Merge branch 'freqtrade:develop' into plot_hyperopt_stats

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.github/FUNDING.yml vendored Normal file
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@ -0,0 +1,3 @@
# These are supported funding model platforms
github: [xmatthias]

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.gitignore vendored
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@ -10,6 +10,9 @@ freqtrade-plot.html
freqtrade-profit-plot.html
freqtrade/rpc/api_server/ui/*
# Macos related
.DS_Store
# Byte-compiled / optimized / DLL files
__pycache__/
*.py[cod]

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@ -5,10 +5,14 @@
[![Documentation](https://readthedocs.org/projects/freqtrade/badge/)](https://www.freqtrade.io)
[![Maintainability](https://api.codeclimate.com/v1/badges/5737e6d668200b7518ff/maintainability)](https://codeclimate.com/github/freqtrade/freqtrade/maintainability)
Freqtrade is a free and open source crypto trading bot written in Python. It is designed to support all major exchanges and be controlled via Telegram. It contains backtesting, plotting and money management tools as well as strategy optimization by machine learning.
Freqtrade is a free and open source crypto trading bot written in Python. It is designed to support all major exchanges and be controlled via Telegram or webUI. It contains backtesting, plotting and money management tools as well as strategy optimization by machine learning.
![freqtrade](https://raw.githubusercontent.com/freqtrade/freqtrade/develop/docs/assets/freqtrade-screenshot.png)
## Sponsored promotion
[![tokenbot-promo](https://raw.githubusercontent.com/freqtrade/freqtrade/develop/docs/assets/TokenBot-Freqtrade-banner.png)](https://tokenbot.com/?utm_source=github&utm_medium=freqtrade&utm_campaign=algodevs)
## Disclaimer
This software is for educational purposes only. Do not risk money which
@ -31,7 +35,7 @@ Please read the [exchange specific notes](docs/exchanges.md) to learn about even
- [X] [FTX](https://ftx.com)
- [X] [Gate.io](https://www.gate.io/ref/6266643)
- [X] [Kraken](https://kraken.com/)
- [X] [OKEX](https://www.okex.com/)
- [X] [OKX](https://www.okx.com/)
- [ ] [potentially many others](https://github.com/ccxt/ccxt/). _(We cannot guarantee they will work)_
### Community tested
@ -57,9 +61,9 @@ Please find the complete documentation on the [freqtrade website](https://www.fr
- [x] **Edge position sizing** Calculate your win rate, risk reward ratio, the best stoploss and adjust your position size before taking a position for each specific market. [Learn more](https://www.freqtrade.io/en/stable/edge/).
- [x] **Whitelist crypto-currencies**: Select which crypto-currency you want to trade or use dynamic whitelists.
- [x] **Blacklist crypto-currencies**: Select which crypto-currency you want to avoid.
- [x] **Builtin WebUI**: Builtin web UI to manage your bot.
- [x] **Manageable via Telegram**: Manage the bot with Telegram.
- [x] **Display profit/loss in fiat**: Display your profit/loss in 33 fiat.
- [x] **Daily summary of profit/loss**: Provide a daily summary of your profit/loss.
- [x] **Display profit/loss in fiat**: Display your profit/loss in fiat currency.
- [x] **Performance status report**: Provide a performance status of your current trades.
## Quick start

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@ -86,6 +86,7 @@
"key": "your_exchange_key",
"secret": "your_exchange_secret",
"password": "",
"log_responses": false,
"ccxt_config": {},
"ccxt_async_config": {},
"pair_whitelist": [

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@ -313,6 +313,7 @@ A backtesting result will look like that:
| Avg. Duration Winners | 4:23:00 |
| Avg. Duration Loser | 6:55:00 |
| Rejected Buy signals | 3089 |
| Entry/Exit Timeouts | 0 / 0 |
| | |
| Min balance | 0.00945123 BTC |
| Max balance | 0.01846651 BTC |
@ -400,6 +401,7 @@ It contains some useful key metrics about performance of your strategy on backte
| Avg. Duration Winners | 4:23:00 |
| Avg. Duration Loser | 6:55:00 |
| Rejected Buy signals | 3089 |
| Entry/Exit Timeouts | 0 / 0 |
| | |
| Min balance | 0.00945123 BTC |
| Max balance | 0.01846651 BTC |
@ -429,6 +431,7 @@ It contains some useful key metrics about performance of your strategy on backte
- `Days win/draw/lose`: Winning / Losing days (draws are usually days without closed trade).
- `Avg. Duration Winners` / `Avg. Duration Loser`: Average durations for winning and losing trades.
- `Rejected Buy signals`: Buy signals that could not be acted upon due to max_open_trades being reached.
- `Entry/Exit Timeouts`: Entry/exit orders which did not fill (only applicable if custom pricing is used).
- `Min balance` / `Max balance`: Lowest and Highest Wallet balance during the backtest period.
- `Drawdown (Account)`: Maximum Account Drawdown experienced. Calculated as $(Absolute Drawdown) / (DrawdownHigh + startingBalance)$.
- `Drawdown`: Maximum, absolute drawdown experienced. Difference between Drawdown High and Subsequent Low point.

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@ -62,6 +62,7 @@ This loop will be repeated again and again until the bot is stopped.
* Check position adjustments for open trades if enabled and call `adjust_trade_position()` to determine if an additional order is requested.
* Call `custom_stoploss()` and `custom_sell()` to find custom exit points.
* For sells based on sell-signal and custom-sell: Call `custom_exit_price()` to determine exit price (Prices are moved to be within the closing candle).
* Check for Order timeouts, either via the `unfilledtimeout` configuration, or via `check_buy_timeout()` / `check_sell_timeout()` strategy callbacks.
* Generate backtest report output
!!! Note

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@ -1,6 +1,6 @@
# Analyzing bot data with Jupyter notebooks
# Analyzing bot data with Jupyter notebooks
You can analyze the results of backtests and trading history easily using Jupyter notebooks. Sample notebooks are located at `user_data/notebooks/` after initializing the user directory with `freqtrade create-userdir --userdir user_data`.
You can analyze the results of backtests and trading history easily using Jupyter notebooks. Sample notebooks are located at `user_data/notebooks/` after initializing the user directory with `freqtrade create-userdir --userdir user_data`.
## Quick start with docker
@ -41,32 +41,35 @@ ipython kernel install --user --name=freqtrade
!!! Warning
Some tasks don't work especially well in notebooks. For example, anything using asynchronous execution is a problem for Jupyter. Also, freqtrade's primary entry point is the shell cli, so using pure python in a notebook bypasses arguments that provide required objects and parameters to helper functions. You may need to set those values or create expected objects manually.
## Recommended workflow
## Recommended workflow
| Task | Tool |
--- | ---
Bot operations | CLI
| Task | Tool |
--- | ---
Bot operations | CLI
Repetitive tasks | Shell scripts
Data analysis & visualization | Notebook
Data analysis & visualization | Notebook
1. Use the CLI to
* download historical data
* run a backtest
* run with real-time data
* export results
* export results
1. Collect these actions in shell scripts
* save complicated commands with arguments
* execute multi-step operations
* execute multi-step operations
* automate testing strategies and preparing data for analysis
1. Use a notebook to
* visualize data
* munge and plot to generate insights
* mangle and plot to generate insights
## Example utility snippets
## Example utility snippets
### Change directory to root
### Change directory to root
Jupyter notebooks execute from the notebook directory. The following snippet searches for the project root, so relative paths remain consistent.

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@ -182,13 +182,13 @@ Kucoin supports [time_in_force](configuration.md#understand-order_time_in_force)
For Kucoin, please add `"KCS/<STAKE>"` to your blacklist to avoid issues.
Accounts having KCS accounts use this to pay for fees - if your first trade happens to be on `KCS`, further trades will consume this position and make the initial KCS trade unsellable as the expected amount is not there anymore.
## OKEX
## OKX
OKEX requires a passphrase for each api key, you will therefore need to add this key into the configuration so your exchange section looks as follows:
OKX requires a passphrase for each api key, you will therefore need to add this key into the configuration so your exchange section looks as follows:
```json
"exchange": {
"name": "okex",
"name": "okx",
"key": "your_exchange_key",
"secret": "your_exchange_secret",
"password": "your_exchange_api_key_password",
@ -197,7 +197,7 @@ OKEX requires a passphrase for each api key, you will therefore need to add this
```
!!! Warning
OKEX only provides 100 candles per api call. Therefore, the strategy will only have a pretty low amount of data available in backtesting mode.
OKX only provides 100 candles per api call. Therefore, the strategy will only have a pretty low amount of data available in backtesting mode.
## Gate.io

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@ -116,7 +116,7 @@ optional arguments:
ShortTradeDurHyperOptLoss, OnlyProfitHyperOptLoss,
SharpeHyperOptLoss, SharpeHyperOptLossDaily,
SortinoHyperOptLoss, SortinoHyperOptLossDaily,
CalmarHyperOptLoss, MaxDrawDownHyperOptLoss
CalmarHyperOptLoss, MaxDrawDownHyperOptLoss, ProfitDrawDownHyperOptLoss
--disable-param-export
Disable automatic hyperopt parameter export.
--ignore-missing-spaces, --ignore-unparameterized-spaces
@ -525,6 +525,7 @@ Currently, the following loss functions are builtin:
* `SortinoHyperOptLossDaily` - optimizes Sortino Ratio calculated on **daily** trade returns relative to **downside** standard deviation.
* `MaxDrawDownHyperOptLoss` - Optimizes Maximum drawdown.
* `CalmarHyperOptLoss` - Optimizes Calmar Ratio calculated on trade returns relative to max drawdown.
* `ProfitDrawDownHyperOptLoss` - Optimizes by max Profit & min Drawdown objective. `DRAWDOWN_MULT` variable within the hyperoptloss file can be adjusted to be stricter or more flexible on drawdown purposes.
Creation of a custom loss function is covered in the [Advanced Hyperopt](advanced-hyperopt.md) part of the documentation.

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@ -246,7 +246,7 @@ On exchanges that deduct fees from the receiving currency (e.g. FTX) - this can
The `low_price_ratio` setting removes pairs where a raise of 1 price unit (pip) is above the `low_price_ratio` ratio.
This option is disabled by default, and will only apply if set to > 0.
For `PriceFiler` at least one of its `min_price`, `max_price` or `low_price_ratio` settings must be applied.
For `PriceFilter` at least one of its `min_price`, `max_price` or `low_price_ratio` settings must be applied.
Calculation example:

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@ -11,7 +11,7 @@
## Introduction
Freqtrade is a crypto-currency algorithmic trading software developed in python (3.8+) and supported on Windows, macOS and Linux.
Freqtrade is a free and open source crypto trading bot written in Python. It is designed to support all major exchanges and be controlled via Telegram or webUI. It contains backtesting, plotting and money management tools as well as strategy optimization by machine learning.
!!! Danger "DISCLAIMER"
This software is for educational purposes only. Do not risk money which you are afraid to lose. USE THE SOFTWARE AT YOUR OWN RISK. THE AUTHORS AND ALL AFFILIATES ASSUME NO RESPONSIBILITY FOR YOUR TRADING RESULTS.
@ -20,6 +20,12 @@ Freqtrade is a crypto-currency algorithmic trading software developed in python
We strongly recommend you to have basic coding skills and Python knowledge. Do not hesitate to read the source code and understand the mechanisms of this bot, algorithms and techniques implemented in it.
![freqtrade screenshot](assets/freqtrade-screenshot.png)
## Sponsored promotion
[![tokenbot-promo](assets/TokenBot-Freqtrade-banner.png)](https://tokenbot.com/?utm_source=github&utm_medium=freqtrade&utm_campaign=algodevs)
## Features
- Develop your Strategy: Write your strategy in python, using [pandas](https://pandas.pydata.org/). Example strategies to inspire you are available in the [strategy repository](https://github.com/freqtrade/freqtrade-strategies).
@ -29,7 +35,7 @@ Freqtrade is a crypto-currency algorithmic trading software developed in python
- Select markets: Create your static list or use an automatic one based on top traded volumes and/or prices (not available during backtesting). You can also explicitly blacklist markets you don't want to trade.
- Run: Test your strategy with simulated money (Dry-Run mode) or deploy it with real money (Live-Trade mode).
- Run using Edge (optional module): The concept is to find the best historical [trade expectancy](edge.md#expectancy) by markets based on variation of the stop-loss and then allow/reject markets to trade. The sizing of the trade is based on a risk of a percentage of your capital.
- Control/Monitor: Use Telegram or a REST API (start/stop the bot, show profit/loss, daily summary, current open trades results, etc.).
- Control/Monitor: Use Telegram or a WebUI (start/stop the bot, show profit/loss, daily summary, current open trades results, etc.).
- Analyse: Further analysis can be performed on either Backtesting data or Freqtrade trading history (SQL database), including automated standard plots, and methods to load the data into [interactive environments](data-analysis.md).
## Supported exchange marketplaces
@ -41,7 +47,7 @@ Please read the [exchange specific notes](exchanges.md) to learn about eventual,
- [X] [FTX](https://ftx.com)
- [X] [Gate.io](https://www.gate.io/ref/6266643)
- [X] [Kraken](https://kraken.com/)
- [X] [OKEX](https://www.okex.com/)
- [X] [OKX](https://www.okx.com/)
- [ ] [potentially many others through <img alt="ccxt" width="30px" src="assets/ccxt-logo.svg" />](https://github.com/ccxt/ccxt/). _(We cannot guarantee they will work)_
### Community tested

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@ -24,7 +24,7 @@ The easiest way to install and run Freqtrade is to clone the bot Github reposito
The `stable` branch contains the code of the last release (done usually once per month on an approximately one week old snapshot of the `develop` branch to prevent packaging bugs, so potentially it's more stable).
!!! Note
Python3.7 or higher and the corresponding `pip` are assumed to be available. The install-script will warn you and stop if that's not the case. `git` is also needed to clone the Freqtrade repository.
Python3.8 or higher and the corresponding `pip` are assumed to be available. The install-script will warn you and stop if that's not the case. `git` is also needed to clone the Freqtrade repository.
Also, python headers (`python<yourversion>-dev` / `python<yourversion>-devel`) must be available for the installation to complete successfully.
!!! Warning "Up-to-date clock"
@ -54,7 +54,7 @@ We've included/collected install instructions for Ubuntu, MacOS, and Windows. Th
OS Specific steps are listed first, the [Common](#common) section below is necessary for all systems.
!!! Note
Python3.7 or higher and the corresponding pip are assumed to be available.
Python3.8 or higher and the corresponding pip are assumed to be available.
=== "Debian/Ubuntu"
#### Install necessary dependencies
@ -69,7 +69,7 @@ OS Specific steps are listed first, the [Common](#common) section below is neces
=== "RaspberryPi/Raspbian"
The following assumes the latest [Raspbian Buster lite image](https://www.raspberrypi.org/downloads/raspbian/).
This image comes with python3.7 preinstalled, making it easy to get freqtrade up and running.
This image comes with python3.9 preinstalled, making it easy to get freqtrade up and running.
Tested using a Raspberry Pi 3 with the Raspbian Buster lite image, all updates applied.
@ -169,7 +169,7 @@ You can as well update, configure and reset the codebase of your bot with `./scr
** --install **
With this option, the script will install the bot and most dependencies:
You will need to have git and python3.7+ installed beforehand for this to work.
You will need to have git and python3.8+ installed beforehand for this to work.
* Mandatory software as: `ta-lib`
* Setup your virtualenv under `.env/`

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@ -318,8 +318,8 @@ optional arguments:
Specify what timerange of data to use.
--export EXPORT Export backtest results, argument are: trades.
Example: `--export=trades`
--export-filename PATH
Save backtest results to the file with this filename.
--export-filename PATH, --backtest-filename PATH
Use backtest results from this filename.
Requires `--export` to be set as well. Example:
`--export-filename=user_data/backtest_results/backtest
_today.json`

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@ -1,4 +1,4 @@
mkdocs==1.2.3
mkdocs-material==8.1.9
mkdocs-material==8.1.11
mdx_truly_sane_lists==1.2
pymdown-extensions==9.1
pymdown-extensions==9.2

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@ -2,6 +2,7 @@
The `stoploss` configuration parameter is loss as ratio that should trigger a sale.
For example, value `-0.10` will cause immediate sell if the profit dips below -10% for a given trade. This parameter is optional.
Stoploss calculations do include fees, so a stoploss of -10% is placed exactly 10% below the entry point.
Most of the strategy files already include the optimal `stoploss` value.
@ -30,7 +31,7 @@ These modes can be configured with these values:
### stoploss_on_exchange and stoploss_on_exchange_limit_ratio
Enable or Disable stop loss on exchange.
If the stoploss is *on exchange* it means a stoploss limit order is placed on the exchange immediately after buy order happens successfully. This will protect you against sudden crashes in market as the order will be in the queue immediately and if market goes down then the order has more chance of being fulfilled.
If the stoploss is *on exchange* it means a stoploss limit order is placed on the exchange immediately after buy order fills. This will protect you against sudden crashes in market, as the order execution happens purely within the exchange, and has no potential network overhead.
If `stoploss_on_exchange` uses limit orders, the exchange needs 2 prices, the stoploss_price and the Limit price.
`stoploss` defines the stop-price where the limit order is placed - and limit should be slightly below this.

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@ -54,7 +54,7 @@ Called before entering a trade, makes it possible to manage your position size w
class AwesomeStrategy(IStrategy):
def custom_stake_amount(self, pair: str, current_time: datetime, current_rate: float,
proposed_stake: float, min_stake: float, max_stake: float,
**kwargs) -> float:
entry_tag: Optional[str], **kwargs) -> float:
dataframe, _ = self.dp.get_analyzed_dataframe(pair=pair, timeframe=self.timeframe)
current_candle = dataframe.iloc[-1].squeeze()
@ -389,8 +389,8 @@ class AwesomeStrategy(IStrategy):
If the new_entryprice is 97, the proposed_rate is 100 and the `custom_price_max_distance_ratio` is set to 2%, The retained valid custom entry price will be 98, which is 2% below the current (proposed) rate.
!!! Warning "Backtesting"
While Custom prices are supported in backtesting (starting with 2021.12), prices will be moved to within the candle's high/low prices.
This behavior is currently being tested, and might be changed at a later point.
Custom prices are supported in backtesting (starting with 2021.12), and orders will fill if the price falls within the candle's low/high range.
Orders that don't fill immediately are subject to regular timeout handling, which happens once per (detail) candle.
`custom_exit_price()` is only called for sells of type Sell_signal and Custom sell. All other sell-types will use regular backtesting prices.
## Custom order timeout rules
@ -400,7 +400,8 @@ Simple, time-based order-timeouts can be configured either via strategy or in th
However, freqtrade also offers a custom callback for both order types, which allows you to decide based on custom criteria if an order did time out or not.
!!! Note
Unfilled order timeouts are not relevant during backtesting or hyperopt, and are only relevant during real (live) trading. Therefore these methods are only called in these circumstances.
Backtesting fills orders if their price falls within the candle's low/high range.
The below callbacks will be called once per (detail) candle for orders that don't fill immediately (which use custom pricing).
### Custom order timeout example
@ -467,7 +468,8 @@ class AwesomeStrategy(IStrategy):
'sell': 60 * 25
}
def check_buy_timeout(self, pair: str, trade: Trade, order: dict, **kwargs) -> bool:
def check_buy_timeout(self, pair: str, trade: Trade, order: dict,
current_time: datetime, **kwargs) -> bool:
ob = self.dp.orderbook(pair, 1)
current_price = ob['bids'][0][0]
# Cancel buy order if price is more than 2% above the order.
@ -476,7 +478,8 @@ class AwesomeStrategy(IStrategy):
return False
def check_sell_timeout(self, pair: str, trade: Trade, order: dict, **kwargs) -> bool:
def check_sell_timeout(self, pair: str, trade: Trade, order: dict,
current_time: datetime, **kwargs) -> bool:
ob = self.dp.orderbook(pair, 1)
current_price = ob['asks'][0][0]
# Cancel sell order if price is more than 2% below the order.

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@ -75,7 +75,7 @@ ARGS_PLOT_DATAFRAME = ["pairs", "indicators1", "indicators2", "plot_limit",
"timerange", "timeframe", "no_trades"]
ARGS_PLOT_PROFIT = ["pairs", "timerange", "export", "exportfilename", "db_url",
"trade_source", "timeframe", "plot_auto_open"]
"trade_source", "timeframe", "plot_auto_open", ]
ARGS_INSTALL_UI = ["erase_ui_only", 'ui_version']

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@ -112,7 +112,7 @@ def ask_user_config() -> Dict[str, Any]:
"ftx",
"kucoin",
"gateio",
"okex",
"okx",
Separator(),
"other",
],
@ -140,7 +140,7 @@ def ask_user_config() -> Dict[str, Any]:
"type": "password",
"name": "exchange_key_password",
"message": "Insert Exchange API Key password",
"when": lambda x: not x['dry_run'] and x['exchange_name'] in ('kucoin', 'okex')
"when": lambda x: not x['dry_run'] and x['exchange_name'] in ('kucoin', 'okx')
},
{
"type": "confirm",

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@ -182,11 +182,12 @@ AVAILABLE_CLI_OPTIONS = {
),
"exportfilename": Arg(
'--export-filename',
help='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`',
metavar='PATH',
"--export-filename",
"--backtest-filename",
help="Use this filename for backtest results."
"Requires `--export` to be set as well. "
"Example: `--export-filename=user_data/backtest_results/backtest_today.json`",
metavar="PATH",
),
"disableparamexport": Arg(
'--disable-param-export',

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@ -431,7 +431,6 @@ class Configuration:
logstring='Using "{}" to store trades data.')
def _process_data_options(self, config: Dict[str, Any]) -> None:
self._args_to_config(config, argname='new_pairs_days',
logstring='Detected --new-pairs-days: {}')

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@ -26,7 +26,7 @@ HYPEROPT_LOSS_BUILTIN = ['ShortTradeDurHyperOptLoss', 'OnlyProfitHyperOptLoss',
'SharpeHyperOptLoss', 'SharpeHyperOptLossDaily',
'SortinoHyperOptLoss', 'SortinoHyperOptLossDaily',
'CalmarHyperOptLoss',
'MaxDrawDownHyperOptLoss']
'MaxDrawDownHyperOptLoss', 'ProfitDrawDownHyperOptLoss']
AVAILABLE_PAIRLISTS = ['StaticPairList', 'VolumePairList',
'AgeFilter', 'OffsetFilter', 'PerformanceFilter',
'PrecisionFilter', 'PriceFilter', 'RangeStabilityFilter',
@ -456,6 +456,7 @@ SCHEMA_BACKTEST_REQUIRED = [
'dry_run_wallet',
'dataformat_ohlcv',
'dataformat_trades',
'unfilledtimeout',
]
SCHEMA_MINIMAL_REQUIRED = [

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@ -5,7 +5,7 @@ from pathlib import Path
from typing import Dict, List, Optional, Tuple
import arrow
from pandas import DataFrame
from pandas import DataFrame, concat
from freqtrade.configuration import TimeRange
from freqtrade.constants import DEFAULT_DATAFRAME_COLUMNS
@ -208,7 +208,7 @@ def _download_pair_history(pair: str, *,
else:
# Run cleaning again to ensure there were no duplicate candles
# Especially between existing and new data.
data = clean_ohlcv_dataframe(data.append(new_dataframe), timeframe, pair,
data = clean_ohlcv_dataframe(concat([data, new_dataframe], axis=0), timeframe, pair,
fill_missing=False, drop_incomplete=False)
logger.debug("New Start: %s",

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@ -20,4 +20,4 @@ from freqtrade.exchange.gateio import Gateio
from freqtrade.exchange.hitbtc import Hitbtc
from freqtrade.exchange.kraken import Kraken
from freqtrade.exchange.kucoin import Kucoin
from freqtrade.exchange.okex import Okex
from freqtrade.exchange.okx import Okx

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@ -27,13 +27,15 @@ API_FETCH_ORDER_RETRY_COUNT = 5
BAD_EXCHANGES = {
"bitmex": "Various reasons.",
"phemex": "Does not provide history. ",
"phemex": "Does not provide history.",
"probit": "Requires additional, regular calls to `signIn()`.",
"poloniex": "Does not provide fetch_order endpoint to fetch both open and closed orders.",
}
MAP_EXCHANGE_CHILDCLASS = {
'binanceus': 'binance',
'binanceje': 'binance',
'okex': 'okx',
}

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@ -1587,7 +1587,7 @@ def is_exchange_known_ccxt(exchange_name: str, ccxt_module: CcxtModuleType = Non
def is_exchange_officially_supported(exchange_name: str) -> bool:
return exchange_name in ['bittrex', 'binance', 'kraken', 'ftx', 'gateio', 'okex']
return exchange_name in ['bittrex', 'binance', 'kraken', 'ftx', 'gateio', 'okx']
def ccxt_exchanges(ccxt_module: CcxtModuleType = None) -> List[str]:

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@ -7,8 +7,8 @@ from freqtrade.exchange import Exchange
logger = logging.getLogger(__name__)
class Okex(Exchange):
"""Okex exchange class.
class Okx(Exchange):
"""Okx exchange class.
Contains adjustments needed for Freqtrade to work with this exchange.
"""

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@ -100,6 +100,8 @@ class FreqtradeBot(LoggingMixin):
self._exit_lock = Lock()
LoggingMixin.__init__(self, logger, timeframe_to_seconds(self.strategy.timeframe))
self.last_process = datetime(1970, 1, 1, tzinfo=timezone.utc)
def notify_status(self, msg: str) -> None:
"""
Public method for users of this class (worker, etc.) to send notifications
@ -187,6 +189,7 @@ class FreqtradeBot(LoggingMixin):
self.enter_positions()
Trade.commit()
self.last_process = datetime.now(timezone.utc)
def process_stopped(self) -> None:
"""
@ -295,28 +298,6 @@ class FreqtradeBot(LoggingMixin):
self.update_trade_state(trade, order.order_id, send_msg=False)
def handle_insufficient_funds(self, trade: Trade):
"""
Determine if we ever opened a sell order for this trade.
If not, try update buy fees - otherwise "refind" the open order we obviously lost.
"""
sell_order = trade.select_order('sell', None)
if sell_order:
self.refind_lost_order(trade)
else:
self.reupdate_enter_order_fees(trade)
def reupdate_enter_order_fees(self, trade: Trade):
"""
Get buy order from database, and try to reupdate.
Handles trades where the initial fee-update did not work.
"""
logger.info(f"Trying to reupdate buy fees for {trade}")
order = trade.select_order('buy', False)
if order:
logger.info(f"Updating buy-fee on trade {trade} for order {order.order_id}.")
self.update_trade_state(trade, order.order_id, send_msg=False)
def refind_lost_order(self, trade):
"""
Try refinding a lost trade.
Only used when InsufficientFunds appears on sell orders (stoploss or sell).
@ -329,9 +310,6 @@ class FreqtradeBot(LoggingMixin):
if not order.ft_is_open:
logger.debug(f"Order {order} is no longer open.")
continue
if order.ft_order_side == 'buy':
# Skip buy side - this is handled by reupdate_buy_order_fees
continue
try:
fo = self.exchange.fetch_order_or_stoploss_order(order.order_id, order.ft_pair,
order.ft_order_side == 'stoploss')
@ -343,6 +321,9 @@ class FreqtradeBot(LoggingMixin):
if fo and fo['status'] == 'open':
# Assume this as the open order
trade.open_order_id = order.order_id
elif order.ft_order_side == 'buy':
if fo and fo['status'] == 'open':
trade.open_order_id = order.order_id
if fo:
logger.info(f"Found {order} for trade {trade}.")
self.update_trade_state(trade, order.order_id, fo,
@ -984,18 +965,20 @@ class FreqtradeBot(LoggingMixin):
fully_cancelled = self.update_trade_state(trade, trade.open_order_id, order)
order_obj = trade.select_order_by_order_id(trade.open_order_id)
if (order['side'] == 'buy' and (order['status'] == 'open' or fully_cancelled) and (
fully_cancelled
or self.strategy.ft_check_timed_out(
'buy', trade, order, datetime.now(timezone.utc))
)):
or (order_obj and self.strategy.ft_check_timed_out(
'buy', trade, order_obj, datetime.now(timezone.utc))
))):
self.handle_cancel_enter(trade, order, constants.CANCEL_REASON['TIMEOUT'])
elif (order['side'] == 'sell' and (order['status'] == 'open' or fully_cancelled) and (
fully_cancelled
or self.strategy.ft_check_timed_out(
'sell', trade, order, datetime.now(timezone.utc)))
):
or (order_obj and self.strategy.ft_check_timed_out(
'sell', trade, order_obj, datetime.now(timezone.utc))
))):
self.handle_cancel_exit(trade, order, constants.CANCEL_REASON['TIMEOUT'])
canceled_count = trade.get_exit_order_count()
max_timeouts = self.config.get('unfilledtimeout', {}).get('exit_timeout_count', 0)

View File

@ -63,6 +63,8 @@ class Backtesting:
LoggingMixin.show_output = False
self.config = config
self.results: Dict[str, Any] = {}
self.trade_id_counter: int = 0
self.order_id_counter: int = 0
config['dry_run'] = True
self.run_ids: Dict[str, str] = {}
@ -231,6 +233,8 @@ class Backtesting:
PairLocks.reset_locks()
Trade.reset_trades()
self.rejected_trades = 0
self.timedout_entry_orders = 0
self.timedout_exit_orders = 0
self.dataprovider.clear_cache()
if enable_protections:
self._load_protections(self.strategy)
@ -275,6 +279,13 @@ class Backtesting:
# Trim startup period from analyzed dataframe
df_analyzed = processed[pair] = pair_data = trim_dataframe(
df_analyzed, self.timerange, startup_candles=self.required_startup)
# Update dataprovider cache
self.dataprovider._set_cached_df(pair, self.timeframe, df_analyzed)
# Create a copy of the dataframe before shifting, that way the buy signal/tag
# remains on the correct candle for callbacks.
df_analyzed = df_analyzed.copy()
# To avoid using data from future, we use buy/sell signals shifted
# from the previous candle
df_analyzed.loc[:, 'buy'] = df_analyzed.loc[:, 'buy'].shift(1)
@ -282,9 +293,6 @@ class Backtesting:
df_analyzed.loc[:, 'buy_tag'] = df_analyzed.loc[:, 'buy_tag'].shift(1)
df_analyzed.loc[:, 'exit_tag'] = df_analyzed.loc[:, 'exit_tag'].shift(1)
# Update dataprovider cache
self.dataprovider._set_cached_df(pair, self.timeframe, df_analyzed)
df_analyzed = df_analyzed.drop(df_analyzed.head(1).index)
# Convert from Pandas to list for performance reasons
@ -349,7 +357,10 @@ class Backtesting:
# use Open rate if open_rate > calculated sell rate
return sell_row[OPEN_IDX]
return close_rate
# Use the maximum between close_rate and low as we
# cannot sell outside of a candle.
# Applies when a new ROI setting comes in place and the whole candle is above that.
return min(max(close_rate, sell_row[LOW_IDX]), sell_row[HIGH_IDX])
else:
# This should not be reached...
@ -372,10 +383,15 @@ class Backtesting:
if stake_amount is not None and stake_amount > 0.0:
pos_trade = self._enter_trade(trade.pair, row, stake_amount, trade)
if pos_trade is not None:
self.wallets.update()
return pos_trade
return trade
def _get_order_filled(self, rate: float, row: Tuple) -> bool:
""" Rate is within candle, therefore filled"""
return row[LOW_IDX] <= rate <= row[HIGH_IDX]
def _get_sell_trade_entry_for_candle(self, trade: LocalTrade,
sell_row: Tuple) -> Optional[LocalTrade]:
@ -401,18 +417,21 @@ class Backtesting:
closerate = self._get_close_rate(sell_row, trade, sell, trade_dur)
# call the custom exit price,with default value as previous closerate
current_profit = trade.calc_profit_ratio(closerate)
order_type = self.strategy.order_types['sell']
if sell.sell_type in (SellType.SELL_SIGNAL, SellType.CUSTOM_SELL):
# Custom exit pricing only for sell-signals
closerate = strategy_safe_wrapper(self.strategy.custom_exit_price,
default_retval=closerate)(
pair=trade.pair, trade=trade,
current_time=sell_row[DATE_IDX],
proposed_rate=closerate, current_profit=current_profit)
# Use the maximum between close_rate and low as we cannot sell outside of a candle.
closerate = min(max(closerate, sell_row[LOW_IDX]), sell_row[HIGH_IDX])
if order_type == 'limit':
closerate = strategy_safe_wrapper(self.strategy.custom_exit_price,
default_retval=closerate)(
pair=trade.pair, trade=trade,
current_time=sell_candle_time,
proposed_rate=closerate, current_profit=current_profit)
# We can't place orders lower than current low.
# freqtrade does not support this in live, and the order would fill immediately
closerate = max(closerate, sell_row[LOW_IDX])
# Confirm trade exit:
time_in_force = self.strategy.order_time_in_force['sell']
if not strategy_safe_wrapper(self.strategy.confirm_trade_exit, default_retval=True)(
pair=trade.pair, trade=trade, order_type='limit', amount=trade.amount,
rate=closerate,
@ -432,7 +451,28 @@ class Backtesting:
):
trade.sell_reason = sell_row[EXIT_TAG_IDX]
trade.close(closerate, show_msg=False)
self.order_id_counter += 1
order = Order(
id=self.order_id_counter,
ft_trade_id=trade.id,
order_date=sell_candle_time,
order_update_date=sell_candle_time,
ft_is_open=True,
ft_pair=trade.pair,
order_id=str(self.order_id_counter),
symbol=trade.pair,
ft_order_side="sell",
side="sell",
order_type=order_type,
status="open",
price=closerate,
average=closerate,
amount=trade.amount,
filled=0,
remaining=trade.amount,
cost=trade.amount * closerate,
)
trade.orders.append(order)
return trade
return None
@ -471,13 +511,16 @@ class Backtesting:
current_time = row[DATE_IDX].to_pydatetime()
entry_tag = row[BUY_TAG_IDX] if len(row) >= BUY_TAG_IDX + 1 else None
# let's call the custom entry price, using the open price as default price
propose_rate = strategy_safe_wrapper(self.strategy.custom_entry_price,
default_retval=row[OPEN_IDX])(
pair=pair, current_time=current_time,
proposed_rate=row[OPEN_IDX], entry_tag=entry_tag) # default value is the open rate
# Move rate to within the candle's low/high rate
propose_rate = min(max(propose_rate, row[LOW_IDX]), row[HIGH_IDX])
order_type = self.strategy.order_types['buy']
propose_rate = row[OPEN_IDX]
if order_type == 'limit':
propose_rate = strategy_safe_wrapper(self.strategy.custom_entry_price,
default_retval=row[OPEN_IDX])(
pair=pair, current_time=current_time,
proposed_rate=propose_rate, entry_tag=entry_tag) # default value is the open rate
# We can't place orders higher than current high (otherwise it'd be a stop limit buy)
# which freqtrade does not support in live.
propose_rate = min(propose_rate, row[HIGH_IDX])
min_stake_amount = self.exchange.get_min_pair_stake_amount(pair, propose_rate, -0.05) or 0
max_stake_amount = self.wallets.get_available_stake_amount()
@ -485,9 +528,9 @@ class Backtesting:
pos_adjust = trade is not None
if not pos_adjust:
try:
stake_amount = self.wallets.get_trade_stake_amount(pair, None)
stake_amount = self.wallets.get_trade_stake_amount(pair, None, update=False)
except DependencyException:
return trade
return None
stake_amount = strategy_safe_wrapper(self.strategy.custom_stake_amount,
default_retval=stake_amount)(
@ -502,8 +545,7 @@ class Backtesting:
# If not pos adjust, trade is None
return trade
order_type = self.strategy.order_types['buy']
time_in_force = self.strategy.order_time_in_force['sell']
time_in_force = self.strategy.order_time_in_force['buy']
# Confirm trade entry:
if not pos_adjust:
if not strategy_safe_wrapper(self.strategy.confirm_trade_entry, default_retval=True)(
@ -513,15 +555,21 @@ class Backtesting:
return None
if stake_amount and (not min_stake_amount or stake_amount > min_stake_amount):
self.order_id_counter += 1
amount = round(stake_amount / propose_rate, 8)
if trade is None:
# Enter trade
self.trade_id_counter += 1
trade = LocalTrade(
id=self.trade_id_counter,
open_order_id=self.order_id_counter,
pair=pair,
open_rate=propose_rate,
open_rate_requested=propose_rate,
open_date=current_time,
stake_amount=stake_amount,
amount=amount,
amount_requested=amount,
fee_open=self.fee,
fee_close=self.fee,
is_open=True,
@ -529,28 +577,36 @@ class Backtesting:
exchange='backtesting',
orders=[]
)
trade.adjust_stop_loss(trade.open_rate, self.strategy.stoploss, initial=True)
order = Order(
ft_is_open=False,
id=self.order_id_counter,
ft_trade_id=trade.id,
ft_is_open=True,
ft_pair=trade.pair,
order_id=str(self.order_id_counter),
symbol=trade.pair,
ft_order_side="buy",
side="buy",
order_type="market",
status="closed",
order_type=order_type,
status="open",
order_date=current_time,
order_filled_date=current_time,
order_update_date=current_time,
price=propose_rate,
average=propose_rate,
amount=amount,
filled=amount,
cost=stake_amount + trade.fee_open
filled=0,
remaining=amount,
cost=stake_amount + trade.fee_open,
)
if pos_adjust and self._get_order_filled(order.price, row):
order.close_bt_order(current_time)
else:
trade.open_order_id = str(self.order_id_counter)
trade.orders.append(order)
if pos_adjust:
trade.recalc_trade_from_orders()
trade.recalc_trade_from_orders()
return trade
@ -563,6 +619,9 @@ class Backtesting:
for pair in open_trades.keys():
if len(open_trades[pair]) > 0:
for trade in open_trades[pair]:
if trade.open_order_id and trade.nr_of_successful_buys == 0:
# Ignore trade if buy-order did not fill yet
continue
sell_row = data[pair][-1]
trade.close_date = sell_row[DATE_IDX].to_pydatetime()
@ -583,6 +642,51 @@ class Backtesting:
self.rejected_trades += 1
return False
def run_protections(self, enable_protections, pair: str, current_time: datetime):
if enable_protections:
self.protections.stop_per_pair(pair, current_time)
self.protections.global_stop(current_time)
def check_order_cancel(self, trade: LocalTrade, current_time) -> bool:
"""
Check if an order has been canceled.
Returns True if the trade should be Deleted (initial order was canceled).
"""
for order in [o for o in trade.orders if o.ft_is_open]:
timedout = self.strategy.ft_check_timed_out(order.side, trade, order, current_time)
if timedout:
if order.side == 'buy':
self.timedout_entry_orders += 1
if trade.nr_of_successful_buys == 0:
# Remove trade due to buy timeout expiration.
return True
else:
# Close additional buy order
del trade.orders[trade.orders.index(order)]
if order.side == 'sell':
self.timedout_exit_orders += 1
# Close sell order and retry selling on next signal.
del trade.orders[trade.orders.index(order)]
return False
def validate_row(
self, data: Dict, pair: str, row_index: int, current_time: datetime) -> Optional[Tuple]:
try:
# Row is treated as "current incomplete candle".
# Buy / sell signals are shifted by 1 to compensate for this.
row = data[pair][row_index]
except IndexError:
# missing Data for one pair at the end.
# Warnings for this are shown during data loading
return None
# Waits until the time-counter reaches the start of the data for this pair.
if row[DATE_IDX] > current_time:
return None
return row
def backtest(self, processed: Dict,
start_date: datetime, end_date: datetime,
max_open_trades: int = 0, position_stacking: bool = False,
@ -605,14 +709,15 @@ class Backtesting:
"""
trades: List[LocalTrade] = []
self.prepare_backtest(enable_protections)
# Ensure wallets are uptodate (important for --strategy-list)
self.wallets.update()
# Use dict of lists with data for performance
# (looping lists is a lot faster than pandas DataFrames)
data: Dict = self._get_ohlcv_as_lists(processed)
# Indexes per pair, so some pairs are allowed to have a missing start.
indexes: Dict = defaultdict(int)
tmp = start_date + timedelta(minutes=self.timeframe_min)
current_time = start_date + timedelta(minutes=self.timeframe_min)
open_trades: Dict[str, List[LocalTrade]] = defaultdict(list)
open_trade_count = 0
@ -621,35 +726,27 @@ class Backtesting:
(end_date - start_date) / timedelta(minutes=self.timeframe_min)))
# Loop timerange and get candle for each pair at that point in time
while tmp <= end_date:
while current_time <= end_date:
open_trade_count_start = open_trade_count
self.check_abort()
for i, pair in enumerate(data):
row_index = indexes[pair]
try:
# Row is treated as "current incomplete candle".
# Buy / sell signals are shifted by 1 to compensate for this.
row = data[pair][row_index]
except IndexError:
# missing Data for one pair at the end.
# Warnings for this are shown during data loading
continue
# Waits until the time-counter reaches the start of the data for this pair.
if row[DATE_IDX] > tmp:
row = self.validate_row(data, pair, row_index, current_time)
if not row:
continue
row_index += 1
indexes[pair] = row_index
self.dataprovider._set_dataframe_max_index(row_index)
# 1. Process buys.
# without positionstacking, we can only have one open trade per pair.
# max_open_trades must be respected
# don't open on the last row
if (
(position_stacking or len(open_trades[pair]) == 0)
and self.trade_slot_available(max_open_trades, open_trade_count_start)
and tmp != end_date
and current_time != end_date
and row[BUY_IDX] == 1
and row[SELL_IDX] != 1
and not PairLocks.is_pair_locked(pair, row[DATE_IDX])
@ -657,32 +754,51 @@ class Backtesting:
trade = self._enter_trade(pair, row)
if trade:
# TODO: hacky workaround to avoid opening > max_open_trades
# This emulates previous behaviour - not sure if this is correct
# This emulates previous behavior - not sure if this is correct
# Prevents buying if the trade-slot was freed in this candle
open_trade_count_start += 1
open_trade_count += 1
# logger.debug(f"{pair} - Emulate creation of new trade: {trade}.")
open_trades[pair].append(trade)
LocalTrade.add_bt_trade(trade)
for trade in list(open_trades[pair]):
# also check the buying candle for sell conditions.
trade_entry = self._get_sell_trade_entry(trade, row)
# Sell occurred
if trade_entry:
# 2. Process buy orders.
order = trade.select_order('buy', is_open=True)
if order and self._get_order_filled(order.price, row):
order.close_bt_order(current_time)
trade.open_order_id = None
LocalTrade.add_bt_trade(trade)
self.wallets.update()
# 3. Create sell orders (if any)
if not trade.open_order_id:
self._get_sell_trade_entry(trade, row) # Place sell order if necessary
# 4. Process sell orders.
order = trade.select_order('sell', is_open=True)
if order and self._get_order_filled(order.price, row):
trade.open_order_id = None
trade.close_date = current_time
trade.close(order.price, show_msg=False)
# logger.debug(f"{pair} - Backtesting sell {trade}")
open_trade_count -= 1
open_trades[pair].remove(trade)
LocalTrade.close_bt_trade(trade)
trades.append(trade_entry)
if enable_protections:
self.protections.stop_per_pair(pair, row[DATE_IDX])
self.protections.global_stop(tmp)
trades.append(trade)
self.wallets.update()
self.run_protections(enable_protections, pair, current_time)
# 5. Cancel expired buy/sell orders.
if self.check_order_cancel(trade, current_time):
# Close trade due to buy timeout expiration.
open_trade_count -= 1
open_trades[pair].remove(trade)
self.wallets.update()
# Move time one configured time_interval ahead.
self.progress.increment()
tmp += timedelta(minutes=self.timeframe_min)
current_time += timedelta(minutes=self.timeframe_min)
trades += self.handle_left_open(open_trades, data=data)
self.wallets.update()
@ -693,6 +809,8 @@ class Backtesting:
'config': self.strategy.config,
'locks': PairLocks.get_all_locks(),
'rejected_signals': self.rejected_trades,
'timedout_entry_orders': self.timedout_entry_orders,
'timedout_exit_orders': self.timedout_exit_orders,
'final_balance': self.wallets.get_total(self.strategy.config['stake_currency']),
}

View File

@ -0,0 +1,30 @@
"""
ProfitDrawDownHyperOptLoss
This module defines the alternative HyperOptLoss class based on Profit &
Drawdown objective which can be used for Hyperoptimization.
Possible to change `DRAWDOWN_MULT` to penalize drawdown objective for
individual needs.
"""
from pandas import DataFrame
from freqtrade.data.btanalysis import calculate_max_drawdown
from freqtrade.optimize.hyperopt import IHyperOptLoss
# higher numbers penalize drawdowns more severely
DRAWDOWN_MULT = 0.075
class ProfitDrawDownHyperOptLoss(IHyperOptLoss):
@staticmethod
def hyperopt_loss_function(results: DataFrame, trade_count: int, *args, **kwargs) -> float:
total_profit = results["profit_abs"].sum()
try:
max_drawdown_abs = calculate_max_drawdown(results, value_col="profit_abs")[5]
except ValueError:
max_drawdown_abs = 0
return -1 * (total_profit * (1 - max_drawdown_abs * DRAWDOWN_MULT))

View File

@ -436,6 +436,8 @@ def generate_strategy_stats(pairlist: List[str],
'dry_run_wallet': starting_balance,
'final_balance': content['final_balance'],
'rejected_signals': content['rejected_signals'],
'timedout_entry_orders': content['timedout_entry_orders'],
'timedout_exit_orders': content['timedout_exit_orders'],
'max_open_trades': max_open_trades,
'max_open_trades_setting': (config['max_open_trades']
if config['max_open_trades'] != float('inf') else -1),
@ -726,6 +728,9 @@ def text_table_add_metrics(strat_results: Dict) -> str:
('Avg. Duration Winners', f"{strat_results['winner_holding_avg']}"),
('Avg. Duration Loser', f"{strat_results['loser_holding_avg']}"),
('Rejected Buy signals', strat_results.get('rejected_signals', 'N/A')),
('Entry/Exit Timeouts',
f"{strat_results.get('timedout_entry_orders', 'N/A')} / "
f"{strat_results.get('timedout_exit_orders', 'N/A')}"),
('', ''), # Empty line to improve readability
('Min balance', round_coin_value(strat_results['csum_min'],

View File

@ -28,7 +28,36 @@ def get_backup_name(tabs, backup_prefix: str):
return table_back_name
def migrate_trades_table(decl_base, inspector, engine, table_back_name: str, cols: List):
def get_last_sequence_ids(engine, trade_back_name, order_back_name):
order_id: int = None
trade_id: int = None
if engine.name == 'postgresql':
with engine.begin() as connection:
trade_id = connection.execute(text("select nextval('trades_id_seq')")).fetchone()[0]
order_id = connection.execute(text("select nextval('orders_id_seq')")).fetchone()[0]
with engine.begin() as connection:
connection.execute(text(
f"ALTER SEQUENCE orders_id_seq rename to {order_back_name}_id_seq_bak"))
connection.execute(text(
f"ALTER SEQUENCE trades_id_seq rename to {trade_back_name}_id_seq_bak"))
return order_id, trade_id
def set_sequence_ids(engine, order_id, trade_id):
if engine.name == 'postgresql':
with engine.begin() as connection:
if order_id:
connection.execute(text(f"ALTER SEQUENCE orders_id_seq RESTART WITH {order_id}"))
if trade_id:
connection.execute(text(f"ALTER SEQUENCE trades_id_seq RESTART WITH {trade_id}"))
def migrate_trades_and_orders_table(
decl_base, inspector, engine,
trade_back_name: str, cols: List,
order_back_name: str):
fee_open = get_column_def(cols, 'fee_open', 'fee')
fee_open_cost = get_column_def(cols, 'fee_open_cost', 'null')
fee_open_currency = get_column_def(cols, 'fee_open_currency', 'null')
@ -64,11 +93,20 @@ def migrate_trades_table(decl_base, inspector, engine, table_back_name: str, col
# Schema migration necessary
with engine.begin() as connection:
connection.execute(text(f"alter table trades rename to {table_back_name}"))
connection.execute(text(f"alter table trades rename to {trade_back_name}"))
with engine.begin() as connection:
# drop indexes on backup table in new session
for index in inspector.get_indexes(table_back_name):
connection.execute(text(f"drop index {index['name']}"))
for index in inspector.get_indexes(trade_back_name):
if engine.name == 'mysql':
connection.execute(text(f"drop index {index['name']} on {trade_back_name}"))
else:
connection.execute(text(f"drop index {index['name']}"))
order_id, trade_id = get_last_sequence_ids(engine, trade_back_name, order_back_name)
drop_orders_table(engine, order_back_name)
# let SQLAlchemy create the schema as required
decl_base.metadata.create_all(engine)
@ -100,9 +138,12 @@ def migrate_trades_table(decl_base, inspector, engine, table_back_name: str, col
{sell_order_status} sell_order_status,
{strategy} strategy, {buy_tag} buy_tag, {timeframe} timeframe,
{open_trade_value} open_trade_value, {close_profit_abs} close_profit_abs
from {table_back_name}
from {trade_back_name}
"""))
migrate_orders_table(engine, order_back_name, cols)
set_sequence_ids(engine, order_id, trade_id)
def migrate_open_orders_to_trades(engine):
with engine.begin() as connection:
@ -121,19 +162,18 @@ def migrate_open_orders_to_trades(engine):
"""))
def migrate_orders_table(decl_base, inspector, engine, table_back_name: str, cols: List):
# Schema migration necessary
def drop_orders_table(engine, table_back_name: str):
# Drop and recreate orders table as backup
# This drops foreign keys, too.
with engine.begin() as connection:
connection.execute(text(f"alter table orders rename to {table_back_name}"))
connection.execute(text(f"create table {table_back_name} as select * from orders"))
connection.execute(text("drop table orders"))
with engine.begin() as connection:
# drop indexes on backup table in new session
for index in inspector.get_indexes(table_back_name):
connection.execute(text(f"drop index {index['name']}"))
def migrate_orders_table(engine, table_back_name: str, cols: List):
# let SQLAlchemy create the schema as required
decl_base.metadata.create_all(engine)
with engine.begin() as connection:
connection.execute(text(f"""
insert into orders ( id, ft_trade_id, ft_order_side, ft_pair, ft_is_open, order_id,
@ -155,11 +195,16 @@ def check_migrate(engine, decl_base, previous_tables) -> None:
cols = inspector.get_columns('trades')
tabs = get_table_names_for_table(inspector, 'trades')
table_back_name = get_backup_name(tabs, 'trades_bak')
order_tabs = get_table_names_for_table(inspector, 'orders')
order_table_bak_name = get_backup_name(order_tabs, 'orders_bak')
# Check for latest column
# Check if migration necessary
# Migrates both trades and orders table!
if not has_column(cols, 'buy_tag'):
logger.info(f'Running database migration for trades - backup: {table_back_name}')
migrate_trades_table(decl_base, inspector, engine, table_back_name, cols)
logger.info(f"Running database migration for trades - "
f"backup: {table_back_name}, {order_table_bak_name}")
migrate_trades_and_orders_table(
decl_base, inspector, engine, table_back_name, cols, order_table_bak_name)
# Reread columns - the above recreated the table!
inspector = inspect(engine)
cols = inspector.get_columns('trades')
@ -167,12 +212,3 @@ def check_migrate(engine, decl_base, previous_tables) -> None:
if 'orders' not in previous_tables and 'trades' in previous_tables:
logger.info('Moving open orders to Orders table.')
migrate_open_orders_to_trades(engine)
else:
cols_order = inspector.get_columns('orders')
if not has_column(cols_order, 'average'):
tabs = get_table_names_for_table(inspector, 'orders')
# Empty for now - as there is only one iteration of the orders table so far.
table_back_name = get_backup_name(tabs, 'orders_bak')
migrate_orders_table(decl_base, inspector, engine, table_back_name, cols)

View File

@ -132,6 +132,10 @@ class Order(_DECL_BASE):
order_filled_date = Column(DateTime, nullable=True)
order_update_date = Column(DateTime, nullable=True)
@property
def order_date_utc(self):
return self.order_date.replace(tzinfo=timezone.utc)
def __repr__(self):
return (f'Order(id={self.id}, order_id={self.order_id}, trade_id={self.ft_trade_id}, '
@ -165,6 +169,35 @@ class Order(_DECL_BASE):
self.order_filled_date = datetime.now(timezone.utc)
self.order_update_date = datetime.now(timezone.utc)
def to_json(self) -> Dict[str, Any]:
return {
'amount': self.amount,
'average': round(self.average, 8) if self.average else 0,
'cost': self.cost if self.cost else 0,
'filled': self.filled,
'ft_order_side': self.ft_order_side,
'is_open': self.ft_is_open,
'order_date': self.order_date.strftime(DATETIME_PRINT_FORMAT)
if self.order_date else None,
'order_timestamp': int(self.order_date.replace(
tzinfo=timezone.utc).timestamp() * 1000) if self.order_date else None,
'order_filled_date': self.order_filled_date.strftime(DATETIME_PRINT_FORMAT)
if self.order_filled_date else None,
'order_filled_timestamp': int(self.order_filled_date.replace(
tzinfo=timezone.utc).timestamp() * 1000) if self.order_filled_date else None,
'order_type': self.order_type,
'pair': self.ft_pair,
'price': self.price,
'remaining': self.remaining,
'status': self.status,
}
def close_bt_order(self, close_date: datetime):
self.order_filled_date = close_date
self.filled = self.amount
self.status = 'closed'
self.ft_is_open = False
@staticmethod
def update_orders(orders: List['Order'], order: Dict[str, Any]):
"""
@ -282,6 +315,16 @@ class LocalTrade():
return self.close_date.replace(tzinfo=timezone.utc)
def to_json(self) -> Dict[str, Any]:
filled_orders = self.select_filled_orders()
filled_entries = []
filled_exits = []
if len(filled_orders) > 0:
for order in filled_orders:
if order.ft_order_side == 'buy':
filled_entries.append(order.to_json())
if order.ft_order_side == 'sell':
filled_exits.append(order.to_json())
return {
'trade_id': self.id,
'pair': self.pair,
@ -345,6 +388,8 @@ class LocalTrade():
'max_rate': self.max_rate,
'open_order_id': self.open_order_id,
'filled_entry_orders': filled_entries,
'filled_exit_orders': filled_exits,
}
@staticmethod
@ -600,14 +645,27 @@ class LocalTrade():
if self.stop_loss_pct is not None and self.open_rate is not None:
self.adjust_stop_loss(self.open_rate, self.stop_loss_pct)
def select_order(self, order_side: str, is_open: Optional[bool]) -> Optional[Order]:
def select_order_by_order_id(self, order_id: str) -> Optional[Order]:
"""
Finds order object by Order id.
:param order_id: Exchange order id
"""
for o in self.orders:
if o.order_id == order_id:
return o
return None
def select_order(
self, order_side: str = None, is_open: Optional[bool] = None) -> Optional[Order]:
"""
Finds latest order for this orderside and status
:param order_side: Side of the order (either 'buy' or 'sell')
:param order_side: ft_order_side of the order (either 'buy', 'sell' or 'stoploss')
:param is_open: Only search for open orders?
:return: latest Order object if it exists, else None
"""
orders = [o for o in self.orders if o.side == order_side]
orders = self.orders
if order_side:
orders = [o for o in self.orders if o.ft_order_side == order_side]
if is_open is not None:
orders = [o for o in orders if o.ft_is_open == is_open]
if len(orders) > 0:
@ -615,14 +673,14 @@ class LocalTrade():
else:
return None
def select_filled_orders(self, order_side: str) -> List['Order']:
def select_filled_orders(self, order_side: Optional[str] = None) -> List['Order']:
"""
Finds filled orders for this orderside.
:param order_side: Side of the order (either 'buy' or 'sell')
:param order_side: Side of the order (either 'buy', 'sell', or None)
:return: array of Order objects
"""
return [o for o in self.orders if o.ft_order_side == order_side and
o.ft_is_open is False and
return [o for o in self.orders if ((o.ft_order_side == order_side) or (order_side is None))
and o.ft_is_open is False and
(o.filled or 0) > 0 and
o.status in NON_OPEN_EXCHANGE_STATES]

View File

@ -61,8 +61,8 @@ def init_plotscript(config, markets: List, startup_candles: int = 0):
startup_candles, min_date)
no_trades = False
filename = config.get('exportfilename')
if config.get('no_trades', False):
filename = config.get("exportfilename")
if config.get("no_trades", False):
no_trades = True
elif config['trade_source'] == 'file':
if not filename.is_dir() and not filename.is_file():

View File

@ -60,6 +60,7 @@ class PerformanceFilter(IPairList):
# Get pairlist from performance dataframe values
list_df = pd.DataFrame({'pair': pairlist})
list_df['prior_idx'] = list_df.index
# Set initial value for pairs with no trades to 0
# Sort the list using:
@ -67,7 +68,7 @@ class PerformanceFilter(IPairList):
# - then count (low to high, so as to favor same performance with fewer trades)
# - then pair name alphametically
sorted_df = list_df.merge(performance, on='pair', how='left')\
.fillna(0).sort_values(by=['count', 'pair'], ascending=True)\
.fillna(0).sort_values(by=['count', 'prior_idx'], ascending=True)\
.sort_values(by=['profit_ratio'], ascending=False)
if self._min_profit is not None:
removed = sorted_df[sorted_df['profit_ratio'] < self._min_profit]

View File

@ -32,6 +32,10 @@ async def api_start_backtest(bt_settings: BacktestRequest, background_tasks: Bac
for setting in settings.keys():
if settings[setting] is not None:
btconfig[setting] = settings[setting]
try:
btconfig['stake_amount'] = float(btconfig['stake_amount'])
except ValueError:
pass
# Force dry-run for backtesting
btconfig['dry_run'] = True
@ -57,8 +61,7 @@ async def api_start_backtest(bt_settings: BacktestRequest, background_tasks: Bac
):
from freqtrade.optimize.backtesting import Backtesting
ApiServer._bt = Backtesting(btconfig)
if ApiServer._bt.timeframe_detail:
ApiServer._bt.load_bt_data_detail()
ApiServer._bt.load_bt_data_detail()
else:
ApiServer._bt.config = btconfig
ApiServer._bt.init_backtest()

View File

@ -109,7 +109,7 @@ class SellReason(BaseModel):
class Stats(BaseModel):
sell_reasons: Dict[str, SellReason]
durations: Dict[str, Union[str, float]]
durations: Dict[str, Optional[float]]
class DailyRecord(BaseModel):
@ -149,7 +149,7 @@ class ShowConfig(BaseModel):
api_version: float
dry_run: bool
stake_currency: str
stake_amount: Union[float, str]
stake_amount: str
available_capital: Optional[float]
stake_currency_decimals: int
max_open_trades: int
@ -280,6 +280,7 @@ class ForceBuyPayload(BaseModel):
price: Optional[float]
ordertype: Optional[OrderTypeValues]
stakeamount: Optional[float]
entry_tag: Optional[str]
class ForceSellPayload(BaseModel):
@ -365,7 +366,7 @@ class BacktestRequest(BaseModel):
timeframe_detail: Optional[str]
timerange: Optional[str]
max_open_trades: Optional[int]
stake_amount: Optional[Union[float, str]]
stake_amount: Optional[str]
enable_protections: bool
dry_run_wallet: Optional[float]
@ -384,3 +385,8 @@ class BacktestResponse(BaseModel):
class SysInfo(BaseModel):
cpu_pct: List[float]
ram_pct: float
class Health(BaseModel):
last_process: datetime
last_process_ts: int

View File

@ -14,12 +14,12 @@ from freqtrade.rpc import RPC
from freqtrade.rpc.api_server.api_schemas import (AvailablePairs, Balances, BlacklistPayload,
BlacklistResponse, Count, Daily,
DeleteLockRequest, DeleteTrade, ForceBuyPayload,
ForceBuyResponse, ForceSellPayload, Locks, Logs,
OpenTradeSchema, PairHistory, PerformanceEntry,
Ping, PlotConfig, Profit, ResultMsg, ShowConfig,
Stats, StatusMsg, StrategyListResponse,
StrategyResponse, SysInfo, Version,
WhitelistResponse)
ForceBuyResponse, ForceSellPayload, Health, Locks,
Logs, OpenTradeSchema, PairHistory,
PerformanceEntry, Ping, PlotConfig, Profit,
ResultMsg, ShowConfig, Stats, StatusMsg,
StrategyListResponse, StrategyResponse, SysInfo,
Version, WhitelistResponse)
from freqtrade.rpc.api_server.deps import get_config, get_exchange, get_rpc, get_rpc_optional
from freqtrade.rpc.rpc import RPCException
@ -136,8 +136,9 @@ def show_config(rpc: Optional[RPC] = Depends(get_rpc_optional), config=Depends(g
def forcebuy(payload: ForceBuyPayload, rpc: RPC = Depends(get_rpc)):
ordertype = payload.ordertype.value if payload.ordertype else None
stake_amount = payload.stakeamount if payload.stakeamount else None
entry_tag = payload.entry_tag if payload.entry_tag else None
trade = rpc._rpc_forcebuy(payload.pair, payload.price, ordertype, stake_amount)
trade = rpc._rpc_forcebuy(payload.pair, payload.price, ordertype, stake_amount, entry_tag)
if trade:
return ForceBuyResponse.parse_obj(trade.to_json())
@ -291,3 +292,8 @@ def list_available_pairs(timeframe: Optional[str] = None, stake_currency: Option
@router.get('/sysinfo', response_model=SysInfo, tags=['info'])
def sysinfo():
return RPC._rpc_sysinfo()
@router.get('/health', response_model=Health, tags=['info'])
def health(rpc: RPC = Depends(get_rpc)):
return rpc._health()

View File

@ -17,6 +17,15 @@ from freqtrade.constants import SUPPORTED_FIAT
logger = logging.getLogger(__name__)
# Manually map symbol to ID for some common coins
# with duplicate coingecko entries
coingecko_mapping = {
'eth': 'ethereum',
'bnb': 'binancecoin',
'sol': 'solana',
}
class CryptoToFiatConverter:
"""
Main class to initiate Crypto to FIAT.
@ -77,8 +86,9 @@ class CryptoToFiatConverter:
else:
return None
found = [x for x in self._coinlistings if x['symbol'] == crypto_symbol]
if crypto_symbol == 'eth':
found = [x for x in self._coinlistings if x['id'] == 'ethereum']
if crypto_symbol in coingecko_mapping.keys():
found = [x for x in self._coinlistings if x['id'] == coingecko_mapping[crypto_symbol]]
if len(found) == 1:
return found[0]['id']

View File

@ -10,8 +10,9 @@ from typing import Any, Dict, List, Optional, Tuple, Union
import arrow
import psutil
from dateutil.relativedelta import relativedelta
from dateutil.tz import tzlocal
from numpy import NAN, inf, int64, mean
from pandas import DataFrame
from pandas import DataFrame, NaT
from freqtrade import __version__
from freqtrade.configuration.timerange import TimeRange
@ -111,7 +112,7 @@ class RPC:
'dry_run': config['dry_run'],
'stake_currency': config['stake_currency'],
'stake_currency_decimals': decimals_per_coin(config['stake_currency']),
'stake_amount': config['stake_amount'],
'stake_amount': str(config['stake_amount']),
'available_capital': config.get('available_capital'),
'max_open_trades': (config['max_open_trades']
if config['max_open_trades'] != float('inf') else -1),
@ -263,7 +264,7 @@ class RPC:
profitcol += " (" + fiat_display_currency + ")"
if self._config.get('position_adjustment_enable', False):
columns = ['ID', 'Pair', 'Since', profitcol, '# Buys']
columns = ['ID', 'Pair', 'Since', profitcol, '# Entries']
else:
columns = ['ID', 'Pair', 'Since', profitcol]
return trades_list, columns, fiat_profit_sum
@ -439,9 +440,9 @@ class RPC:
trade_dur = (trade.close_date - trade.open_date).total_seconds()
dur[trade_win_loss(trade)].append(trade_dur)
wins_dur = sum(dur['wins']) / len(dur['wins']) if len(dur['wins']) > 0 else 'N/A'
draws_dur = sum(dur['draws']) / len(dur['draws']) if len(dur['draws']) > 0 else 'N/A'
losses_dur = sum(dur['losses']) / len(dur['losses']) if len(dur['losses']) > 0 else 'N/A'
wins_dur = sum(dur['wins']) / len(dur['wins']) if len(dur['wins']) > 0 else None
draws_dur = sum(dur['draws']) / len(dur['draws']) if len(dur['draws']) > 0 else None
losses_dur = sum(dur['losses']) / len(dur['losses']) if len(dur['losses']) > 0 else None
durations = {'wins': wins_dur, 'draws': draws_dur, 'losses': losses_dur}
return {'sell_reasons': sell_reasons, 'durations': durations}
@ -716,7 +717,8 @@ class RPC:
return {'result': f'Created sell order for trade {trade_id}.'}
def _rpc_forcebuy(self, pair: str, price: Optional[float], order_type: Optional[str] = None,
stake_amount: Optional[float] = None) -> Optional[Trade]:
stake_amount: Optional[float] = None,
buy_tag: Optional[str] = None) -> Optional[Trade]:
"""
Handler for forcebuy <asset> <price>
Buys a pair trade at the given or current price
@ -750,7 +752,7 @@ class RPC:
order_type = self._freqtrade.strategy.order_types.get(
'forcebuy', self._freqtrade.strategy.order_types['buy'])
if self._freqtrade.execute_entry(pair, stake_amount, price,
ordertype=order_type, trade=trade):
ordertype=order_type, trade=trade, buy_tag=buy_tag):
Trade.commit()
trade = Trade.get_trades([Trade.is_open.is_(True), Trade.pair == pair]).first()
return trade
@ -962,8 +964,16 @@ class RPC:
sell_mask = (dataframe['sell'] == 1)
sell_signals = int(sell_mask.sum())
dataframe.loc[sell_mask, '_sell_signal_close'] = dataframe.loc[sell_mask, 'close']
dataframe = dataframe.replace([inf, -inf], NAN)
dataframe = dataframe.replace({NAN: None})
# band-aid until this is fixed:
# https://github.com/pandas-dev/pandas/issues/45836
datetime_types = ['datetime', 'datetime64', 'datetime64[ns, UTC]']
date_columns = dataframe.select_dtypes(include=datetime_types)
for date_column in date_columns:
# replace NaT with `None`
dataframe[date_column] = dataframe[date_column].astype(object).replace({NaT: None})
dataframe = dataframe.replace({inf: None, -inf: None, NAN: None})
res = {
'pair': pair,
@ -1038,3 +1048,11 @@ class RPC:
"cpu_pct": psutil.cpu_percent(interval=1, percpu=True),
"ram_pct": psutil.virtual_memory().percent
}
def _health(self) -> Dict[str, Union[str, int]]:
last_p = self._freqtrade.last_process
return {
'last_process': str(last_p),
'last_process_loc': last_p.astimezone(tzlocal()).strftime(DATETIME_PRINT_FORMAT),
'last_process_ts': int(last_p.timestamp()),
}

View File

@ -113,7 +113,7 @@ class Telegram(RPCHandler):
r'/stopbuy$', r'/reload_config$', r'/show_config$',
r'/logs$', r'/whitelist$', r'/blacklist$', r'/bl_delete$',
r'/weekly$', r'/weekly \d+$', r'/monthly$', r'/monthly \d+$',
r'/forcebuy$', r'/edge$', r'/help$', r'/version$']
r'/forcebuy$', r'/edge$', r'/health$', r'/help$', r'/version$']
# Create keys for generation
valid_keys_print = [k.replace('$', '') for k in valid_keys]
@ -173,6 +173,7 @@ class Telegram(RPCHandler):
CommandHandler(['blacklist_delete', 'bl_delete'], self._blacklist_delete),
CommandHandler('logs', self._logs),
CommandHandler('edge', self._edge),
CommandHandler('health', self._health),
CommandHandler('help', self._help),
CommandHandler('version', self._version),
]
@ -369,6 +370,48 @@ class Telegram(RPCHandler):
else:
return "\N{CROSS MARK}"
def _prepare_entry_details(self, filled_orders, base_currency, is_open):
"""
Prepare details of trade with entry adjustment enabled
"""
lines = []
for x, order in enumerate(filled_orders):
cur_entry_datetime = arrow.get(order["order_filled_date"])
cur_entry_amount = order["amount"]
cur_entry_average = order["average"]
lines.append(" ")
if x == 0:
lines.append("*Entry #{}:*".format(x+1))
lines.append("*Entry Amount:* {} ({:.8f} {})"
.format(cur_entry_amount, order["cost"], base_currency))
lines.append("*Average Entry Price:* {}".format(cur_entry_average))
else:
sumA = 0
sumB = 0
for y in range(x):
sumA += (filled_orders[y]["amount"] * filled_orders[y]["average"])
sumB += filled_orders[y]["amount"]
prev_avg_price = sumA/sumB
price_to_1st_entry = ((cur_entry_average - filled_orders[0]["average"])
/ filled_orders[0]["average"])
minus_on_entry = (cur_entry_average - prev_avg_price)/prev_avg_price
dur_entry = cur_entry_datetime - arrow.get(filled_orders[x-1]["order_filled_date"])
days = dur_entry.days
hours, remainder = divmod(dur_entry.seconds, 3600)
minutes, seconds = divmod(remainder, 60)
lines.append("*Entry #{}:* at {:.2%} avg profit".format(x+1, minus_on_entry))
if is_open:
lines.append("({})".format(cur_entry_datetime
.humanize(granularity=["day", "hour", "minute"])))
lines.append("*Entry Amount:* {} ({:.8f} {})"
.format(cur_entry_amount, order["cost"], base_currency))
lines.append("*Average Entry Price:* {} ({:.2%} from 1st entry rate)"
.format(cur_entry_average, price_to_1st_entry))
lines.append("*Order filled at:* {}".format(order["order_filled_date"]))
lines.append("({}d {}h {}m {}s from previous entry)"
.format(days, hours, minutes, seconds))
return lines
@authorized_only
def _status(self, update: Update, context: CallbackContext) -> None:
"""
@ -392,37 +435,57 @@ class Telegram(RPCHandler):
trade_ids = [int(i) for i in context.args if i.isnumeric()]
results = self._rpc._rpc_trade_status(trade_ids=trade_ids)
position_adjust = self._config.get('position_adjustment_enable', False)
max_entries = self._config.get('max_entry_position_adjustment', -1)
messages = []
for r in results:
r['open_date_hum'] = arrow.get(r['open_date']).humanize()
r['num_entries'] = len(r['filled_entry_orders'])
r['sell_reason'] = r.get('sell_reason', "")
lines = [
"*Trade ID:* `{trade_id}` `(since {open_date_hum})`",
"*Trade ID:* `{trade_id}`" +
("` (since {open_date_hum})`" if r['is_open'] else ""),
"*Current Pair:* {pair}",
"*Amount:* `{amount} ({stake_amount} {base_currency})`",
"*Buy Tag:* `{buy_tag}`" if r['buy_tag'] else "",
"*Entry Tag:* `{buy_tag}`" if r['buy_tag'] else "",
"*Exit Reason:* `{sell_reason}`" if r['sell_reason'] else "",
]
if position_adjust:
max_buy_str = (f"/{max_entries + 1}" if (max_entries > 0) else "")
lines.append("*Number of Entries:* `{num_entries}`" + max_buy_str)
lines.extend([
"*Open Rate:* `{open_rate:.8f}`",
"*Close Rate:* `{close_rate}`" if r['close_rate'] else "",
"*Current Rate:* `{current_rate:.8f}`",
"*Close Rate:* `{close_rate:.8f}`" if r['close_rate'] else "",
"*Open Date:* `{open_date}`",
"*Close Date:* `{close_date}`" if r['close_date'] else "",
"*Current Rate:* `{current_rate:.8f}`" if r['is_open'] else "",
("*Current Profit:* " if r['is_open'] else "*Close Profit: *")
+ "`{profit_ratio:.2%}`",
]
if (r['stop_loss_abs'] != r['initial_stop_loss_abs']
and r['initial_stop_loss_ratio'] is not None):
# Adding initial stoploss only if it is different from stoploss
lines.append("*Initial Stoploss:* `{initial_stop_loss_abs:.8f}` "
"`({initial_stop_loss_ratio:.2%})`")
])
# Adding stoploss and stoploss percentage only if it is not None
lines.append("*Stoploss:* `{stop_loss_abs:.8f}` " +
("`({stop_loss_ratio:.2%})`" if r['stop_loss_ratio'] else ""))
lines.append("*Stoploss distance:* `{stoploss_current_dist:.8f}` "
"`({stoploss_current_dist_ratio:.2%})`")
if r['open_order']:
if r['sell_order_status']:
lines.append("*Open Order:* `{open_order}` - `{sell_order_status}`")
else:
lines.append("*Open Order:* `{open_order}`")
if r['is_open']:
if (r['stop_loss_abs'] != r['initial_stop_loss_abs']
and r['initial_stop_loss_ratio'] is not None):
# Adding initial stoploss only if it is different from stoploss
lines.append("*Initial Stoploss:* `{initial_stop_loss_abs:.8f}` "
"`({initial_stop_loss_ratio:.2%})`")
# Adding stoploss and stoploss percentage only if it is not None
lines.append("*Stoploss:* `{stop_loss_abs:.8f}` " +
("`({stop_loss_ratio:.2%})`" if r['stop_loss_ratio'] else ""))
lines.append("*Stoploss distance:* `{stoploss_current_dist:.8f}` "
"`({stoploss_current_dist_ratio:.2%})`")
if r['open_order']:
if r['sell_order_status']:
lines.append("*Open Order:* `{open_order}` - `{sell_order_status}`")
else:
lines.append("*Open Order:* `{open_order}`")
lines_detail = self._prepare_entry_details(
r['filled_entry_orders'], r['base_currency'], r['is_open'])
lines.extend((lines_detail if (len(r['filled_entry_orders']) > 1) else ""))
# Filter empty lines using list-comprehension
messages.append("\n".join([line for line in lines if line]).format(**r))
@ -703,9 +766,9 @@ class Telegram(RPCHandler):
duration_msg = tabulate(
[
['Wins', str(timedelta(seconds=durations['wins']))
if durations['wins'] != 'N/A' else 'N/A'],
if durations['wins'] is not None else 'N/A'],
['Losses', str(timedelta(seconds=durations['losses']))
if durations['losses'] != 'N/A' else 'N/A']
if durations['losses'] is not None else 'N/A']
],
headers=['', 'Avg. Duration']
)
@ -851,10 +914,11 @@ class Telegram(RPCHandler):
self._send_msg(str(e))
def _forcebuy_action(self, pair, price=None):
try:
self._rpc._rpc_forcebuy(pair, price)
except RPCException as e:
self._send_msg(str(e))
if pair != 'cancel':
try:
self._rpc._rpc_forcebuy(pair, price)
except RPCException as e:
self._send_msg(str(e))
def _forcebuy_inline(self, update: Update, _: CallbackContext) -> None:
if update.callback_query:
@ -884,10 +948,13 @@ class Telegram(RPCHandler):
self._forcebuy_action(pair, price)
else:
whitelist = self._rpc._rpc_whitelist()['whitelist']
pairs = [InlineKeyboardButton(text=pair, callback_data=pair) for pair in whitelist]
pair_buttons = [
InlineKeyboardButton(text=pair, callback_data=pair) for pair in sorted(whitelist)]
buttons_aligned = self._layout_inline_keyboard(pair_buttons)
buttons_aligned.append([InlineKeyboardButton(text='Cancel', callback_data='cancel')])
self._send_msg(msg="Which pair?",
keyboard=self._layout_inline_keyboard(pairs))
keyboard=buttons_aligned)
@authorized_only
def _trades(self, update: Update, context: CallbackContext) -> None:
@ -1282,6 +1349,7 @@ class Telegram(RPCHandler):
"*/logs [limit]:* `Show latest logs - defaults to 10` \n"
"*/count:* `Show number of active trades compared to allowed number of trades`\n"
"*/edge:* `Shows validated pairs by Edge if it is enabled` \n"
"*/health* `Show latest process timestamp - defaults to 1970-01-01 00:00:00` \n"
"_Statistics_\n"
"------------\n"
@ -1309,6 +1377,19 @@ class Telegram(RPCHandler):
self._send_msg(message, parse_mode=ParseMode.MARKDOWN)
@authorized_only
def _health(self, update: Update, context: CallbackContext) -> None:
"""
Handler for /health
Shows the last process timestamp
"""
try:
health = self._rpc._health()
message = f"Last process: `{health['last_process_loc']}`"
self._send_msg(message)
except RPCException as e:
self._send_msg(str(e))
@authorized_only
def _version(self, update: Update, context: CallbackContext) -> None:
"""

View File

@ -18,6 +18,7 @@ from freqtrade.exceptions import OperationalException, StrategyError
from freqtrade.exchange import timeframe_to_minutes, timeframe_to_seconds
from freqtrade.exchange.exchange import timeframe_to_next_date
from freqtrade.persistence import PairLocks, Trade
from freqtrade.persistence.models import LocalTrade, Order
from freqtrade.strategy.hyper import HyperStrategyMixin
from freqtrade.strategy.informative_decorator import (InformativeData, PopulateIndicators,
_create_and_merge_informative_pair,
@ -686,7 +687,7 @@ class IStrategy(ABC, HyperStrategyMixin):
else:
return False
def should_sell(self, trade: Trade, rate: float, date: datetime, buy: bool,
def should_sell(self, trade: Trade, rate: float, current_time: datetime, buy: bool,
sell: bool, low: float = None, high: float = None,
force_stoploss: float = 0) -> SellCheckTuple:
"""
@ -703,7 +704,8 @@ class IStrategy(ABC, HyperStrategyMixin):
trade.adjust_min_max_rates(high or current_rate, low or current_rate)
stoplossflag = self.stop_loss_reached(current_rate=current_rate, trade=trade,
current_time=date, current_profit=current_profit,
current_time=current_time,
current_profit=current_profit,
force_stoploss=force_stoploss, low=low, high=high)
# Set current rate to high for backtesting sell
@ -713,7 +715,7 @@ class IStrategy(ABC, HyperStrategyMixin):
# if buy signal and ignore_roi is set, we don't need to evaluate min_roi.
roi_reached = (not (buy and self.ignore_roi_if_buy_signal)
and self.min_roi_reached(trade=trade, current_profit=current_profit,
current_time=date))
current_time=current_time))
sell_signal = SellType.NONE
custom_reason = ''
@ -729,8 +731,8 @@ class IStrategy(ABC, HyperStrategyMixin):
sell_signal = SellType.SELL_SIGNAL
else:
custom_reason = strategy_safe_wrapper(self.custom_sell, default_retval=False)(
pair=trade.pair, trade=trade, current_time=date, current_rate=current_rate,
current_profit=current_profit)
pair=trade.pair, trade=trade, current_time=current_time,
current_rate=current_rate, current_profit=current_profit)
if custom_reason:
sell_signal = SellType.CUSTOM_SELL
if isinstance(custom_reason, str):
@ -862,23 +864,22 @@ class IStrategy(ABC, HyperStrategyMixin):
else:
return current_profit > roi
def ft_check_timed_out(self, side: str, trade: Trade, order: Dict,
def ft_check_timed_out(self, side: str, trade: LocalTrade, order: Order,
current_time: datetime) -> bool:
"""
FT Internal method.
Check if timeout is active, and if the order is still open and timed out
"""
timeout = self.config.get('unfilledtimeout', {}).get(side)
ordertime = arrow.get(order['datetime']).datetime
if timeout is not None:
timeout_unit = self.config.get('unfilledtimeout', {}).get('unit', 'minutes')
timeout_kwargs = {timeout_unit: -timeout}
timeout_threshold = current_time + timedelta(**timeout_kwargs)
timedout = (order['status'] == 'open' and order['side'] == side
and ordertime < timeout_threshold)
timedout = (order.status == 'open' and order.side == side
and order.order_date_utc < timeout_threshold)
if timedout:
return True
time_method = self.check_sell_timeout if order['side'] == 'sell' else self.check_buy_timeout
time_method = self.check_sell_timeout if order.side == 'sell' else self.check_buy_timeout
return strategy_safe_wrapper(time_method,
default_retval=False)(

View File

@ -3,7 +3,7 @@
import logging
from copy import deepcopy
from typing import Any, Dict, NamedTuple
from typing import Any, Dict, NamedTuple, Optional
import arrow
@ -211,7 +211,7 @@ class Wallets:
return stake_amount
def get_trade_stake_amount(self, pair: str, edge=None) -> float:
def get_trade_stake_amount(self, pair: str, edge=None, update: bool = True) -> float:
"""
Calculate stake amount for the trade
:return: float: Stake amount
@ -219,7 +219,8 @@ class Wallets:
"""
stake_amount: float
# Ensure wallets are uptodate.
self.update()
if update:
self.update()
val_tied_up = Trade.total_open_trades_stakes()
available_amount = self.get_available_stake_amount()
@ -238,14 +239,15 @@ class Wallets:
return self._check_available_stake_amount(stake_amount, available_amount)
def validate_stake_amount(self, pair, stake_amount, min_stake_amount):
def validate_stake_amount(
self, pair: str, stake_amount: Optional[float], min_stake_amount: Optional[float]):
if not stake_amount:
logger.debug(f"Stake amount is {stake_amount}, ignoring possible trade for {pair}.")
return 0
max_stake_amount = self.get_available_stake_amount()
if min_stake_amount > max_stake_amount:
if min_stake_amount is not None and min_stake_amount > max_stake_amount:
if self._log:
logger.warning("Minimum stake amount > available balance.")
return 0

View File

@ -7,8 +7,8 @@ coveralls==3.3.1
flake8==4.0.1
flake8-tidy-imports==4.6.0
mypy==0.931
pytest==6.2.5
pytest-asyncio==0.17.2
pytest==7.0.1
pytest-asyncio==0.18.1
pytest-cov==3.0.0
pytest-mock==3.7.0
pytest-random-order==1.0.4
@ -17,12 +17,12 @@ isort==5.10.1
time-machine==2.6.0
# Convert jupyter notebooks to markdown documents
nbconvert==6.4.1
nbconvert==6.4.2
# mypy types
types-cachetools==4.2.9
types-filelock==3.2.5
types-requests==2.27.7
types-requests==2.27.9
types-tabulate==0.8.5
# Extensions to datetime library

View File

@ -2,7 +2,7 @@
-r requirements.txt
# Required for hyperopt
scipy==1.7.3
scipy==1.8.0
scikit-learn==1.0.2
scikit-optimize==0.9.0
filelock==3.4.2

View File

@ -1,5 +1,5 @@
# Include all requirements to run the bot.
-r requirements.txt
plotly==5.5.0
plotly==5.6.0

View File

@ -1,13 +1,13 @@
numpy==1.22.1
pandas==1.4.0
numpy==1.22.2
pandas==1.4.1
pandas-ta==0.3.14b
ccxt==1.71.46
ccxt==1.72.98
# Pin cryptography for now due to rust build errors with piwheels
cryptography==36.0.1
aiohttp==3.8.1
SQLAlchemy==1.4.31
python-telegram-bot==13.10
python-telegram-bot==13.11
arrow==1.2.2
cachetools==4.2.2
requests==2.27.1
@ -32,7 +32,7 @@ sdnotify==0.3.2
# API Server
fastapi==0.73.0
uvicorn==0.17.1
uvicorn==0.17.4
pyjwt==2.3.0
aiofiles==0.8.0
psutil==5.9.0
@ -41,6 +41,6 @@ psutil==5.9.0
colorama==0.4.4
# Building config files interactively
questionary==1.10.0
prompt-toolkit==3.0.26
prompt-toolkit==3.0.28
# Extensions to datetime library
python-dateutil==2.8.2

View File

@ -36,7 +36,7 @@ function check_installed_python() {
fi
done
echo "No usable python found. Please make sure to have python3.7 or newer installed."
echo "No usable python found. Please make sure to have python3.8 or newer installed."
exit 1
}

View File

@ -19,13 +19,14 @@ from freqtrade.edge import PairInfo
from freqtrade.enums import RunMode
from freqtrade.exchange import Exchange
from freqtrade.freqtradebot import FreqtradeBot
from freqtrade.persistence import LocalTrade, Trade, init_db
from freqtrade.persistence import LocalTrade, Order, Trade, init_db
from freqtrade.resolvers import ExchangeResolver
from freqtrade.worker import Worker
from tests.conftest_trades import (mock_trade_1, mock_trade_2, mock_trade_3, mock_trade_4,
mock_trade_5, mock_trade_6)
from tests.conftest_trades_usdt import (mock_trade_usdt_1, mock_trade_usdt_2, mock_trade_usdt_3,
mock_trade_usdt_4, mock_trade_usdt_5, mock_trade_usdt_6)
mock_trade_usdt_4, mock_trade_usdt_5, mock_trade_usdt_6,
mock_trade_usdt_7)
logging.getLogger('').setLevel(logging.INFO)
@ -258,6 +259,8 @@ def create_mock_trades_usdt(fee, use_db: bool = True):
trade = mock_trade_usdt_6(fee)
add_trade(trade)
trade = mock_trade_usdt_7(fee)
add_trade(trade)
if use_db:
Trade.commit()
@ -1982,7 +1985,7 @@ def import_fails() -> None:
@pytest.fixture(scope="function")
def open_trade():
return Trade(
trade = Trade(
pair='ETH/BTC',
open_rate=0.00001099,
exchange='binance',
@ -1994,6 +1997,26 @@ def open_trade():
open_date=arrow.utcnow().shift(minutes=-601).datetime,
is_open=True
)
trade.orders = [
Order(
ft_order_side='buy',
ft_pair=trade.pair,
ft_is_open=False,
order_id='123456789',
status="closed",
symbol=trade.pair,
order_type="market",
side="buy",
price=trade.open_rate,
average=trade.open_rate,
filled=trade.amount,
remaining=0,
cost=trade.open_rate * trade.amount,
order_date=trade.open_date,
order_filled_date=trade.open_date,
)
]
return trade
@pytest.fixture(scope="function")

View File

@ -14,6 +14,7 @@ def mock_order_1():
'side': 'buy',
'type': 'limit',
'price': 0.123,
'average': 0.123,
'amount': 123.0,
'filled': 123.0,
'remaining': 0.0,

View File

@ -303,3 +303,61 @@ def mock_trade_usdt_6(fee):
o = Order.parse_from_ccxt_object(mock_order_usdt_6_sell(), 'LTC/USDT', 'sell')
trade.orders.append(o)
return trade
def mock_order_usdt_7():
return {
'id': 'prod_buy_7',
'symbol': 'LTC/USDT',
'status': 'closed',
'side': 'buy',
'type': 'limit',
'price': 10.0,
'amount': 2.0,
'filled': 2.0,
'remaining': 0.0,
}
def mock_order_usdt_7_sell():
return {
'id': 'prod_sell_7',
'symbol': 'LTC/USDT',
'status': 'closed',
'side': 'sell',
'type': 'limit',
'price': 8.0,
'amount': 2.0,
'filled': 2.0,
'remaining': 0.0,
}
def mock_trade_usdt_7(fee):
"""
Simulate prod entry with open sell order
"""
trade = Trade(
pair='LTC/USDT',
stake_amount=20.0,
amount=2.0,
amount_requested=2.0,
open_date=datetime.now(tz=timezone.utc) - timedelta(minutes=20),
close_date=datetime.now(tz=timezone.utc) - timedelta(minutes=5),
fee_open=fee.return_value,
fee_close=fee.return_value,
is_open=False,
open_rate=10.0,
close_rate=8.0,
close_profit=-0.2,
close_profit_abs=-4.0,
exchange='binance',
strategy='SampleStrategy',
open_order_id="prod_sell_6",
timeframe=5,
)
o = Order.parse_from_ccxt_object(mock_order_usdt_7(), 'LTC/USDT', 'buy')
trade.orders.append(o)
o = Order.parse_from_ccxt_object(mock_order_usdt_7_sell(), 'LTC/USDT', 'sell')
trade.orders.append(o)
return trade

View File

@ -53,7 +53,7 @@ EXCHANGES = {
'hasQuoteVolume': True,
'timeframe': '5m',
},
'okex': {
'okx': {
'pair': 'BTC/USDT',
'stake_currency': 'USDT',
'hasQuoteVolume': True,

View File

@ -36,6 +36,8 @@ class BTContainer(NamedTuple):
trailing_stop_positive_offset: float = 0.0
use_sell_signal: bool = False
use_custom_stoploss: bool = False
custom_entry_price: Optional[float] = None
custom_exit_price: Optional[float] = None
def _get_frame_time_from_offset(offset):

View File

@ -1,5 +1,6 @@
# pragma pylint: disable=missing-docstring, W0212, line-too-long, C0103, C0330, unused-argument
import logging
from unittest.mock import MagicMock
import pytest
@ -534,6 +535,80 @@ tc33 = BTContainer(data=[
)]
)
# Test 34: Custom-entry-price below all candles should timeout - so no trade happens.
tc34 = BTContainer(data=[
# D O H L C V B S
[0, 5000, 5050, 4950, 5000, 6172, 1, 0],
[1, 5000, 5500, 4951, 5000, 6172, 0, 0], # timeout
[2, 4900, 5250, 4500, 5100, 6172, 0, 0],
[3, 5100, 5100, 4650, 4750, 6172, 0, 0],
[4, 4750, 4950, 4350, 4750, 6172, 0, 0]],
stop_loss=-0.01, roi={"0": 0.10}, profit_perc=0.0,
custom_entry_price=4200, trades=[]
)
# Test 35: Custom-entry-price above all candles should have rate adjusted to "entry candle high"
tc35 = BTContainer(data=[
# D O H L C V B S
[0, 5000, 5050, 4950, 5000, 6172, 1, 0],
[1, 5000, 5500, 4951, 5000, 6172, 0, 0], # Timeout
[2, 4900, 5250, 4500, 5100, 6172, 0, 0],
[3, 5100, 5100, 4650, 4750, 6172, 0, 0],
[4, 4750, 4950, 4350, 4750, 6172, 0, 0]],
stop_loss=-0.01, roi={"0": 0.10}, profit_perc=-0.01,
custom_entry_price=7200, trades=[
BTrade(sell_reason=SellType.STOP_LOSS, open_tick=1, close_tick=1)
]
)
# Test 36: Custom-entry-price around candle low
# Causes immediate ROI exit. This is currently expected behavior (#6261)
# https://github.com/freqtrade/freqtrade/issues/6261
# But may change at a later point.
tc36 = BTContainer(data=[
# D O H L C V B S BT
[0, 5000, 5050, 4950, 5000, 6172, 1, 0],
[1, 5000, 5500, 4951, 4999, 6172, 0, 0], # Enter and immediate ROI
[2, 4900, 5250, 4500, 5100, 6172, 0, 0],
[3, 5100, 5100, 4650, 4750, 6172, 0, 0],
[4, 4750, 4950, 4350, 4750, 6172, 0, 0]],
stop_loss=-0.10, roi={"0": 0.01}, profit_perc=0.01,
custom_entry_price=4952,
trades=[BTrade(sell_reason=SellType.ROI, open_tick=1, close_tick=1)]
)
# Test 37: Custom exit price below all candles
# Price adjusted to candle Low.
tc37 = BTContainer(data=[
# D O H L C V B S BT
[0, 5000, 5050, 4950, 5000, 6172, 1, 0],
[1, 5000, 5500, 4951, 5000, 6172, 0, 0],
[2, 4900, 5250, 4900, 5100, 6172, 0, 1], # exit - but timeout
[3, 5100, 5100, 4950, 4950, 6172, 0, 0],
[4, 5000, 5100, 4950, 4950, 6172, 0, 0]],
stop_loss=-0.10, roi={"0": 0.10}, profit_perc=-0.01,
use_sell_signal=True,
custom_exit_price=4552,
trades=[BTrade(sell_reason=SellType.SELL_SIGNAL, open_tick=1, close_tick=3)]
)
# Test 38: Custom exit price above all candles
# causes sell signal timeout
tc38 = BTContainer(data=[
# D O H L C V B S BT
[0, 5000, 5050, 4950, 5000, 6172, 1, 0],
[1, 5000, 5500, 4951, 5000, 6172, 0, 0],
[2, 4900, 5250, 4900, 5100, 6172, 0, 1], # exit - but timeout
[3, 5100, 5100, 4950, 4950, 6172, 0, 0],
[4, 5000, 5100, 4950, 4950, 6172, 0, 0]],
stop_loss=-0.10, roi={"0": 0.10}, profit_perc=0.0,
use_sell_signal=True,
custom_exit_price=6052,
trades=[BTrade(sell_reason=SellType.FORCE_SELL, open_tick=1, close_tick=4)]
)
TESTS = [
tc0,
tc1,
@ -569,6 +644,11 @@ TESTS = [
tc31,
tc32,
tc33,
tc34,
tc35,
tc36,
tc37,
tc38,
]
@ -597,6 +677,10 @@ def test_backtest_results(default_conf, fee, mocker, caplog, data) -> None:
backtesting.required_startup = 0
backtesting.strategy.advise_buy = lambda a, m: frame
backtesting.strategy.advise_sell = lambda a, m: frame
if data.custom_entry_price:
backtesting.strategy.custom_entry_price = MagicMock(return_value=data.custom_entry_price)
if data.custom_exit_price:
backtesting.strategy.custom_exit_price = MagicMock(return_value=data.custom_exit_price)
backtesting.strategy.use_custom_stoploss = data.use_custom_stoploss
caplog.set_level(logging.DEBUG)

View File

@ -21,6 +21,7 @@ from freqtrade.data.dataprovider import DataProvider
from freqtrade.data.history import get_timerange
from freqtrade.enums import RunMode, SellType
from freqtrade.exceptions import DependencyException, OperationalException
from freqtrade.exchange.exchange import timeframe_to_next_date
from freqtrade.misc import get_strategy_run_id
from freqtrade.optimize.backtesting import Backtesting
from freqtrade.persistence import LocalTrade
@ -520,6 +521,7 @@ def test_backtest__enter_trade(default_conf, fee, mocker) -> None:
# Fake 2 trades, so there's not enough amount for the next trade left.
LocalTrade.trades_open.append(trade)
LocalTrade.trades_open.append(trade)
backtesting.wallets.update()
trade = backtesting._enter_trade(pair, row=row)
assert trade is None
LocalTrade.trades_open.pop()
@ -527,6 +529,7 @@ def test_backtest__enter_trade(default_conf, fee, mocker) -> None:
assert trade is not None
backtesting.strategy.custom_stake_amount = lambda **kwargs: 123.5
backtesting.wallets.update()
trade = backtesting._enter_trade(pair, row=row)
assert trade
assert trade.stake_amount == 123.5
@ -634,7 +637,8 @@ def test_backtest__get_sell_trade_entry(default_conf, fee, mocker) -> None:
assert res.sell_reason == SellType.ROI.value
# Sell at minute 3 (not available above!)
assert res.close_date_utc == datetime(2020, 1, 1, 5, 3, tzinfo=timezone.utc)
assert round(res.close_rate, 3) == round(209.0225, 3)
sell_order = res.select_order('sell', True)
assert sell_order is not None
def test_backtest_one(default_conf, fee, mocker, testdatadir) -> None:
@ -650,6 +654,7 @@ def test_backtest_one(default_conf, fee, mocker, testdatadir) -> None:
timerange=timerange)
processed = backtesting.strategy.advise_all_indicators(data)
min_date, max_date = get_timerange(processed)
result = backtesting.backtest(
processed=deepcopy(processed),
start_date=min_date,
@ -741,6 +746,46 @@ def test_processed(default_conf, mocker, testdatadir) -> None:
assert col in cols
def test_backtest_dataprovider_analyzed_df(default_conf, fee, mocker, testdatadir) -> None:
default_conf['use_sell_signal'] = False
mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
mocker.patch("freqtrade.exchange.Exchange.get_min_pair_stake_amount", return_value=0.00001)
patch_exchange(mocker)
backtesting = Backtesting(default_conf)
backtesting._set_strategy(backtesting.strategylist[0])
timerange = TimeRange('date', None, 1517227800, 0)
data = history.load_data(datadir=testdatadir, timeframe='5m', pairs=['UNITTEST/BTC'],
timerange=timerange)
processed = backtesting.strategy.advise_all_indicators(data)
min_date, max_date = get_timerange(processed)
global count
count = 0
def tmp_confirm_entry(pair, current_time, **kwargs):
dp = backtesting.strategy.dp
df, _ = dp.get_analyzed_dataframe(pair, backtesting.strategy.timeframe)
current_candle = df.iloc[-1].squeeze()
assert current_candle['buy'] == 1
candle_date = timeframe_to_next_date(backtesting.strategy.timeframe, current_candle['date'])
assert candle_date == current_time
# These asserts don't properly raise as they are nested,
# therefore we increment count and assert for that.
global count
count = count + 1
backtesting.strategy.confirm_trade_entry = tmp_confirm_entry
backtesting.backtest(
processed=deepcopy(processed),
start_date=min_date,
end_date=max_date,
max_open_trades=10,
position_stacking=False,
)
assert count == 5
def test_backtest_pricecontours_protections(default_conf, fee, mocker, testdatadir) -> None:
# While this test IS a copy of test_backtest_pricecontours, it's needed to ensure
# results do not carry-over to the next run, which is not given by using parametrize.
@ -978,6 +1023,8 @@ def test_backtest_start_multi_strat(default_conf, mocker, caplog, testdatadir):
'config': default_conf,
'locks': [],
'rejected_signals': 20,
'timedout_entry_orders': 0,
'timedout_exit_orders': 0,
'final_balance': 1000,
})
mocker.patch('freqtrade.plugins.pairlistmanager.PairListManager.whitelist',
@ -1086,6 +1133,8 @@ def test_backtest_start_multi_strat_nomock(default_conf, mocker, caplog, testdat
'config': default_conf,
'locks': [],
'rejected_signals': 20,
'timedout_entry_orders': 0,
'timedout_exit_orders': 0,
'final_balance': 1000,
},
{
@ -1093,6 +1142,8 @@ def test_backtest_start_multi_strat_nomock(default_conf, mocker, caplog, testdat
'config': default_conf,
'locks': [],
'rejected_signals': 20,
'timedout_entry_orders': 0,
'timedout_exit_orders': 0,
'final_balance': 1000,
}
])
@ -1195,6 +1246,8 @@ def test_backtest_start_multi_strat_nomock_detail(default_conf, mocker,
'config': default_conf,
'locks': [],
'rejected_signals': 20,
'timedout_entry_orders': 0,
'timedout_exit_orders': 0,
'final_balance': 1000,
},
{
@ -1202,6 +1255,8 @@ def test_backtest_start_multi_strat_nomock_detail(default_conf, mocker,
'config': default_conf,
'locks': [],
'rejected_signals': 20,
'timedout_entry_orders': 0,
'timedout_exit_orders': 0,
'final_balance': 1000,
}
])
@ -1263,6 +1318,8 @@ def test_backtest_start_multi_strat_caching(default_conf, mocker, caplog, testda
'config': default_conf,
'locks': [],
'rejected_signals': 20,
'timedout_entry_orders': 0,
'timedout_exit_orders': 0,
'final_balance': 1000,
})
mocker.patch('freqtrade.plugins.pairlistmanager.PairListManager.whitelist',

View File

@ -364,6 +364,8 @@ def test_hyperopt_format_results(hyperopt):
'locks': [],
'final_balance': 0.02,
'rejected_signals': 2,
'timedout_entry_orders': 0,
'timedout_exit_orders': 0,
'backtest_start_time': 1619718665,
'backtest_end_time': 1619718665,
}
@ -431,6 +433,8 @@ def test_generate_optimizer(mocker, hyperopt_conf) -> None:
'config': hyperopt_conf,
'locks': [],
'rejected_signals': 20,
'timedout_entry_orders': 0,
'timedout_exit_orders': 0,
'final_balance': 1000,
}

View File

@ -86,6 +86,7 @@ def test_loss_calculation_has_limited_profit(hyperopt_conf, hyperopt_results) ->
"SharpeHyperOptLossDaily",
"MaxDrawDownHyperOptLoss",
"CalmarHyperOptLoss",
"ProfitDrawDownHyperOptLoss",
])
def test_loss_functions_better_profits(default_conf, hyperopt_results, lossfunction) -> None:
@ -106,7 +107,7 @@ def test_loss_functions_better_profits(default_conf, hyperopt_results, lossfunct
config=default_conf,
processed=None,
backtest_stats={'profit_total': hyperopt_results['profit_abs'].sum()}
)
)
over = hl.hyperopt_loss_function(
results_over,
trade_count=len(results_over),

View File

@ -82,6 +82,8 @@ def test_generate_backtest_stats(default_conf, testdatadir, tmpdir):
'locks': [],
'final_balance': 1000.02,
'rejected_signals': 20,
'timedout_entry_orders': 0,
'timedout_exit_orders': 0,
'backtest_start_time': Arrow.utcnow().int_timestamp,
'backtest_end_time': Arrow.utcnow().int_timestamp,
'run_id': '123',
@ -131,6 +133,8 @@ def test_generate_backtest_stats(default_conf, testdatadir, tmpdir):
'locks': [],
'final_balance': 1000.02,
'rejected_signals': 20,
'timedout_entry_orders': 0,
'timedout_exit_orders': 0,
'backtest_start_time': Arrow.utcnow().int_timestamp,
'backtest_end_time': Arrow.utcnow().int_timestamp,
'run_id': '124',

View File

@ -4,6 +4,7 @@ import logging
import time
from unittest.mock import MagicMock, PropertyMock
import pandas as pd
import pytest
import time_machine
@ -14,7 +15,7 @@ from freqtrade.persistence import Trade
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,
from tests.conftest import (create_mock_trades_usdt, get_patched_exchange, get_patched_freqtradebot,
log_has, log_has_re, num_log_has)
@ -492,7 +493,7 @@ def test_VolumePairList_whitelist_gen(mocker, whitelist_conf, shitcoinmarkets, t
ohlcv_data = {
('ETH/BTC', '1d'): ohlcv_history,
('TKN/BTC', '1d'): ohlcv_history,
('LTC/BTC', '1d'): ohlcv_history.append(ohlcv_history),
('LTC/BTC', '1d'): pd.concat([ohlcv_history, ohlcv_history]),
('XRP/BTC', '1d'): ohlcv_history,
('HOT/BTC', '1d'): ohlcv_history_high_vola,
}
@ -714,29 +715,58 @@ def test_ShuffleFilter_init(mocker, whitelist_conf, caplog) -> None:
@pytest.mark.usefixtures("init_persistence")
def test_PerformanceFilter_lookback(mocker, whitelist_conf, fee, caplog) -> None:
whitelist_conf['exchange']['pair_whitelist'].append('XRP/BTC')
whitelist_conf['pairlists'] = [
def test_PerformanceFilter_lookback(mocker, default_conf_usdt, fee, caplog) -> None:
default_conf_usdt['exchange']['pair_whitelist'].extend(['ADA/USDT', 'XRP/USDT', 'ETC/USDT'])
default_conf_usdt['pairlists'] = [
{"method": "StaticPairList"},
{"method": "PerformanceFilter", "minutes": 60, "min_profit": 0.01}
]
mocker.patch('freqtrade.exchange.Exchange.exchange_has', MagicMock(return_value=True))
exchange = get_patched_exchange(mocker, whitelist_conf)
pm = PairListManager(exchange, whitelist_conf)
exchange = get_patched_exchange(mocker, default_conf_usdt)
pm = PairListManager(exchange, default_conf_usdt)
pm.refresh_pairlist()
assert pm.whitelist == ['ETH/BTC', 'TKN/BTC', 'XRP/BTC']
assert pm.whitelist == ['ETH/USDT', 'XRP/USDT', 'NEO/USDT', 'TKN/USDT']
with time_machine.travel("2021-09-01 05:00:00 +00:00") as t:
create_mock_trades(fee)
create_mock_trades_usdt(fee)
pm.refresh_pairlist()
assert pm.whitelist == ['XRP/BTC']
assert pm.whitelist == ['XRP/USDT']
assert log_has_re(r'Removing pair .* since .* is below .*', caplog)
# Move to "outside" of lookback window, so original sorting is restored.
t.move_to("2021-09-01 07:00:00 +00:00")
pm.refresh_pairlist()
assert pm.whitelist == ['ETH/BTC', 'TKN/BTC', 'XRP/BTC']
assert pm.whitelist == ['ETH/USDT', 'XRP/USDT', 'NEO/USDT', 'TKN/USDT']
@pytest.mark.usefixtures("init_persistence")
def test_PerformanceFilter_keep_mid_order(mocker, default_conf_usdt, fee, caplog) -> None:
default_conf_usdt['exchange']['pair_whitelist'].extend(['ADA/USDT', 'ETC/USDT'])
default_conf_usdt['pairlists'] = [
{"method": "StaticPairList", "allow_inactive": True},
{"method": "PerformanceFilter", "minutes": 60, }
]
mocker.patch('freqtrade.exchange.Exchange.exchange_has', return_value=True)
exchange = get_patched_exchange(mocker, default_conf_usdt)
pm = PairListManager(exchange, default_conf_usdt)
pm.refresh_pairlist()
assert pm.whitelist == ['ETH/USDT', 'LTC/USDT', 'XRP/USDT',
'NEO/USDT', 'TKN/USDT', 'ADA/USDT', 'ETC/USDT']
with time_machine.travel("2021-09-01 05:00:00 +00:00") as t:
create_mock_trades_usdt(fee)
pm.refresh_pairlist()
assert pm.whitelist == ['XRP/USDT', 'ETC/USDT', 'ETH/USDT',
'NEO/USDT', 'TKN/USDT', 'ADA/USDT', 'LTC/USDT']
# assert log_has_re(r'Removing pair .* since .* is below .*', caplog)
# Move to "outside" of lookback window, so original sorting is restored.
t.move_to("2021-09-01 07:00:00 +00:00")
pm.refresh_pairlist()
assert pm.whitelist == ['ETH/USDT', 'LTC/USDT', 'XRP/USDT',
'NEO/USDT', 'TKN/USDT', 'ADA/USDT', 'ETC/USDT']
def test_gen_pair_whitelist_not_supported(mocker, default_conf, tickers) -> None:
@ -1167,13 +1197,13 @@ def test_pairlistmanager_no_pairlist(mocker, whitelist_conf):
{'pair': 'TKN/BTC', 'profit_ratio': -0.0501, 'count': 2},
{'pair': 'ETH/BTC', 'profit_ratio': -0.0501, 'count': 100}],
['TKN/BTC', 'ETH/BTC', 'LTC/BTC']),
# Tie in performance and count, broken by alphabetical sort
# Tie in performance and count, broken by prior sorting sort
([{"method": "StaticPairList"}, {"method": "PerformanceFilter"}],
['ETH/BTC', 'TKN/BTC', 'LTC/BTC'],
[{'pair': 'LTC/BTC', 'profit_ratio': -0.0501, 'count': 1},
{'pair': 'TKN/BTC', 'profit_ratio': -0.0501, 'count': 1},
{'pair': 'ETH/BTC', 'profit_ratio': -0.0501, 'count': 1}],
['ETH/BTC', 'LTC/BTC', 'TKN/BTC']),
['ETH/BTC', 'TKN/BTC', 'LTC/BTC']),
])
def test_performance_filter(mocker, whitelist_conf, pairlists, pair_allowlist, overall_performance,
allowlist_result, tickers, markets, ohlcv_history_list):

View File

@ -108,6 +108,14 @@ def test_rpc_trade_status(default_conf, ticker, fee, mocker) -> None:
'stoploss_entry_dist_ratio': -0.10448878,
'open_order': None,
'exchange': 'binance',
'filled_entry_orders': [{
'amount': 91.07468123, 'average': 1.098e-05,
'cost': 0.0009999999999054, 'filled': 91.07468123, 'ft_order_side': 'buy',
'order_date': ANY, 'order_timestamp': ANY, 'order_filled_date': ANY,
'order_filled_timestamp': ANY, 'order_type': 'limit', 'price': 1.098e-05,
'is_open': False, 'pair': 'ETH/BTC',
'remaining': ANY, 'status': ANY}],
'filled_exit_orders': []
}
mocker.patch('freqtrade.exchange.Exchange.get_rate',
@ -175,6 +183,14 @@ def test_rpc_trade_status(default_conf, ticker, fee, mocker) -> None:
'stoploss_entry_dist_ratio': -0.10448878,
'open_order': None,
'exchange': 'binance',
'filled_entry_orders': [{
'amount': 91.07468123, 'average': 1.098e-05,
'cost': 0.0009999999999054, 'filled': 91.07468123, 'ft_order_side': 'buy',
'order_date': ANY, 'order_timestamp': ANY, 'order_filled_date': ANY,
'order_filled_timestamp': ANY, 'order_type': 'limit', 'price': 1.098e-05,
'is_open': False, 'pair': 'ETH/BTC',
'remaining': ANY, 'status': ANY}],
'filled_exit_orders': []
}
@ -223,7 +239,7 @@ def test_rpc_status_table(default_conf, ticker, fee, mocker) -> None:
rpc._config['position_adjustment_enable'] = True
rpc._config['max_entry_position_adjustment'] = 3
result, headers, fiat_profit_sum = rpc._rpc_status_table(default_conf['stake_currency'], 'USD')
assert "# Buys" in headers
assert "# Entries" in headers
assert len(result[0]) == 5
# 4th column should be 1/4 - as 1 order filled (a total of 4 is possible)
# 3 on top of the initial one.
@ -1276,3 +1292,13 @@ def test_rpc_edge_enabled(mocker, edge_conf) -> None:
assert ret[0]['Winrate'] == 0.66
assert ret[0]['Expectancy'] == 1.71
assert ret[0]['Stoploss'] == -0.02
def test_rpc_health(mocker, default_conf) -> None:
mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
freqtradebot = get_patched_freqtradebot(mocker, default_conf)
rpc = RPC(freqtradebot)
result = rpc._health()
assert result['last_process'] == '1970-01-01 00:00:00+00:00'
assert result['last_process_ts'] == 0

View File

@ -7,6 +7,7 @@ from datetime import datetime, timedelta, timezone
from pathlib import Path
from unittest.mock import ANY, MagicMock, PropertyMock
import pandas as pd
import pytest
import uvicorn
from fastapi import FastAPI
@ -1181,6 +1182,24 @@ def test_api_pair_candles(botclient, ohlcv_history):
0.7039405, 8.885e-05, 0, 0, 1511686800000, None, None]
])
ohlcv_history['sell'] = ohlcv_history['sell'].astype('float64')
ohlcv_history.at[0, 'sell'] = float('inf')
ohlcv_history['date1'] = ohlcv_history['date']
ohlcv_history.at[0, 'date1'] = pd.NaT
ftbot.dataprovider._set_cached_df("XRP/BTC", timeframe, ohlcv_history)
rc = client_get(client,
f"{BASE_URI}/pair_candles?limit={amount}&pair=XRP%2FBTC&timeframe={timeframe}")
assert_response(rc)
assert (rc.json()['data'] ==
[['2017-11-26 08:50:00', 8.794e-05, 8.948e-05, 8.794e-05, 8.88e-05, 0.0877869,
None, 0, None, None, 1511686200000, None, None],
['2017-11-26 08:55:00', 8.88e-05, 8.942e-05, 8.88e-05,
8.893e-05, 0.05874751, 8.886500000000001e-05, 1, 0.0, '2017-11-26 08:55:00',
1511686500000, 8.893e-05, None],
['2017-11-26 09:00:00', 8.891e-05, 8.893e-05, 8.875e-05, 8.877e-05,
0.7039405, 8.885e-05, 0, 0.0, '2017-11-26 09:00:00', 1511686800000, None, None]
])
def test_api_pair_history(botclient, ohlcv_history):
@ -1442,3 +1461,14 @@ def test_api_backtesting(botclient, mocker, fee, caplog, tmpdir):
assert result['status'] == 'reset'
assert not result['running']
assert result['status_msg'] == 'Backtest reset'
def test_health(botclient):
ftbot, client = botclient
rc = client_get(client, f"{BASE_URI}/health")
assert_response(rc)
ret = rc.json()
assert ret['last_process_ts'] == 0
assert ret['last_process'] == '1970-01-01T00:00:00+00:00'

View File

@ -23,6 +23,7 @@ from freqtrade.exceptions import OperationalException
from freqtrade.freqtradebot import FreqtradeBot
from freqtrade.loggers import setup_logging
from freqtrade.persistence import PairLocks, Trade
from freqtrade.persistence.models import Order
from freqtrade.rpc import RPC
from freqtrade.rpc.rpc import RPCException
from freqtrade.rpc.telegram import Telegram, authorized_only
@ -99,7 +100,7 @@ def test_telegram_init(default_conf, mocker, caplog) -> None:
"['count'], ['locks'], ['unlock', 'delete_locks'], "
"['reload_config', 'reload_conf'], ['show_config', 'show_conf'], "
"['stopbuy'], ['whitelist'], ['blacklist'], ['blacklist_delete', 'bl_delete'], "
"['logs'], ['edge'], ['help'], ['version']"
"['logs'], ['edge'], ['health'], ['help'], ['version']"
"]")
assert log_has(message_str, caplog)
@ -201,7 +202,8 @@ def test_telegram_status(default_conf, update, mocker) -> None:
'stoploss_current_dist_ratio': -0.0002,
'stop_loss_ratio': -0.0001,
'open_order': '(limit buy rem=0.00000000)',
'is_open': True
'is_open': True,
'filled_entry_orders': []
}]),
)
@ -217,6 +219,80 @@ def test_telegram_status(default_conf, update, mocker) -> None:
assert status_table.call_count == 1
@pytest.mark.usefixtures("init_persistence")
def test_telegram_status_multi_entry(default_conf, update, mocker, fee) -> None:
update.message.chat.id = "123"
default_conf['telegram']['enabled'] = False
default_conf['telegram']['chat_id'] = "123"
default_conf['position_adjustment_enable'] = True
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
fetch_order=MagicMock(return_value=None),
get_rate=MagicMock(return_value=0.22),
)
telegram, _, msg_mock = get_telegram_testobject(mocker, default_conf)
create_mock_trades(fee)
trades = Trade.get_open_trades()
trade = trades[0]
trade.orders.append(Order(
order_id='5412vbb',
ft_order_side='buy',
ft_pair=trade.pair,
ft_is_open=False,
status="closed",
symbol=trade.pair,
order_type="market",
side="buy",
price=trade.open_rate * 0.95,
average=trade.open_rate * 0.95,
filled=trade.amount,
remaining=0,
cost=trade.amount,
order_date=trade.open_date,
order_filled_date=trade.open_date,
)
)
trade.recalc_trade_from_orders()
Trade.commit()
telegram._status(update=update, context=MagicMock())
assert msg_mock.call_count == 4
msg = msg_mock.call_args_list[0][0][0]
assert re.search(r'Number of Entries.*2', msg)
assert re.search(r'Average Entry Price', msg)
assert re.search(r'Order filled at', msg)
assert re.search(r'Close Date:', msg) is None
assert re.search(r'Close Profit:', msg) is None
@pytest.mark.usefixtures("init_persistence")
def test_telegram_status_closed_trade(default_conf, update, mocker, fee) -> None:
update.message.chat.id = "123"
default_conf['telegram']['enabled'] = False
default_conf['telegram']['chat_id'] = "123"
default_conf['position_adjustment_enable'] = True
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
fetch_order=MagicMock(return_value=None),
get_rate=MagicMock(return_value=0.22),
)
telegram, _, msg_mock = get_telegram_testobject(mocker, default_conf)
create_mock_trades(fee)
trades = Trade.get_trades([Trade.is_open.is_(False)])
trade = trades[0]
context = MagicMock()
context.args = [str(trade.id)]
telegram._status(update=update, context=context)
assert msg_mock.call_count == 1
msg = msg_mock.call_args_list[0][0][0]
assert re.search(r'Close Date:', msg)
assert re.search(r'Close Profit:', msg)
def test_status_handle(default_conf, update, ticker, fee, mocker) -> None:
default_conf['max_open_trades'] = 3
mocker.patch.multiple(
@ -1184,7 +1260,8 @@ def test_forcebuy_no_pair(default_conf, update, mocker) -> None:
assert msg_mock.call_args_list[0][1]['msg'] == 'Which pair?'
# assert msg_mock.call_args_list[0][1]['callback_query_handler'] == 'forcebuy'
keyboard = msg_mock.call_args_list[0][1]['keyboard']
assert reduce(lambda acc, x: acc + len(x), keyboard, 0) == 4
# One additional button - cancel
assert reduce(lambda acc, x: acc + len(x), keyboard, 0) == 5
update = MagicMock()
update.callback_query = MagicMock()
update.callback_query.data = 'XRP/USDT'

View File

@ -437,7 +437,8 @@ def test_stop_loss_reached(default_conf, fee, profit, adjusted, expected, traili
strategy.custom_stoploss = custom_stop
now = arrow.utcnow().datetime
sl_flag = strategy.stop_loss_reached(current_rate=trade.open_rate * (1 + profit), trade=trade,
current_rate = trade.open_rate * (1 + profit)
sl_flag = strategy.stop_loss_reached(current_rate=current_rate, trade=trade,
current_time=now, current_profit=profit,
force_stoploss=0, high=None)
assert isinstance(sl_flag, SellCheckTuple)
@ -447,8 +448,9 @@ def test_stop_loss_reached(default_conf, fee, profit, adjusted, expected, traili
else:
assert sl_flag.sell_flag is True
assert round(trade.stop_loss, 2) == adjusted
current_rate2 = trade.open_rate * (1 + profit2)
sl_flag = strategy.stop_loss_reached(current_rate=trade.open_rate * (1 + profit2), trade=trade,
sl_flag = strategy.stop_loss_reached(current_rate=current_rate2, trade=trade,
current_time=now, current_profit=profit2,
force_stoploss=0, high=None)
assert sl_flag.sell_type == expected2

View File

@ -2042,6 +2042,7 @@ def test_check_handle_timedout_buy_usercustom(default_conf_usdt, ticker_usdt, li
def test_check_handle_timedout_buy(default_conf_usdt, ticker_usdt, limit_buy_order_old, open_trade,
fee, mocker) -> None:
rpc_mock = patch_RPCManager(mocker)
limit_buy_order_old['id'] = open_trade.open_order_id
limit_buy_cancel = deepcopy(limit_buy_order_old)
limit_buy_cancel['status'] = 'canceled'
cancel_order_mock = MagicMock(return_value=limit_buy_cancel)
@ -2126,6 +2127,8 @@ def test_check_handle_timedout_buy_exception(default_conf_usdt, ticker_usdt,
def test_check_handle_timedout_sell_usercustom(default_conf_usdt, ticker_usdt, limit_sell_order_old,
mocker, open_trade, caplog) -> None:
default_conf_usdt["unfilledtimeout"] = {"buy": 1440, "sell": 1440, "exit_timeout_count": 1}
limit_sell_order_old['id'] = open_trade.open_order_id
rpc_mock = patch_RPCManager(mocker)
cancel_order_mock = MagicMock()
patch_exchange(mocker)
@ -2174,7 +2177,7 @@ def test_check_handle_timedout_sell_usercustom(default_conf_usdt, ticker_usdt, l
# 2nd canceled trade - Fail execute sell
caplog.clear()
open_trade.open_order_id = 'order_id_2'
open_trade.open_order_id = limit_sell_order_old['id']
mocker.patch('freqtrade.persistence.Trade.get_exit_order_count', return_value=1)
mocker.patch('freqtrade.freqtradebot.FreqtradeBot.execute_trade_exit',
side_effect=DependencyException)
@ -2185,7 +2188,7 @@ def test_check_handle_timedout_sell_usercustom(default_conf_usdt, ticker_usdt, l
caplog.clear()
# 2nd canceled trade ...
open_trade.open_order_id = 'order_id_2'
open_trade.open_order_id = limit_sell_order_old['id']
freqtrade.check_handle_timedout()
assert log_has_re('Emergencyselling trade.*', caplog)
assert et_mock.call_count == 1
@ -2195,6 +2198,7 @@ def test_check_handle_timedout_sell(default_conf_usdt, ticker_usdt, limit_sell_o
open_trade) -> None:
rpc_mock = patch_RPCManager(mocker)
cancel_order_mock = MagicMock()
limit_sell_order_old['id'] = open_trade.open_order_id
patch_exchange(mocker)
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
@ -2253,6 +2257,7 @@ def test_check_handle_cancelled_sell(default_conf_usdt, ticker_usdt, limit_sell_
def test_check_handle_timedout_partial(default_conf_usdt, ticker_usdt, limit_buy_order_old_partial,
open_trade, mocker) -> None:
rpc_mock = patch_RPCManager(mocker)
limit_buy_order_old_partial['id'] = open_trade.open_order_id
limit_buy_canceled = deepcopy(limit_buy_order_old_partial)
limit_buy_canceled['status'] = 'canceled'
@ -2283,6 +2288,7 @@ def test_check_handle_timedout_partial_fee(default_conf_usdt, ticker_usdt, open_
limit_buy_order_old_partial, trades_for_order,
limit_buy_order_old_partial_canceled, mocker) -> None:
rpc_mock = patch_RPCManager(mocker)
limit_buy_order_old_partial['id'] = open_trade.open_order_id
cancel_order_mock = MagicMock(return_value=limit_buy_order_old_partial_canceled)
mocker.patch('freqtrade.wallets.Wallets.get_free', MagicMock(return_value=0))
patch_exchange(mocker)
@ -2322,6 +2328,8 @@ def test_check_handle_timedout_partial_except(default_conf_usdt, ticker_usdt, op
fee, limit_buy_order_old_partial, trades_for_order,
limit_buy_order_old_partial_canceled, mocker) -> None:
rpc_mock = patch_RPCManager(mocker)
limit_buy_order_old_partial_canceled['id'] = open_trade.open_order_id
limit_buy_order_old_partial['id'] = open_trade.open_order_id
cancel_order_mock = MagicMock(return_value=limit_buy_order_old_partial_canceled)
patch_exchange(mocker)
mocker.patch.multiple(
@ -4102,15 +4110,17 @@ def test_reupdate_enter_order_fees(mocker, default_conf_usdt, fee, caplog):
freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
mock_uts = mocker.patch('freqtrade.freqtradebot.FreqtradeBot.update_trade_state')
mocker.patch('freqtrade.exchange.Exchange.fetch_order_or_stoploss_order',
return_value={'status': 'open'})
create_mock_trades(fee)
trades = Trade.get_trades().all()
freqtrade.reupdate_enter_order_fees(trades[0])
assert log_has_re(r"Trying to reupdate buy fees for .*", caplog)
freqtrade.handle_insufficient_funds(trades[3])
# assert log_has_re(r"Trying to reupdate buy fees for .*", caplog)
assert mock_uts.call_count == 1
assert mock_uts.call_args_list[0][0][0] == trades[0]
assert mock_uts.call_args_list[0][0][1] == mock_order_1()['id']
assert log_has_re(r"Updating buy-fee on trade .* for order .*\.", caplog)
assert mock_uts.call_args_list[0][0][0] == trades[3]
assert mock_uts.call_args_list[0][0][1] == mock_order_4()['id']
assert log_has_re(r"Trying to refind lost order for .*", caplog)
mock_uts.reset_mock()
caplog.clear()
@ -4128,52 +4138,13 @@ def test_reupdate_enter_order_fees(mocker, default_conf_usdt, fee, caplog):
)
Trade.query.session.add(trade)
freqtrade.reupdate_enter_order_fees(trade)
assert log_has_re(r"Trying to reupdate buy fees for .*", caplog)
freqtrade.handle_insufficient_funds(trade)
# assert log_has_re(r"Trying to reupdate buy fees for .*", caplog)
assert mock_uts.call_count == 0
assert not log_has_re(r"Updating buy-fee on trade .* for order .*\.", caplog)
@pytest.mark.usefixtures("init_persistence")
def test_handle_insufficient_funds(mocker, default_conf_usdt, fee):
freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
mock_rlo = mocker.patch('freqtrade.freqtradebot.FreqtradeBot.refind_lost_order')
mock_bof = mocker.patch('freqtrade.freqtradebot.FreqtradeBot.reupdate_enter_order_fees')
create_mock_trades(fee)
trades = Trade.get_trades().all()
# Trade 0 has only a open buy order, no closed order
freqtrade.handle_insufficient_funds(trades[0])
assert mock_rlo.call_count == 0
assert mock_bof.call_count == 1
mock_rlo.reset_mock()
mock_bof.reset_mock()
# Trade 1 has closed buy and sell orders
freqtrade.handle_insufficient_funds(trades[1])
assert mock_rlo.call_count == 1
assert mock_bof.call_count == 0
mock_rlo.reset_mock()
mock_bof.reset_mock()
# Trade 2 has closed buy and sell orders
freqtrade.handle_insufficient_funds(trades[2])
assert mock_rlo.call_count == 1
assert mock_bof.call_count == 0
mock_rlo.reset_mock()
mock_bof.reset_mock()
# Trade 3 has an opne buy order
freqtrade.handle_insufficient_funds(trades[3])
assert mock_rlo.call_count == 0
assert mock_bof.call_count == 1
@pytest.mark.usefixtures("init_persistence")
def test_refind_lost_order(mocker, default_conf_usdt, fee, caplog):
def test_handle_insufficient_funds(mocker, default_conf_usdt, fee, caplog):
caplog.set_level(logging.DEBUG)
freqtrade = get_patched_freqtradebot(mocker, default_conf_usdt)
mock_uts = mocker.patch('freqtrade.freqtradebot.FreqtradeBot.update_trade_state')
@ -4196,7 +4167,7 @@ def test_refind_lost_order(mocker, default_conf_usdt, fee, caplog):
assert trade.open_order_id is None
assert trade.stoploss_order_id is None
freqtrade.refind_lost_order(trade)
freqtrade.handle_insufficient_funds(trade)
order = mock_order_1()
assert log_has_re(r"Order Order(.*order_id=" + order['id'] + ".*) is no longer open.", caplog)
assert mock_fo.call_count == 0
@ -4214,13 +4185,13 @@ def test_refind_lost_order(mocker, default_conf_usdt, fee, caplog):
assert trade.open_order_id is None
assert trade.stoploss_order_id is None
freqtrade.refind_lost_order(trade)
freqtrade.handle_insufficient_funds(trade)
order = mock_order_4()
assert log_has_re(r"Trying to refind Order\(.*", caplog)
assert mock_fo.call_count == 0
assert mock_uts.call_count == 0
# No change to orderid - as update_trade_state is mocked
assert trade.open_order_id is None
assert mock_fo.call_count == 1
assert mock_uts.call_count == 1
# Found open buy order
assert trade.open_order_id is not None
assert trade.stoploss_order_id is None
caplog.clear()
@ -4232,11 +4203,11 @@ def test_refind_lost_order(mocker, default_conf_usdt, fee, caplog):
assert trade.open_order_id is None
assert trade.stoploss_order_id is None
freqtrade.refind_lost_order(trade)
freqtrade.handle_insufficient_funds(trade)
order = mock_order_5_stoploss()
assert log_has_re(r"Trying to refind Order\(.*", caplog)
assert mock_fo.call_count == 1
assert mock_uts.call_count == 1
assert mock_uts.call_count == 2
# stoploss_order_id is "refound" and added to the trade
assert trade.open_order_id is None
assert trade.stoploss_order_id is not None
@ -4251,7 +4222,7 @@ def test_refind_lost_order(mocker, default_conf_usdt, fee, caplog):
assert trade.open_order_id is None
assert trade.stoploss_order_id is None
freqtrade.refind_lost_order(trade)
freqtrade.handle_insufficient_funds(trade)
order = mock_order_6_sell()
assert log_has_re(r"Trying to refind Order\(.*", caplog)
assert mock_fo.call_count == 1
@ -4267,7 +4238,7 @@ def test_refind_lost_order(mocker, default_conf_usdt, fee, caplog):
side_effect=ExchangeError())
order = mock_order_5_stoploss()
freqtrade.refind_lost_order(trades[4])
freqtrade.handle_insufficient_funds(trades[4])
assert log_has(f"Error updating {order['id']}.", caplog)

View File

@ -8,11 +8,12 @@ from unittest.mock import MagicMock
import arrow
import pytest
from sqlalchemy import create_engine, inspect, text
from sqlalchemy import create_engine, text
from freqtrade import constants
from freqtrade.exceptions import DependencyException, OperationalException
from freqtrade.persistence import LocalTrade, Order, Trade, clean_dry_run_db, init_db
from freqtrade.persistence.migrations import get_last_sequence_ids, set_sequence_ids
from tests.conftest import create_mock_trades, create_mock_trades_usdt, log_has, log_has_re
@ -600,7 +601,8 @@ def test_migrate_new(mocker, default_conf, fee, caplog):
assert trade.stoploss_last_update is None
assert log_has("trying trades_bak1", caplog)
assert log_has("trying trades_bak2", caplog)
assert log_has("Running database migration for trades - backup: trades_bak2", caplog)
assert log_has("Running database migration for trades - backup: trades_bak2, orders_bak0",
caplog)
assert trade.open_trade_value == trade._calc_open_trade_value()
assert trade.close_profit_abs is None
@ -613,65 +615,6 @@ def test_migrate_new(mocker, default_conf, fee, caplog):
assert orders[1].order_id == 'stop_order_id222'
assert orders[1].ft_order_side == 'stoploss'
caplog.clear()
# Drop latest column
with engine.begin() as connection:
connection.execute(text("alter table orders rename to orders_bak"))
inspector = inspect(engine)
with engine.begin() as connection:
for index in inspector.get_indexes('orders_bak'):
connection.execute(text(f"drop index {index['name']}"))
# Recreate table
connection.execute(text("""
CREATE TABLE orders (
id INTEGER NOT NULL,
ft_trade_id INTEGER,
ft_order_side VARCHAR NOT NULL,
ft_pair VARCHAR NOT NULL,
ft_is_open BOOLEAN NOT NULL,
order_id VARCHAR NOT NULL,
status VARCHAR,
symbol VARCHAR,
order_type VARCHAR,
side VARCHAR,
price FLOAT,
amount FLOAT,
filled FLOAT,
remaining FLOAT,
cost FLOAT,
order_date DATETIME,
order_filled_date DATETIME,
order_update_date DATETIME,
PRIMARY KEY (id),
CONSTRAINT _order_pair_order_id UNIQUE (ft_pair, order_id),
FOREIGN KEY(ft_trade_id) REFERENCES trades (id)
)
"""))
connection.execute(text("""
insert into orders ( id, ft_trade_id, ft_order_side, ft_pair, ft_is_open, order_id, status,
symbol, order_type, side, price, amount, filled, remaining, cost, order_date,
order_filled_date, order_update_date)
select id, ft_trade_id, ft_order_side, ft_pair, ft_is_open, order_id, status,
symbol, order_type, side, price, amount, filled, remaining, cost, order_date,
order_filled_date, order_update_date
from orders_bak
"""))
# Run init to test migration
init_db(default_conf['db_url'], default_conf['dry_run'])
assert log_has("trying orders_bak1", caplog)
orders = Order.query.all()
assert len(orders) == 2
assert orders[0].order_id == 'buy_order'
assert orders[0].ft_order_side == 'buy'
assert orders[1].order_id == 'stop_order_id222'
assert orders[1].ft_order_side == 'stoploss'
def test_migrate_mid_state(mocker, default_conf, fee, caplog):
"""
@ -733,7 +676,40 @@ def test_migrate_mid_state(mocker, default_conf, fee, caplog):
assert trade.initial_stop_loss == 0.0
assert trade.open_trade_value == trade._calc_open_trade_value()
assert log_has("trying trades_bak0", caplog)
assert log_has("Running database migration for trades - backup: trades_bak0", caplog)
assert log_has("Running database migration for trades - backup: trades_bak0, orders_bak0",
caplog)
def test_migrate_get_last_sequence_ids():
engine = MagicMock()
engine.begin = MagicMock()
engine.name = 'postgresql'
get_last_sequence_ids(engine, 'trades_bak', 'orders_bak')
assert engine.begin.call_count == 2
engine.reset_mock()
engine.begin.reset_mock()
engine.name = 'somethingelse'
get_last_sequence_ids(engine, 'trades_bak', 'orders_bak')
assert engine.begin.call_count == 0
def test_migrate_set_sequence_ids():
engine = MagicMock()
engine.begin = MagicMock()
engine.name = 'postgresql'
set_sequence_ids(engine, 22, 55)
assert engine.begin.call_count == 1
engine.reset_mock()
engine.begin.reset_mock()
engine.name = 'somethingelse'
set_sequence_ids(engine, 22, 55)
assert engine.begin.call_count == 0
def test_adjust_stop_loss(fee):
@ -903,6 +879,8 @@ def test_to_json(default_conf, fee):
'buy_tag': None,
'timeframe': None,
'exchange': 'binance',
'filled_entry_orders': [],
'filled_exit_orders': []
}
# Simulate dry_run entries
@ -970,6 +948,8 @@ def test_to_json(default_conf, fee):
'buy_tag': 'buys_signal_001',
'timeframe': None,
'exchange': 'binance',
'filled_entry_orders': [],
'filled_exit_orders': []
}
@ -1297,11 +1277,14 @@ def test_select_order(fee):
order = trades[4].select_order('buy', False)
assert order is not None
trades[4].orders[1].ft_order_side = 'sell'
order = trades[4].select_order('sell', True)
assert order is not None
trades[4].orders[1].ft_order_side = 'stoploss'
order = trades[4].select_order('stoploss', None)
assert order is not None
assert order.ft_order_side == 'stoploss'
order = trades[4].select_order('sell', False)
assert order is None
def test_Trade_object_idem():

View File

@ -188,6 +188,7 @@ def test_get_trade_stake_amount_unlimited_amount(default_conf, ticker, balance_r
(9, 11, 100, 11), # Below min stake
(1, 15, 10, 0), # Below min stake and min_stake > max_stake
(20, 50, 100, 0), # Below min stake and stake * 1.3 > min_stake
(1000, None, 1000, 1000), # No min-stake-amount could be determined
])
def test_validate_stake_amount(mocker, default_conf,