Merge branch 'develop' into pr/xataxxx/6079
This commit is contained in:
Matthias
commit
711a6a6dbc
22
.github/workflows/ci.yml
vendored
22
.github/workflows/ci.yml
vendored
@ -3,7 +3,6 @@ name: Freqtrade CI
|
||||
on:
|
||||
push:
|
||||
branches:
|
||||
- master
|
||||
- stable
|
||||
- develop
|
||||
tags:
|
||||
@ -20,7 +19,7 @@ jobs:
|
||||
strategy:
|
||||
matrix:
|
||||
os: [ ubuntu-18.04, ubuntu-20.04 ]
|
||||
python-version: [3.7, 3.8, 3.9]
|
||||
python-version: ["3.7", "3.8", "3.9", "3.10"]
|
||||
|
||||
steps:
|
||||
- uses: actions/checkout@v2
|
||||
@ -39,7 +38,7 @@ jobs:
|
||||
|
||||
- name: pip cache (linux)
|
||||
uses: actions/cache@v2
|
||||
if: startsWith(matrix.os, 'ubuntu')
|
||||
if: runner.os == 'Linux'
|
||||
with:
|
||||
path: ~/.cache/pip
|
||||
key: test-${{ matrix.os }}-${{ matrix.python-version }}-pip
|
||||
@ -50,8 +49,9 @@ jobs:
|
||||
cd build_helpers && ./install_ta-lib.sh ${HOME}/dependencies/; cd ..
|
||||
|
||||
- name: Installation - *nix
|
||||
if: runner.os == 'Linux'
|
||||
run: |
|
||||
python -m pip install --upgrade pip
|
||||
python -m pip install --upgrade pip wheel
|
||||
export LD_LIBRARY_PATH=${HOME}/dependencies/lib:$LD_LIBRARY_PATH
|
||||
export TA_LIBRARY_PATH=${HOME}/dependencies/lib
|
||||
export TA_INCLUDE_PATH=${HOME}/dependencies/include
|
||||
@ -69,7 +69,7 @@ jobs:
|
||||
if: matrix.python-version == '3.9'
|
||||
|
||||
- name: Coveralls
|
||||
if: (startsWith(matrix.os, 'ubuntu-20') && matrix.python-version == '3.8')
|
||||
if: (runner.os == 'Linux' && matrix.python-version == '3.8')
|
||||
env:
|
||||
# Coveralls token. Not used as secret due to github not providing secrets to forked repositories
|
||||
COVERALLS_REPO_TOKEN: 6D1m0xupS3FgutfuGao8keFf9Hc0FpIXu
|
||||
@ -114,7 +114,7 @@ jobs:
|
||||
strategy:
|
||||
matrix:
|
||||
os: [ macos-latest ]
|
||||
python-version: [3.7, 3.8, 3.9]
|
||||
python-version: ["3.7", "3.8", "3.9", "3.10"]
|
||||
|
||||
steps:
|
||||
- uses: actions/checkout@v2
|
||||
@ -133,7 +133,7 @@ jobs:
|
||||
|
||||
- name: pip cache (macOS)
|
||||
uses: actions/cache@v2
|
||||
if: startsWith(matrix.os, 'macOS')
|
||||
if: runner.os == 'macOS'
|
||||
with:
|
||||
path: ~/Library/Caches/pip
|
||||
key: test-${{ matrix.os }}-${{ matrix.python-version }}-pip
|
||||
@ -144,10 +144,11 @@ jobs:
|
||||
cd build_helpers && ./install_ta-lib.sh ${HOME}/dependencies/; cd ..
|
||||
|
||||
- name: Installation - macOS
|
||||
if: runner.os == 'macOS'
|
||||
run: |
|
||||
brew update
|
||||
brew install hdf5 c-blosc
|
||||
python -m pip install --upgrade pip
|
||||
python -m pip install --upgrade pip wheel
|
||||
export LD_LIBRARY_PATH=${HOME}/dependencies/lib:$LD_LIBRARY_PATH
|
||||
export TA_LIBRARY_PATH=${HOME}/dependencies/lib
|
||||
export TA_INCLUDE_PATH=${HOME}/dependencies/include
|
||||
@ -159,7 +160,7 @@ jobs:
|
||||
pytest --random-order --cov=freqtrade --cov-config=.coveragerc
|
||||
|
||||
- name: Coveralls
|
||||
if: (startsWith(matrix.os, 'ubuntu-20') && matrix.python-version == '3.8')
|
||||
if: (runner.os == 'Linux' && matrix.python-version == '3.8')
|
||||
env:
|
||||
# Coveralls token. Not used as secret due to github not providing secrets to forked repositories
|
||||
COVERALLS_REPO_TOKEN: 6D1m0xupS3FgutfuGao8keFf9Hc0FpIXu
|
||||
@ -205,7 +206,7 @@ jobs:
|
||||
strategy:
|
||||
matrix:
|
||||
os: [ windows-latest ]
|
||||
python-version: [3.7, 3.8]
|
||||
python-version: ["3.7", "3.8", "3.9", "3.10"]
|
||||
|
||||
steps:
|
||||
- uses: actions/checkout@v2
|
||||
@ -217,7 +218,6 @@ jobs:
|
||||
|
||||
- name: Pip cache (Windows)
|
||||
uses: actions/cache@preview
|
||||
if: startsWith(runner.os, 'Windows')
|
||||
with:
|
||||
path: ~\AppData\Local\pip\Cache
|
||||
key: ${{ matrix.os }}-${{ matrix.python-version }}-pip
|
||||
|
||||
@ -1,4 +1,4 @@
|
||||
FROM python:3.9.9-slim-bullseye as base
|
||||
FROM python:3.10.0-slim-bullseye as base
|
||||
|
||||
# Setup env
|
||||
ENV LANG C.UTF-8
|
||||
|
||||
@ -197,7 +197,7 @@ To run this bot we recommend you a cloud instance with a minimum of:
|
||||
|
||||
### Software requirements
|
||||
|
||||
- [Python 3.7.x](http://docs.python-guide.org/en/latest/starting/installation/)
|
||||
- [Python >= 3.7](http://docs.python-guide.org/en/latest/starting/installation/)
|
||||
- [pip](https://pip.pypa.io/en/stable/installing/)
|
||||
- [git](https://git-scm.com/book/en/v2/Getting-Started-Installing-Git)
|
||||
- [TA-Lib](https://mrjbq7.github.io/ta-lib/install.html)
|
||||
|
||||
BIN
build_helpers/TA_Lib-0.4.22-cp310-cp310-win_amd64.whl
Normal file
BIN
build_helpers/TA_Lib-0.4.22-cp310-cp310-win_amd64.whl
Normal file
Binary file not shown.
@ -1,7 +1,7 @@
|
||||
# Downloads don't work automatically, since the URL is regenerated via javascript.
|
||||
# Downloaded from https://www.lfd.uci.edu/~gohlke/pythonlibs/#ta-lib
|
||||
|
||||
python -m pip install --upgrade pip
|
||||
python -m pip install --upgrade pip wheel
|
||||
|
||||
$pyv = python -c "import sys; print(f'{sys.version_info.major}.{sys.version_info.minor}')"
|
||||
|
||||
@ -14,6 +14,8 @@ if ($pyv -eq '3.8') {
|
||||
if ($pyv -eq '3.9') {
|
||||
pip install build_helpers\TA_Lib-0.4.22-cp39-cp39-win_amd64.whl
|
||||
}
|
||||
|
||||
if ($pyv -eq '3.10') {
|
||||
pip install build_helpers\TA_Lib-0.4.22-cp310-cp310-win_amd64.whl
|
||||
}
|
||||
pip install -r requirements-dev.txt
|
||||
pip install -e .
|
||||
|
||||
@ -176,12 +176,15 @@ Log messages are send to `syslog` with the `user` facility. So you can see them
|
||||
On many systems `syslog` (`rsyslog`) fetches data from `journald` (and vice versa), so both `--logfile syslog` or `--logfile journald` can be used and the messages be viewed with both `journalctl` and a syslog viewer utility. You can combine this in any way which suites you better.
|
||||
|
||||
For `rsyslog` the messages from the bot can be redirected into a separate dedicated log file. To achieve this, add
|
||||
|
||||
```
|
||||
if $programname startswith "freqtrade" then -/var/log/freqtrade.log
|
||||
```
|
||||
|
||||
to one of the rsyslog configuration files, for example at the end of the `/etc/rsyslog.d/50-default.conf`.
|
||||
|
||||
For `syslog` (`rsyslog`), the reduction mode can be switched on. This will reduce the number of repeating messages. For instance, multiple bot Heartbeat messages will be reduced to a single message when nothing else happens with the bot. To achieve this, set in `/etc/rsyslog.conf`:
|
||||
|
||||
```
|
||||
# Filter duplicated messages
|
||||
$RepeatedMsgReduction on
|
||||
|
||||
Binary file not shown.
|
Before Width: | Height: | Size: 121 KiB After Width: | Height: | Size: 143 KiB |
@ -484,8 +484,8 @@ Since backtesting lacks some detailed information about what happens within a ca
|
||||
- ROI applies before trailing-stop, ensuring profits are "top-capped" at ROI if both ROI and trailing stop applies
|
||||
- Sell-reason does not explain if a trade was positive or negative, just what triggered the sell (this can look odd if negative ROI values are used)
|
||||
- Evaluation sequence (if multiple signals happen on the same candle)
|
||||
- ROI (if not stoploss)
|
||||
- Sell-signal
|
||||
- ROI (if not stoploss)
|
||||
- Stoploss
|
||||
|
||||
Taking these assumptions, backtesting tries to mirror real trading as closely as possible. However, backtesting will **never** replace running a strategy in dry-run mode.
|
||||
|
||||
@ -56,10 +56,6 @@ OS Specific steps are listed first, the [Common](#common) section below is neces
|
||||
!!! Note
|
||||
Python3.7 or higher and the corresponding pip are assumed to be available.
|
||||
|
||||
!!! Warning "Python 3.10 support"
|
||||
Due to issues with dependencies, freqtrade is currently unable to support python 3.10.
|
||||
We're working on supporting python 3.10, are however dependant on support from dependencies.
|
||||
|
||||
=== "Debian/Ubuntu"
|
||||
#### Install necessary dependencies
|
||||
|
||||
@ -424,16 +420,3 @@ open /Library/Developer/CommandLineTools/Packages/macOS_SDK_headers_for_macOS_10
|
||||
```
|
||||
|
||||
If this file is inexistent, then you're probably on a different version of MacOS, so you may need to consult the internet for specific resolution details.
|
||||
|
||||
### MacOS installation error with python 3.9
|
||||
|
||||
When using python 3.9 on macOS, it's currently necessary to install some os-level modules to allow dependencies to compile.
|
||||
The errors you'll see happen during installation and are related to the installation of `tables` or `blosc`.
|
||||
|
||||
You can install the necessary libraries with the following command:
|
||||
|
||||
```bash
|
||||
brew install hdf5 c-blosc
|
||||
```
|
||||
|
||||
After this, please run the installation (script) again.
|
||||
|
||||
@ -286,6 +286,8 @@ The `plot-profit` subcommand shows an interactive graph with three plots:
|
||||
* The summarized profit made by backtesting.
|
||||
Note that this is not the real-world profit, but more of an estimate.
|
||||
* Profit for each individual pair.
|
||||
* Parallelism of trades.
|
||||
* Underwater (Periods of drawdown).
|
||||
|
||||
The first graph is good to get a grip of how the overall market progresses.
|
||||
|
||||
@ -295,6 +297,8 @@ This graph will also highlight the start (and end) of the Max drawdown period.
|
||||
|
||||
The third graph can be useful to spot outliers, events in pairs that cause profit spikes.
|
||||
|
||||
The forth graph can help you analyze trade parallelism, showing how often max_open_trades have been maxed out.
|
||||
|
||||
Possible options for the `freqtrade plot-profit` subcommand:
|
||||
|
||||
```
|
||||
|
||||
@ -25,7 +25,7 @@ Install ta-lib according to the [ta-lib documentation](https://github.com/mrjbq7
|
||||
|
||||
As compiling from source on windows has heavy dependencies (requires a partial visual studio installation), there is also a repository of unofficial pre-compiled windows Wheels [here](https://www.lfd.uci.edu/~gohlke/pythonlibs/#ta-lib), which need to be downloaded and installed using `pip install TA_Lib‑0.4.22‑cp38‑cp38‑win_amd64.whl` (make sure to use the version matching your python version).
|
||||
|
||||
Freqtrade provides these dependencies for the latest 3 Python versions (3.7, 3.8 and 3.9) and for 64bit Windows.
|
||||
Freqtrade provides these dependencies for the latest 3 Python versions (3.7, 3.8, 3.9 and 3.10) and for 64bit Windows.
|
||||
Other versions must be downloaded from the above link.
|
||||
|
||||
``` powershell
|
||||
|
||||
@ -1,6 +1,6 @@
|
||||
from datetime import datetime, timezone
|
||||
|
||||
from cachetools.ttl import TTLCache
|
||||
from cachetools import TTLCache
|
||||
|
||||
|
||||
class PeriodicCache(TTLCache):
|
||||
|
||||
@ -325,6 +325,7 @@ def combine_dataframes_with_mean(data: Dict[str, pd.DataFrame],
|
||||
:param column: Column in the original dataframes to use
|
||||
:return: DataFrame with the column renamed to the dict key, and a column
|
||||
named mean, containing the mean of all pairs.
|
||||
:raise: ValueError if no data is provided.
|
||||
"""
|
||||
df_comb = pd.concat([data[pair].set_index('date').rename(
|
||||
{column: pair}, axis=1)[pair] for pair in data], axis=1)
|
||||
@ -360,6 +361,36 @@ def create_cum_profit(df: pd.DataFrame, trades: pd.DataFrame, col_name: str,
|
||||
return df
|
||||
|
||||
|
||||
def _calc_drawdown_series(profit_results: pd.DataFrame, *, date_col: str, value_col: str
|
||||
) -> pd.DataFrame:
|
||||
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']
|
||||
max_drawdown_df['date'] = profit_results.loc[:, date_col]
|
||||
return max_drawdown_df
|
||||
|
||||
|
||||
def calculate_underwater(trades: pd.DataFrame, *, date_col: str = 'close_date',
|
||||
value_col: str = 'profit_ratio'
|
||||
):
|
||||
"""
|
||||
Calculate max drawdown and the corresponding close dates
|
||||
:param trades: DataFrame containing trades (requires columns close_date and profit_ratio)
|
||||
:param date_col: Column in DataFrame to use for dates (defaults to 'close_date')
|
||||
:param value_col: Column in DataFrame to use for values (defaults to 'profit_ratio')
|
||||
:return: Tuple (float, highdate, lowdate, highvalue, lowvalue) with absolute max drawdown,
|
||||
high and low time and high and low value.
|
||||
:raise: ValueError if trade-dataframe was found empty.
|
||||
"""
|
||||
if len(trades) == 0:
|
||||
raise ValueError("Trade dataframe empty.")
|
||||
profit_results = trades.sort_values(date_col).reset_index(drop=True)
|
||||
max_drawdown_df = _calc_drawdown_series(profit_results, date_col=date_col, value_col=value_col)
|
||||
|
||||
return max_drawdown_df
|
||||
|
||||
|
||||
def calculate_max_drawdown(trades: pd.DataFrame, *, date_col: str = 'close_date',
|
||||
value_col: str = 'profit_ratio'
|
||||
) -> Tuple[float, pd.Timestamp, pd.Timestamp, float, float]:
|
||||
@ -375,10 +406,7 @@ def calculate_max_drawdown(trades: pd.DataFrame, *, date_col: str = 'close_date'
|
||||
if len(trades) == 0:
|
||||
raise ValueError("Trade dataframe empty.")
|
||||
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']
|
||||
max_drawdown_df = _calc_drawdown_series(profit_results, date_col=date_col, value_col=value_col)
|
||||
|
||||
idxmin = max_drawdown_df['drawdown'].idxmin()
|
||||
if idxmin == 0:
|
||||
|
||||
@ -201,7 +201,7 @@ class IDataHandler(ABC):
|
||||
enddate = pairdf.iloc[-1]['date']
|
||||
|
||||
if timerange_startup:
|
||||
self._validate_pairdata(pair, pairdf, timerange_startup)
|
||||
self._validate_pairdata(pair, pairdf, timeframe, timerange_startup)
|
||||
pairdf = trim_dataframe(pairdf, timerange_startup)
|
||||
if self._check_empty_df(pairdf, pair, timeframe, warn_no_data):
|
||||
return pairdf
|
||||
@ -228,7 +228,7 @@ class IDataHandler(ABC):
|
||||
return True
|
||||
return False
|
||||
|
||||
def _validate_pairdata(self, pair, pairdata: DataFrame, timerange: TimeRange):
|
||||
def _validate_pairdata(self, pair, pairdata: DataFrame, timeframe: str, timerange: TimeRange):
|
||||
"""
|
||||
Validates pairdata for missing data at start end end and logs warnings.
|
||||
:param pairdata: Dataframe to validate
|
||||
@ -238,12 +238,12 @@ class IDataHandler(ABC):
|
||||
if timerange.starttype == 'date':
|
||||
start = datetime.fromtimestamp(timerange.startts, tz=timezone.utc)
|
||||
if pairdata.iloc[0]['date'] > start:
|
||||
logger.warning(f"Missing data at start for pair {pair}, "
|
||||
logger.warning(f"Missing data at start for pair {pair} at {timeframe}, "
|
||||
f"data starts at {pairdata.iloc[0]['date']:%Y-%m-%d %H:%M:%S}")
|
||||
if timerange.stoptype == 'date':
|
||||
stop = datetime.fromtimestamp(timerange.stopts, tz=timezone.utc)
|
||||
if pairdata.iloc[-1]['date'] < stop:
|
||||
logger.warning(f"Missing data at end for pair {pair}, "
|
||||
logger.warning(f"Missing data at end for pair {pair} at {timeframe}, "
|
||||
f"data ends at {pairdata.iloc[-1]['date']:%Y-%m-%d %H:%M:%S}")
|
||||
|
||||
|
||||
|
||||
@ -4,9 +4,20 @@ import time
|
||||
from functools import wraps
|
||||
|
||||
from freqtrade.exceptions import DDosProtection, RetryableOrderError, TemporaryError
|
||||
from freqtrade.mixins import LoggingMixin
|
||||
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
__logging_mixin = None
|
||||
|
||||
|
||||
def _get_logging_mixin():
|
||||
# Logging-mixin to cache kucoin responses
|
||||
# Only to be used in retrier
|
||||
global __logging_mixin
|
||||
if not __logging_mixin:
|
||||
__logging_mixin = LoggingMixin(logger)
|
||||
return __logging_mixin
|
||||
|
||||
|
||||
# Maximum default retry count.
|
||||
@ -72,28 +83,33 @@ def calculate_backoff(retrycount, max_retries):
|
||||
def retrier_async(f):
|
||||
async def wrapper(*args, **kwargs):
|
||||
count = kwargs.pop('count', API_RETRY_COUNT)
|
||||
kucoin = args[0].name == "Kucoin" # Check if the exchange is KuCoin.
|
||||
try:
|
||||
return await f(*args, **kwargs)
|
||||
except TemporaryError as ex:
|
||||
logger.warning('%s() returned exception: "%s"', f.__name__, ex)
|
||||
msg = f'{f.__name__}() returned exception: "{ex}". '
|
||||
if count > 0:
|
||||
logger.warning('retrying %s() still for %s times', f.__name__, count)
|
||||
msg += f'Retrying still for {count} times.'
|
||||
count -= 1
|
||||
kwargs.update({'count': count})
|
||||
kwargs['count'] = count
|
||||
if isinstance(ex, DDosProtection):
|
||||
if "kucoin" in str(ex) and "429000" in str(ex):
|
||||
if kucoin and "429000" in str(ex):
|
||||
# Temporary fix for 429000 error on kucoin
|
||||
# see https://github.com/freqtrade/freqtrade/issues/5700 for details.
|
||||
logger.warning(
|
||||
_get_logging_mixin().log_once(
|
||||
f"Kucoin 429 error, avoid triggering DDosProtection backoff delay. "
|
||||
f"{count} tries left before giving up")
|
||||
f"{count} tries left before giving up", logmethod=logger.warning)
|
||||
# Reset msg to avoid logging too many times.
|
||||
msg = ''
|
||||
else:
|
||||
backoff_delay = calculate_backoff(count + 1, API_RETRY_COUNT)
|
||||
logger.info(f"Applying DDosProtection backoff delay: {backoff_delay}")
|
||||
await asyncio.sleep(backoff_delay)
|
||||
if msg:
|
||||
logger.warning(msg)
|
||||
return await wrapper(*args, **kwargs)
|
||||
else:
|
||||
logger.warning('Giving up retrying: %s()', f.__name__)
|
||||
logger.warning(msg + 'Giving up.')
|
||||
raise ex
|
||||
return wrapper
|
||||
|
||||
@ -106,9 +122,9 @@ def retrier(_func=None, retries=API_RETRY_COUNT):
|
||||
try:
|
||||
return f(*args, **kwargs)
|
||||
except (TemporaryError, RetryableOrderError) as ex:
|
||||
logger.warning('%s() returned exception: "%s"', f.__name__, ex)
|
||||
msg = f'{f.__name__}() returned exception: "{ex}". '
|
||||
if count > 0:
|
||||
logger.warning('retrying %s() still for %s times', f.__name__, count)
|
||||
logger.warning(msg + f'Retrying still for {count} times.')
|
||||
count -= 1
|
||||
kwargs.update({'count': count})
|
||||
if isinstance(ex, (DDosProtection, RetryableOrderError)):
|
||||
@ -118,7 +134,7 @@ def retrier(_func=None, retries=API_RETRY_COUNT):
|
||||
time.sleep(backoff_delay)
|
||||
return wrapper(*args, **kwargs)
|
||||
else:
|
||||
logger.warning('Giving up retrying: %s()', f.__name__)
|
||||
logger.warning(msg + 'Giving up.')
|
||||
raise ex
|
||||
return wrapper
|
||||
# Support both @retrier and @retrier(retries=2) syntax
|
||||
|
||||
@ -83,6 +83,8 @@ class Exchange:
|
||||
self._api: ccxt.Exchange = None
|
||||
self._api_async: ccxt_async.Exchange = None
|
||||
self._markets: Dict = {}
|
||||
self.loop = asyncio.new_event_loop()
|
||||
asyncio.set_event_loop(self.loop)
|
||||
|
||||
self._config.update(config)
|
||||
|
||||
@ -170,8 +172,10 @@ class Exchange:
|
||||
|
||||
def close(self):
|
||||
logger.debug("Exchange object destroyed, closing async loop")
|
||||
if self._api_async and inspect.iscoroutinefunction(self._api_async.close):
|
||||
asyncio.get_event_loop().run_until_complete(self._api_async.close())
|
||||
if (self._api_async and inspect.iscoroutinefunction(self._api_async.close)
|
||||
and self._api_async.session):
|
||||
logger.info("Closing async ccxt session.")
|
||||
self.loop.run_until_complete(self._api_async.close())
|
||||
|
||||
def _init_ccxt(self, exchange_config: Dict[str, Any], ccxt_module: CcxtModuleType = ccxt,
|
||||
ccxt_kwargs: Dict = {}) -> ccxt.Exchange:
|
||||
@ -326,7 +330,7 @@ class Exchange:
|
||||
def _load_async_markets(self, reload: bool = False) -> None:
|
||||
try:
|
||||
if self._api_async:
|
||||
asyncio.get_event_loop().run_until_complete(
|
||||
self.loop.run_until_complete(
|
||||
self._api_async.load_markets(reload=reload))
|
||||
|
||||
except (asyncio.TimeoutError, ccxt.BaseError) as e:
|
||||
@ -1227,7 +1231,7 @@ class Exchange:
|
||||
:param since_ms: Timestamp in milliseconds to get history from
|
||||
:return: List with candle (OHLCV) data
|
||||
"""
|
||||
pair, timeframe, data = asyncio.get_event_loop().run_until_complete(
|
||||
pair, timeframe, data = self.loop.run_until_complete(
|
||||
self._async_get_historic_ohlcv(pair=pair, timeframe=timeframe,
|
||||
since_ms=since_ms, is_new_pair=is_new_pair))
|
||||
logger.info(f"Downloaded data for {pair} with length {len(data)}.")
|
||||
@ -1329,8 +1333,10 @@ class Exchange:
|
||||
results_df = {}
|
||||
# Chunk requests into batches of 100 to avoid overwelming ccxt Throttling
|
||||
for input_coro in chunks(input_coroutines, 100):
|
||||
results = asyncio.get_event_loop().run_until_complete(
|
||||
asyncio.gather(*input_coro, return_exceptions=True))
|
||||
async def gather_stuff():
|
||||
return await asyncio.gather(*input_coro, return_exceptions=True)
|
||||
|
||||
results = self.loop.run_until_complete(gather_stuff())
|
||||
|
||||
# handle caching
|
||||
for res in results:
|
||||
@ -1566,7 +1572,7 @@ class Exchange:
|
||||
if not self.exchange_has("fetchTrades"):
|
||||
raise OperationalException("This exchange does not support downloading Trades.")
|
||||
|
||||
return asyncio.get_event_loop().run_until_complete(
|
||||
return self.loop.run_until_complete(
|
||||
self._async_get_trade_history(pair=pair, since=since,
|
||||
until=until, from_id=from_id))
|
||||
|
||||
|
||||
@ -126,6 +126,7 @@ class FreqtradeBot(LoggingMixin):
|
||||
|
||||
self.rpc.cleanup()
|
||||
cleanup_db()
|
||||
self.exchange.close()
|
||||
|
||||
def startup(self) -> None:
|
||||
"""
|
||||
|
||||
@ -246,6 +246,9 @@ class Backtesting:
|
||||
Helper function to convert a processed dataframes into lists for performance reasons.
|
||||
|
||||
Used by backtest() - so keep this optimized for performance.
|
||||
|
||||
:param processed: a processed dictionary with format {pair, data}, which gets cleared to
|
||||
optimize memory usage!
|
||||
"""
|
||||
# Every change to this headers list must evaluate further usages of the resulting tuple
|
||||
# and eventually change the constants for indexes at the top
|
||||
@ -254,7 +257,8 @@ class Backtesting:
|
||||
self.progress.init_step(BacktestState.CONVERT, len(processed))
|
||||
|
||||
# Create dict with data
|
||||
for pair, pair_data in processed.items():
|
||||
for pair in processed.keys():
|
||||
pair_data = processed[pair]
|
||||
self.check_abort()
|
||||
self.progress.increment()
|
||||
if not pair_data.empty:
|
||||
@ -283,6 +287,9 @@ class Backtesting:
|
||||
# Convert from Pandas to list for performance reasons
|
||||
# (Looping Pandas is slow.)
|
||||
data[pair] = df_analyzed[headers].values.tolist()
|
||||
|
||||
# Do not hold on to old data to reduce memory usage
|
||||
processed[pair] = pair_data = None
|
||||
return data
|
||||
|
||||
def _get_close_rate(self, sell_row: Tuple, trade: LocalTrade, sell: SellCheckTuple,
|
||||
@ -571,7 +578,8 @@ class Backtesting:
|
||||
Of course try to not have ugly code. By some accessor are sometime slower than functions.
|
||||
Avoid extensive logging in this method and functions it calls.
|
||||
|
||||
:param processed: a processed dictionary with format {pair, data}
|
||||
:param processed: a processed dictionary with format {pair, data}, which gets cleared to
|
||||
optimize memory usage!
|
||||
:param start_date: backtesting timerange start datetime
|
||||
:param end_date: backtesting timerange end datetime
|
||||
:param max_open_trades: maximum number of concurrent trades, <= 0 means unlimited
|
||||
|
||||
@ -422,6 +422,7 @@ class Hyperopt:
|
||||
self.backtesting.exchange.close()
|
||||
self.backtesting.exchange._api = None # type: ignore
|
||||
self.backtesting.exchange._api_async = None # type: ignore
|
||||
self.backtesting.exchange.loop = None # type: ignore
|
||||
# self.backtesting.exchange = None # type: ignore
|
||||
self.backtesting.pairlists = None # type: ignore
|
||||
|
||||
|
||||
@ -5,7 +5,8 @@ from typing import Any, Dict, List
|
||||
import pandas as pd
|
||||
|
||||
from freqtrade.configuration import TimeRange
|
||||
from freqtrade.data.btanalysis import (calculate_max_drawdown, combine_dataframes_with_mean,
|
||||
from freqtrade.data.btanalysis import (analyze_trade_parallelism, calculate_max_drawdown,
|
||||
calculate_underwater, combine_dataframes_with_mean,
|
||||
create_cum_profit, extract_trades_of_period, load_trades)
|
||||
from freqtrade.data.converter import trim_dataframe
|
||||
from freqtrade.data.dataprovider import DataProvider
|
||||
@ -185,6 +186,48 @@ def add_max_drawdown(fig, row, trades: pd.DataFrame, df_comb: pd.DataFrame,
|
||||
return fig
|
||||
|
||||
|
||||
def add_underwater(fig, row, trades: pd.DataFrame) -> make_subplots:
|
||||
"""
|
||||
Add underwater plot
|
||||
"""
|
||||
try:
|
||||
underwater = calculate_underwater(trades, value_col="profit_abs")
|
||||
|
||||
underwater = go.Scatter(
|
||||
x=underwater['date'],
|
||||
y=underwater['drawdown'],
|
||||
name="Underwater Plot",
|
||||
fill='tozeroy',
|
||||
fillcolor='#cc362b',
|
||||
line={'color': '#cc362b'},
|
||||
)
|
||||
fig.add_trace(underwater, row, 1)
|
||||
except ValueError:
|
||||
logger.warning("No trades found - not plotting underwater plot")
|
||||
return fig
|
||||
|
||||
|
||||
def add_parallelism(fig, row, trades: pd.DataFrame, timeframe: str) -> make_subplots:
|
||||
"""
|
||||
Add Chart showing trade parallelism
|
||||
"""
|
||||
try:
|
||||
result = analyze_trade_parallelism(trades, timeframe)
|
||||
|
||||
drawdown = go.Scatter(
|
||||
x=result.index,
|
||||
y=result['open_trades'],
|
||||
name="Parallel trades",
|
||||
fill='tozeroy',
|
||||
fillcolor='#242222',
|
||||
line={'color': '#242222'},
|
||||
)
|
||||
fig.add_trace(drawdown, row, 1)
|
||||
except ValueError:
|
||||
logger.warning("No trades found - not plotting Parallelism.")
|
||||
return fig
|
||||
|
||||
|
||||
def plot_trades(fig, trades: pd.DataFrame) -> make_subplots:
|
||||
"""
|
||||
Add trades to "fig"
|
||||
@ -460,7 +503,12 @@ def generate_candlestick_graph(pair: str, data: pd.DataFrame, trades: pd.DataFra
|
||||
def generate_profit_graph(pairs: str, data: Dict[str, pd.DataFrame],
|
||||
trades: pd.DataFrame, timeframe: str, stake_currency: str) -> go.Figure:
|
||||
# Combine close-values for all pairs, rename columns to "pair"
|
||||
try:
|
||||
df_comb = combine_dataframes_with_mean(data, "close")
|
||||
except ValueError:
|
||||
raise OperationalException(
|
||||
"No data found. Please make sure that data is available for "
|
||||
"the timerange and pairs selected.")
|
||||
|
||||
# Trim trades to available OHLCV data
|
||||
trades = extract_trades_of_period(df_comb, trades, date_index=True)
|
||||
@ -477,20 +525,30 @@ def generate_profit_graph(pairs: str, data: Dict[str, pd.DataFrame],
|
||||
name='Avg close price',
|
||||
)
|
||||
|
||||
fig = make_subplots(rows=3, cols=1, shared_xaxes=True,
|
||||
row_width=[1, 1, 1],
|
||||
fig = make_subplots(rows=5, cols=1, shared_xaxes=True,
|
||||
row_heights=[1, 1, 1, 0.5, 1],
|
||||
vertical_spacing=0.05,
|
||||
subplot_titles=["AVG Close Price", "Combined Profit", "Profit per pair"])
|
||||
subplot_titles=[
|
||||
"AVG Close Price",
|
||||
"Combined Profit",
|
||||
"Profit per pair",
|
||||
"Parallelism",
|
||||
"Underwater",
|
||||
])
|
||||
fig['layout'].update(title="Freqtrade Profit plot")
|
||||
fig['layout']['yaxis1'].update(title='Price')
|
||||
fig['layout']['yaxis2'].update(title=f'Profit {stake_currency}')
|
||||
fig['layout']['yaxis3'].update(title=f'Profit {stake_currency}')
|
||||
fig['layout']['yaxis4'].update(title='Trade count')
|
||||
fig['layout']['yaxis5'].update(title='Underwater Plot')
|
||||
fig['layout']['xaxis']['rangeslider'].update(visible=False)
|
||||
fig.update_layout(modebar_add=["v1hovermode", "toggleSpikeLines"])
|
||||
|
||||
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, timeframe)
|
||||
fig = add_parallelism(fig, 4, trades, timeframe)
|
||||
fig = add_underwater(fig, 5, trades)
|
||||
|
||||
for pair in pairs:
|
||||
profit_col = f'cum_profit_{pair}'
|
||||
|
||||
@ -8,7 +8,7 @@ from typing import Any, Dict, List, Optional
|
||||
|
||||
import arrow
|
||||
import numpy as np
|
||||
from cachetools.ttl import TTLCache
|
||||
from cachetools import TTLCache
|
||||
from pandas import DataFrame
|
||||
|
||||
from freqtrade.exceptions import OperationalException
|
||||
|
||||
@ -8,7 +8,7 @@ from functools import partial
|
||||
from typing import Any, Dict, List
|
||||
|
||||
import arrow
|
||||
from cachetools.ttl import TTLCache
|
||||
from cachetools import TTLCache
|
||||
|
||||
from freqtrade.exceptions import OperationalException
|
||||
from freqtrade.exchange import timeframe_to_minutes
|
||||
|
||||
@ -6,7 +6,7 @@ from copy import deepcopy
|
||||
from typing import Any, Dict, List, Optional
|
||||
|
||||
import arrow
|
||||
from cachetools.ttl import TTLCache
|
||||
from cachetools import TTLCache
|
||||
from pandas import DataFrame
|
||||
|
||||
from freqtrade.exceptions import OperationalException
|
||||
|
||||
@ -47,7 +47,7 @@ class UvicornServer(uvicorn.Server):
|
||||
else:
|
||||
asyncio.set_event_loop(uvloop.new_event_loop())
|
||||
try:
|
||||
loop = asyncio.get_event_loop()
|
||||
loop = asyncio.get_running_loop()
|
||||
except RuntimeError:
|
||||
# When running in a thread, we'll not have an eventloop yet.
|
||||
loop = asyncio.new_event_loop()
|
||||
|
||||
@ -7,7 +7,7 @@ import datetime
|
||||
import logging
|
||||
from typing import Dict, List
|
||||
|
||||
from cachetools.ttl import TTLCache
|
||||
from cachetools import TTLCache
|
||||
from pycoingecko import CoinGeckoAPI
|
||||
from requests.exceptions import RequestException
|
||||
|
||||
|
||||
@ -199,8 +199,8 @@ class Telegram(RPCHandler):
|
||||
|
||||
self._updater.start_polling(
|
||||
bootstrap_retries=-1,
|
||||
timeout=30,
|
||||
read_latency=60,
|
||||
timeout=20,
|
||||
read_latency=60, # Assumed transmission latency
|
||||
drop_pending_updates=True,
|
||||
)
|
||||
logger.info(
|
||||
@ -213,6 +213,7 @@ class Telegram(RPCHandler):
|
||||
Stops all running telegram threads.
|
||||
:return: None
|
||||
"""
|
||||
# This can take up to `timeout` from the call to `start_polling`.
|
||||
self._updater.stop()
|
||||
|
||||
def _format_buy_msg(self, msg: Dict[str, Any]) -> str:
|
||||
|
||||
@ -727,23 +727,21 @@ class IStrategy(ABC, HyperStrategyMixin):
|
||||
custom_reason = custom_reason[:CUSTOM_SELL_MAX_LENGTH]
|
||||
else:
|
||||
custom_reason = None
|
||||
# TODO: return here if sell-signal should be favored over ROI
|
||||
|
||||
# Start evaluations
|
||||
# Sequence:
|
||||
# ROI (if not stoploss)
|
||||
# Sell-signal
|
||||
# Stoploss
|
||||
if roi_reached and stoplossflag.sell_type != SellType.STOP_LOSS:
|
||||
logger.debug(f"{trade.pair} - Required profit reached. sell_type=SellType.ROI")
|
||||
return SellCheckTuple(sell_type=SellType.ROI)
|
||||
|
||||
if sell_signal != SellType.NONE:
|
||||
if sell_signal in (SellType.CUSTOM_SELL, SellType.SELL_SIGNAL):
|
||||
logger.debug(f"{trade.pair} - Sell signal received. "
|
||||
f"sell_type=SellType.{sell_signal.name}" +
|
||||
(f", custom_reason={custom_reason}" if custom_reason else ""))
|
||||
return SellCheckTuple(sell_type=sell_signal, sell_reason=custom_reason)
|
||||
|
||||
# Start evaluations
|
||||
# Sequence:
|
||||
# Sell-signal
|
||||
# ROI (if not stoploss)
|
||||
# Stoploss
|
||||
if roi_reached and stoplossflag.sell_type != SellType.STOP_LOSS:
|
||||
logger.debug(f"{trade.pair} - Required profit reached. sell_type=SellType.ROI")
|
||||
return SellCheckTuple(sell_type=SellType.ROI)
|
||||
|
||||
if stoplossflag.sell_flag:
|
||||
|
||||
logger.debug(f"{trade.pair} - Stoploss hit. sell_type={stoplossflag.sell_type}")
|
||||
|
||||
@ -23,6 +23,7 @@ exclude = '''
|
||||
line_length = 100
|
||||
multi_line_output=0
|
||||
lines_after_imports=2
|
||||
skip_glob = ["**/.env*", "**/env/*", "**/.venv/*", "**/docs/*"]
|
||||
|
||||
[build-system]
|
||||
requires = ["setuptools >= 46.4.0", "wheel"]
|
||||
|
||||
@ -1,4 +1,5 @@
|
||||
numpy==1.21.5
|
||||
numpy==1.21.5; python_version <= '3.7'
|
||||
numpy==1.22.0; python_version > '3.7'
|
||||
pandas==1.3.5
|
||||
pandas-ta==0.3.14b
|
||||
|
||||
@ -18,7 +19,7 @@ technical==1.3.0
|
||||
tabulate==0.8.9
|
||||
pycoingecko==2.2.0
|
||||
jinja2==3.0.3
|
||||
tables==3.6.1
|
||||
tables==3.7.0
|
||||
blosc==1.10.6
|
||||
|
||||
# find first, C search in arrays
|
||||
|
||||
@ -17,6 +17,7 @@ classifiers =
|
||||
Programming Language :: Python :: 3.7
|
||||
Programming Language :: Python :: 3.8
|
||||
Programming Language :: Python :: 3.9
|
||||
Programming Language :: Python :: 3.10
|
||||
Operating System :: MacOS
|
||||
Operating System :: Unix
|
||||
Topic :: Office/Business :: Financial :: Investment
|
||||
|
||||
5
setup.sh
5
setup.sh
@ -25,7 +25,7 @@ function check_installed_python() {
|
||||
exit 2
|
||||
fi
|
||||
|
||||
for v in 9 8 7
|
||||
for v in 9 10 8 7
|
||||
do
|
||||
PYTHON="python3.${v}"
|
||||
which $PYTHON
|
||||
@ -37,7 +37,6 @@ function check_installed_python() {
|
||||
done
|
||||
|
||||
echo "No usable python found. Please make sure to have python3.7 or newer installed."
|
||||
echo "python3.10 is currently not supported."
|
||||
exit 1
|
||||
}
|
||||
|
||||
@ -220,7 +219,7 @@ function install() {
|
||||
install_redhat
|
||||
else
|
||||
echo "This script does not support your OS."
|
||||
echo "If you have Python version 3.7 - 3.9, pip, virtualenv, ta-lib you can continue."
|
||||
echo "If you have Python version 3.7 - 3.10, pip, virtualenv, ta-lib you can continue."
|
||||
echo "Wait 10 seconds to continue the next install steps or use ctrl+c to interrupt this shell."
|
||||
sleep 10
|
||||
fi
|
||||
|
||||
@ -4,7 +4,6 @@ import logging
|
||||
import re
|
||||
from copy import deepcopy
|
||||
from datetime import datetime, timedelta
|
||||
from functools import reduce
|
||||
from pathlib import Path
|
||||
from unittest.mock import MagicMock, Mock, PropertyMock
|
||||
|
||||
@ -50,17 +49,23 @@ def pytest_configure(config):
|
||||
|
||||
|
||||
def log_has(line, logs):
|
||||
# caplog mocker returns log as a tuple: ('freqtrade.something', logging.WARNING, 'foobar')
|
||||
# and we want to match line against foobar in the tuple
|
||||
return reduce(lambda a, b: a or b,
|
||||
filter(lambda x: x[2] == line, logs.record_tuples),
|
||||
False)
|
||||
"""Check if line is found on some caplog's message."""
|
||||
return any(line == message for message in logs.messages)
|
||||
|
||||
|
||||
def log_has_re(line, logs):
|
||||
return reduce(lambda a, b: a or b,
|
||||
filter(lambda x: re.match(line, x[2]), logs.record_tuples),
|
||||
False)
|
||||
"""Check if line matches some caplog's message."""
|
||||
return any(re.match(line, message) for message in logs.messages)
|
||||
|
||||
|
||||
def num_log_has(line, logs):
|
||||
"""Check how many times line is found in caplog's messages."""
|
||||
return sum(line == message for message in logs.messages)
|
||||
|
||||
|
||||
def num_log_has_re(line, logs):
|
||||
"""Check how many times line matches caplog's messages."""
|
||||
return sum(bool(re.match(line, message)) for message in logs.messages)
|
||||
|
||||
|
||||
def get_args(args):
|
||||
|
||||
@ -11,10 +11,10 @@ from freqtrade.constants import LAST_BT_RESULT_FN
|
||||
from freqtrade.data.btanalysis import (BT_DATA_COLUMNS, BT_DATA_COLUMNS_MID, BT_DATA_COLUMNS_OLD,
|
||||
analyze_trade_parallelism, calculate_csum,
|
||||
calculate_market_change, calculate_max_drawdown,
|
||||
combine_dataframes_with_mean, create_cum_profit,
|
||||
extract_trades_of_period, get_latest_backtest_filename,
|
||||
get_latest_hyperopt_file, load_backtest_data, load_trades,
|
||||
load_trades_from_db)
|
||||
calculate_underwater, combine_dataframes_with_mean,
|
||||
create_cum_profit, extract_trades_of_period,
|
||||
get_latest_backtest_filename, get_latest_hyperopt_file,
|
||||
load_backtest_data, load_trades, load_trades_from_db)
|
||||
from freqtrade.data.history import load_data, load_pair_history
|
||||
from tests.conftest import create_mock_trades
|
||||
from tests.conftest_trades import MOCK_TRADE_COUNT
|
||||
@ -234,6 +234,13 @@ def test_combine_dataframes_with_mean(testdatadir):
|
||||
assert "mean" in df.columns
|
||||
|
||||
|
||||
def test_combine_dataframes_with_mean_no_data(testdatadir):
|
||||
pairs = ["ETH/BTC", "ADA/BTC"]
|
||||
data = load_data(datadir=testdatadir, pairs=pairs, timeframe='6m')
|
||||
with pytest.raises(ValueError, match=r"No objects to concatenate"):
|
||||
combine_dataframes_with_mean(data)
|
||||
|
||||
|
||||
def test_create_cum_profit(testdatadir):
|
||||
filename = testdatadir / "backtest-result_test.json"
|
||||
bt_data = load_backtest_data(filename)
|
||||
@ -284,9 +291,16 @@ def test_calculate_max_drawdown(testdatadir):
|
||||
assert isinstance(lval, float)
|
||||
assert hdate == Timestamp('2018-01-24 14:25:00', tz='UTC')
|
||||
assert lowdate == Timestamp('2018-01-30 04:45:00', tz='UTC')
|
||||
|
||||
underwater = calculate_underwater(bt_data)
|
||||
assert isinstance(underwater, DataFrame)
|
||||
|
||||
with pytest.raises(ValueError, match='Trade dataframe empty.'):
|
||||
drawdown, hdate, lowdate, hval, lval = calculate_max_drawdown(DataFrame())
|
||||
|
||||
with pytest.raises(ValueError, match='Trade dataframe empty.'):
|
||||
calculate_underwater(DataFrame())
|
||||
|
||||
|
||||
def test_calculate_csum(testdatadir):
|
||||
filename = testdatadir / "backtest-result_test.json"
|
||||
|
||||
@ -311,7 +311,7 @@ def test_load_partial_missing(testdatadir, caplog) -> None:
|
||||
assert td != len(data['UNITTEST/BTC'])
|
||||
start_real = data['UNITTEST/BTC'].iloc[0, 0]
|
||||
assert log_has(f'Missing data at start for pair '
|
||||
f'UNITTEST/BTC, data starts at {start_real.strftime("%Y-%m-%d %H:%M:%S")}',
|
||||
f'UNITTEST/BTC at 5m, data starts at {start_real.strftime("%Y-%m-%d %H:%M:%S")}',
|
||||
caplog)
|
||||
# Make sure we start fresh - test missing data at end
|
||||
caplog.clear()
|
||||
@ -326,7 +326,7 @@ def test_load_partial_missing(testdatadir, caplog) -> None:
|
||||
# Shift endtime with +5 - as last candle is dropped (partial candle)
|
||||
end_real = arrow.get(data['UNITTEST/BTC'].iloc[-1, 0]).shift(minutes=5)
|
||||
assert log_has(f'Missing data at end for pair '
|
||||
f'UNITTEST/BTC, data ends at {end_real.strftime("%Y-%m-%d %H:%M:%S")}',
|
||||
f'UNITTEST/BTC at 5m, data ends at {end_real.strftime("%Y-%m-%d %H:%M:%S")}',
|
||||
caplog)
|
||||
|
||||
|
||||
|
||||
@ -20,7 +20,7 @@ from freqtrade.exchange.exchange import (market_is_active, timeframe_to_minutes,
|
||||
timeframe_to_next_date, timeframe_to_prev_date,
|
||||
timeframe_to_seconds)
|
||||
from freqtrade.resolvers.exchange_resolver import ExchangeResolver
|
||||
from tests.conftest import get_mock_coro, get_patched_exchange, log_has, log_has_re
|
||||
from tests.conftest import get_mock_coro, get_patched_exchange, log_has, log_has_re, num_log_has_re
|
||||
|
||||
|
||||
# Make sure to always keep one exchange here which is NOT subclassed!!
|
||||
@ -1740,6 +1740,44 @@ async def test__async_get_candle_history(default_conf, mocker, caplog, exchange_
|
||||
(arrow.utcnow().int_timestamp - 2000) * 1000)
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test__async_kucoin_get_candle_history(default_conf, mocker, caplog):
|
||||
caplog.set_level(logging.INFO)
|
||||
api_mock = MagicMock()
|
||||
api_mock.fetch_ohlcv = MagicMock(side_effect=ccxt.DDoSProtection(
|
||||
"kucoin GET https://openapi-v2.kucoin.com/api/v1/market/candles?"
|
||||
"symbol=ETH-BTC&type=5min&startAt=1640268735&endAt=1640418735"
|
||||
"429 Too Many Requests" '{"code":"429000","msg":"Too Many Requests"}'))
|
||||
exchange = get_patched_exchange(mocker, default_conf, api_mock, id="kucoin")
|
||||
|
||||
msg = "Kucoin 429 error, avoid triggering DDosProtection backoff delay"
|
||||
assert not num_log_has_re(msg, caplog)
|
||||
|
||||
for _ in range(3):
|
||||
with pytest.raises(DDosProtection, match=r'429 Too Many Requests'):
|
||||
await exchange._async_get_candle_history(
|
||||
"ETH/BTC", "5m", (arrow.utcnow().int_timestamp - 2000) * 1000, count=3)
|
||||
assert num_log_has_re(msg, caplog) == 3
|
||||
|
||||
caplog.clear()
|
||||
# Test regular non-kucoin message
|
||||
api_mock.fetch_ohlcv = MagicMock(side_effect=ccxt.DDoSProtection(
|
||||
"kucoin GET https://openapi-v2.kucoin.com/api/v1/market/candles?"
|
||||
"symbol=ETH-BTC&type=5min&startAt=1640268735&endAt=1640418735"
|
||||
"429 Too Many Requests" '{"code":"2222222","msg":"Too Many Requests"}'))
|
||||
|
||||
msg = r'_async_get_candle_history\(\) returned exception: .*'
|
||||
msg2 = r'Applying DDosProtection backoff delay: .*'
|
||||
with patch('freqtrade.exchange.common.asyncio.sleep', get_mock_coro(None)):
|
||||
for _ in range(3):
|
||||
with pytest.raises(DDosProtection, match=r'429 Too Many Requests'):
|
||||
await exchange._async_get_candle_history(
|
||||
"ETH/BTC", "5m", (arrow.utcnow().int_timestamp - 2000) * 1000, count=3)
|
||||
# Expect the "returned exception" message 12 times (4 retries * 3 (loop))
|
||||
assert num_log_has_re(msg, caplog) == 12
|
||||
assert num_log_has_re(msg2, caplog) == 9
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test__async_get_candle_history_empty(default_conf, mocker, caplog):
|
||||
""" Test empty exchange result """
|
||||
|
||||
@ -426,8 +426,6 @@ tc26 = BTContainer(data=[
|
||||
|
||||
# Test 27: Sell with signal sell in candle 3 (ROI at signal candle)
|
||||
# Stoploss at 10% (irrelevant), ROI at 5% (will trigger) - Wins over Sell-signal
|
||||
# TODO: figure out if sell-signal should win over ROI
|
||||
# Sell-signal wins over stoploss
|
||||
tc27 = BTContainer(data=[
|
||||
# D O H L C V B S
|
||||
[0, 5000, 5025, 4975, 4987, 6172, 1, 0],
|
||||
@ -436,8 +434,8 @@ tc27 = BTContainer(data=[
|
||||
[3, 5010, 5012, 4986, 5010, 6172, 0, 1], # sell-signal
|
||||
[4, 5010, 5251, 4855, 4995, 6172, 0, 0], # Triggers ROI, sell-signal acted on
|
||||
[5, 4995, 4995, 4950, 4950, 6172, 0, 0]],
|
||||
stop_loss=-0.10, roi={"0": 0.05}, profit_perc=0.05, use_sell_signal=True,
|
||||
trades=[BTrade(sell_reason=SellType.ROI, open_tick=1, close_tick=4)]
|
||||
stop_loss=-0.10, roi={"0": 0.05}, profit_perc=0.002, use_sell_signal=True,
|
||||
trades=[BTrade(sell_reason=SellType.SELL_SIGNAL, open_tick=1, close_tick=4)]
|
||||
)
|
||||
|
||||
# Test 28: trailing_stop should raise so candle 3 causes a stoploss
|
||||
|
||||
@ -1,6 +1,7 @@
|
||||
# pragma pylint: disable=missing-docstring, W0212, line-too-long, C0103, unused-argument
|
||||
|
||||
import random
|
||||
from copy import deepcopy
|
||||
from datetime import datetime, timedelta, timezone
|
||||
from pathlib import Path
|
||||
from unittest.mock import MagicMock, PropertyMock
|
||||
@ -648,7 +649,7 @@ def test_backtest_one(default_conf, fee, mocker, testdatadir) -> None:
|
||||
processed = backtesting.strategy.advise_all_indicators(data)
|
||||
min_date, max_date = get_timerange(processed)
|
||||
result = backtesting.backtest(
|
||||
processed=processed,
|
||||
processed=deepcopy(processed),
|
||||
start_date=min_date,
|
||||
end_date=max_date,
|
||||
max_open_trades=10,
|
||||
@ -887,7 +888,7 @@ def test_backtest_multi_pair(default_conf, fee, mocker, tres, pair, testdatadir)
|
||||
processed = backtesting.strategy.advise_all_indicators(data)
|
||||
min_date, max_date = get_timerange(processed)
|
||||
backtest_conf = {
|
||||
'processed': processed,
|
||||
'processed': deepcopy(processed),
|
||||
'start_date': min_date,
|
||||
'end_date': max_date,
|
||||
'max_open_trades': 3,
|
||||
@ -909,7 +910,7 @@ def test_backtest_multi_pair(default_conf, fee, mocker, tres, pair, testdatadir)
|
||||
'NXT/BTC', '5m')[0]) == len(data['NXT/BTC']) - 1 - backtesting.strategy.startup_candle_count
|
||||
|
||||
backtest_conf = {
|
||||
'processed': processed,
|
||||
'processed': deepcopy(processed),
|
||||
'start_date': min_date,
|
||||
'end_date': max_date,
|
||||
'max_open_trades': 1,
|
||||
|
||||
@ -15,7 +15,7 @@ from freqtrade.plugins.pairlist.pairlist_helpers import expand_pairlist
|
||||
from freqtrade.plugins.pairlistmanager import PairListManager
|
||||
from freqtrade.resolvers import PairListResolver
|
||||
from tests.conftest import (create_mock_trades, get_patched_exchange, get_patched_freqtradebot,
|
||||
log_has, log_has_re)
|
||||
log_has, log_has_re, num_log_has)
|
||||
|
||||
|
||||
@pytest.fixture(scope="function")
|
||||
@ -237,19 +237,13 @@ def test_remove_logs_for_pairs_already_in_blacklist(mocker, markets, static_pl_c
|
||||
# Ensure that log message wasn't generated.
|
||||
assert not log_has('Pair BLK/BTC in your blacklist. Removing it from whitelist...', caplog)
|
||||
|
||||
new_whitelist = freqtrade.pairlists.verify_blacklist(whitelist + ['BLK/BTC'], logger.warning)
|
||||
for _ in range(3):
|
||||
new_whitelist = freqtrade.pairlists.verify_blacklist(
|
||||
whitelist + ['BLK/BTC'], logger.warning)
|
||||
# Ensure that the pair is removed from the white list, and properly logged.
|
||||
assert set(whitelist) == set(new_whitelist)
|
||||
matches = sum(1 for message in caplog.messages
|
||||
if message == 'Pair BLK/BTC in your blacklist. Removing it from whitelist...')
|
||||
assert matches == 1
|
||||
|
||||
new_whitelist = freqtrade.pairlists.verify_blacklist(whitelist + ['BLK/BTC'], logger.warning)
|
||||
# Ensure that the pair is not logged anymore when being removed from the pair list.
|
||||
assert set(whitelist) == set(new_whitelist)
|
||||
matches = sum(1 for message in caplog.messages
|
||||
if message == 'Pair BLK/BTC in your blacklist. Removing it from whitelist...')
|
||||
assert matches == 1
|
||||
assert num_log_has('Pair BLK/BTC in your blacklist. Removing it from whitelist...',
|
||||
caplog) == 1
|
||||
|
||||
|
||||
def test_refresh_pairlist_dynamic(mocker, shitcoinmarkets, tickers, whitelist_conf):
|
||||
|
||||
@ -424,7 +424,7 @@ def test_rpc_trade_statistics(default_conf, ticker, ticker_sell_up, fee,
|
||||
assert stats['trade_count'] == 2
|
||||
assert stats['first_trade_date'] == 'just now'
|
||||
assert stats['latest_trade_date'] == 'just now'
|
||||
assert stats['avg_duration'] in ('0:00:00', '0:00:01')
|
||||
assert stats['avg_duration'] in ('0:00:00', '0:00:01', '0:00:02')
|
||||
assert stats['best_pair'] == 'ETH/BTC'
|
||||
assert prec_satoshi(stats['best_rate'], 6.2)
|
||||
|
||||
@ -435,7 +435,7 @@ def test_rpc_trade_statistics(default_conf, ticker, ticker_sell_up, fee,
|
||||
assert stats['trade_count'] == 2
|
||||
assert stats['first_trade_date'] == 'just now'
|
||||
assert stats['latest_trade_date'] == 'just now'
|
||||
assert stats['avg_duration'] in ('0:00:00', '0:00:01')
|
||||
assert stats['avg_duration'] in ('0:00:00', '0:00:01', '0:00:02')
|
||||
assert stats['best_pair'] == 'ETH/BTC'
|
||||
assert prec_satoshi(stats['best_rate'], 6.2)
|
||||
assert isnan(stats['profit_all_coin'])
|
||||
|
||||
@ -584,7 +584,7 @@ def test_monthly_handle(default_conf, update, ticker, limit_buy_order, fee,
|
||||
assert 'Monthly Profit over the last 2 months</b>:' in msg_mock.call_args_list[0][0][0]
|
||||
assert 'Month ' in msg_mock.call_args_list[0][0][0]
|
||||
today = datetime.utcnow().date()
|
||||
current_month = f"{today.year}-{today.month} "
|
||||
current_month = f"{today.year}-{today.month:02} "
|
||||
assert current_month in msg_mock.call_args_list[0][0][0]
|
||||
assert str(' 0.00006217 BTC') in msg_mock.call_args_list[0][0][0]
|
||||
assert str(' 0.933 USD') in msg_mock.call_args_list[0][0][0]
|
||||
|
||||
@ -1905,7 +1905,7 @@ def test_handle_trade_roi(default_conf_usdt, ticker_usdt, limit_buy_order_usdt_o
|
||||
# we might just want to check if we are in a sell condition without
|
||||
# executing
|
||||
# if ROI is reached we must sell
|
||||
patch_get_signal(freqtrade, value=(False, True, None, None))
|
||||
patch_get_signal(freqtrade, value=(False, False, None, None))
|
||||
assert freqtrade.handle_trade(trade)
|
||||
assert log_has("ETH/USDT - Required profit reached. sell_type=SellType.ROI",
|
||||
caplog)
|
||||
@ -3242,7 +3242,7 @@ def test_ignore_roi_if_buy_signal(default_conf_usdt, limit_buy_order_usdt,
|
||||
assert freqtrade.handle_trade(trade) is False
|
||||
|
||||
# Test if buy-signal is absent (should sell due to roi = true)
|
||||
patch_get_signal(freqtrade, value=(False, True, None, None))
|
||||
patch_get_signal(freqtrade, value=(False, False, None, None))
|
||||
assert freqtrade.handle_trade(trade) is True
|
||||
assert trade.sell_reason == SellType.ROI.value
|
||||
|
||||
@ -3428,11 +3428,11 @@ def test_disable_ignore_roi_if_buy_signal(default_conf_usdt, limit_buy_order_usd
|
||||
trade = Trade.query.first()
|
||||
trade.update(limit_buy_order_usdt)
|
||||
# Sell due to min_roi_reached
|
||||
patch_get_signal(freqtrade, value=(True, True, None, None))
|
||||
patch_get_signal(freqtrade, value=(True, False, None, None))
|
||||
assert freqtrade.handle_trade(trade) is True
|
||||
|
||||
# Test if buy-signal is absent
|
||||
patch_get_signal(freqtrade, value=(False, True, None, None))
|
||||
patch_get_signal(freqtrade, value=(False, False, None, None))
|
||||
assert freqtrade.handle_trade(trade) is True
|
||||
assert trade.sell_reason == SellType.ROI.value
|
||||
|
||||
|
||||
@ -336,15 +336,20 @@ def test_generate_profit_graph(testdatadir):
|
||||
assert fig.layout.yaxis3.title.text == "Profit BTC"
|
||||
|
||||
figure = fig.layout.figure
|
||||
assert len(figure.data) == 5
|
||||
assert len(figure.data) == 7
|
||||
|
||||
avgclose = find_trace_in_fig_data(figure.data, "Avg close price")
|
||||
assert isinstance(avgclose, go.Scatter)
|
||||
|
||||
profit = find_trace_in_fig_data(figure.data, "Profit")
|
||||
assert isinstance(profit, go.Scatter)
|
||||
profit = find_trace_in_fig_data(figure.data, "Max drawdown 10.45%")
|
||||
assert isinstance(profit, go.Scatter)
|
||||
drawdown = find_trace_in_fig_data(figure.data, "Max drawdown 10.45%")
|
||||
assert isinstance(drawdown, go.Scatter)
|
||||
parallel = find_trace_in_fig_data(figure.data, "Parallel trades")
|
||||
assert isinstance(parallel, go.Scatter)
|
||||
|
||||
underwater = find_trace_in_fig_data(figure.data, "Underwater Plot")
|
||||
assert isinstance(underwater, go.Scatter)
|
||||
|
||||
for pair in pairs:
|
||||
profit_pair = find_trace_in_fig_data(figure.data, f"Profit {pair}")
|
||||
|
||||
Loading…
Reference in New Issue
Block a user