Merge branch 'develop' into interface_ordertimeoutcallback

This commit is contained in:
Matthias 2020-04-19 06:58:44 +02:00
commit 431b244f43
57 changed files with 1241 additions and 487 deletions

1
.gitignore vendored
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@ -6,7 +6,6 @@ user_data/*
!user_data/strategy/sample_strategy.py
!user_data/notebooks
user_data/notebooks/*
!user_data/notebooks/*example.ipynb
freqtrade-plot.html
freqtrade-profit-plot.html

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@ -2,3 +2,4 @@ include LICENSE
include README.md
include config.json.example
recursive-include freqtrade *.py
recursive-include freqtrade/templates/ *.j2 *.ipynb

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@ -144,10 +144,10 @@ It is recommended to use version control to keep track of changes to your strate
### How to use **--strategy**?
This parameter will allow you to load your custom strategy class.
Per default without `--strategy` or `-s` the bot will load the
`DefaultStrategy` included with the bot (`freqtrade/strategy/default_strategy.py`).
To test the bot installation, you can use the `SampleStrategy` installed by the `create-userdir` subcommand (usually `user_data/strategy/sample_strategy.py`).
The bot will search your strategy file within `user_data/strategies` and `freqtrade/strategy`.
The bot will search your strategy file within `user_data/strategies`.
To use other directories, please read the next section about `--strategy-path`.
To load a strategy, simply pass the class name (e.g.: `CustomStrategy`) in this parameter.

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@ -34,13 +34,13 @@ The prevelance for all Options is as follows:
- CLI arguments override any other option
- Configuration files are used in sequence (last file wins), and override Strategy configurations.
- Strategy configurations are only used if they are not set via configuration or via command line arguments. These options are market with [Strategy Override](#parameters-in-the-strategy) in the below table.
- Strategy configurations are only used if they are not set via configuration or via command line arguments. These options are marked with [Strategy Override](#parameters-in-the-strategy) in the below table.
Mandatory parameters are marked as **Required**, which means that they are required to be set in one of the possible ways.
| Parameter | Description |
|------------|-------------|
| `max_open_trades` | **Required.** Number of trades open your bot will have. If -1 then it is ignored (i.e. potentially unlimited open trades). [More information below](#configuring-amount-per-trade).<br> **Datatype:** Positive integer or -1.
| `max_open_trades` | **Required.** Number of open trades your bot is allowed to have. Only one open trade per pair is possible, so the length of your pairlist is another limitation which can apply. If -1 then it is ignored (i.e. potentially unlimited open trades, limited by the pairlist). [More information below](#configuring-amount-per-trade).<br> **Datatype:** Positive integer or -1.
| `stake_currency` | **Required.** Crypto-currency used for trading. [Strategy Override](#parameters-in-the-strategy). <br> **Datatype:** String
| `stake_amount` | **Required.** Amount of crypto-currency your bot will use for each trade. Set it to `"unlimited"` to allow the bot to use all available balance. [More information below](#configuring-amount-per-trade). [Strategy Override](#parameters-in-the-strategy). <br> **Datatype:** Positive float or `"unlimited"`.
| `tradable_balance_ratio` | Ratio of the total account balance the bot is allowed to trade. [More information below](#configuring-amount-per-trade). <br>*Defaults to `0.99` 99%).*<br> **Datatype:** Positive float between `0.1` and `1.0`.

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@ -74,23 +74,13 @@ Should you experience constant errors with Nonce (like `InvalidNonce`), it is be
$ pip3 install web3
```
### Send incomplete candles to the strategy
### Getting latest price / Incomplete candles
Most exchanges return current incomplete candle via their OHLCV/klines API interface.
By default, Freqtrade assumes that incomplete candle is fetched from the exchange and removes the last candle assuming it's the incomplete candle.
Whether your exchange returns incomplete candles or not can be checked using [the helper script](developer.md#Incomplete-candles) from the Contributor documentation.
If the exchange does return incomplete candles and you would like to have incomplete candles in your strategy, you can set the following parameter in the configuration file.
Due to the danger of repainting, Freqtrade does not allow you to use this incomplete candle.
``` json
{
"exchange": {
"_ft_has_params": {"ohlcv_partial_candle": false}
}
}
```
!!! Warning "Danger of repainting"
Changing this parameter makes the strategy responsible to avoid repainting and handle this accordingly. Doing this is therefore not recommended, and should only be performed by experienced users who are fully aware of the impact this setting has.
However, if it is based on the need for the latest price for your strategy - then this requirement can be acquired using the [data provider](strategy-customization.md#possible-options-for-dataprovider) from within the strategy.

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@ -16,6 +16,24 @@ To learn how to get data for the pairs and exchange you're interested in, head o
!!! Bug
Hyperopt can crash when used with only 1 CPU Core as found out in [Issue #1133](https://github.com/freqtrade/freqtrade/issues/1133)
## Install hyperopt dependencies
Since Hyperopt dependencies are not needed to run the bot itself, are heavy, can not be easily built on some platforms (like Raspberry PI), they are not installed by default. Before you run Hyperopt, you need to install the corresponding dependencies, as described in this section below.
!!! Note
Since Hyperopt is a resource intensive process, running it on a Raspberry Pi is not recommended nor supported.
### Docker
The docker-image includes hyperopt dependencies, no further action needed.
### Easy installation script (setup.sh) / Manual installation
```bash
source .env/bin/activate
pip install -r requirements-hyperopt.txt
```
## Prepare Hyperopting
Before we start digging into Hyperopt, we recommend you to take a look at

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@ -23,44 +23,64 @@ The `freqtrade plot-dataframe` subcommand shows an interactive graph with three
Possible arguments:
```
usage: freqtrade plot-dataframe [-h] [-v] [--logfile FILE] [-V] [-c PATH] [-d PATH] [--userdir PATH] [-s NAME]
[--strategy-path PATH] [-p PAIRS [PAIRS ...]] [--indicators1 INDICATORS1 [INDICATORS1 ...]]
[--indicators2 INDICATORS2 [INDICATORS2 ...]] [--plot-limit INT] [--db-url PATH]
[--trade-source {DB,file}] [--export EXPORT] [--export-filename PATH] [--timerange TIMERANGE]
[-i TICKER_INTERVAL]
usage: freqtrade plot-dataframe [-h] [-v] [--logfile FILE] [-V] [-c PATH]
[-d PATH] [--userdir PATH] [-s NAME]
[--strategy-path PATH] [-p PAIRS [PAIRS ...]]
[--indicators1 INDICATORS1 [INDICATORS1 ...]]
[--indicators2 INDICATORS2 [INDICATORS2 ...]]
[--plot-limit INT] [--db-url PATH]
[--trade-source {DB,file}] [--export EXPORT]
[--export-filename PATH]
[--timerange TIMERANGE] [-i TICKER_INTERVAL]
[--no-trades]
optional arguments:
-h, --help show this help message and exit
-p PAIRS [PAIRS ...], --pairs PAIRS [PAIRS ...]
Show profits for only these pairs. Pairs are space-separated.
Show profits for only these pairs. Pairs are space-
separated.
--indicators1 INDICATORS1 [INDICATORS1 ...]
Set indicators from your strategy you want in the first row of the graph. Space-separated list. Example:
Set indicators from your strategy you want in the
first row of the graph. Space-separated list. Example:
`ema3 ema5`. Default: `['sma', 'ema3', 'ema5']`.
--indicators2 INDICATORS2 [INDICATORS2 ...]
Set indicators from your strategy you want in the third row of the graph. Space-separated list. Example:
Set indicators from your strategy you want in the
third row of the graph. Space-separated list. Example:
`fastd fastk`. Default: `['macd', 'macdsignal']`.
--plot-limit INT Specify tick limit for plotting. Notice: too high values cause huge files. Default: 750.
--db-url PATH Override trades database URL, this is useful in custom deployments (default: `sqlite:///tradesv3.sqlite`
for Live Run mode, `sqlite:///tradesv3.dryrun.sqlite` for Dry Run).
--plot-limit INT Specify tick limit for plotting. Notice: too high
values cause huge files. Default: 750.
--db-url PATH Override trades database URL, this is useful in custom
deployments (default: `sqlite:///tradesv3.sqlite` for
Live Run mode, `sqlite:///tradesv3.dryrun.sqlite` for
Dry Run).
--trade-source {DB,file}
Specify the source for trades (Can be DB or file (backtest file)) Default: file
--export EXPORT Export backtest results, argument are: trades. Example: `--export=trades`
Specify the source for trades (Can be DB or file
(backtest file)) Default: file
--export EXPORT Export backtest results, argument are: trades.
Example: `--export=trades`
--export-filename PATH
Save backtest results to the file with this filename. Requires `--export` to be set as well. Example:
`--export-filename=user_data/backtest_results/backtest_today.json`
Save backtest results to the file with this filename.
Requires `--export` to be set as well. Example:
`--export-filename=user_data/backtest_results/backtest
_today.json`
--timerange TIMERANGE
Specify what timerange of data to use.
-i TICKER_INTERVAL, --ticker-interval TICKER_INTERVAL
Specify ticker interval (`1m`, `5m`, `30m`, `1h`, `1d`).
Specify ticker interval (`1m`, `5m`, `30m`, `1h`,
`1d`).
--no-trades Skip using trades from backtesting file and DB.
Common arguments:
-v, --verbose Verbose mode (-vv for more, -vvv to get all messages).
--logfile FILE Log to the file specified. Special values are: 'syslog', 'journald'. See the documentation for more
--logfile FILE Log to the file specified. Special values are:
'syslog', 'journald'. See the documentation for more
details.
-V, --version show program's version number and exit
-c PATH, --config PATH
Specify configuration file (default: `config.json`). Multiple --config options may be used. Can be set to
`-` to read config from stdin.
Specify configuration file (default:
`userdir/config.json` or `config.json` whichever
exists). Multiple --config options may be used. Can be
set to `-` to read config from stdin.
-d PATH, --datadir PATH
Path to directory with historical backtesting data.
--userdir PATH, --user-data-dir PATH
@ -68,9 +88,9 @@ Common arguments:
Strategy arguments:
-s NAME, --strategy NAME
Specify strategy class name which will be used by the bot.
Specify strategy class name which will be used by the
bot.
--strategy-path PATH Specify additional strategy lookup path.
```
Example:

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@ -1,2 +1,2 @@
mkdocs-material==4.6.3
mkdocs-material==5.1.0
mdx_truly_sane_lists==1.2

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@ -24,4 +24,11 @@ if __version__ == 'develop':
# stderr=subprocess.DEVNULL).decode("utf-8").rstrip().strip('"')
except Exception:
# git not available, ignore
pass
try:
# Try Fallback to freqtrade_commit file (created by CI while building docker image)
from pathlib import Path
versionfile = Path('./freqtrade_commit')
if versionfile.is_file():
__version__ = f"docker-{versionfile.read_text()[:8]}"
except Exception:
pass

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@ -59,7 +59,7 @@ ARGS_DOWNLOAD_DATA = ["pairs", "pairs_file", "days", "download_trades", "exchang
ARGS_PLOT_DATAFRAME = ["pairs", "indicators1", "indicators2", "plot_limit",
"db_url", "trade_source", "export", "exportfilename",
"timerange", "ticker_interval"]
"timerange", "ticker_interval", "no_trades"]
ARGS_PLOT_PROFIT = ["pairs", "timerange", "export", "exportfilename", "db_url",
"trade_source", "ticker_interval"]

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@ -413,6 +413,11 @@ AVAILABLE_CLI_OPTIONS = {
metavar='INT',
default=750,
),
"no_trades": Arg(
'--no-trades',
help='Skip using trades from backtesting file and DB.',
action='store_true',
),
"trade_source": Arg(
'--trade-source',
help='Specify the source for trades (Can be DB or file (backtest file)) '

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@ -52,8 +52,8 @@ def start_hyperopt_list(args: Dict[str, Any]) -> None:
if not export_csv:
try:
Hyperopt.print_result_table(config, trials, total_epochs,
not filteroptions['only_best'], print_colorized, 0)
print(Hyperopt.get_result_table(config, trials, total_epochs,
not filteroptions['only_best'], print_colorized, 0))
except KeyboardInterrupt:
print('User interrupted..')

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@ -359,6 +359,9 @@ class Configuration:
self._args_to_config(config, argname='erase',
logstring='Erase detected. Deleting existing data.')
self._args_to_config(config, argname='no_trades',
logstring='Parameter --no-trades detected.')
self._args_to_config(config, argname='timeframes',
logstring='timeframes --timeframes: {}')

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@ -1,13 +1,15 @@
"""
This module contain functions to load the configuration file
"""
import rapidjson
import logging
import re
import sys
from pathlib import Path
from typing import Any, Dict
from freqtrade.exceptions import OperationalException
import rapidjson
from freqtrade.exceptions import OperationalException
logger = logging.getLogger(__name__)
@ -15,6 +17,26 @@ logger = logging.getLogger(__name__)
CONFIG_PARSE_MODE = rapidjson.PM_COMMENTS | rapidjson.PM_TRAILING_COMMAS
def log_config_error_range(path: str, errmsg: str) -> str:
"""
Parses configuration file and prints range around error
"""
if path != '-':
offsetlist = re.findall(r'(?<=Parse\serror\sat\soffset\s)\d+', errmsg)
if offsetlist:
offset = int(offsetlist[0])
text = Path(path).read_text()
# Fetch an offset of 80 characters around the error line
subtext = text[offset-min(80, offset):offset+80]
segments = subtext.split('\n')
if len(segments) > 3:
# Remove first and last lines, to avoid odd truncations
return '\n'.join(segments[1:-1])
else:
return subtext
return ''
def load_config_file(path: str) -> Dict[str, Any]:
"""
Loads a config file from the given path
@ -29,5 +51,12 @@ def load_config_file(path: str) -> Dict[str, Any]:
raise OperationalException(
f'Config file "{path}" not found!'
' Please create a config file or check whether it exists.')
except rapidjson.JSONDecodeError as e:
err_range = log_config_error_range(path, str(e))
raise OperationalException(
f'{e}\n'
f'Please verify the following segment of your configuration:\n{err_range}'
if err_range else 'Please verify your configuration file for syntax errors.'
)
return config

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@ -111,7 +111,7 @@ def load_trades_from_db(db_url: str) -> pd.DataFrame:
t.calc_profit(), t.calc_profit_ratio(),
t.open_rate, t.close_rate, t.amount,
(round((t.close_date.timestamp() - t.open_date.timestamp()) / 60, 2)
if t.close_date else None),
if t.close_date else None),
t.sell_reason,
t.fee_open, t.fee_close,
t.open_rate_requested,
@ -129,7 +129,8 @@ def load_trades_from_db(db_url: str) -> pd.DataFrame:
return trades
def load_trades(source: str, db_url: str, exportfilename: Path) -> pd.DataFrame:
def load_trades(source: str, db_url: str, exportfilename: Path,
no_trades: bool = False) -> pd.DataFrame:
"""
Based on configuration option "trade_source":
* loads data from DB (using `db_url`)
@ -137,21 +138,33 @@ def load_trades(source: str, db_url: str, exportfilename: Path) -> pd.DataFrame:
:param source: "DB" or "file" - specify source to load from
:param db_url: sqlalchemy formatted url to a database
:param exportfilename: Json file generated by backtesting
:param no_trades: Skip using trades, only return backtesting data columns
:return: DataFrame containing trades
"""
if no_trades:
df = pd.DataFrame(columns=BT_DATA_COLUMNS)
return df
if source == "DB":
return load_trades_from_db(db_url)
elif source == "file":
return load_backtest_data(exportfilename)
def extract_trades_of_period(dataframe: pd.DataFrame, trades: pd.DataFrame) -> pd.DataFrame:
def extract_trades_of_period(dataframe: pd.DataFrame, trades: pd.DataFrame,
date_index=False) -> pd.DataFrame:
"""
Compare trades and backtested pair DataFrames to get trades performed on backtested period
:return: the DataFrame of a trades of period
"""
trades = trades.loc[(trades['open_time'] >= dataframe.iloc[0]['date']) &
(trades['close_time'] <= dataframe.iloc[-1]['date'])]
if date_index:
trades_start = dataframe.index[0]
trades_stop = dataframe.index[-1]
else:
trades_start = dataframe.iloc[0]['date']
trades_stop = dataframe.iloc[-1]['date']
trades = trades.loc[(trades['open_time'] >= trades_start) &
(trades['close_time'] <= trades_stop)]
return trades
@ -207,13 +220,15 @@ def calculate_max_drawdown(trades: pd.DataFrame, *, date_col: str = 'close_time'
"""
if len(trades) == 0:
raise ValueError("Trade dataframe empty.")
profit_results = trades.sort_values(date_col)
profit_results = trades.sort_values(date_col).reset_index(drop=True)
max_drawdown_df = pd.DataFrame()
max_drawdown_df['cumulative'] = profit_results[value_col].cumsum()
max_drawdown_df['high_value'] = max_drawdown_df['cumulative'].cummax()
max_drawdown_df['drawdown'] = max_drawdown_df['cumulative'] - max_drawdown_df['high_value']
high_date = profit_results.loc[max_drawdown_df['high_value'].idxmax(), date_col]
low_date = profit_results.loc[max_drawdown_df['drawdown'].idxmin(), date_col]
idxmin = max_drawdown_df['drawdown'].idxmin()
if idxmin == 0:
raise ValueError("No losing trade, therefore no drawdown.")
high_date = profit_results.loc[max_drawdown_df.iloc[:idxmin]['high_value'].idxmax(), date_col]
low_date = profit_results.loc[idxmin, date_col]
return abs(min(max_drawdown_df['drawdown'])), high_date, low_date

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@ -8,10 +8,10 @@ import numpy as np
import utils_find_1st as utf1st
from pandas import DataFrame
from freqtrade import constants
from freqtrade.configuration import TimeRange
from freqtrade.data import history
from freqtrade.constants import UNLIMITED_STAKE_AMOUNT
from freqtrade.exceptions import OperationalException
from freqtrade.data.history import get_timerange, load_data, refresh_data
from freqtrade.strategy.interface import SellType
logger = logging.getLogger(__name__)
@ -54,7 +54,7 @@ class Edge:
if self.config['max_open_trades'] != float('inf'):
logger.critical('max_open_trades should be -1 in config !')
if self.config['stake_amount'] != constants.UNLIMITED_STAKE_AMOUNT:
if self.config['stake_amount'] != UNLIMITED_STAKE_AMOUNT:
raise OperationalException('Edge works only with unlimited stake amount')
# Deprecated capital_available_percentage. Will use tradable_balance_ratio in the future.
@ -96,7 +96,7 @@ class Edge:
logger.info('Using local backtesting data (using whitelist in given config) ...')
if self._refresh_pairs:
history.refresh_data(
refresh_data(
datadir=self.config['datadir'],
pairs=pairs,
exchange=self.exchange,
@ -104,7 +104,7 @@ class Edge:
timerange=self._timerange,
)
data = history.load_data(
data = load_data(
datadir=self.config['datadir'],
pairs=pairs,
timeframe=self.strategy.ticker_interval,
@ -122,7 +122,7 @@ class Edge:
preprocessed = self.strategy.ohlcvdata_to_dataframe(data)
# Print timeframe
min_date, max_date = history.get_timerange(preprocessed)
min_date, max_date = get_timerange(preprocessed)
logger.info(
'Measuring data from %s up to %s (%s days) ...',
min_date.isoformat(),

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@ -452,6 +452,17 @@ class Exchange:
price = ceil(big_price) / pow(10, symbol_prec)
return price
def price_get_one_pip(self, pair: str, price: float) -> float:
"""
Get's the "1 pip" value for this pair.
Used in PriceFilter to calculate the 1pip movements.
"""
precision = self.markets[pair]['precision']['price']
if self.precisionMode == TICK_SIZE:
return precision
else:
return 1 / pow(10, precision)
def dry_run_order(self, pair: str, ordertype: str, side: str, amount: float,
rate: float, params: Dict = {}) -> Dict[str, Any]:
order_id = f'dry_run_{side}_{randint(0, 10**6)}'
@ -902,6 +913,14 @@ class Exchange:
self._async_get_trade_history(pair=pair, since=since,
until=until, from_id=from_id))
def check_order_canceled_empty(self, order: Dict) -> bool:
"""
Verify if an order has been cancelled without being partially filled
:param order: Order dict as returned from get_order()
:return: True if order has been cancelled without being filled, False otherwise.
"""
return order.get('status') in ('closed', 'canceled') and order.get('filled') == 0.0
@retrier
def cancel_order(self, order_id: str, pair: str) -> Dict:
if self._config['dry_run']:
@ -918,6 +937,37 @@ class Exchange:
except ccxt.BaseError as e:
raise OperationalException(e) from e
def is_cancel_order_result_suitable(self, corder) -> bool:
if not isinstance(corder, dict):
return False
required = ('fee', 'status', 'amount')
return all(k in corder for k in required)
def cancel_order_with_result(self, order_id: str, pair: str, amount: float) -> Dict:
"""
Cancel order returning a result.
Creates a fake result if cancel order returns a non-usable result
and get_order does not work (certain exchanges don't return cancelled orders)
:param order_id: Orderid to cancel
:param pair: Pair corresponding to order_id
:param amount: Amount to use for fake response
:return: Result from either cancel_order if usable, or fetch_order
"""
try:
corder = self.cancel_order(order_id, pair)
if self.is_cancel_order_result_suitable(corder):
return corder
except InvalidOrderException:
logger.warning(f"Could not cancel order {order_id}.")
try:
order = self.get_order(order_id, pair)
except InvalidOrderException:
logger.warning(f"Could not fetch cancelled order {order_id}.")
order = {'fee': {}, 'status': 'canceled', 'amount': amount, 'info': {}}
return order
@retrier
def get_order(self, order_id: str, pair: str) -> Dict:
if self._config['dry_run']:

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@ -20,6 +20,7 @@ from freqtrade.data.dataprovider import DataProvider
from freqtrade.edge import Edge
from freqtrade.exceptions import DependencyException, InvalidOrderException
from freqtrade.exchange import timeframe_to_minutes, timeframe_to_next_date
from freqtrade.misc import safe_value_fallback
from freqtrade.pairlist.pairlistmanager import PairListManager
from freqtrade.persistence import Trade
from freqtrade.resolvers import ExchangeResolver, StrategyResolver
@ -144,6 +145,10 @@ class FreqtradeBot:
self.dataprovider.refresh(self._create_pair_whitelist(self.active_pair_whitelist),
self.strategy.informative_pairs())
with self._sell_lock:
# Check and handle any timed out open orders
self.check_handle_timedout()
# Protect from collisions with forcesell.
# Without this, freqtrade my try to recreate stoploss_on_exchange orders
# while selling is in process, since telegram messages arrive in an different thread.
@ -155,8 +160,6 @@ class FreqtradeBot:
if self.get_free_open_trades():
self.enter_positions()
# Check and handle any timed out open orders
self.check_handle_timedout()
Trade.session.flush()
def _refresh_whitelist(self, trades: List[Trade] = []) -> List[str]:
@ -395,16 +398,18 @@ class FreqtradeBot:
logger.info(f"Pair {pair} is currently locked.")
return False
# get_free_open_trades is checked before create_trade is called
# but it is still used here to prevent opening too many trades within one iteration
if not self.get_free_open_trades():
logger.debug(f"Can't open a new trade for {pair}: max number of trades is reached.")
return False
# running get_signal on historical data fetched
(buy, sell) = self.strategy.get_signal(
pair, self.strategy.ticker_interval,
self.dataprovider.ohlcv(pair, self.strategy.ticker_interval))
if buy and not sell:
if not self.get_free_open_trades():
logger.debug("Can't open a new trade: max number of trades is reached.")
return False
stake_amount = self.get_trade_stake_amount(pair)
if not stake_amount:
logger.debug(f"Stake amount is 0, ignoring possible trade for {pair}.")
@ -599,7 +604,6 @@ class FreqtradeBot:
trades_closed = 0
for trade in trades:
try:
self.update_trade_state(trade)
if (self.strategy.order_types.get('stoploss_on_exchange') and
self.handle_stoploss_on_exchange(trade)):
@ -859,19 +863,13 @@ class FreqtradeBot:
continue
order = self.exchange.get_order(trade.open_order_id, trade.pair)
except (RequestException, DependencyException, InvalidOrderException):
logger.info(
'Cannot query order for %s due to %s',
trade,
traceback.format_exc())
logger.info('Cannot query order for %s due to %s', trade, traceback.format_exc())
continue
# Check if trade is still actually open
if float(order.get('remaining', 0.0)) == 0.0:
self.wallets.update()
continue
trade_state_update = self.update_trade_state(trade, order)
if (order['side'] == 'buy' and (
order['status'] == 'canceled'
trade_state_update
or self._check_timed_out('buy', order)
or strategy_safe_wrapper(self.strategy.check_buy_timeout,
default_retval=False)(pair=trade.pair,
@ -884,16 +882,16 @@ class FreqtradeBot:
self._notify_buy_cancel(trade, order_type)
elif (order['side'] == 'sell' and (
order['status'] == 'canceled'
trade_state_update
or self._check_timed_out('sell', order)
or strategy_safe_wrapper(self.strategy.check_sell_timeout,
default_retval=False)(pair=trade.pair,
trade=trade,
order=order))):
self.handle_timedout_limit_sell(trade, order)
reason = self.handle_timedout_limit_sell(trade, order)
self.wallets.update()
order_type = self.strategy.order_types['sell']
self._notify_sell_cancel(trade, order_type)
self._notify_sell_cancel(trade, order_type, reason)
def handle_timedout_limit_buy(self, trade: Trade, order: Dict) -> bool:
"""
@ -902,15 +900,17 @@ class FreqtradeBot:
"""
if order['status'] != 'canceled':
reason = "cancelled due to timeout"
corder = self.exchange.cancel_order(trade.open_order_id, trade.pair)
logger.info('Buy order %s for %s.', reason, trade)
corder = self.exchange.cancel_order_with_result(trade.open_order_id, trade.pair,
trade.amount)
else:
# Order was cancelled already, so we can reuse the existing dict
corder = order
reason = "cancelled on exchange"
logger.info('Buy order %s for %s.', reason, trade)
if corder.get('remaining', order['remaining']) == order['amount']:
logger.info('Buy order %s for %s.', reason, trade)
if safe_value_fallback(corder, order, 'remaining', 'remaining') == order['amount']:
logger.info('Buy order fully cancelled. Removing %s from database.', trade)
# if trade is not partially completed, just delete the trade
Trade.session.delete(trade)
Trade.session.flush()
@ -921,19 +921,10 @@ class FreqtradeBot:
# cancel_order may not contain the full order dict, so we need to fallback
# to the order dict aquired before cancelling.
# we need to fall back to the values from order if corder does not contain these keys.
trade.amount = order['amount'] - corder.get('remaining', order['remaining'])
trade.amount = order['amount'] - safe_value_fallback(corder, order,
'remaining', 'remaining')
trade.stake_amount = trade.amount * trade.open_rate
# verify if fees were taken from amount to avoid problems during selling
try:
new_amount = self.get_real_amount(trade, corder if 'fee' in corder else order,
trade.amount)
if not isclose(order['amount'], new_amount, abs_tol=constants.MATH_CLOSE_PREC):
trade.amount = new_amount
# Fee was applied, so set to 0
trade.fee_open = 0
trade.recalc_open_trade_price()
except DependencyException as e:
logger.warning("Could not update trade amount: %s", e)
self.update_trade_state(trade, corder, trade.amount)
trade.open_order_id = None
logger.info('Partial buy order timeout for %s.', trade)
@ -943,14 +934,14 @@ class FreqtradeBot:
})
return False
def handle_timedout_limit_sell(self, trade: Trade, order: Dict) -> bool:
def handle_timedout_limit_sell(self, trade: Trade, order: Dict) -> str:
"""
Sell timeout - cancel order and update trade
:return: True if order was fully cancelled
:return: Reason for cancel
"""
# if trade is not partially completed, just cancel the trade
if order['remaining'] == order['amount']:
if order["status"] != "canceled":
if order['remaining'] == order['amount'] or order.get('filled') == 0.0:
if not self.exchange.check_order_canceled_empty(order):
reason = "cancelled due to timeout"
# if trade is not partially completed, just delete the trade
self.exchange.cancel_order(trade.open_order_id, trade.pair)
@ -960,15 +951,17 @@ class FreqtradeBot:
logger.info('Sell order %s for %s.', reason, trade)
trade.close_rate = None
trade.close_rate_requested = None
trade.close_profit = None
trade.close_profit_abs = None
trade.close_date = None
trade.is_open = True
trade.open_order_id = None
return True
return reason
# TODO: figure out how to handle partially complete sell orders
return False
return 'partially filled - keeping order open'
def _safe_sell_amount(self, pair: str, amount: float) -> float:
"""
@ -1087,7 +1080,7 @@ class FreqtradeBot:
# Send the message
self.rpc.send_msg(msg)
def _notify_sell_cancel(self, trade: Trade, order_type: str) -> None:
def _notify_sell_cancel(self, trade: Trade, order_type: str, reason: str) -> None:
"""
Sends rpc notification when a sell cancel occured.
"""
@ -1114,6 +1107,7 @@ class FreqtradeBot:
'close_date': trade.close_date,
'stake_currency': self.config['stake_currency'],
'fiat_currency': self.config.get('fiat_display_currency', None),
'reason': reason,
}
if 'fiat_display_currency' in self.config:
@ -1128,9 +1122,12 @@ class FreqtradeBot:
# Common update trade state methods
#
def update_trade_state(self, trade: Trade, action_order: dict = None) -> None:
def update_trade_state(self, trade: Trade, action_order: dict = None,
order_amount: float = None) -> bool:
"""
Checks trades with open orders and updates the amount if necessary
Handles closing both buy and sell orders.
:return: True if order has been cancelled without being filled partially, False otherwise
"""
# Get order details for actual price per unit
if trade.open_order_id:
@ -1140,25 +1137,31 @@ class FreqtradeBot:
order = action_order or self.exchange.get_order(trade.open_order_id, trade.pair)
except InvalidOrderException as exception:
logger.warning('Unable to fetch order %s: %s', trade.open_order_id, exception)
return
return False
# Try update amount (binance-fix)
try:
new_amount = self.get_real_amount(trade, order)
new_amount = self.get_real_amount(trade, order, order_amount)
if not isclose(order['amount'], new_amount, abs_tol=constants.MATH_CLOSE_PREC):
order['amount'] = new_amount
order.pop('filled', None)
# Fee was applied, so set to 0
trade.fee_open = 0
trade.recalc_open_trade_price()
except DependencyException as exception:
logger.warning("Could not update trade amount: %s", exception)
if self.exchange.check_order_canceled_empty(order):
# Trade has been cancelled on exchange
# Handling of this will happen in check_handle_timeout.
return True
trade.update(order)
# Updating wallets when order is closed
if not trade.is_open:
self.wallets.update()
return False
def get_real_amount(self, trade: Trade, order: Dict, order_amount: float = None) -> float:
"""
Get real amount for the trade

View File

@ -18,13 +18,13 @@ def _set_loggers(verbosity: int = 0) -> None:
"""
logging.getLogger('requests').setLevel(
logging.INFO if verbosity <= 1 else logging.DEBUG
logging.INFO if verbosity <= 1 else logging.DEBUG
)
logging.getLogger("urllib3").setLevel(
logging.INFO if verbosity <= 1 else logging.DEBUG
logging.INFO if verbosity <= 1 else logging.DEBUG
)
logging.getLogger('ccxt.base.exchange').setLevel(
logging.INFO if verbosity <= 2 else logging.DEBUG
logging.INFO if verbosity <= 2 else logging.DEBUG
)
logging.getLogger('telegram').setLevel(logging.INFO)

View File

@ -134,6 +134,21 @@ def round_dict(d, n):
return {k: (round(v, n) if isinstance(v, float) else v) for k, v in d.items()}
def safe_value_fallback(dict1: dict, dict2: dict, key1: str, key2: str, default_value=None):
"""
Search a value in dict1, return this if it's not None.
Fall back to dict2 - return key2 from dict2 if it's not None.
Else falls back to None.
"""
if key1 in dict1 and dict1[key1] is not None:
return dict1[key1]
else:
if key2 in dict2 and dict2[key2] is not None:
return dict2[key2]
return default_value
def plural(num: float, singular: str, plural: str = None) -> str:
return singular if (num == 1 or num == -1) else plural or singular + 's'

View File

@ -6,8 +6,7 @@ This module contains the backtesting logic
import logging
from copy import deepcopy
from datetime import datetime, timedelta
from pathlib import Path
from typing import Any, Dict, List, NamedTuple, Optional
from typing import Any, Dict, List, NamedTuple, Optional, Tuple
import arrow
from pandas import DataFrame
@ -19,10 +18,8 @@ from freqtrade.data.converter import trim_dataframe
from freqtrade.data.dataprovider import DataProvider
from freqtrade.exceptions import OperationalException
from freqtrade.exchange import timeframe_to_minutes, timeframe_to_seconds
from freqtrade.misc import file_dump_json
from freqtrade.optimize.optimize_reports import (
generate_text_table, generate_text_table_sell_reason,
generate_text_table_strategy)
from freqtrade.optimize.optimize_reports import (show_backtest_results,
store_backtest_result)
from freqtrade.persistence import Trade
from freqtrade.resolvers import ExchangeResolver, StrategyResolver
from freqtrade.state import RunMode
@ -108,7 +105,7 @@ class Backtesting:
# And the regular "stoploss" function would not apply to that case
self.strategy.order_types['stoploss_on_exchange'] = False
def load_bt_data(self):
def load_bt_data(self) -> Tuple[Dict[str, DataFrame], TimeRange]:
timerange = TimeRange.parse_timerange(None if self.config.get(
'timerange') is None else str(self.config.get('timerange')))
@ -134,23 +131,6 @@ class Backtesting:
return data, timerange
def _store_backtest_result(self, recordfilename: Path, results: DataFrame,
strategyname: Optional[str] = None) -> None:
records = [(t.pair, t.profit_percent, t.open_time.timestamp(),
t.close_time.timestamp(), t.open_index - 1, t.trade_duration,
t.open_rate, t.close_rate, t.open_at_end, t.sell_reason.value)
for index, t in results.iterrows()]
if records:
if strategyname:
# Inject strategyname to filename
recordfilename = Path.joinpath(
recordfilename.parent,
f'{recordfilename.stem}-{strategyname}').with_suffix(recordfilename.suffix)
logger.info(f'Dumping backtest results to {recordfilename}')
file_dump_json(recordfilename, records)
def _get_ohlcv_as_lists(self, processed: Dict) -> Dict[str, DataFrame]:
"""
Helper function to convert a processed dataframes into lists for performance reasons.
@ -169,8 +149,8 @@ class Backtesting:
# To avoid using data from future, we use buy/sell signals shifted
# from the previous candle
df_analyzed.loc[:, 'buy'] = df_analyzed['buy'].shift(1)
df_analyzed.loc[:, 'sell'] = df_analyzed['sell'].shift(1)
df_analyzed.loc[:, 'buy'] = df_analyzed.loc[:, 'buy'].shift(1)
df_analyzed.loc[:, 'sell'] = df_analyzed.loc[:, 'sell'].shift(1)
df_analyzed.drop(df_analyzed.head(1).index, inplace=True)
@ -418,44 +398,7 @@ class Backtesting:
position_stacking=position_stacking,
)
for strategy, results in all_results.items():
if self.config.get('export', False):
self._store_backtest_result(self.config['exportfilename'], results,
strategy if len(self.strategylist) > 1 else None)
print(f"Result for strategy {strategy}")
table = generate_text_table(data, stake_currency=self.config['stake_currency'],
max_open_trades=self.config['max_open_trades'],
results=results)
if isinstance(table, str):
print(' BACKTESTING REPORT '.center(len(table.splitlines()[0]), '='))
print(table)
table = generate_text_table_sell_reason(data,
stake_currency=self.config['stake_currency'],
max_open_trades=self.config['max_open_trades'],
results=results)
if isinstance(table, str):
print(' SELL REASON STATS '.center(len(table.splitlines()[0]), '='))
print(table)
table = generate_text_table(data,
stake_currency=self.config['stake_currency'],
max_open_trades=self.config['max_open_trades'],
results=results.loc[results.open_at_end], skip_nan=True)
if isinstance(table, str):
print(' LEFT OPEN TRADES REPORT '.center(len(table.splitlines()[0]), '='))
print(table)
if isinstance(table, str):
print('=' * len(table.splitlines()[0]))
print()
if len(all_results) > 1:
# Print Strategy summary table
table = generate_text_table_strategy(self.config['stake_currency'],
self.config['max_open_trades'],
all_results=all_results)
print(' STRATEGY SUMMARY '.center(len(table.splitlines()[0]), '='))
print(table)
print('=' * len(table.splitlines()[0]))
print('\nFor more details, please look at the detail tables above')
if self.config.get('export', False):
store_backtest_result(self.config['exportfilename'], all_results)
# Show backtest results
show_backtest_results(self.config, data, all_results)

View File

@ -7,7 +7,6 @@ This module contains the hyperopt logic
import locale
import logging
import random
import sys
import warnings
from math import ceil
from collections import OrderedDict
@ -18,10 +17,10 @@ from typing import Any, Dict, List, Optional
import rapidjson
from colorama import Fore, Style
from colorama import init as colorama_init
from joblib import (Parallel, cpu_count, delayed, dump, load,
wrap_non_picklable_objects)
from pandas import DataFrame, json_normalize, isna
import progressbar
import tabulate
from os import path
import io
@ -43,7 +42,8 @@ with warnings.catch_warnings():
from skopt import Optimizer
from skopt.space import Dimension
progressbar.streams.wrap_stderr()
progressbar.streams.wrap_stdout()
logger = logging.getLogger(__name__)
@ -266,21 +266,33 @@ class Hyperopt:
Log results if it is better than any previous evaluation
"""
is_best = results['is_best']
if not self.print_all:
# Print '\n' after each 100th epoch to separate dots from the log messages.
# Otherwise output is messy on a terminal.
print('.', end='' if results['current_epoch'] % 100 != 0 else None) # type: ignore
sys.stdout.flush()
if self.print_all or is_best:
if not self.print_all:
# Separate the results explanation string from dots
print("\n")
self.print_result_table(self.config, results, self.total_epochs,
self.print_all, self.print_colorized,
self.hyperopt_table_header)
print(
self.get_result_table(
self.config, results, self.total_epochs,
self.print_all, self.print_colorized,
self.hyperopt_table_header
)
)
self.hyperopt_table_header = 2
def get_results(self, results) -> str:
"""
Log results if it is better than any previous evaluation
"""
output = ''
is_best = results['is_best']
if self.print_all or is_best:
output = self.get_result_table(
self.config, results, self.total_epochs,
self.print_all, self.print_colorized,
self.hyperopt_table_header
)
self.hyperopt_table_header = 2
return output
@staticmethod
def print_results_explanation(results, total_epochs, highlight_best: bool,
print_colorized: bool) -> None:
@ -304,13 +316,13 @@ class Hyperopt:
f"Objective: {results['loss']:.5f}")
@staticmethod
def print_result_table(config: dict, results: list, total_epochs: int, highlight_best: bool,
print_colorized: bool, remove_header: int) -> None:
def get_result_table(config: dict, results: list, total_epochs: int, highlight_best: bool,
print_colorized: bool, remove_header: int) -> str:
"""
Log result table
"""
if not results:
return
return ''
tabulate.PRESERVE_WHITESPACE = True
@ -381,7 +393,7 @@ class Hyperopt:
trials.to_dict(orient='list'), tablefmt='psql',
headers='keys', stralign="right"
)
print(table)
return table
@staticmethod
def export_csv_file(config: dict, results: list, total_epochs: int, highlight_best: bool,
@ -653,48 +665,75 @@ class Hyperopt:
self.dimensions: List[Dimension] = self.hyperopt_space()
self.opt = self.get_optimizer(self.dimensions, config_jobs)
if self.print_colorized:
colorama_init(autoreset=True)
try:
with Parallel(n_jobs=config_jobs) as parallel:
jobs = parallel._effective_n_jobs()
logger.info(f'Effective number of parallel workers used: {jobs}')
EVALS = ceil(self.total_epochs / jobs)
for i in range(EVALS):
# Correct the number of epochs to be processed for the last
# iteration (should not exceed self.total_epochs in total)
n_rest = (i + 1) * jobs - self.total_epochs
current_jobs = jobs - n_rest if n_rest > 0 else jobs
asked = self.opt.ask(n_points=current_jobs)
f_val = self.run_optimizer_parallel(parallel, asked, i)
self.opt.tell(asked, [v['loss'] for v in f_val])
self.fix_optimizer_models_list()
# Define progressbar
if self.print_colorized:
widgets = [
' [Epoch ', progressbar.Counter(), ' of ', str(self.total_epochs),
' (', progressbar.Percentage(), ')] ',
progressbar.Bar(marker=progressbar.AnimatedMarker(
fill='\N{FULL BLOCK}',
fill_wrap=Fore.GREEN + '{}' + Fore.RESET,
marker_wrap=Style.BRIGHT + '{}' + Style.RESET_ALL,
)),
' [', progressbar.ETA(), ', ', progressbar.Timer(), ']',
]
else:
widgets = [
' [Epoch ', progressbar.Counter(), ' of ', str(self.total_epochs),
' (', progressbar.Percentage(), ')] ',
progressbar.Bar(marker=progressbar.AnimatedMarker(
fill='\N{FULL BLOCK}',
)),
' [', progressbar.ETA(), ', ', progressbar.Timer(), ']',
]
with progressbar.ProgressBar(
maxval=self.total_epochs, redirect_stdout=False, redirect_stderr=False,
widgets=widgets
) as pbar:
EVALS = ceil(self.total_epochs / jobs)
for i in range(EVALS):
# Correct the number of epochs to be processed for the last
# iteration (should not exceed self.total_epochs in total)
n_rest = (i + 1) * jobs - self.total_epochs
current_jobs = jobs - n_rest if n_rest > 0 else jobs
for j, val in enumerate(f_val):
# Use human-friendly indexes here (starting from 1)
current = i * jobs + j + 1
val['current_epoch'] = current
val['is_initial_point'] = current <= INITIAL_POINTS
logger.debug(f"Optimizer epoch evaluated: {val}")
asked = self.opt.ask(n_points=current_jobs)
f_val = self.run_optimizer_parallel(parallel, asked, i)
self.opt.tell(asked, [v['loss'] for v in f_val])
self.fix_optimizer_models_list()
is_best = self.is_best_loss(val, self.current_best_loss)
# This value is assigned here and not in the optimization method
# to keep proper order in the list of results. That's because
# evaluations can take different time. Here they are aligned in the
# order they will be shown to the user.
val['is_best'] = is_best
# Calculate progressbar outputs
for j, val in enumerate(f_val):
# Use human-friendly indexes here (starting from 1)
current = i * jobs + j + 1
val['current_epoch'] = current
val['is_initial_point'] = current <= INITIAL_POINTS
self.print_results(val)
logger.debug(f"Optimizer epoch evaluated: {val}")
is_best = self.is_best_loss(val, self.current_best_loss)
# This value is assigned here and not in the optimization method
# to keep proper order in the list of results. That's because
# evaluations can take different time. Here they are aligned in the
# order they will be shown to the user.
val['is_best'] = is_best
self.print_results(val)
if is_best:
self.current_best_loss = val['loss']
self.trials.append(val)
# Save results after each best epoch and every 100 epochs
if is_best or current % 100 == 0:
self.save_trials()
pbar.update(current)
if is_best:
self.current_best_loss = val['loss']
self.trials.append(val)
# Save results after each best epoch and every 100 epochs
if is_best or current % 100 == 0:
self.save_trials()
except KeyboardInterrupt:
print('User interrupted..')

View File

@ -1,9 +1,38 @@
import logging
from datetime import timedelta
from pathlib import Path
from typing import Dict
from pandas import DataFrame
from tabulate import tabulate
from freqtrade.misc import file_dump_json
logger = logging.getLogger(__name__)
def store_backtest_result(recordfilename: Path, all_results: Dict[str, DataFrame]) -> None:
"""
Stores backtest results to file (one file per strategy)
:param recordfilename: Destination filename
:param all_results: Dict of Dataframes, one results dataframe per strategy
"""
for strategy, results in all_results.items():
records = [(t.pair, t.profit_percent, t.open_time.timestamp(),
t.close_time.timestamp(), t.open_index - 1, t.trade_duration,
t.open_rate, t.close_rate, t.open_at_end, t.sell_reason.value)
for index, t in results.iterrows()]
if records:
filename = recordfilename
if len(all_results) > 1:
# Inject strategy to filename
filename = Path.joinpath(
recordfilename.parent,
f'{recordfilename.stem}-{strategy}').with_suffix(recordfilename.suffix)
logger.info(f'Dumping backtest results to {filename}')
file_dump_json(filename, records)
def generate_text_table(data: Dict[str, Dict], stake_currency: str, max_open_trades: int,
results: DataFrame, skip_nan: bool = False) -> str:
@ -69,12 +98,12 @@ def generate_text_table(data: Dict[str, Dict], stake_currency: str, max_open_tra
floatfmt=floatfmt, tablefmt="orgtbl", stralign="right") # type: ignore
def generate_text_table_sell_reason(
data: Dict[str, Dict], stake_currency: str, max_open_trades: int, results: DataFrame
) -> str:
def generate_text_table_sell_reason(stake_currency: str, max_open_trades: int,
results: DataFrame) -> str:
"""
Generate small table outlining Backtest results
:param data: Dict of <pair: dataframe> containing data that was used during backtesting.
:param stake_currency: Stakecurrency used
:param max_open_trades: Max_open_trades parameter
:param results: Dataframe containing the backtest results
:return: pretty printed table with tabulate as string
"""
@ -173,3 +202,43 @@ def generate_edge_table(results: dict) -> str:
# Ignore type as floatfmt does allow tuples but mypy does not know that
return tabulate(tabular_data, headers=headers,
floatfmt=floatfmt, tablefmt="orgtbl", stralign="right") # type: ignore
def show_backtest_results(config: Dict, btdata: Dict[str, DataFrame],
all_results: Dict[str, DataFrame]):
for strategy, results in all_results.items():
print(f"Result for strategy {strategy}")
table = generate_text_table(btdata, stake_currency=config['stake_currency'],
max_open_trades=config['max_open_trades'],
results=results)
if isinstance(table, str):
print(' BACKTESTING REPORT '.center(len(table.splitlines()[0]), '='))
print(table)
table = generate_text_table_sell_reason(stake_currency=config['stake_currency'],
max_open_trades=config['max_open_trades'],
results=results)
if isinstance(table, str):
print(' SELL REASON STATS '.center(len(table.splitlines()[0]), '='))
print(table)
table = generate_text_table(btdata,
stake_currency=config['stake_currency'],
max_open_trades=config['max_open_trades'],
results=results.loc[results.open_at_end], skip_nan=True)
if isinstance(table, str):
print(' LEFT OPEN TRADES REPORT '.center(len(table.splitlines()[0]), '='))
print(table)
if isinstance(table, str):
print('=' * len(table.splitlines()[0]))
print()
if len(all_results) > 1:
# Print Strategy summary table
table = generate_text_table_strategy(config['stake_currency'],
config['max_open_trades'],
all_results=all_results)
print(' STRATEGY SUMMARY '.center(len(table.splitlines()[0]), '='))
print(table)
print('=' * len(table.splitlines()[0]))
print('\nFor more details, please look at the detail tables above')

View File

@ -9,6 +9,8 @@ from abc import ABC, abstractmethod, abstractproperty
from copy import deepcopy
from typing import Any, Dict, List
from cachetools import TTLCache, cached
from freqtrade.exchange import market_is_active
logger = logging.getLogger(__name__)
@ -31,6 +33,9 @@ class IPairList(ABC):
self._config = config
self._pairlistconfig = pairlistconfig
self._pairlist_pos = pairlist_pos
self.refresh_period = self._pairlistconfig.get('refresh_period', 1800)
self._last_refresh = 0
self._log_cache = TTLCache(maxsize=1024, ttl=self.refresh_period)
@property
def name(self) -> str:
@ -40,6 +45,24 @@ class IPairList(ABC):
"""
return self.__class__.__name__
def log_on_refresh(self, logmethod, message: str) -> None:
"""
Logs message - not more often than "refresh_period" to avoid log spamming
Logs the log-message as debug as well to simplify debugging.
:param logmethod: Function that'll be called. Most likely `logger.info`.
:param message: String containing the message to be sent to the function.
:return: None.
"""
@cached(cache=self._log_cache)
def _log_on_refresh(message: str):
logmethod(message)
# Log as debug first
logger.debug(message)
# Call hidden function.
_log_on_refresh(message)
@abstractproperty
def needstickers(self) -> bool:
"""

View File

@ -39,8 +39,9 @@ class PrecisionFilter(IPairList):
stop_gap_price = self._exchange.price_to_precision(ticker["symbol"], stop_price * 0.99)
logger.debug(f"{ticker['symbol']} - {sp} : {stop_gap_price}")
if sp <= stop_gap_price:
logger.info(f"Removed {ticker['symbol']} from whitelist, "
f"because stop price {sp} would be <= stop limit {stop_gap_price}")
self.log_on_refresh(logger.info,
f"Removed {ticker['symbol']} from whitelist, "
f"because stop price {sp} would be <= stop limit {stop_gap_price}")
return False
return True

View File

@ -35,16 +35,14 @@ class PriceFilter(IPairList):
"""
Check if if one price-step (pip) is > than a certain barrier.
:param ticker: ticker dict as returned from ccxt.load_markets()
:param precision: Precision
:return: True if the pair can stay, false if it should be removed
"""
precision = self._exchange.markets[ticker['symbol']]['precision']['price']
compare = ticker['last'] + 1 / pow(10, precision)
compare = ticker['last'] + self._exchange.price_get_one_pip(ticker['symbol'],
ticker['last'])
changeperc = (compare - ticker['last']) / ticker['last']
if changeperc > self._low_price_ratio:
logger.info(f"Removed {ticker['symbol']} from whitelist, "
f"because 1 unit is {changeperc * 100:.3f}%")
self.log_on_refresh(logger.info, f"Removed {ticker['symbol']} from whitelist, "
f"because 1 unit is {changeperc * 100:.3f}%")
return False
return True

View File

@ -49,9 +49,9 @@ class SpreadFilter(IPairList):
if 'bid' in ticker and 'ask' in ticker:
spread = 1 - ticker['bid'] / ticker['ask']
if not ticker or spread > self._max_spread_ratio:
logger.info(f"Removed {ticker['symbol']} from whitelist, "
f"because spread {spread * 100:.3f}% >"
f"{self._max_spread_ratio * 100}%")
self.log_on_refresh(logger.info, f"Removed {ticker['symbol']} from whitelist, "
f"because spread {spread * 100:.3f}% >"
f"{self._max_spread_ratio * 100}%")
pairlist.remove(p)
else:
pairlist.remove(p)

View File

@ -39,7 +39,6 @@ class VolumePairList(IPairList):
if not self._validate_keys(self._sort_key):
raise OperationalException(
f'key {self._sort_key} not in {SORT_VALUES}')
self._last_refresh = 0
@property
def needstickers(self) -> bool:
@ -68,16 +67,18 @@ class VolumePairList(IPairList):
:return: new whitelist
"""
# Generate dynamic whitelist
if self._last_refresh + self.refresh_period < datetime.now().timestamp():
# Must always run if this pairlist is not the first in the list.
if (self._pairlist_pos != 0 or
(self._last_refresh + self.refresh_period < datetime.now().timestamp())):
self._last_refresh = int(datetime.now().timestamp())
return self._gen_pair_whitelist(pairlist,
tickers,
self._config['stake_currency'],
self._sort_key,
self._min_value
)
pairs = self._gen_pair_whitelist(pairlist, tickers,
self._config['stake_currency'],
self._sort_key, self._min_value)
else:
return pairlist
pairs = pairlist
self.log_on_refresh(logger.info, f"Searching {self._number_pairs} pairs: {pairs}")
return pairs
def _gen_pair_whitelist(self, pairlist: List[str], tickers: Dict,
base_currency: str, key: str, min_val: int) -> List[str]:
@ -88,7 +89,6 @@ class VolumePairList(IPairList):
:param tickers: Tickers (from exchange.get_tickers()).
:return: List of pairs
"""
if self._pairlist_pos == 0:
# If VolumePairList is the first in the list, use fresh pairlist
# Check if pair quote currency equals to the stake currency.
@ -109,6 +109,5 @@ class VolumePairList(IPairList):
pairs = self._verify_blacklist(pairs, aswarning=False)
# Limit to X number of pairs
pairs = pairs[:self._number_pairs]
logger.info(f"Searching {self._number_pairs} pairs: {pairs}")
return pairs

View File

@ -86,7 +86,7 @@ def check_migrate(engine) -> None:
logger.debug(f'trying {table_back_name}')
# Check for latest column
if not has_column(cols, 'open_trade_price'):
if not has_column(cols, 'close_profit_abs'):
logger.info(f'Running database migration - backup available as {table_back_name}')
fee_open = get_column_def(cols, 'fee_open', 'fee')
@ -106,6 +106,9 @@ def check_migrate(engine) -> None:
ticker_interval = get_column_def(cols, 'ticker_interval', 'null')
open_trade_price = get_column_def(cols, 'open_trade_price',
f'amount * open_rate * (1 + {fee_open})')
close_profit_abs = get_column_def(
cols, 'close_profit_abs',
f"(amount * close_rate * (1 - {fee_close})) - {open_trade_price}")
# Schema migration necessary
engine.execute(f"alter table trades rename to {table_back_name}")
@ -123,7 +126,7 @@ def check_migrate(engine) -> None:
stop_loss, stop_loss_pct, initial_stop_loss, initial_stop_loss_pct,
stoploss_order_id, stoploss_last_update,
max_rate, min_rate, sell_reason, strategy,
ticker_interval, open_trade_price
ticker_interval, open_trade_price, close_profit_abs
)
select id, lower(exchange),
case
@ -143,7 +146,7 @@ def check_migrate(engine) -> None:
{stoploss_order_id} stoploss_order_id, {stoploss_last_update} stoploss_last_update,
{max_rate} max_rate, {min_rate} min_rate, {sell_reason} sell_reason,
{strategy} strategy, {ticker_interval} ticker_interval,
{open_trade_price} open_trade_price
{open_trade_price} open_trade_price, {close_profit_abs} close_profit_abs
from {table_back_name}
""")
@ -185,11 +188,12 @@ class Trade(_DECL_BASE):
fee_close = Column(Float, nullable=False, default=0.0)
open_rate = Column(Float)
open_rate_requested = Column(Float)
# open_trade_price - calcuated via _calc_open_trade_price
# open_trade_price - calculated via _calc_open_trade_price
open_trade_price = Column(Float)
close_rate = Column(Float)
close_rate_requested = Column(Float)
close_profit = Column(Float)
close_profit_abs = Column(Float)
stake_amount = Column(Float, nullable=False)
amount = Column(Float)
open_date = Column(DateTime, nullable=False, default=datetime.utcnow)
@ -229,6 +233,9 @@ class Trade(_DECL_BASE):
return {
'trade_id': self.id,
'pair': self.pair,
'is_open': self.is_open,
'fee_open': self.fee_open,
'fee_close': self.fee_close,
'open_date_hum': arrow.get(self.open_date).humanize(),
'open_date': self.open_date.strftime("%Y-%m-%d %H:%M:%S"),
'close_date_hum': (arrow.get(self.close_date).humanize()
@ -236,14 +243,24 @@ class Trade(_DECL_BASE):
'close_date': (self.close_date.strftime("%Y-%m-%d %H:%M:%S")
if self.close_date else None),
'open_rate': self.open_rate,
'open_rate_requested': self.open_rate_requested,
'open_trade_price': self.open_trade_price,
'close_rate': self.close_rate,
'close_rate_requested': self.close_rate_requested,
'amount': round(self.amount, 8),
'stake_amount': round(self.stake_amount, 8),
'close_profit': self.close_profit,
'sell_reason': self.sell_reason,
'stop_loss': self.stop_loss,
'stop_loss_pct': (self.stop_loss_pct * 100) if self.stop_loss_pct else None,
'initial_stop_loss': self.initial_stop_loss,
'initial_stop_loss_pct': (self.initial_stop_loss_pct * 100
if self.initial_stop_loss_pct else None),
'min_rate': self.min_rate,
'max_rate': self.max_rate,
'strategy': self.strategy,
'ticker_interval': self.ticker_interval,
'open_order_id': self.open_order_id,
}
def adjust_min_max_rates(self, current_price: float) -> None:
@ -311,7 +328,7 @@ class Trade(_DECL_BASE):
if order_type in ('market', 'limit') and order['side'] == 'buy':
# Update open rate and actual amount
self.open_rate = Decimal(order['price'])
self.amount = Decimal(order['amount'])
self.amount = Decimal(order.get('filled', order['amount']))
self.recalc_open_trade_price()
logger.info('%s_BUY has been fulfilled for %s.', order_type.upper(), self)
self.open_order_id = None
@ -334,6 +351,7 @@ class Trade(_DECL_BASE):
"""
self.close_rate = Decimal(rate)
self.close_profit = self.calc_profit_ratio()
self.close_profit_abs = self.calc_profit()
self.close_date = datetime.utcnow()
self.is_open = False
self.open_order_id = None

View File

@ -10,6 +10,7 @@ from freqtrade.data.btanalysis import (calculate_max_drawdown,
create_cum_profit,
extract_trades_of_period, load_trades)
from freqtrade.data.converter import trim_dataframe
from freqtrade.exchange import timeframe_to_prev_date
from freqtrade.data.history import load_data
from freqtrade.misc import pair_to_filename
from freqtrade.resolvers import StrategyResolver
@ -48,11 +49,21 @@ def init_plotscript(config):
data_format=config.get('dataformat_ohlcv', 'json'),
)
trades = load_trades(config['trade_source'],
db_url=config.get('db_url'),
exportfilename=config.get('exportfilename'),
)
no_trades = False
if config.get('no_trades', False):
no_trades = True
elif not config['exportfilename'].is_file() and config['trade_source'] == 'file':
logger.warning("Backtest file is missing skipping trades.")
no_trades = True
trades = load_trades(
config['trade_source'],
db_url=config.get('db_url'),
exportfilename=config.get('exportfilename'),
no_trades=no_trades
)
trades = trim_dataframe(trades, timerange, 'open_time')
return {"ohlcv": data,
"trades": trades,
"pairs": pairs,
@ -112,7 +123,8 @@ def add_profit(fig, row, data: pd.DataFrame, column: str, name: str) -> make_sub
return fig
def add_max_drawdown(fig, row, trades: pd.DataFrame, df_comb: pd.DataFrame) -> make_subplots:
def add_max_drawdown(fig, row, trades: pd.DataFrame, df_comb: pd.DataFrame,
timeframe: str) -> make_subplots:
"""
Add scatter points indicating max drawdown
"""
@ -122,12 +134,12 @@ def add_max_drawdown(fig, row, trades: pd.DataFrame, df_comb: pd.DataFrame) -> m
drawdown = go.Scatter(
x=[highdate, lowdate],
y=[
df_comb.loc[highdate, 'cum_profit'],
df_comb.loc[lowdate, 'cum_profit'],
df_comb.loc[timeframe_to_prev_date(timeframe, highdate), 'cum_profit'],
df_comb.loc[timeframe_to_prev_date(timeframe, lowdate), 'cum_profit'],
],
mode='markers',
name=f"Max drawdown {max_drawdown:.2f}%",
text=f"Max drawdown {max_drawdown:.2f}%",
name=f"Max drawdown {max_drawdown * 100:.2f}%",
text=f"Max drawdown {max_drawdown * 100:.2f}%",
marker=dict(
symbol='square-open',
size=9,
@ -373,6 +385,9 @@ def generate_profit_graph(pairs: str, data: Dict[str, pd.DataFrame],
# Combine close-values for all pairs, rename columns to "pair"
df_comb = combine_dataframes_with_mean(data, "close")
# Trim trades to available OHLCV data
trades = extract_trades_of_period(df_comb, trades, date_index=True)
# Add combined cumulative profit
df_comb = create_cum_profit(df_comb, trades, 'cum_profit', timeframe)
@ -395,7 +410,7 @@ def generate_profit_graph(pairs: str, data: Dict[str, pd.DataFrame],
fig.add_trace(avgclose, 1, 1)
fig = add_profit(fig, 2, df_comb, 'cum_profit', 'Profit')
fig = add_max_drawdown(fig, 2, trades, df_comb)
fig = add_max_drawdown(fig, 2, trades, df_comb, timeframe)
for pair in pairs:
profit_col = f'cum_profit_{pair}'

View File

@ -173,7 +173,8 @@ class ApiServer(RPC):
view_func=self._show_config, methods=['GET'])
self.app.add_url_rule(f'{BASE_URI}/ping', 'ping',
view_func=self._ping, methods=['GET'])
self.app.add_url_rule(f'{BASE_URI}/trades', 'trades',
view_func=self._trades, methods=['GET'])
# Combined actions and infos
self.app.add_url_rule(f'{BASE_URI}/blacklist', 'blacklist', view_func=self._blacklist,
methods=['GET', 'POST'])
@ -358,6 +359,18 @@ class ApiServer(RPC):
self._config.get('fiat_display_currency', ''))
return self.rest_dump(results)
@require_login
@rpc_catch_errors
def _trades(self):
"""
Handler for /trades.
Returns the X last trades in json format
"""
limit = int(request.args.get('limit', 0))
results = self._rpc_trade_history(limit)
return self.rest_dump(results)
@require_login
@rpc_catch_errors
def _whitelist(self):

View File

@ -197,7 +197,7 @@ class RPC:
Trade.close_date >= profitday,
Trade.close_date < (profitday + timedelta(days=1))
]).order_by(Trade.close_date).all()
curdayprofit = sum(trade.calc_profit() for trade in trades)
curdayprofit = sum(trade.close_profit_abs for trade in trades)
profit_days[profitday] = {
'amount': f'{curdayprofit:.8f}',
'trades': len(trades)
@ -226,6 +226,20 @@ class RPC:
for key, value in profit_days.items()
]
def _rpc_trade_history(self, limit: int) -> Dict:
""" Returns the X last trades """
if limit > 0:
trades = Trade.get_trades().order_by(Trade.id.desc()).limit(limit)
else:
trades = Trade.get_trades().order_by(Trade.id.desc()).all()
output = [trade.to_json() for trade in trades]
return {
"trades": output,
"trades_count": len(output)
}
def _rpc_trade_statistics(
self, stake_currency: str, fiat_display_currency: str) -> Dict[str, Any]:
""" Returns cumulative profit statistics """
@ -246,8 +260,8 @@ class RPC:
durations.append((trade.close_date - trade.open_date).total_seconds())
if not trade.is_open:
profit_ratio = trade.calc_profit_ratio()
profit_closed_coin.append(trade.calc_profit())
profit_ratio = trade.close_profit
profit_closed_coin.append(trade.close_profit_abs)
profit_closed_ratio.append(profit_ratio)
else:
# Get current rate

View File

@ -172,7 +172,8 @@ class Telegram(RPC):
' / {profit_fiat:.3f} {fiat_currency})`').format(**msg)
elif msg['type'] == RPCMessageType.SELL_CANCEL_NOTIFICATION:
message = "*{exchange}:* Cancelling Open Sell Order for {pair}".format(**msg)
message = ("*{exchange}:* Cancelling Open Sell Order "
"for {pair}. Reason: {reason}").format(**msg)
elif msg['type'] == RPCMessageType.STATUS_NOTIFICATION:
message = '*Status:* `{status}`'.format(**msg)

View File

@ -278,8 +278,25 @@ class IStrategy(ABC):
return dataframe
def get_signal(self, pair: str, interval: str,
dataframe: DataFrame) -> Tuple[bool, bool]:
@staticmethod
def preserve_df(dataframe: DataFrame) -> Tuple[int, float, datetime]:
""" keep some data for dataframes """
return len(dataframe), dataframe["close"].iloc[-1], dataframe["date"].iloc[-1]
@staticmethod
def assert_df(dataframe: DataFrame, df_len: int, df_close: float, df_date: datetime):
""" make sure data is unmodified """
message = ""
if df_len != len(dataframe):
message = "length"
elif df_close != dataframe["close"].iloc[-1]:
message = "last close price"
elif df_date != dataframe["date"].iloc[-1]:
message = "last date"
if message:
raise StrategyError(f"Dataframe returned from strategy has mismatching {message}.")
def get_signal(self, pair: str, interval: str, dataframe: DataFrame) -> Tuple[bool, bool]:
"""
Calculates current signal based several technical analysis indicators
:param pair: pair in format ANT/BTC
@ -291,10 +308,13 @@ class IStrategy(ABC):
logger.warning('Empty candle (OHLCV) data for pair %s', pair)
return False, False
latest_date = dataframe['date'].max()
try:
df_len, df_close, df_date = self.preserve_df(dataframe)
dataframe = strategy_safe_wrapper(
self._analyze_ticker_internal, message=""
)(dataframe, {'pair': pair})
self.assert_df(dataframe, df_len, df_close, df_date)
except StrategyError as error:
logger.warning(f"Unable to analyze candle (OHLCV) data for pair {pair}: {error}")
@ -304,7 +324,7 @@ class IStrategy(ABC):
logger.warning('Empty dataframe for pair %s', pair)
return False, False
latest = dataframe.iloc[-1]
latest = dataframe.loc[dataframe['date'] == latest_date].iloc[-1]
# Check if dataframe is out of date
signal_date = arrow.get(latest['date'])
@ -473,8 +493,11 @@ class IStrategy(ABC):
"""
Creates a dataframe and populates indicators for given candle (OHLCV) data
Used by optimize operations only, not during dry / live runs.
Using .copy() to get a fresh copy of the dataframe for every strategy run.
Has positive effects on memory usage for whatever reason - also when
using only one strategy.
"""
return {pair: self.advise_indicators(pair_data, {'pair': pair})
return {pair: self.advise_indicators(pair_data.copy(), {'pair': pair})
for pair, pair_data in data.items()}
def advise_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:

View File

@ -1,18 +1,18 @@
# requirements without requirements installable via conda
# mainly used for Raspberry pi installs
ccxt==1.23.81
SQLAlchemy==1.3.13
python-telegram-bot==12.4.2
ccxt==1.26.32
SQLAlchemy==1.3.16
python-telegram-bot==12.6.1
arrow==0.15.5
cachetools==4.0.0
cachetools==4.1.0
requests==2.23.0
urllib3==1.25.8
wrapt==1.12.1
jsonschema==3.2.0
TA-Lib==0.4.17
tabulate==0.8.6
tabulate==0.8.7
pycoingecko==1.2.0
jinja2==2.11.1
jinja2==2.11.2
# find first, C search in arrays
py_find_1st==1.1.4
@ -24,10 +24,10 @@ python-rapidjson==0.9.1
sdnotify==0.3.2
# Api server
flask==1.1.1
flask==1.1.2
# Support for colorized terminal output
colorama==0.4.3
# Building config files interactively
questionary==1.5.1
prompt-toolkit==3.0.4
prompt-toolkit==3.0.5

View File

@ -3,15 +3,15 @@
-r requirements-plot.txt
-r requirements-hyperopt.txt
coveralls==1.11.1
coveralls==2.0.0
flake8==3.7.9
flake8-type-annotations==0.1.0
flake8-tidy-imports==4.0.0
mypy==0.761
pytest==5.3.5
flake8-tidy-imports==4.1.0
mypy==0.770
pytest==5.4.1
pytest-asyncio==0.10.0
pytest-cov==2.8.1
pytest-mock==2.0.0
pytest-mock==3.0.0
pytest-random-order==1.0.4
# Convert jupyter notebooks to markdown documents

View File

@ -7,3 +7,4 @@ scikit-learn==0.22.2.post1
scikit-optimize==0.7.4
filelock==3.0.12
joblib==0.14.1
progressbar2==3.50.1

View File

@ -1,5 +1,5 @@
# Include all requirements to run the bot.
-r requirements.txt
plotly==4.5.3
plotly==4.6.0

View File

@ -1,5 +1,5 @@
# Load common requirements
-r requirements-common.txt
numpy==1.18.1
pandas==1.0.1
numpy==1.18.2
pandas==1.0.3

View File

@ -156,6 +156,14 @@ class FtRestClient():
"""
return self._get("show_config")
def trades(self, limit=None):
"""Return trades history.
:param limit: Limits trades to the X last trades. No limit to get all the trades.
:return: json object
"""
return self._get("trades", params={"limit": limit} if limit else 0)
def whitelist(self):
"""Show the current whitelist.

View File

@ -24,6 +24,7 @@ hyperopt = [
'scikit-optimize',
'filelock',
'joblib',
'progressbar2',
]
develop = [

View File

@ -166,6 +166,52 @@ def patch_get_signal(freqtrade: FreqtradeBot, value=(True, False)) -> None:
freqtrade.exchange.refresh_latest_ohlcv = lambda p: None
def create_mock_trades(fee):
"""
Create some fake trades ...
"""
# Simulate dry_run entries
trade = Trade(
pair='ETH/BTC',
stake_amount=0.001,
amount=123.0,
fee_open=fee.return_value,
fee_close=fee.return_value,
open_rate=0.123,
exchange='bittrex',
open_order_id='dry_run_buy_12345'
)
Trade.session.add(trade)
trade = Trade(
pair='ETC/BTC',
stake_amount=0.001,
amount=123.0,
fee_open=fee.return_value,
fee_close=fee.return_value,
open_rate=0.123,
close_rate=0.128,
close_profit=0.005,
exchange='bittrex',
is_open=False,
open_order_id='dry_run_sell_12345'
)
Trade.session.add(trade)
# Simulate prod entry
trade = Trade(
pair='ETC/BTC',
stake_amount=0.001,
amount=123.0,
fee_open=fee.return_value,
fee_close=fee.return_value,
open_rate=0.123,
exchange='bittrex',
open_order_id='prod_buy_12345'
)
Trade.session.add(trade)
@pytest.fixture(autouse=True)
def patch_coingekko(mocker) -> None:
"""
@ -712,6 +758,7 @@ def limit_buy_order():
'datetime': arrow.utcnow().isoformat(),
'price': 0.00001099,
'amount': 90.99181073,
'filled': 90.99181073,
'remaining': 0.0,
'status': 'closed'
}
@ -727,6 +774,7 @@ def market_buy_order():
'datetime': arrow.utcnow().isoformat(),
'price': 0.00004099,
'amount': 91.99181073,
'filled': 91.99181073,
'remaining': 0.0,
'status': 'closed'
}
@ -742,6 +790,7 @@ def market_sell_order():
'datetime': arrow.utcnow().isoformat(),
'price': 0.00004173,
'amount': 91.99181073,
'filled': 91.99181073,
'remaining': 0.0,
'status': 'closed'
}
@ -757,6 +806,7 @@ def limit_buy_order_old():
'datetime': str(arrow.utcnow().shift(minutes=-601).datetime),
'price': 0.00001099,
'amount': 90.99181073,
'filled': 0.0,
'remaining': 90.99181073,
'status': 'open'
}
@ -772,6 +822,7 @@ def limit_sell_order_old():
'datetime': arrow.utcnow().shift(minutes=-601).isoformat(),
'price': 0.00001099,
'amount': 90.99181073,
'filled': 0.0,
'remaining': 90.99181073,
'status': 'open'
}
@ -787,6 +838,7 @@ def limit_buy_order_old_partial():
'datetime': arrow.utcnow().shift(minutes=-601).isoformat(),
'price': 0.00001099,
'amount': 90.99181073,
'filled': 23.0,
'remaining': 67.99181073,
'status': 'open'
}
@ -810,6 +862,7 @@ def limit_sell_order():
'datetime': arrow.utcnow().isoformat(),
'price': 0.00001173,
'amount': 90.99181073,
'filled': 90.99181073,
'remaining': 0.0,
'status': 'closed'
}

View File

@ -15,7 +15,7 @@ from freqtrade.data.btanalysis import (BT_DATA_COLUMNS,
load_backtest_data, load_trades,
load_trades_from_db)
from freqtrade.data.history import load_data, load_pair_history
from tests.test_persistence import create_mock_trades
from tests.conftest import create_mock_trades
def test_load_backtest_data(testdatadir):
@ -105,6 +105,7 @@ def test_load_trades(default_conf, mocker):
load_trades("DB",
db_url=default_conf.get('db_url'),
exportfilename=default_conf.get('exportfilename'),
no_trades=False
)
assert db_mock.call_count == 1
@ -115,11 +116,24 @@ def test_load_trades(default_conf, mocker):
default_conf['exportfilename'] = Path("testfile.json")
load_trades("file",
db_url=default_conf.get('db_url'),
exportfilename=default_conf.get('exportfilename'),)
exportfilename=default_conf.get('exportfilename'),
)
assert db_mock.call_count == 0
assert bt_mock.call_count == 1
db_mock.reset_mock()
bt_mock.reset_mock()
default_conf['exportfilename'] = "testfile.json"
load_trades("file",
db_url=default_conf.get('db_url'),
exportfilename=default_conf.get('exportfilename'),
no_trades=True
)
assert db_mock.call_count == 0
assert bt_mock.call_count == 0
def test_combine_dataframes_with_mean(testdatadir):
pairs = ["ETH/BTC", "ADA/BTC"]
@ -177,3 +191,28 @@ def test_calculate_max_drawdown(testdatadir):
assert low == Timestamp('2018-01-30 04:45:00', tz='UTC')
with pytest.raises(ValueError, match='Trade dataframe empty.'):
drawdown, h, low = calculate_max_drawdown(DataFrame())
def test_calculate_max_drawdown2():
values = [0.011580, 0.010048, 0.011340, 0.012161, 0.010416, 0.010009, 0.020024,
-0.024662, -0.022350, 0.020496, -0.029859, -0.030511, 0.010041, 0.010872,
-0.025782, 0.010400, 0.012374, 0.012467, 0.114741, 0.010303, 0.010088,
-0.033961, 0.010680, 0.010886, -0.029274, 0.011178, 0.010693, 0.010711]
dates = [Arrow(2020, 1, 1).shift(days=i) for i in range(len(values))]
df = DataFrame(zip(values, dates), columns=['profit', 'open_time'])
# sort by profit and reset index
df = df.sort_values('profit').reset_index(drop=True)
df1 = df.copy()
drawdown, h, low = calculate_max_drawdown(df, date_col='open_time', value_col='profit')
# Ensure df has not been altered.
assert df.equals(df1)
assert isinstance(drawdown, float)
# High must be before low
assert h < low
assert drawdown == 0.091755
df = DataFrame(zip(values[:5], dates[:5]), columns=['profit', 'open_time'])
with pytest.raises(ValueError, match='No losing trade, therefore no drawdown.'):
calculate_max_drawdown(df, date_col='open_time', value_col='profit')

View File

@ -292,8 +292,8 @@ def mocked_load_data(datadir, pairs=[], timeframe='0m',
def test_edge_process_downloaded_data(mocker, edge_conf):
freqtrade = get_patched_freqtradebot(mocker, edge_conf)
mocker.patch('freqtrade.exchange.Exchange.get_fee', MagicMock(return_value=0.001))
mocker.patch('freqtrade.data.history.refresh_data', MagicMock())
mocker.patch('freqtrade.data.history.load_data', mocked_load_data)
mocker.patch('freqtrade.edge.edge_positioning.refresh_data', MagicMock())
mocker.patch('freqtrade.edge.edge_positioning.load_data', mocked_load_data)
edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)
assert edge.calculate()
@ -304,8 +304,8 @@ def test_edge_process_downloaded_data(mocker, edge_conf):
def test_edge_process_no_data(mocker, edge_conf, caplog):
freqtrade = get_patched_freqtradebot(mocker, edge_conf)
mocker.patch('freqtrade.exchange.Exchange.get_fee', MagicMock(return_value=0.001))
mocker.patch('freqtrade.data.history.refresh_data', MagicMock())
mocker.patch('freqtrade.data.history.load_data', MagicMock(return_value={}))
mocker.patch('freqtrade.edge.edge_positioning.refresh_data', MagicMock())
mocker.patch('freqtrade.edge.edge_positioning.load_data', MagicMock(return_value={}))
edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)
assert not edge.calculate()
@ -317,8 +317,8 @@ def test_edge_process_no_data(mocker, edge_conf, caplog):
def test_edge_process_no_trades(mocker, edge_conf, caplog):
freqtrade = get_patched_freqtradebot(mocker, edge_conf)
mocker.patch('freqtrade.exchange.Exchange.get_fee', MagicMock(return_value=0.001))
mocker.patch('freqtrade.data.history.refresh_data', MagicMock())
mocker.patch('freqtrade.data.history.load_data', mocked_load_data)
mocker.patch('freqtrade.edge.edge_positioning.refresh_data', MagicMock())
mocker.patch('freqtrade.edge.edge_positioning.load_data', mocked_load_data)
# Return empty
mocker.patch('freqtrade.edge.Edge._find_trades_for_stoploss_range', MagicMock(return_value=[]))
edge = Edge(edge_conf, freqtrade.exchange, freqtrade.strategy)

View File

@ -253,6 +253,32 @@ def test_price_to_precision(default_conf, mocker, price, precision_mode, precisi
assert pytest.approx(exchange.price_to_precision(pair, price)) == expected
@pytest.mark.parametrize("price,precision_mode,precision,expected", [
(2.34559, 2, 4, 0.0001),
(2.34559, 2, 5, 0.00001),
(2.34559, 2, 3, 0.001),
(2.9999, 2, 3, 0.001),
(200.0511, 2, 3, 0.001),
# Tests for Tick_size
(2.34559, 4, 0.0001, 0.0001),
(2.34559, 4, 0.00001, 0.00001),
(2.34559, 4, 0.0025, 0.0025),
(2.9909, 4, 0.0025, 0.0025),
(234.43, 4, 0.5, 0.5),
(234.43, 4, 0.0025, 0.0025),
(234.43, 4, 0.00013, 0.00013),
])
def test_price_get_one_pip(default_conf, mocker, price, precision_mode, precision, expected):
markets = PropertyMock(return_value={'ETH/BTC': {'precision': {'price': precision}}})
exchange = get_patched_exchange(mocker, default_conf, id="binance")
mocker.patch('freqtrade.exchange.Exchange.markets', markets)
mocker.patch('freqtrade.exchange.Exchange.precisionMode',
PropertyMock(return_value=precision_mode))
pair = 'ETH/BTC'
assert pytest.approx(exchange.price_get_one_pip(pair, price)) == expected
def test_set_sandbox(default_conf, mocker):
"""
Test working scenario
@ -1705,6 +1731,68 @@ def test_cancel_order_dry_run(default_conf, mocker, exchange_name):
assert exchange.cancel_order(order_id='123', pair='TKN/BTC') == {}
@pytest.mark.parametrize("exchange_name", EXCHANGES)
@pytest.mark.parametrize("order,result", [
({'status': 'closed', 'filled': 10}, False),
({'status': 'closed', 'filled': 0.0}, True),
({'status': 'canceled', 'filled': 0.0}, True),
({'status': 'canceled', 'filled': 10.0}, False),
({'status': 'unknown', 'filled': 10.0}, False),
({'result': 'testest123'}, False),
])
def test_check_order_canceled_empty(mocker, default_conf, exchange_name, order, result):
exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
assert exchange.check_order_canceled_empty(order) == result
@pytest.mark.parametrize("exchange_name", EXCHANGES)
@pytest.mark.parametrize("order,result", [
({'status': 'closed', 'amount': 10, 'fee': {}}, True),
({'status': 'closed', 'amount': 0.0, 'fee': {}}, True),
({'status': 'canceled', 'amount': 0.0, 'fee': {}}, True),
({'status': 'canceled', 'amount': 10.0}, False),
({'amount': 10.0, 'fee': {}}, False),
({'result': 'testest123'}, False),
('hello_world', False),
])
def test_is_cancel_order_result_suitable(mocker, default_conf, exchange_name, order, result):
exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
assert exchange.is_cancel_order_result_suitable(order) == result
@pytest.mark.parametrize("exchange_name", EXCHANGES)
@pytest.mark.parametrize("corder,call_corder,call_forder", [
({'status': 'closed', 'amount': 10, 'fee': {}}, 1, 0),
({'amount': 10, 'fee': {}}, 1, 1),
])
def test_cancel_order_with_result(default_conf, mocker, exchange_name, corder,
call_corder, call_forder):
default_conf['dry_run'] = False
api_mock = MagicMock()
api_mock.cancel_order = MagicMock(return_value=corder)
api_mock.fetch_order = MagicMock(return_value={})
exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
res = exchange.cancel_order_with_result('1234', 'ETH/BTC', 1234)
assert isinstance(res, dict)
assert api_mock.cancel_order.call_count == call_corder
assert api_mock.fetch_order.call_count == call_forder
@pytest.mark.parametrize("exchange_name", EXCHANGES)
def test_cancel_order_with_result_error(default_conf, mocker, exchange_name, caplog):
default_conf['dry_run'] = False
api_mock = MagicMock()
api_mock.cancel_order = MagicMock(side_effect=ccxt.InvalidOrder("Did not find order"))
api_mock.fetch_order = MagicMock(side_effect=ccxt.InvalidOrder("Did not find order"))
exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
res = exchange.cancel_order_with_result('1234', 'ETH/BTC', 1541)
assert isinstance(res, dict)
assert log_has("Could not cancel order 1234.", caplog)
assert log_has("Could not fetch cancelled order 1234.", caplog)
assert res['amount'] == 1541
# Ensure that if not dry_run, we should call API
@pytest.mark.parametrize("exchange_name", EXCHANGES)
def test_cancel_order(default_conf, mocker, exchange_name):

View File

@ -331,8 +331,8 @@ def test_backtesting_start(default_conf, mocker, testdatadir, caplog) -> None:
mocker.patch('freqtrade.data.history.get_timerange', get_timerange)
patch_exchange(mocker)
mocker.patch('freqtrade.optimize.backtesting.Backtesting.backtest', MagicMock())
mocker.patch('freqtrade.optimize.backtesting.generate_text_table', MagicMock(return_value=1))
mocker.patch('freqtrade.optimize.backtesting.Backtesting.backtest')
mocker.patch('freqtrade.optimize.backtesting.show_backtest_results')
default_conf['exchange']['pair_whitelist'] = ['UNITTEST/BTC']
default_conf['ticker_interval'] = '1m'
@ -361,8 +361,8 @@ def test_backtesting_start_no_data(default_conf, mocker, caplog, testdatadir) ->
MagicMock(return_value=pd.DataFrame()))
mocker.patch('freqtrade.data.history.get_timerange', get_timerange)
patch_exchange(mocker)
mocker.patch('freqtrade.optimize.backtesting.Backtesting.backtest', MagicMock())
mocker.patch('freqtrade.optimize.backtesting.generate_text_table', MagicMock(return_value=1))
mocker.patch('freqtrade.optimize.backtesting.Backtesting.backtest')
mocker.patch('freqtrade.optimize.backtesting.show_backtest_results')
default_conf['exchange']['pair_whitelist'] = ['UNITTEST/BTC']
default_conf['ticker_interval'] = "1m"
@ -507,7 +507,6 @@ def test_backtest_only_sell(mocker, default_conf, testdatadir):
def test_backtest_alternate_buy_sell(default_conf, fee, mocker, testdatadir):
mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
mocker.patch('freqtrade.optimize.backtesting.file_dump_json', MagicMock())
backtest_conf = _make_backtest_conf(mocker, conf=default_conf,
pair='UNITTEST/BTC', datadir=testdatadir)
default_conf['ticker_interval'] = '1m'
@ -515,7 +514,6 @@ def test_backtest_alternate_buy_sell(default_conf, fee, mocker, testdatadir):
backtesting.strategy.advise_buy = _trend_alternate # Override
backtesting.strategy.advise_sell = _trend_alternate # Override
results = backtesting.backtest(**backtest_conf)
backtesting._store_backtest_result("test_.json", results)
# 200 candles in backtest data
# won't buy on first (shifted by 1)
# 100 buys signals
@ -586,84 +584,12 @@ def test_backtest_multi_pair(default_conf, fee, mocker, tres, pair, testdatadir)
assert len(evaluate_result_multi(results, '5m', 1)) == 0
def test_backtest_record(default_conf, fee, mocker):
names = []
records = []
patch_exchange(mocker)
mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
mocker.patch(
'freqtrade.optimize.backtesting.file_dump_json',
new=lambda n, r: (names.append(n), records.append(r))
)
backtesting = Backtesting(default_conf)
results = pd.DataFrame({"pair": ["UNITTEST/BTC", "UNITTEST/BTC",
"UNITTEST/BTC", "UNITTEST/BTC"],
"profit_percent": [0.003312, 0.010801, 0.013803, 0.002780],
"profit_abs": [0.000003, 0.000011, 0.000014, 0.000003],
"open_time": [Arrow(2017, 11, 14, 19, 32, 00).datetime,
Arrow(2017, 11, 14, 21, 36, 00).datetime,
Arrow(2017, 11, 14, 22, 12, 00).datetime,
Arrow(2017, 11, 14, 22, 44, 00).datetime],
"close_time": [Arrow(2017, 11, 14, 21, 35, 00).datetime,
Arrow(2017, 11, 14, 22, 10, 00).datetime,
Arrow(2017, 11, 14, 22, 43, 00).datetime,
Arrow(2017, 11, 14, 22, 58, 00).datetime],
"open_rate": [0.002543, 0.003003, 0.003089, 0.003214],
"close_rate": [0.002546, 0.003014, 0.003103, 0.003217],
"open_index": [1, 119, 153, 185],
"close_index": [118, 151, 184, 199],
"trade_duration": [123, 34, 31, 14],
"open_at_end": [False, False, False, True],
"sell_reason": [SellType.ROI, SellType.STOP_LOSS,
SellType.ROI, SellType.FORCE_SELL]
})
backtesting._store_backtest_result("backtest-result.json", results)
assert len(results) == 4
# Assert file_dump_json was only called once
assert names == ['backtest-result.json']
records = records[0]
# Ensure records are of correct type
assert len(records) == 4
# reset test to test with strategy name
names = []
records = []
backtesting._store_backtest_result(Path("backtest-result.json"), results, "DefStrat")
assert len(results) == 4
# Assert file_dump_json was only called once
assert names == [Path('backtest-result-DefStrat.json')]
records = records[0]
# Ensure records are of correct type
assert len(records) == 4
# ('UNITTEST/BTC', 0.00331158, '1510684320', '1510691700', 0, 117)
# Below follows just a typecheck of the schema/type of trade-records
oix = None
for (pair, profit, date_buy, date_sell, buy_index, dur,
openr, closer, open_at_end, sell_reason) in records:
assert pair == 'UNITTEST/BTC'
assert isinstance(profit, float)
# FIX: buy/sell should be converted to ints
assert isinstance(date_buy, float)
assert isinstance(date_sell, float)
assert isinstance(openr, float)
assert isinstance(closer, float)
assert isinstance(open_at_end, bool)
assert isinstance(sell_reason, str)
isinstance(buy_index, pd._libs.tslib.Timestamp)
if oix:
assert buy_index > oix
oix = buy_index
assert dur > 0
def test_backtest_start_timerange(default_conf, mocker, caplog, testdatadir):
default_conf['exchange']['pair_whitelist'] = ['UNITTEST/BTC']
patch_exchange(mocker)
mocker.patch('freqtrade.optimize.backtesting.Backtesting.backtest', MagicMock())
mocker.patch('freqtrade.optimize.backtesting.generate_text_table', MagicMock())
mocker.patch('freqtrade.optimize.backtesting.show_backtest_results', MagicMock())
patched_configuration_load_config_file(mocker, default_conf)
@ -705,9 +631,10 @@ def test_backtest_start_multi_strat(default_conf, mocker, caplog, testdatadir):
backtestmock = MagicMock()
mocker.patch('freqtrade.optimize.backtesting.Backtesting.backtest', backtestmock)
gen_table_mock = MagicMock()
mocker.patch('freqtrade.optimize.backtesting.generate_text_table', gen_table_mock)
mocker.patch('freqtrade.optimize.optimize_reports.generate_text_table', gen_table_mock)
gen_strattable_mock = MagicMock()
mocker.patch('freqtrade.optimize.backtesting.generate_text_table_strategy', gen_strattable_mock)
mocker.patch('freqtrade.optimize.optimize_reports.generate_text_table_strategy',
gen_strattable_mock)
patched_configuration_load_config_file(mocker, default_conf)
args = [

View File

@ -1,10 +1,14 @@
from pathlib import Path
import pandas as pd
from arrow import Arrow
from freqtrade.edge import PairInfo
from freqtrade.optimize.optimize_reports import (
generate_edge_table, generate_text_table, generate_text_table_sell_reason,
generate_text_table_strategy)
generate_text_table_strategy, store_backtest_result)
from freqtrade.strategy.interface import SellType
from tests.conftest import patch_exchange
def test_generate_text_table(default_conf, mocker):
@ -61,10 +65,8 @@ def test_generate_text_table_sell_reason(default_conf, mocker):
'| stop_loss | 1 | 0 | 0 | 1 |'
' -10 | -10 | -0.2 | -5 |'
)
assert generate_text_table_sell_reason(
data={'ETH/BTC': {}},
stake_currency='BTC', max_open_trades=2,
results=results) == result_str
assert generate_text_table_sell_reason(stake_currency='BTC', max_open_trades=2,
results=results) == result_str
def test_generate_text_table_strategy(default_conf, mocker):
@ -115,3 +117,77 @@ def test_generate_edge_table(edge_conf, mocker):
assert generate_edge_table(results).count('| ETH/BTC |') == 1
assert generate_edge_table(results).count(
'| Risk Reward Ratio | Required Risk Reward | Expectancy |') == 1
def test_backtest_record(default_conf, fee, mocker):
names = []
records = []
patch_exchange(mocker)
mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
mocker.patch(
'freqtrade.optimize.optimize_reports.file_dump_json',
new=lambda n, r: (names.append(n), records.append(r))
)
results = {'DefStrat': pd.DataFrame({"pair": ["UNITTEST/BTC", "UNITTEST/BTC",
"UNITTEST/BTC", "UNITTEST/BTC"],
"profit_percent": [0.003312, 0.010801, 0.013803, 0.002780],
"profit_abs": [0.000003, 0.000011, 0.000014, 0.000003],
"open_time": [Arrow(2017, 11, 14, 19, 32, 00).datetime,
Arrow(2017, 11, 14, 21, 36, 00).datetime,
Arrow(2017, 11, 14, 22, 12, 00).datetime,
Arrow(2017, 11, 14, 22, 44, 00).datetime],
"close_time": [Arrow(2017, 11, 14, 21, 35, 00).datetime,
Arrow(2017, 11, 14, 22, 10, 00).datetime,
Arrow(2017, 11, 14, 22, 43, 00).datetime,
Arrow(2017, 11, 14, 22, 58, 00).datetime],
"open_rate": [0.002543, 0.003003, 0.003089, 0.003214],
"close_rate": [0.002546, 0.003014, 0.003103, 0.003217],
"open_index": [1, 119, 153, 185],
"close_index": [118, 151, 184, 199],
"trade_duration": [123, 34, 31, 14],
"open_at_end": [False, False, False, True],
"sell_reason": [SellType.ROI, SellType.STOP_LOSS,
SellType.ROI, SellType.FORCE_SELL]
})}
store_backtest_result(Path("backtest-result.json"), results)
# Assert file_dump_json was only called once
assert names == [Path('backtest-result.json')]
records = records[0]
# Ensure records are of correct type
assert len(records) == 4
# reset test to test with strategy name
names = []
records = []
results['Strat'] = results['DefStrat']
results['Strat2'] = results['DefStrat']
store_backtest_result(Path("backtest-result.json"), results)
assert names == [
Path('backtest-result-DefStrat.json'),
Path('backtest-result-Strat.json'),
Path('backtest-result-Strat2.json'),
]
records = records[0]
# Ensure records are of correct type
assert len(records) == 4
# ('UNITTEST/BTC', 0.00331158, '1510684320', '1510691700', 0, 117)
# Below follows just a typecheck of the schema/type of trade-records
oix = None
for (pair, profit, date_buy, date_sell, buy_index, dur,
openr, closer, open_at_end, sell_reason) in records:
assert pair == 'UNITTEST/BTC'
assert isinstance(profit, float)
# FIX: buy/sell should be converted to ints
assert isinstance(date_buy, float)
assert isinstance(date_sell, float)
assert isinstance(openr, float)
assert isinstance(closer, float)
assert isinstance(open_at_end, bool)
assert isinstance(sell_reason, str)
isinstance(buy_index, pd._libs.tslib.Timestamp)
if oix:
assert buy_index > oix
oix = buy_index
assert dur > 0

View File

@ -46,6 +46,28 @@ def static_pl_conf(whitelist_conf):
return whitelist_conf
def test_log_on_refresh(mocker, static_pl_conf, markets, tickers):
mocker.patch.multiple('freqtrade.exchange.Exchange',
markets=PropertyMock(return_value=markets),
exchange_has=MagicMock(return_value=True),
get_tickers=tickers
)
freqtrade = get_patched_freqtradebot(mocker, static_pl_conf)
logmock = MagicMock()
# Assign starting whitelist
pl = freqtrade.pairlists._pairlists[0]
pl.log_on_refresh(logmock, 'Hello world')
assert logmock.call_count == 1
pl.log_on_refresh(logmock, 'Hello world')
assert logmock.call_count == 1
assert pl._log_cache.currsize == 1
assert ('Hello world',) in pl._log_cache._Cache__data
pl.log_on_refresh(logmock, 'Hello world2')
assert logmock.call_count == 2
assert pl._log_cache.currsize == 2
def test_load_pairlist_noexist(mocker, markets, default_conf):
bot = get_patched_freqtradebot(mocker, default_conf)
mocker.patch('freqtrade.exchange.Exchange.markets', PropertyMock(return_value=markets))

View File

@ -13,7 +13,7 @@ from freqtrade.persistence import Trade
from freqtrade.rpc import RPC, RPCException
from freqtrade.rpc.fiat_convert import CryptoToFiatConverter
from freqtrade.state import State
from tests.conftest import get_patched_freqtradebot, patch_get_signal
from tests.conftest import get_patched_freqtradebot, patch_get_signal, create_mock_trades
# Functions for recurrent object patching
@ -49,6 +49,18 @@ def test_rpc_trade_status(default_conf, ticker, fee, mocker) -> None:
'base_currency': 'BTC',
'open_date': ANY,
'open_date_hum': ANY,
'is_open': ANY,
'fee_open': ANY,
'fee_close': ANY,
'open_rate_requested': ANY,
'open_trade_price': ANY,
'close_rate_requested': ANY,
'sell_reason': ANY,
'min_rate': ANY,
'max_rate': ANY,
'strategy': ANY,
'ticker_interval': ANY,
'open_order_id': ANY,
'close_date': None,
'close_date_hum': None,
'open_rate': 1.098e-05,
@ -76,6 +88,18 @@ def test_rpc_trade_status(default_conf, ticker, fee, mocker) -> None:
'base_currency': 'BTC',
'open_date': ANY,
'open_date_hum': ANY,
'is_open': ANY,
'fee_open': ANY,
'fee_close': ANY,
'open_rate_requested': ANY,
'open_trade_price': ANY,
'close_rate_requested': ANY,
'sell_reason': ANY,
'min_rate': ANY,
'max_rate': ANY,
'strategy': ANY,
'ticker_interval': ANY,
'open_order_id': ANY,
'close_date': None,
'close_date_hum': None,
'open_rate': 1.098e-05,
@ -187,6 +211,32 @@ def test_rpc_daily_profit(default_conf, update, ticker, fee,
rpc._rpc_daily_profit(0, stake_currency, fiat_display_currency)
def test_rpc_trade_history(mocker, default_conf, markets, fee):
mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
markets=PropertyMock(return_value=markets)
)
freqtradebot = get_patched_freqtradebot(mocker, default_conf)
create_mock_trades(fee)
rpc = RPC(freqtradebot)
rpc._fiat_converter = CryptoToFiatConverter()
trades = rpc._rpc_trade_history(2)
assert len(trades['trades']) == 2
assert trades['trades_count'] == 2
assert isinstance(trades['trades'][0], dict)
assert isinstance(trades['trades'][1], dict)
trades = rpc._rpc_trade_history(0)
assert len(trades['trades']) == 3
assert trades['trades_count'] == 3
# The first trade is for ETH ... sorting is descending
assert trades['trades'][-1]['pair'] == 'ETH/BTC'
assert trades['trades'][0]['pair'] == 'ETC/BTC'
assert trades['trades'][1]['pair'] == 'ETC/BTC'
def test_rpc_trade_statistics(default_conf, ticker, ticker_sell_up, fee,
limit_buy_order, limit_sell_order, mocker) -> None:
mocker.patch.multiple(

View File

@ -13,7 +13,7 @@ from freqtrade.__init__ import __version__
from freqtrade.persistence import Trade
from freqtrade.rpc.api_server import BASE_URI, ApiServer
from freqtrade.state import State
from tests.conftest import get_patched_freqtradebot, log_has, patch_get_signal
from tests.conftest import get_patched_freqtradebot, log_has, patch_get_signal, create_mock_trades
_TEST_USER = "FreqTrader"
_TEST_PASS = "SuperSecurePassword1!"
@ -302,6 +302,30 @@ def test_api_daily(botclient, mocker, ticker, fee, markets):
assert rc.json[0][0] == str(datetime.utcnow().date())
def test_api_trades(botclient, mocker, ticker, fee, markets):
ftbot, client = botclient
patch_get_signal(ftbot, (True, False))
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
markets=PropertyMock(return_value=markets)
)
rc = client_get(client, f"{BASE_URI}/trades")
assert_response(rc)
assert len(rc.json) == 2
assert rc.json['trades_count'] == 0
create_mock_trades(fee)
rc = client_get(client, f"{BASE_URI}/trades")
assert_response(rc)
assert len(rc.json['trades']) == 3
assert rc.json['trades_count'] == 3
rc = client_get(client, f"{BASE_URI}/trades?limit=2")
assert_response(rc)
assert len(rc.json['trades']) == 2
assert rc.json['trades_count'] == 2
def test_api_edge_disabled(botclient, mocker, ticker, fee, markets):
ftbot, client = botclient
patch_get_signal(ftbot, (True, False))
@ -444,7 +468,21 @@ def test_api_status(botclient, mocker, ticker, fee, markets):
'stake_amount': 0.001,
'stop_loss': 0.0,
'stop_loss_pct': None,
'trade_id': 1}]
'trade_id': 1,
'close_rate_requested': None,
'current_rate': 1.099e-05,
'fee_close': 0.0025,
'fee_open': 0.0025,
'open_date': ANY,
'is_open': True,
'max_rate': 0.0,
'min_rate': None,
'open_order_id': ANY,
'open_rate_requested': 1.098e-05,
'open_trade_price': 0.0010025,
'sell_reason': None,
'strategy': 'DefaultStrategy',
'ticker_interval': 5}]
def test_api_version(botclient):
@ -533,7 +571,21 @@ def test_api_forcebuy(botclient, mocker, fee):
'stake_amount': 1,
'stop_loss': None,
'stop_loss_pct': None,
'trade_id': None}
'trade_id': None,
'close_profit': None,
'close_rate_requested': None,
'fee_close': 0.0025,
'fee_open': 0.0025,
'is_open': False,
'max_rate': None,
'min_rate': None,
'open_order_id': '123456',
'open_rate_requested': None,
'open_trade_price': 0.2460546025,
'sell_reason': None,
'strategy': None,
'ticker_interval': None
}
def test_api_forcesell(botclient, mocker, ticker, fee, markets):

View File

@ -1316,18 +1316,20 @@ def test_send_msg_sell_cancel_notification(default_conf, mocker) -> None:
'type': RPCMessageType.SELL_CANCEL_NOTIFICATION,
'exchange': 'Binance',
'pair': 'KEY/ETH',
'reason': 'Cancelled on exchange'
})
assert msg_mock.call_args[0][0] \
== ('*Binance:* Cancelling Open Sell Order for KEY/ETH')
== ('*Binance:* Cancelling Open Sell Order for KEY/ETH. Reason: Cancelled on exchange')
msg_mock.reset_mock()
telegram.send_msg({
'type': RPCMessageType.SELL_CANCEL_NOTIFICATION,
'exchange': 'Binance',
'pair': 'KEY/ETH',
'reason': 'timeout'
})
assert msg_mock.call_args[0][0] \
== ('*Binance:* Cancelling Open Sell Order for KEY/ETH')
== ('*Binance:* Cancelling Open Sell Order for KEY/ETH. Reason: timeout')
# Reset singleton function to avoid random breaks
telegram._fiat_converter.convert_amount = old_convamount

View File

@ -21,33 +21,36 @@ from .strats.default_strategy import DefaultStrategy
_STRATEGY = DefaultStrategy(config={})
def test_returns_latest_buy_signal(mocker, default_conf, ohlcv_history):
mocker.patch.object(
_STRATEGY, '_analyze_ticker_internal',
return_value=DataFrame([{'buy': 1, 'sell': 0, 'date': arrow.utcnow()}])
)
assert _STRATEGY.get_signal('ETH/BTC', '5m', ohlcv_history) == (True, False)
def test_returns_latest_signal(mocker, default_conf, ohlcv_history):
ohlcv_history.loc[1, 'date'] = arrow.utcnow()
# Take a copy to correctly modify the call
mocked_history = ohlcv_history.copy()
mocked_history['sell'] = 0
mocked_history['buy'] = 0
mocked_history.loc[1, 'sell'] = 1
mocker.patch.object(
_STRATEGY, '_analyze_ticker_internal',
return_value=DataFrame([{'buy': 0, 'sell': 1, 'date': arrow.utcnow()}])
)
assert _STRATEGY.get_signal('ETH/BTC', '5m', ohlcv_history) == (False, True)
def test_returns_latest_sell_signal(mocker, default_conf, ohlcv_history):
mocker.patch.object(
_STRATEGY, '_analyze_ticker_internal',
return_value=DataFrame([{'sell': 1, 'buy': 0, 'date': arrow.utcnow()}])
return_value=mocked_history
)
assert _STRATEGY.get_signal('ETH/BTC', '5m', ohlcv_history) == (False, True)
mocked_history.loc[1, 'sell'] = 0
mocked_history.loc[1, 'buy'] = 1
mocker.patch.object(
_STRATEGY, '_analyze_ticker_internal',
return_value=DataFrame([{'sell': 0, 'buy': 1, 'date': arrow.utcnow()}])
return_value=mocked_history
)
assert _STRATEGY.get_signal('ETH/BTC', '5m', ohlcv_history) == (True, False)
mocked_history.loc[1, 'sell'] = 0
mocked_history.loc[1, 'buy'] = 0
mocker.patch.object(
_STRATEGY, '_analyze_ticker_internal',
return_value=mocked_history
)
assert _STRATEGY.get_signal('ETH/BTC', '5m', ohlcv_history) == (False, False)
def test_get_signal_empty(default_conf, mocker, caplog):
@ -78,26 +81,74 @@ def test_get_signal_empty_dataframe(default_conf, mocker, caplog, ohlcv_history)
_STRATEGY, '_analyze_ticker_internal',
return_value=DataFrame([])
)
mocker.patch.object(_STRATEGY, 'assert_df')
assert (False, False) == _STRATEGY.get_signal('xyz', default_conf['ticker_interval'],
ohlcv_history)
assert log_has('Empty dataframe for pair xyz', caplog)
def test_get_signal_old_dataframe(default_conf, mocker, caplog, ohlcv_history):
caplog.set_level(logging.INFO)
# default_conf defines a 5m interval. we check interval * 2 + 5m
# this is necessary as the last candle is removed (partial candles) by default
oldtime = arrow.utcnow().shift(minutes=-16)
ticks = DataFrame([{'buy': 1, 'date': oldtime}])
ohlcv_history.loc[1, 'date'] = arrow.utcnow().shift(minutes=-16)
# Take a copy to correctly modify the call
mocked_history = ohlcv_history.copy()
mocked_history['sell'] = 0
mocked_history['buy'] = 0
mocked_history.loc[1, 'buy'] = 1
caplog.set_level(logging.INFO)
mocker.patch.object(
_STRATEGY, '_analyze_ticker_internal',
return_value=DataFrame(ticks)
return_value=mocked_history
)
mocker.patch.object(_STRATEGY, 'assert_df')
assert (False, False) == _STRATEGY.get_signal('xyz', default_conf['ticker_interval'],
ohlcv_history)
assert log_has('Outdated history for pair xyz. Last tick is 16 minutes old', caplog)
def test_assert_df_raise(default_conf, mocker, caplog, ohlcv_history):
# default_conf defines a 5m interval. we check interval * 2 + 5m
# this is necessary as the last candle is removed (partial candles) by default
ohlcv_history.loc[1, 'date'] = arrow.utcnow().shift(minutes=-16)
# Take a copy to correctly modify the call
mocked_history = ohlcv_history.copy()
mocked_history['sell'] = 0
mocked_history['buy'] = 0
mocked_history.loc[1, 'buy'] = 1
caplog.set_level(logging.INFO)
mocker.patch.object(
_STRATEGY, 'assert_df',
side_effect=StrategyError('Dataframe returned...')
)
assert (False, False) == _STRATEGY.get_signal('xyz', default_conf['ticker_interval'],
ohlcv_history)
assert log_has('Unable to analyze candle (OHLCV) data for pair xyz: Dataframe returned...',
caplog)
def test_assert_df(default_conf, mocker, ohlcv_history):
# Ensure it's running when passed correctly
_STRATEGY.assert_df(ohlcv_history, len(ohlcv_history),
ohlcv_history.loc[1, 'close'], ohlcv_history.loc[1, 'date'])
with pytest.raises(StrategyError, match=r"Dataframe returned from strategy.*length\."):
_STRATEGY.assert_df(ohlcv_history, len(ohlcv_history) + 1,
ohlcv_history.loc[1, 'close'], ohlcv_history.loc[1, 'date'])
with pytest.raises(StrategyError,
match=r"Dataframe returned from strategy.*last close price\."):
_STRATEGY.assert_df(ohlcv_history, len(ohlcv_history),
ohlcv_history.loc[1, 'close'] + 0.01, ohlcv_history.loc[1, 'date'])
with pytest.raises(StrategyError,
match=r"Dataframe returned from strategy.*last date\."):
_STRATEGY.assert_df(ohlcv_history, len(ohlcv_history),
ohlcv_history.loc[1, 'close'], ohlcv_history.loc[0, 'date'])
def test_get_signal_handles_exceptions(mocker, default_conf):
exchange = get_patched_exchange(mocker, default_conf)
mocker.patch.object(
@ -118,6 +169,19 @@ def test_ohlcvdata_to_dataframe(default_conf, testdatadir) -> None:
assert len(processed['UNITTEST/BTC']) == 102 # partial candle was removed
def test_ohlcvdata_to_dataframe_copy(mocker, default_conf, testdatadir) -> None:
default_conf.update({'strategy': 'DefaultStrategy'})
strategy = StrategyResolver.load_strategy(default_conf)
aimock = mocker.patch('freqtrade.strategy.interface.IStrategy.advise_indicators')
timerange = TimeRange.parse_timerange('1510694220-1510700340')
data = load_data(testdatadir, '1m', ['UNITTEST/BTC'], timerange=timerange,
fill_up_missing=True)
strategy.ohlcvdata_to_dataframe(data)
assert aimock.call_count == 1
# Ensure that a copy of the dataframe is passed to advice_indicators
assert aimock.call_args_list[0][0][0] is not data
def test_min_roi_reached(default_conf, fee) -> None:
# Use list to confirm sequence does not matter

View File

@ -18,7 +18,7 @@ from freqtrade.configuration.config_validation import validate_config_schema
from freqtrade.configuration.deprecated_settings import (
check_conflicting_settings, process_deprecated_setting,
process_temporary_deprecated_settings)
from freqtrade.configuration.load_config import load_config_file
from freqtrade.configuration.load_config import load_config_file, log_config_error_range
from freqtrade.constants import DEFAULT_DB_DRYRUN_URL, DEFAULT_DB_PROD_URL
from freqtrade.exceptions import OperationalException
from freqtrade.loggers import _set_loggers, setup_logging
@ -66,6 +66,30 @@ def test_load_config_file(default_conf, mocker, caplog) -> None:
assert validated_conf.items() >= default_conf.items()
def test_load_config_file_error(default_conf, mocker, caplog) -> None:
del default_conf['user_data_dir']
filedata = json.dumps(default_conf).replace(
'"stake_amount": 0.001,', '"stake_amount": .001,')
mocker.patch('freqtrade.configuration.load_config.open', mocker.mock_open(read_data=filedata))
mocker.patch.object(Path, "read_text", MagicMock(return_value=filedata))
with pytest.raises(OperationalException, match=f".*Please verify the following segment.*"):
load_config_file('somefile')
def test_load_config_file_error_range(default_conf, mocker, caplog) -> None:
del default_conf['user_data_dir']
filedata = json.dumps(default_conf).replace(
'"stake_amount": 0.001,', '"stake_amount": .001,')
mocker.patch.object(Path, "read_text", MagicMock(return_value=filedata))
x = log_config_error_range('somefile', 'Parse error at offset 64: Invalid value.')
assert isinstance(x, str)
assert (x == '{"max_open_trades": 1, "stake_currency": "BTC", '
'"stake_amount": .001, "fiat_display_currency": "USD", '
'"ticker_interval": "5m", "dry_run": true, ')
def test__args_to_config(caplog):
arg_list = ['trade', '--strategy-path', 'TestTest']
@ -73,6 +97,7 @@ def test__args_to_config(caplog):
configuration = Configuration(args)
config = {}
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter("always")
# No warnings ...
configuration._args_to_config(config, argname="strategy_path", logstring="DeadBeef")
assert len(w) == 0
@ -82,6 +107,7 @@ def test__args_to_config(caplog):
configuration = Configuration(args)
config = {}
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter("always")
# Deprecation warnings!
configuration._args_to_config(config, argname="strategy_path", logstring="DeadBeef",
deprecated_msg="Going away soon!")

View File

@ -1592,13 +1592,13 @@ def test_exit_positions_exception(mocker, default_conf, limit_buy_order, caplog)
mocker.patch('freqtrade.exchange.Exchange.get_order', return_value=limit_buy_order)
trade = MagicMock()
trade.open_order_id = '123'
trade.open_order_id = None
trade.open_fee = 0.001
trades = [trade]
# Test raise of DependencyException exception
mocker.patch(
'freqtrade.freqtradebot.FreqtradeBot.update_trade_state',
'freqtrade.freqtradebot.FreqtradeBot.handle_trade',
side_effect=DependencyException()
)
n = freqtrade.exit_positions(trades)
@ -1995,7 +1995,7 @@ def test_check_handle_timedout_buy(default_conf, ticker, limit_buy_order_old, op
'freqtrade.exchange.Exchange',
fetch_ticker=ticker,
get_order=MagicMock(return_value=limit_buy_order_old),
cancel_order=cancel_order_mock,
cancel_order_with_result=cancel_order_mock,
get_fee=fee
)
freqtrade = FreqtradeBot(default_conf)
@ -2020,7 +2020,7 @@ def test_check_handle_cancelled_buy(default_conf, ticker, limit_buy_order_old, o
rpc_mock = patch_RPCManager(mocker)
cancel_order_mock = MagicMock()
patch_exchange(mocker)
limit_buy_order_old.update({"status": "canceled"})
limit_buy_order_old.update({"status": "canceled", 'filled': 0.0})
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
fetch_ticker=ticker,
@ -2147,13 +2147,13 @@ def test_check_handle_cancelled_sell(default_conf, ticker, limit_sell_order_old,
""" Handle sell order cancelled on exchange"""
rpc_mock = patch_RPCManager(mocker)
cancel_order_mock = MagicMock()
limit_sell_order_old.update({"status": "canceled"})
limit_sell_order_old.update({"status": "canceled", 'filled': 0.0})
patch_exchange(mocker)
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
fetch_ticker=ticker,
get_order=MagicMock(return_value=limit_sell_order_old),
cancel_order=cancel_order_mock
cancel_order_with_result=cancel_order_mock
)
freqtrade = FreqtradeBot(default_conf)
@ -2180,7 +2180,7 @@ def test_check_handle_timedout_partial(default_conf, ticker, limit_buy_order_old
'freqtrade.exchange.Exchange',
fetch_ticker=ticker,
get_order=MagicMock(return_value=limit_buy_order_old_partial),
cancel_order=cancel_order_mock
cancel_order_with_result=cancel_order_mock
)
freqtrade = FreqtradeBot(default_conf)
@ -2207,7 +2207,7 @@ def test_check_handle_timedout_partial_fee(default_conf, ticker, open_trade, cap
'freqtrade.exchange.Exchange',
fetch_ticker=ticker,
get_order=MagicMock(return_value=limit_buy_order_old_partial),
cancel_order=cancel_order_mock,
cancel_order_with_result=cancel_order_mock,
get_trades_for_order=MagicMock(return_value=trades_for_order),
)
freqtrade = FreqtradeBot(default_conf)
@ -2227,7 +2227,7 @@ def test_check_handle_timedout_partial_fee(default_conf, ticker, open_trade, cap
assert rpc_mock.call_count == 2
trades = Trade.query.filter(Trade.open_order_id.is_(open_trade.open_order_id)).all()
assert len(trades) == 1
# Verify that tradehas been updated
# Verify that trade has been updated
assert trades[0].amount == (limit_buy_order_old_partial['amount'] -
limit_buy_order_old_partial['remaining']) - 0.0001
assert trades[0].open_order_id is None
@ -2244,7 +2244,7 @@ def test_check_handle_timedout_partial_except(default_conf, ticker, open_trade,
'freqtrade.exchange.Exchange',
fetch_ticker=ticker,
get_order=MagicMock(return_value=limit_buy_order_old_partial),
cancel_order=cancel_order_mock,
cancel_order_with_result=cancel_order_mock,
get_trades_for_order=MagicMock(return_value=trades_for_order),
)
mocker.patch('freqtrade.freqtradebot.FreqtradeBot.get_real_amount',
@ -2266,7 +2266,7 @@ def test_check_handle_timedout_partial_except(default_conf, ticker, open_trade,
assert rpc_mock.call_count == 2
trades = Trade.query.filter(Trade.open_order_id.is_(open_trade.open_order_id)).all()
assert len(trades) == 1
# Verify that tradehas been updated
# Verify that trade has been updated
assert trades[0].amount == (limit_buy_order_old_partial['amount'] -
limit_buy_order_old_partial['remaining'])
@ -2302,14 +2302,11 @@ def test_check_handle_timedout_exception(default_conf, ticker, open_trade, mocke
caplog)
def test_handle_timedout_limit_buy(mocker, default_conf, limit_buy_order) -> None:
def test_handle_timedout_limit_buy(mocker, caplog, default_conf, limit_buy_order) -> None:
patch_RPCManager(mocker)
patch_exchange(mocker)
cancel_order_mock = MagicMock(return_value=limit_buy_order)
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
cancel_order=cancel_order_mock
)
mocker.patch('freqtrade.exchange.Exchange.cancel_order_with_result', cancel_order_mock)
freqtrade = FreqtradeBot(default_conf)
@ -2325,11 +2322,21 @@ def test_handle_timedout_limit_buy(mocker, default_conf, limit_buy_order) -> Non
assert not freqtrade.handle_timedout_limit_buy(trade, limit_buy_order)
assert cancel_order_mock.call_count == 1
mocker.patch('freqtrade.exchange.Exchange.cancel_order', side_effect=InvalidOrderException)
assert not freqtrade.handle_timedout_limit_buy(trade, limit_buy_order)
def test_handle_timedout_limit_buy_corder_empty(mocker, default_conf, limit_buy_order) -> None:
@pytest.mark.parametrize('cancelorder', [
{},
{'remaining': None},
'String Return value',
123
])
def test_handle_timedout_limit_buy_corder_empty(mocker, default_conf, limit_buy_order,
cancelorder) -> None:
patch_RPCManager(mocker)
patch_exchange(mocker)
cancel_order_mock = MagicMock(return_value={})
cancel_order_mock = MagicMock(return_value=cancelorder)
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
cancel_order=cancel_order_mock
@ -2368,7 +2375,8 @@ def test_handle_timedout_limit_sell(mocker, default_conf) -> None:
assert freqtrade.handle_timedout_limit_sell(trade, order)
assert cancel_order_mock.call_count == 1
order['amount'] = 2
assert not freqtrade.handle_timedout_limit_sell(trade, order)
assert (freqtrade.handle_timedout_limit_sell(trade, order)
== 'partially filled - keeping order open')
# Assert cancel_order was not called (callcount remains unchanged)
assert cancel_order_mock.call_count == 1
@ -2591,6 +2599,7 @@ def test_execute_sell_with_stoploss_on_exchange(default_conf, ticker, fee, ticke
assert trade
trades = [trade]
freqtrade.check_handle_timedout()
freqtrade.exit_positions(trades)
# Increase the price and sell it
@ -2636,8 +2645,11 @@ def test_may_execute_sell_after_stoploss_on_exchange_hit(default_conf, ticker, f
# Create some test data
freqtrade.enter_positions()
freqtrade.check_handle_timedout()
trade = Trade.query.first()
trades = [trade]
assert trade.stoploss_order_id is None
freqtrade.exit_positions(trades)
assert trade
assert trade.stoploss_order_id == '123'

View File

@ -10,7 +10,8 @@ from freqtrade.data.converter import ohlcv_to_dataframe
from freqtrade.misc import (datesarray_to_datetimearray, file_dump_json,
file_load_json, format_ms_time, pair_to_filename,
plural, render_template,
render_template_with_fallback, shorten_date)
render_template_with_fallback, safe_value_fallback,
shorten_date)
def test_shorten_date() -> None:
@ -94,6 +95,27 @@ def test_format_ms_time() -> None:
assert format_ms_time(date_in_epoch_ms) == res.astimezone(None).strftime('%Y-%m-%dT%H:%M:%S')
def test_safe_value_fallback():
dict1 = {'keya': None, 'keyb': 2, 'keyc': 5, 'keyd': None}
dict2 = {'keya': 20, 'keyb': None, 'keyc': 6, 'keyd': None}
assert safe_value_fallback(dict1, dict2, 'keya', 'keya') == 20
assert safe_value_fallback(dict2, dict1, 'keya', 'keya') == 20
assert safe_value_fallback(dict1, dict2, 'keyb', 'keyb') == 2
assert safe_value_fallback(dict2, dict1, 'keyb', 'keyb') == 2
assert safe_value_fallback(dict1, dict2, 'keyc', 'keyc') == 5
assert safe_value_fallback(dict2, dict1, 'keyc', 'keyc') == 6
assert safe_value_fallback(dict1, dict2, 'keyd', 'keyd') is None
assert safe_value_fallback(dict2, dict1, 'keyd', 'keyd') is None
assert safe_value_fallback(dict2, dict1, 'keyd', 'keyd', 1234) == 1234
assert safe_value_fallback(dict1, dict2, 'keyNo', 'keyNo') is None
assert safe_value_fallback(dict2, dict1, 'keyNo', 'keyNo') is None
assert safe_value_fallback(dict2, dict1, 'keyNo', 'keyNo', 1234) == 1234
def test_plural() -> None:
assert plural(0, "page") == "pages"
assert plural(0.0, "page") == "pages"

View File

@ -9,53 +9,7 @@ from sqlalchemy import create_engine
from freqtrade import constants
from freqtrade.exceptions import OperationalException
from freqtrade.persistence import Trade, clean_dry_run_db, init
from tests.conftest import log_has
def create_mock_trades(fee):
"""
Create some fake trades ...
"""
# Simulate dry_run entries
trade = Trade(
pair='ETH/BTC',
stake_amount=0.001,
amount=123.0,
fee_open=fee.return_value,
fee_close=fee.return_value,
open_rate=0.123,
exchange='bittrex',
open_order_id='dry_run_buy_12345'
)
Trade.session.add(trade)
trade = Trade(
pair='ETC/BTC',
stake_amount=0.001,
amount=123.0,
fee_open=fee.return_value,
fee_close=fee.return_value,
open_rate=0.123,
close_rate=0.128,
close_profit=0.005,
exchange='bittrex',
is_open=False,
open_order_id='dry_run_sell_12345'
)
Trade.session.add(trade)
# Simulate prod entry
trade = Trade(
pair='ETC/BTC',
stake_amount=0.001,
amount=123.0,
fee_open=fee.return_value,
fee_close=fee.return_value,
open_rate=0.123,
exchange='bittrex',
open_order_id='prod_buy_12345'
)
Trade.session.add(trade)
from tests.conftest import log_has, create_mock_trades
def test_init_create_session(default_conf):
@ -476,12 +430,22 @@ def test_migrate_old(mocker, default_conf, fee):
stake=default_conf.get("stake_amount"),
amount=amount
)
insert_table_old2 = """INSERT INTO trades (exchange, pair, is_open, fee,
open_rate, close_rate, stake_amount, amount, open_date)
VALUES ('BITTREX', 'BTC_ETC', 0, {fee},
0.00258580, 0.00268580, {stake}, {amount},
'2017-11-28 12:44:24.000000')
""".format(fee=fee.return_value,
stake=default_conf.get("stake_amount"),
amount=amount
)
engine = create_engine('sqlite://')
mocker.patch('freqtrade.persistence.create_engine', lambda *args, **kwargs: engine)
# Create table using the old format
engine.execute(create_table_old)
engine.execute(insert_table_old)
engine.execute(insert_table_old2)
# Run init to test migration
init(default_conf['db_url'], default_conf['dry_run'])
@ -500,6 +464,15 @@ def test_migrate_old(mocker, default_conf, fee):
assert trade.stop_loss == 0.0
assert trade.initial_stop_loss == 0.0
assert trade.open_trade_price == trade._calc_open_trade_price()
assert trade.close_profit_abs is None
trade = Trade.query.filter(Trade.id == 2).first()
assert trade.close_rate is not None
assert trade.is_open == 0
assert trade.open_rate_requested is None
assert trade.close_rate_requested is None
assert trade.close_rate is not None
assert pytest.approx(trade.close_profit_abs) == trade.calc_profit()
def test_migrate_new(mocker, default_conf, fee, caplog):
@ -583,6 +556,7 @@ def test_migrate_new(mocker, default_conf, fee, caplog):
assert log_has("trying trades_bak2", caplog)
assert log_has("Running database migration - backup available as trades_bak2", caplog)
assert trade.open_trade_price == trade._calc_open_trade_price()
assert trade.close_profit_abs is None
def test_migrate_mid_state(mocker, default_conf, fee, caplog):
@ -757,18 +731,31 @@ def test_to_json(default_conf, fee):
assert result == {'trade_id': None,
'pair': 'ETH/BTC',
'is_open': None,
'open_date_hum': '2 hours ago',
'open_date': trade.open_date.strftime("%Y-%m-%d %H:%M:%S"),
'open_order_id': 'dry_run_buy_12345',
'close_date_hum': None,
'close_date': None,
'open_rate': 0.123,
'open_rate_requested': None,
'open_trade_price': 15.1668225,
'fee_close': 0.0025,
'fee_open': 0.0025,
'close_rate': None,
'close_rate_requested': None,
'amount': 123.0,
'stake_amount': 0.001,
'close_profit': None,
'sell_reason': None,
'stop_loss': None,
'stop_loss_pct': None,
'initial_stop_loss': None,
'initial_stop_loss_pct': None}
'initial_stop_loss_pct': None,
'min_rate': None,
'max_rate': None,
'strategy': None,
'ticker_interval': None}
# Simulate dry_run entries
trade = Trade(
@ -799,7 +786,20 @@ def test_to_json(default_conf, fee):
'stop_loss': None,
'stop_loss_pct': None,
'initial_stop_loss': None,
'initial_stop_loss_pct': None}
'initial_stop_loss_pct': None,
'close_profit': None,
'close_rate_requested': None,
'fee_close': 0.0025,
'fee_open': 0.0025,
'is_open': None,
'max_rate': None,
'min_rate': None,
'open_order_id': None,
'open_rate_requested': None,
'open_trade_price': 12.33075,
'sell_reason': None,
'strategy': None,
'ticker_interval': None}
def test_stoploss_reinitialization(default_conf, fee):

View File

@ -266,7 +266,7 @@ def test_generate_profit_graph(testdatadir):
filename = testdatadir / "backtest-result_test.json"
trades = load_backtest_data(filename)
timerange = TimeRange.parse_timerange("20180110-20180112")
pairs = ["TRX/BTC", "ADA/BTC"]
pairs = ["TRX/BTC", "XLM/BTC"]
trades = trades[trades['close_time'] < pd.Timestamp('2018-01-12', tz='UTC')]
data = history.load_data(datadir=testdatadir,
@ -292,7 +292,7 @@ def test_generate_profit_graph(testdatadir):
profit = find_trace_in_fig_data(figure.data, "Profit")
assert isinstance(profit, go.Scatter)
profit = find_trace_in_fig_data(figure.data, "Max drawdown 0.00%")
profit = find_trace_in_fig_data(figure.data, "Max drawdown 10.45%")
assert isinstance(profit, go.Scatter)
for pair in pairs: