
@pytest.mark.usefixtures("init_persistence")
def test_PairLocks(use_db):
PairLocks.timeframe = '5m'
# No lock should be present
if use_db:
assert len(PairLock.query.all()) == 0
else:
PairLocks.use_db = False
assert PairLocks.use_db == use_db
pair = 'ETH/BTC'
assert not PairLocks.is_pair_locked(pair)
PairLocks.lock_pair(pair, arrow.utcnow().shift(minutes=4).datetime)
# ETH/BTC locked for 4 minutes
assert PairLocks.is_pair_locked(pair)
# XRP/BTC should not be locked now
pair = 'XRP/BTC'
assert not PairLocks.is_pair_locked(pair)
# Unlocking a pair that's not locked should not raise an error
PairLocks.unlock_pair(pair)
PairLocks.lock_pair(pair, arrow.utcnow().shift(minutes=4).datetime)
assert PairLocks.is_pair_locked(pair)
# Get both locks from above
locks = PairLocks.get_pair_locks(None)
assert len(locks) == 2
# Unlock original pair
pair = 'ETH/BTC'
PairLocks.unlock_pair(pair)
assert not PairLocks.is_pair_locked(pair)
assert not PairLocks.is_global_lock()
pair = 'BTC/USDT'
# Lock until 14:30
lock_time = datetime(2020, 5, 1, 14, 30, 0, tzinfo=timezone.utc)
PairLocks.lock_pair(pair, lock_time)
assert not PairLocks.is_pair_locked(pair)
assert PairLocks.is_pair_locked(pair, lock_time + timedelta(minutes=-10))
assert not PairLocks.is_global_lock(lock_time + timedelta(minutes=-10))
assert PairLocks.is_pair_locked(pair, lock_time + timedelta(minutes=-50))
assert not PairLocks.is_global_lock(lock_time + timedelta(minutes=-50))
# Should not be locked after time expired
assert not PairLocks.is_pair_locked(pair, lock_time + timedelta(minutes=10))
locks = PairLocks.get_pair_locks(pair, lock_time + timedelta(minutes=-2))
assert len(locks) == 1
assert 'PairLock' in str(locks[0])
# Unlock all
PairLocks.unlock_pair(pair, lock_time + timedelta(minutes=-2))
assert not PairLocks.is_global_lock(lock_time + timedelta(minutes=-50))
# Global lock
PairLocks.lock_pair('*', lock_time)
assert PairLocks.is_global_lock(lock_time + timedelta(minutes=-50))
# Global lock also locks every pair seperately
assert PairLocks.is_pair_locked(pair, lock_time + timedelta(minutes=-50))
assert PairLocks.is_pair_locked('XRP/USDT', lock_time + timedelta(minutes=-50))
if use_db:
assert len(PairLock.query.all()) > 0
else:
# Nothing was pushed to the database
assert len(PairLock.query.all()) == 0
# Reset use-db variable
PairLocks.use_db = True

View File

@ -69,8 +69,7 @@ def test_rpc_trade_status(default_conf, ticker, fee, mocker) -> None:
'min_rate': ANY,
'max_rate': ANY,
'strategy': ANY,
'ticker_interval': ANY,
'timeframe': ANY,
'timeframe': 5,
'open_order_id': ANY,
'close_date': None,
'close_date_hum': None,
@ -87,14 +86,15 @@ def test_rpc_trade_status(default_conf, ticker, fee, mocker) -> None:
'current_profit': -0.00408133,
'current_profit_pct': -0.41,
'current_profit_abs': -4.09e-06,
'stop_loss': 9.882e-06,
'profit_ratio': -0.00408133,
'profit_pct': -0.41,
'profit_abs': -4.09e-06,
'stop_loss_abs': 9.882e-06,
'stop_loss_pct': -10.0,
'stop_loss_ratio': -0.1,
'stoploss_order_id': None,
'stoploss_last_update': ANY,
'stoploss_last_update_timestamp': ANY,
'initial_stop_loss': 9.882e-06,
'initial_stop_loss_abs': 9.882e-06,
'initial_stop_loss_pct': -10.0,
'initial_stop_loss_ratio': -0.1,
@ -134,7 +134,6 @@ def test_rpc_trade_status(default_conf, ticker, fee, mocker) -> None:
'min_rate': ANY,
'max_rate': ANY,
'strategy': ANY,
'ticker_interval': ANY,
'timeframe': ANY,
'open_order_id': ANY,
'close_date': None,
@ -152,14 +151,15 @@ def test_rpc_trade_status(default_conf, ticker, fee, mocker) -> None:
'current_profit': ANY,
'current_profit_pct': ANY,
'current_profit_abs': ANY,
'stop_loss': 9.882e-06,
'profit_ratio': ANY,
'profit_pct': ANY,
'profit_abs': ANY,
'stop_loss_abs': 9.882e-06,
'stop_loss_pct': -10.0,
'stop_loss_ratio': -0.1,
'stoploss_order_id': None,
'stoploss_last_update': ANY,
'stoploss_last_update_timestamp': ANY,
'initial_stop_loss': 9.882e-06,
'initial_stop_loss_abs': 9.882e-06,
'initial_stop_loss_pct': -10.0,
'initial_stop_loss_ratio': -0.1,

View File

@ -2,7 +2,7 @@
Unit test file for rpc/api_server.py
"""
from datetime import datetime, timedelta
from datetime import datetime, timedelta, timezone
from pathlib import Path
from unittest.mock import ANY, MagicMock, PropertyMock
@ -12,9 +12,9 @@ from requests.auth import _basic_auth_str
from freqtrade.__init__ import __version__
from freqtrade.loggers import setup_logging, setup_logging_pre
from freqtrade.persistence import PairLock, Trade
from freqtrade.persistence import PairLocks, Trade
from freqtrade.rpc.api_server import BASE_URI, ApiServer
from freqtrade.state import State
from freqtrade.state import RunMode, State
from tests.conftest import create_mock_trades, get_patched_freqtradebot, log_has, patch_get_signal
@ -26,7 +26,7 @@ _TEST_PASS = "SuperSecurePassword1!"
def botclient(default_conf, mocker):
setup_logging_pre()
setup_logging(default_conf)
default_conf['runmode'] = RunMode.DRY_RUN
default_conf.update({"api_server": {"enabled": True,
"listen_ip_address": "127.0.0.1",
"listen_port": 8080,
@ -339,8 +339,8 @@ def test_api_locks(botclient):
assert rc.json['lock_count'] == 0
assert rc.json['lock_count'] == len(rc.json['locks'])
PairLock.lock_pair('ETH/BTC', datetime.utcnow() + timedelta(minutes=4), 'randreason')
PairLock.lock_pair('XRP/BTC', datetime.utcnow() + timedelta(minutes=20), 'deadbeef')
PairLocks.lock_pair('ETH/BTC', datetime.now(timezone.utc) + timedelta(minutes=4), 'randreason')
PairLocks.lock_pair('XRP/BTC', datetime.now(timezone.utc) + timedelta(minutes=20), 'deadbeef')
rc = client_get(client, f"{BASE_URI}/locks")
assert_response(rc)
@ -360,7 +360,6 @@ def test_api_show_config(botclient, mocker):
assert_response(rc)
assert 'dry_run' in rc.json
assert rc.json['exchange'] == 'bittrex'
assert rc.json['ticker_interval'] == '5m'
assert rc.json['timeframe'] == '5m'
assert rc.json['timeframe_ms'] == 300000
assert rc.json['timeframe_min'] == 5
@ -639,6 +638,9 @@ def test_api_status(botclient, mocker, ticker, fee, markets):
'current_profit': -0.00408133,
'current_profit_pct': -0.41,
'current_profit_abs': -4.09e-06,
'profit_ratio': -0.00408133,
'profit_pct': -0.41,
'profit_abs': -4.09e-06,
'current_rate': 1.099e-05,
'open_date': ANY,
'open_date_hum': 'just now',
@ -647,14 +649,12 @@ def test_api_status(botclient, mocker, ticker, fee, markets):
'open_rate': 1.098e-05,
'pair': 'ETH/BTC',
'stake_amount': 0.001,
'stop_loss': 9.882e-06,
'stop_loss_abs': 9.882e-06,
'stop_loss_pct': -10.0,
'stop_loss_ratio': -0.1,
'stoploss_order_id': None,
'stoploss_last_update': ANY,
'stoploss_last_update_timestamp': ANY,
'initial_stop_loss': 9.882e-06,
'initial_stop_loss_abs': 9.882e-06,
'initial_stop_loss_pct': -10.0,
'initial_stop_loss_ratio': -0.1,
@ -682,7 +682,6 @@ def test_api_status(botclient, mocker, ticker, fee, markets):
'sell_reason': None,
'sell_order_status': None,
'strategy': 'DefaultStrategy',
'ticker_interval': 5,
'timeframe': 5,
'exchange': 'bittrex',
}]
@ -779,20 +778,22 @@ def test_api_forcebuy(botclient, mocker, fee):
'open_rate': 0.245441,
'pair': 'ETH/ETH',
'stake_amount': 1,
'stop_loss': None,
'stop_loss_abs': None,
'stop_loss_pct': None,
'stop_loss_ratio': None,
'stoploss_order_id': None,
'stoploss_last_update': None,
'stoploss_last_update_timestamp': None,
'initial_stop_loss': None,
'initial_stop_loss_abs': None,
'initial_stop_loss_pct': None,
'initial_stop_loss_ratio': None,
'close_profit': None,
'close_profit_pct': None,
'close_profit_abs': None,
'close_rate_requested': None,
'profit_ratio': None,
'profit_pct': None,
'profit_abs': None,
'fee_close': 0.0025,
'fee_close_cost': None,
'fee_close_currency': None,
@ -808,7 +809,6 @@ def test_api_forcebuy(botclient, mocker, fee):
'sell_reason': None,
'sell_order_status': None,
'strategy': None,
'ticker_interval': None,
'timeframe': None,
'exchange': 'bittrex',
}

View File

@ -18,10 +18,10 @@ from freqtrade.constants import CANCEL_REASON
from freqtrade.edge import PairInfo
from freqtrade.freqtradebot import FreqtradeBot
from freqtrade.loggers import setup_logging
from freqtrade.persistence import PairLock, Trade
from freqtrade.persistence import PairLocks, Trade
from freqtrade.rpc import RPCMessageType
from freqtrade.rpc.telegram import Telegram, authorized_only
from freqtrade.state import State
from freqtrade.state import RunMode, State
from freqtrade.strategy.interface import SellType
from tests.conftest import (create_mock_trades, get_patched_freqtradebot, log_has, patch_exchange,
patch_get_signal, patch_whitelist)
@ -164,16 +164,17 @@ def test_telegram_status(default_conf, update, mocker) -> None:
'amount': 90.99181074,
'stake_amount': 90.99181074,
'close_profit_pct': None,
'current_profit': -0.0059,
'current_profit_pct': -0.59,
'initial_stop_loss': 1.098e-05,
'stop_loss': 1.099e-05,
'profit': -0.0059,
'profit_pct': -0.59,
'initial_stop_loss_abs': 1.098e-05,
'stop_loss_abs': 1.099e-05,
'sell_order_status': None,
'initial_stop_loss_pct': -0.05,
'stoploss_current_dist': 1e-08,
'stoploss_current_dist_pct': -0.02,
'stop_loss_pct': -0.01,
'open_order': '(limit buy rem=0.00000000)'
'open_order': '(limit buy rem=0.00000000)',
'is_open': True
}]),
_status_table=status_table,
_send_msg=msg_mock
@ -1041,15 +1042,8 @@ def test_telegram_lock_handle(default_conf, update, ticker, fee, mocker) -> None
patch_get_signal(freqtradebot, (True, False))
telegram = Telegram(freqtradebot)
freqtradebot.state = State.STOPPED
telegram._locks(update=update, context=MagicMock())
assert msg_mock.call_count == 1
assert 'not running' in msg_mock.call_args_list[0][0][0]
msg_mock.reset_mock()
freqtradebot.state = State.RUNNING
PairLock.lock_pair('ETH/BTC', arrow.utcnow().shift(minutes=4).datetime, 'randreason')
PairLock.lock_pair('XRP/BTC', arrow.utcnow().shift(minutes=20).datetime, 'deadbeef')
PairLocks.lock_pair('ETH/BTC', arrow.utcnow().shift(minutes=4).datetime, 'randreason')
PairLocks.lock_pair('XRP/BTC', arrow.utcnow().shift(minutes=20).datetime, 'deadbeef')
telegram._locks(update=update, context=MagicMock())
@ -1309,6 +1303,7 @@ def test_show_config_handle(default_conf, update, mocker) -> None:
_init=MagicMock(),
_send_msg=msg_mock
)
default_conf['runmode'] = RunMode.DRY_RUN
freqtradebot = get_patched_freqtradebot(mocker, default_conf)
telegram = Telegram(freqtradebot)

View File

@ -11,7 +11,7 @@ from freqtrade.configuration import TimeRange
from freqtrade.data.dataprovider import DataProvider
from freqtrade.data.history import load_data
from freqtrade.exceptions import StrategyError
from freqtrade.persistence import PairLock, Trade
from freqtrade.persistence import PairLocks, Trade
from freqtrade.resolvers import StrategyResolver
from freqtrade.strategy.strategy_wrapper import strategy_safe_wrapper
from tests.conftest import log_has, log_has_re
@ -362,13 +362,14 @@ def test__analyze_ticker_internal_skip_analyze(ohlcv_history, mocker, caplog) ->
@pytest.mark.usefixtures("init_persistence")
def test_is_pair_locked(default_conf):
default_conf.update({'strategy': 'DefaultStrategy'})
PairLocks.timeframe = default_conf['timeframe']
strategy = StrategyResolver.load_strategy(default_conf)
# No lock should be present
assert len(PairLock.query.all()) == 0
assert len(PairLocks.get_pair_locks(None)) == 0
pair = 'ETH/BTC'
assert not strategy.is_pair_locked(pair)
strategy.lock_pair(pair, arrow.utcnow().shift(minutes=4).datetime)
strategy.lock_pair(pair, arrow.now(timezone.utc).shift(minutes=4).datetime)
# ETH/BTC locked for 4 minutes
assert strategy.is_pair_locked(pair)
@ -387,7 +388,8 @@ def test_is_pair_locked(default_conf):
pair = 'BTC/USDT'
# Lock until 14:30
lock_time = datetime(2020, 5, 1, 14, 30, 0, tzinfo=timezone.utc)
strategy.lock_pair(pair, lock_time)
# Subtract 2 seconds, as locking rounds up to the next candle.
strategy.lock_pair(pair, lock_time - timedelta(seconds=2))
assert not strategy.is_pair_locked(pair)
# latest candle is from 14:20, lock goes to 14:30

View File

@ -6,7 +6,7 @@ from unittest.mock import MagicMock
import pytest
from freqtrade.commands import Arguments
from freqtrade.commands.cli_options import check_int_positive
from freqtrade.commands.cli_options import check_int_nonzero, check_int_positive
# Parse common command-line-arguments. Used for all tools
@ -249,8 +249,31 @@ def test_check_int_positive() -> None:
with pytest.raises(argparse.ArgumentTypeError):
check_int_positive('0')
with pytest.raises(argparse.ArgumentTypeError):
check_int_positive(0)
with pytest.raises(argparse.ArgumentTypeError):
check_int_positive('3.5')
with pytest.raises(argparse.ArgumentTypeError):
check_int_positive('DeadBeef')
def test_check_int_nonzero() -> None:
assert check_int_nonzero('3') == 3
assert check_int_nonzero('1') == 1
assert check_int_nonzero('100') == 100
assert check_int_nonzero('-2') == -2
with pytest.raises(argparse.ArgumentTypeError):
check_int_nonzero('0')
with pytest.raises(argparse.ArgumentTypeError):
check_int_nonzero(0)
with pytest.raises(argparse.ArgumentTypeError):
check_int_nonzero('3.5')
with pytest.raises(argparse.ArgumentTypeError):
check_int_nonzero('DeadBeef')

View File

@ -15,7 +15,8 @@ from freqtrade.exceptions import (DependencyException, ExchangeError, Insufficie
InvalidOrderException, OperationalException, PricingError,
TemporaryError)
from freqtrade.freqtradebot import FreqtradeBot
from freqtrade.persistence import Order, PairLock, Trade
from freqtrade.persistence import Order, Trade
from freqtrade.persistence.models import PairLock
from freqtrade.rpc import RPCMessageType
from freqtrade.state import RunMode, State
from freqtrade.strategy.interface import SellCheckTuple, SellType

View File

@ -1,6 +1,5 @@
# pragma pylint: disable=missing-docstring, C0103
import logging
from datetime import datetime, timedelta, timezone
from unittest.mock import MagicMock
import arrow
@ -9,7 +8,7 @@ from sqlalchemy import create_engine
from freqtrade import constants
from freqtrade.exceptions import DependencyException, OperationalException
from freqtrade.persistence import Order, PairLock, Trade, clean_dry_run_db, init_db
from freqtrade.persistence import Order, Trade, clean_dry_run_db, init_db
from tests.conftest import create_mock_trades, log_has, log_has_re
@ -817,24 +816,25 @@ def test_to_json(default_conf, fee):
'amount_requested': 123.0,
'stake_amount': 0.001,
'close_profit': None,
'close_profit_pct': None,
'close_profit_abs': None,
'profit_ratio': None,
'profit_pct': None,
'profit_abs': None,
'sell_reason': None,
'sell_order_status': None,
'stop_loss': None,
'stop_loss_abs': None,
'stop_loss_ratio': None,
'stop_loss_pct': None,
'stoploss_order_id': None,
'stoploss_last_update': None,
'stoploss_last_update_timestamp': None,
'initial_stop_loss': None,
'initial_stop_loss_abs': None,
'initial_stop_loss_pct': None,
'initial_stop_loss_ratio': None,
'min_rate': None,
'max_rate': None,
'strategy': None,
'ticker_interval': None,
'timeframe': None,
'exchange': 'bittrex',
}
@ -869,19 +869,21 @@ def test_to_json(default_conf, fee):
'amount': 100.0,
'amount_requested': 101.0,
'stake_amount': 0.001,
'stop_loss': None,
'stop_loss_abs': None,
'stop_loss_pct': None,
'stop_loss_ratio': None,
'stoploss_order_id': None,
'stoploss_last_update': None,
'stoploss_last_update_timestamp': None,
'initial_stop_loss': None,
'initial_stop_loss_abs': None,
'initial_stop_loss_pct': None,
'initial_stop_loss_ratio': None,
'close_profit': None,
'close_profit_pct': None,
'close_profit_abs': None,
'profit_ratio': None,
'profit_pct': None,
'profit_abs': None,
'close_rate_requested': None,
'fee_close': 0.0025,
'fee_close_cost': None,
@ -898,7 +900,6 @@ def test_to_json(default_conf, fee):
'sell_reason': None,
'sell_order_status': None,
'strategy': None,
'ticker_interval': None,
'timeframe': None,
'exchange': 'bittrex',
}
@ -1159,49 +1160,3 @@ def test_select_order(fee):
assert order.ft_order_side == 'stoploss'
order = trades[4].select_order('sell', False)
assert order is None
@pytest.mark.usefixtures("init_persistence")
def test_PairLock(default_conf):
# No lock should be present
assert len(PairLock.query.all()) == 0
pair = 'ETH/BTC'
assert not PairLock.is_pair_locked(pair)
PairLock.lock_pair(pair, arrow.utcnow().shift(minutes=4).datetime)
# ETH/BTC locked for 4 minutes
assert PairLock.is_pair_locked(pair)
# XRP/BTC should not be locked now
pair = 'XRP/BTC'
assert not PairLock.is_pair_locked(pair)
# Unlocking a pair that's not locked should not raise an error
PairLock.unlock_pair(pair)
PairLock.lock_pair(pair, arrow.utcnow().shift(minutes=4).datetime)
assert PairLock.is_pair_locked(pair)
# Get both locks from above
locks = PairLock.get_pair_locks(None)
assert len(locks) == 2
# Unlock original pair
pair = 'ETH/BTC'
PairLock.unlock_pair(pair)
assert not PairLock.is_pair_locked(pair)
pair = 'BTC/USDT'
# Lock until 14:30
lock_time = datetime(2020, 5, 1, 14, 30, 0, tzinfo=timezone.utc)
PairLock.lock_pair(pair, lock_time)
assert not PairLock.is_pair_locked(pair)
assert PairLock.is_pair_locked(pair, lock_time + timedelta(minutes=-10))
assert PairLock.is_pair_locked(pair, lock_time + timedelta(minutes=-50))
# Should not be locked after time expired
assert not PairLock.is_pair_locked(pair, lock_time + timedelta(minutes=10))
locks = PairLock.get_pair_locks(pair, lock_time + timedelta(minutes=-2))
assert len(locks) == 1
assert 'PairLock' in str(locks[0])

View File

@ -51,9 +51,10 @@ def test_init_plotscript(default_conf, mocker, testdatadir):
assert "ohlcv" in ret
assert "trades" in ret
assert "pairs" in ret
assert 'timerange' in ret
default_conf['pairs'] = ["TRX/BTC", "ADA/BTC"]
ret = init_plotscript(default_conf)
ret = init_plotscript(default_conf, 20)
assert "ohlcv" in ret
assert "TRX/BTC" in ret["ohlcv"]
assert "ADA/BTC" in ret["ohlcv"]

View File

@ -74,6 +74,10 @@ def test_sync_wallet_at_boot(mocker, default_conf):
freqtrade.wallets.update()
assert update_mock.call_count == 1
assert freqtrade.wallets.get_free('NOCURRENCY') == 0
assert freqtrade.wallets.get_used('NOCURRENCY') == 0
assert freqtrade.wallets.get_total('NOCURRENCY') == 0
def test_sync_wallet_missing_data(mocker, default_conf):
default_conf['dry_run'] = False