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Merge pull request #10553 from freqtrade/dependabot/pip/develop/ruff-0.6.1

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chore(deps-dev): bump ruff from 0.5.7 to 0.6.1
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Matthias 2024-08-19 20:37:12 +02:00 committed by GitHub
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6 changed files with 135 additions and 103 deletions
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2
.pre-commit-config.yaml
View File

@ -31,7 +31,7 @@ repos:
- repo: https://github.com/charliermarsh/ruff-pre-commit
# Ruff version.
rev: 'v0.5.7'
rev: 'v0.6.1'
hooks:
- id: ruff

113
docs/strategy_analysis_example.md
View File

@ -13,19 +13,22 @@ Please follow the [documentation](https://www.freqtrade.io/en/stable/data-downlo
import os
from pathlib import Path
# Change directory
# Modify this cell to insure that the output shows the correct path.
# Define all paths relative to the project root shown in the cell output
project_root = "somedir/freqtrade"
i=0
i = 0
try:
os.chdir(project_root)
assert Path('LICENSE').is_file()
except:
while i<4 and (not Path('LICENSE').is_file()):
os.chdir(Path(Path.cwd(), '../'))
i+=1
project_root = Path.cwd()
if not Path("LICENSE").is_file():
i = 0
while i < 4 and (not Path("LICENSE").is_file()):
os.chdir(Path(Path.cwd(), "../"))
i += 1
project_root = Path.cwd()
except FileNotFoundError:
print("Please define the project root relative to the current directory")
print(Path.cwd())
```
@ -35,6 +38,7 @@ print(Path.cwd())
```python
from freqtrade.configuration import Configuration
# Customize these according to your needs.
# Initialize empty configuration object
@ -58,12 +62,14 @@ pair = "BTC/USDT"
from freqtrade.data.history import load_pair_history
from freqtrade.enums import CandleType
candles = load_pair_history(datadir=data_location,
timeframe=config["timeframe"],
pair=pair,
data_format = "json", # Make sure to update this to your data
candle_type=CandleType.SPOT,
)
candles = load_pair_history(
datadir=data_location,
timeframe=config["timeframe"],
pair=pair,
data_format="json", # Make sure to update this to your data
candle_type=CandleType.SPOT,
)
# Confirm success
print(f"Loaded {len(candles)} rows of data for {pair} from {data_location}")
@ -76,14 +82,16 @@ candles.head()
```python
# Load strategy using values set above
from freqtrade.resolvers import StrategyResolver
from freqtrade.data.dataprovider import DataProvider
from freqtrade.resolvers import StrategyResolver
strategy = StrategyResolver.load_strategy(config)
strategy.dp = DataProvider(config, None, None)
strategy.ft_bot_start()
# Generate buy/sell signals using strategy
df = strategy.analyze_ticker(candles, {'pair': pair})
df = strategy.analyze_ticker(candles, {"pair": pair})
df.tail()
```
@ -102,7 +110,7 @@ df.tail()
```python
# Report results
print(f"Generated {df['enter_long'].sum()} entry signals")
data = df.set_index('date', drop=False)
data = df.set_index("date", drop=False)
data.tail()
```
@ -119,10 +127,13 @@ Analyze a trades dataframe (also used below for plotting)
```python
from freqtrade.data.btanalysis import load_backtest_data, load_backtest_stats
# if backtest_dir points to a directory, it'll automatically load the last backtest file.
backtest_dir = config["user_data_dir"] / "backtest_results"
# backtest_dir can also point to a specific file
# backtest_dir = config["user_data_dir"] / "backtest_results/backtest-result-2020-07-01_20-04-22.json"
# backtest_dir can also point to a specific file
# backtest_dir = (
# config["user_data_dir"] / "backtest_results/backtest-result-2020-07-01_20-04-22.json"
# )
```
@ -131,24 +142,24 @@ backtest_dir = config["user_data_dir"] / "backtest_results"
# This contains all information used to generate the backtest result.
stats = load_backtest_stats(backtest_dir)
strategy = 'SampleStrategy'
# All statistics are available per strategy, so if `--strategy-list` was used during backtest, this will be reflected here as well.
strategy = "SampleStrategy"
# All statistics are available per strategy, so if `--strategy-list` was used during backtest,
# this will be reflected here as well.
# Example usages:
print(stats['strategy'][strategy]['results_per_pair'])
print(stats["strategy"][strategy]["results_per_pair"])
# Get pairlist used for this backtest
print(stats['strategy'][strategy]['pairlist'])
print(stats["strategy"][strategy]["pairlist"])
# Get market change (average change of all pairs from start to end of the backtest period)
print(stats['strategy'][strategy]['market_change'])
print(stats["strategy"][strategy]["market_change"])
# Maximum drawdown ()
print(stats['strategy'][strategy]['max_drawdown'])
print(stats["strategy"][strategy]["max_drawdown"])
# Maximum drawdown start and end
print(stats['strategy'][strategy]['drawdown_start'])
print(stats['strategy'][strategy]['drawdown_end'])
print(stats["strategy"][strategy]["drawdown_start"])
print(stats["strategy"][strategy]["drawdown_end"])
# Get strategy comparison (only relevant if multiple strategies were compared)
print(stats['strategy_comparison'])
print(stats["strategy_comparison"])
```
@ -166,24 +177,25 @@ trades.groupby("pair")["exit_reason"].value_counts()
```python
# Plotting equity line (starting with 0 on day 1 and adding daily profit for each backtested day)
import pandas as pd
import plotly.express as px
from freqtrade.configuration import Configuration
from freqtrade.data.btanalysis import load_backtest_stats
import plotly.express as px
import pandas as pd
# strategy = 'SampleStrategy'
# config = Configuration.from_files(["user_data/config.json"])
# backtest_dir = config["user_data_dir"] / "backtest_results"
stats = load_backtest_stats(backtest_dir)
strategy_stats = stats['strategy'][strategy]
strategy_stats = stats["strategy"][strategy]
df = pd.DataFrame(columns=['dates','equity'], data=strategy_stats['daily_profit'])
df['equity_daily'] = df['equity'].cumsum()
df = pd.DataFrame(columns=["dates", "equity"], data=strategy_stats["daily_profit"])
df["equity_daily"] = df["equity"].cumsum()
fig = px.line(df, x="dates", y="equity_daily")
fig.show()
```
### Load live trading results into a pandas dataframe
@ -194,6 +206,7 @@ In case you did already some trading and want to analyze your performance
```python
from freqtrade.data.btanalysis import load_trades_from_db
# Fetch trades from database
trades = load_trades_from_db("sqlite:///tradesv3.sqlite")
@ -210,8 +223,9 @@ This can be useful to find the best `max_open_trades` parameter, when used with
```python
from freqtrade.data.btanalysis import analyze_trade_parallelism
# Analyze the above
parallel_trades = analyze_trade_parallelism(trades, '5m')
parallel_trades = analyze_trade_parallelism(trades, "5m")
parallel_trades.plot()
```
@ -222,23 +236,23 @@ Freqtrade offers interactive plotting capabilities based on plotly.
```python
from freqtrade.plot.plotting import generate_candlestick_graph
from freqtrade.plot.plotting import generate_candlestick_graph
# Limit graph period to keep plotly quick and reactive
# Filter trades to one pair
trades_red = trades.loc[trades['pair'] == pair]
trades_red = trades.loc[trades["pair"] == pair]
data_red = data['2019-06-01':'2019-06-10']
data_red = data["2019-06-01":"2019-06-10"]
# Generate candlestick graph
graph = generate_candlestick_graph(pair=pair,
data=data_red,
trades=trades_red,
indicators1=['sma20', 'ema50', 'ema55'],
indicators2=['rsi', 'macd', 'macdsignal', 'macdhist']
)
graph = generate_candlestick_graph(
pair=pair,
data=data_red,
trades=trades_red,
indicators1=["sma20", "ema50", "ema55"],
indicators2=["rsi", "macd", "macdsignal", "macdhist"],
)
```
@ -248,7 +262,6 @@ graph = generate_candlestick_graph(pair=pair,
# Render graph in a separate window
graph.show(renderer="browser")
```
## Plot average profit per trade as distribution graph
@ -257,12 +270,12 @@ graph.show(renderer="browser")
```python
import plotly.figure_factory as ff
hist_data = [trades.profit_ratio]
group_labels = ['profit_ratio'] # name of the dataset
group_labels = ["profit_ratio"] # name of the dataset
fig = ff.create_distplot(hist_data, group_labels, bin_size=0.01)
fig.show()
```
Feel free to submit an issue or Pull Request enhancing this document if you would like to share ideas on how to best analyze the data.

2
freqtrade/rpc/api_server/api_ws.py
View File

@ -58,7 +58,7 @@ async def channel_broadcaster(channel: WebSocketChannel, message_stream: Message
" consumers."
)
await channel.send(message, timeout=True)
await channel.send(message, use_timeout=True)
async def _process_consumer_request(request: Dict[str, Any], channel: WebSocketChannel, rpc: RPC):

7
freqtrade/rpc/api_server/ws/channel.py
View File

@ -80,7 +80,7 @@ class WebSocketChannel:
self._send_high_limit = min(max(self.avg_send_time * 2, 1), 3)
async def send(
self, message: Union[WSMessageSchemaType, Dict[str, Any]], timeout: bool = False
self, message: Union[WSMessageSchemaType, Dict[str, Any]], use_timeout: bool = False
):
"""
Send a message on the wrapped websocket. If the sending
@ -88,7 +88,7 @@ class WebSocketChannel:
disconnect the connection.
:param message: The message to send
:param timeout: Enforce send high limit, defaults to False
:param use_timeout: Enforce send high limit, defaults to False
"""
try:
_ = time.time()
@ -96,7 +96,8 @@ class WebSocketChannel:
# a TimeoutError and bubble up to the
# message_endpoint to close the connection
await asyncio.wait_for(
self._wrapped_ws.send(message), timeout=self._send_high_limit if timeout else None
self._wrapped_ws.send(message),
timeout=self._send_high_limit if use_timeout else None,
)
total_time = time.time() - _
self._send_times.append(total_time)

112
freqtrade/templates/strategy_analysis_example.ipynb
View File

@ -29,19 +29,22 @@
"import os\n",
"from pathlib import Path\n",
"\n",
"\n",
"# Change directory\n",
"# Modify this cell to insure that the output shows the correct path.\n",
"# Define all paths relative to the project root shown in the cell output\n",
"project_root = \"somedir/freqtrade\"\n",
"i=0\n",
"i = 0\n",
"try:\n",
" os.chdir(project_root)\n",
" assert Path('LICENSE').is_file()\n",
"except:\n",
" while i<4 and (not Path('LICENSE').is_file()):\n",
" os.chdir(Path(Path.cwd(), '../'))\n",
" i+=1\n",
" project_root = Path.cwd()\n",
" if not Path(\"LICENSE\").is_file():\n",
" i = 0\n",
" while i < 4 and (not Path(\"LICENSE\").is_file()):\n",
" os.chdir(Path(Path.cwd(), \"../\"))\n",
" i += 1\n",
" project_root = Path.cwd()\n",
"except FileNotFoundError:\n",
" print(\"Please define the project root relative to the current directory\")\n",
"print(Path.cwd())"
]
},
@ -60,6 +63,7 @@
"source": [
"from freqtrade.configuration import Configuration\n",
"\n",
"\n",
"# Customize these according to your needs.\n",
"\n",
"# Initialize empty configuration object\n",
@ -87,12 +91,14 @@
"from freqtrade.data.history import load_pair_history\n",
"from freqtrade.enums import CandleType\n",
"\n",
"candles = load_pair_history(datadir=data_location,\n",
" timeframe=config[\"timeframe\"],\n",
" pair=pair,\n",
" data_format = \"json\", # Make sure to update this to your data\n",
" candle_type=CandleType.SPOT,\n",
" )\n",
"\n",
"candles = load_pair_history(\n",
" datadir=data_location,\n",
" timeframe=config[\"timeframe\"],\n",
" pair=pair,\n",
" data_format=\"json\", # Make sure to update this to your data\n",
" candle_type=CandleType.SPOT,\n",
")\n",
"\n",
"# Confirm success\n",
"print(f\"Loaded {len(candles)} rows of data for {pair} from {data_location}\")\n",
@ -114,14 +120,16 @@
"outputs": [],
"source": [
"# Load strategy using values set above\n",
"from freqtrade.resolvers import StrategyResolver\n",
"from freqtrade.data.dataprovider import DataProvider\n",
"from freqtrade.resolvers import StrategyResolver\n",
"\n",
"\n",
"strategy = StrategyResolver.load_strategy(config)\n",
"strategy.dp = DataProvider(config, None, None)\n",
"strategy.ft_bot_start()\n",
"\n",
"# Generate buy/sell signals using strategy\n",
"df = strategy.analyze_ticker(candles, {'pair': pair})\n",
"df = strategy.analyze_ticker(candles, {\"pair\": pair})\n",
"df.tail()"
]
},
@ -148,7 +156,7 @@
"source": [
"# Report results\n",
"print(f\"Generated {df['enter_long'].sum()} entry signals\")\n",
"data = df.set_index('date', drop=False)\n",
"data = df.set_index(\"date\", drop=False)\n",
"data.tail()"
]
},
@ -179,10 +187,13 @@
"source": [
"from freqtrade.data.btanalysis import load_backtest_data, load_backtest_stats\n",
"\n",
"\n",
"# if backtest_dir points to a directory, it'll automatically load the last backtest file.\n",
"backtest_dir = config[\"user_data_dir\"] / \"backtest_results\"\n",
"# backtest_dir can also point to a specific file\n",
"# backtest_dir = config[\"user_data_dir\"] / \"backtest_results/backtest-result-2020-07-01_20-04-22.json\""
"# backtest_dir = (\n",
"# config[\"user_data_dir\"] / \"backtest_results/backtest-result-2020-07-01_20-04-22.json\"\n",
"# )"
]
},
{
@ -195,23 +206,24 @@
"# This contains all information used to generate the backtest result.\n",
"stats = load_backtest_stats(backtest_dir)\n",
"\n",
"strategy = 'SampleStrategy'\n",
"# All statistics are available per strategy, so if `--strategy-list` was used during backtest, this will be reflected here as well.\n",
"strategy = \"SampleStrategy\"\n",
"# All statistics are available per strategy, so if `--strategy-list` was used during backtest,\n",
"# this will be reflected here as well.\n",
"# Example usages:\n",
"print(stats['strategy'][strategy]['results_per_pair'])\n",
"print(stats[\"strategy\"][strategy][\"results_per_pair\"])\n",
"# Get pairlist used for this backtest\n",
"print(stats['strategy'][strategy]['pairlist'])\n",
"print(stats[\"strategy\"][strategy][\"pairlist\"])\n",
"# Get market change (average change of all pairs from start to end of the backtest period)\n",
"print(stats['strategy'][strategy]['market_change'])\n",
"print(stats[\"strategy\"][strategy][\"market_change\"])\n",
"# Maximum drawdown ()\n",
"print(stats['strategy'][strategy]['max_drawdown'])\n",
"print(stats[\"strategy\"][strategy][\"max_drawdown\"])\n",
"# Maximum drawdown start and end\n",
"print(stats['strategy'][strategy]['drawdown_start'])\n",
"print(stats['strategy'][strategy]['drawdown_end'])\n",
"print(stats[\"strategy\"][strategy][\"drawdown_start\"])\n",
"print(stats[\"strategy\"][strategy][\"drawdown_end\"])\n",
"\n",
"\n",
"# Get strategy comparison (only relevant if multiple strategies were compared)\n",
"print(stats['strategy_comparison'])\n"
"print(stats[\"strategy_comparison\"])"
]
},
{
@ -242,23 +254,25 @@
"source": [
"# Plotting equity line (starting with 0 on day 1 and adding daily profit for each backtested day)\n",
"\n",
"import pandas as pd\n",
"import plotly.express as px\n",
"\n",
"from freqtrade.configuration import Configuration\n",
"from freqtrade.data.btanalysis import load_backtest_stats\n",
"import plotly.express as px\n",
"import pandas as pd\n",
"\n",
"\n",
"# strategy = 'SampleStrategy'\n",
"# config = Configuration.from_files([\"user_data/config.json\"])\n",
"# backtest_dir = config[\"user_data_dir\"] / \"backtest_results\"\n",
"\n",
"stats = load_backtest_stats(backtest_dir)\n",
"strategy_stats = stats['strategy'][strategy]\n",
"strategy_stats = stats[\"strategy\"][strategy]\n",
"\n",
"df = pd.DataFrame(columns=['dates','equity'], data=strategy_stats['daily_profit'])\n",
"df['equity_daily'] = df['equity'].cumsum()\n",
"df = pd.DataFrame(columns=[\"dates\", \"equity\"], data=strategy_stats[\"daily_profit\"])\n",
"df[\"equity_daily\"] = df[\"equity\"].cumsum()\n",
"\n",
"fig = px.line(df, x=\"dates\", y=\"equity_daily\")\n",
"fig.show()\n"
"fig.show()"
]
},
{
@ -278,6 +292,7 @@
"source": [
"from freqtrade.data.btanalysis import load_trades_from_db\n",
"\n",
"\n",
"# Fetch trades from database\n",
"trades = load_trades_from_db(\"sqlite:///tradesv3.sqlite\")\n",
"\n",
@ -303,8 +318,9 @@
"source": [
"from freqtrade.data.btanalysis import analyze_trade_parallelism\n",
"\n",
"\n",
"# Analyze the above\n",
"parallel_trades = analyze_trade_parallelism(trades, '5m')\n",
"parallel_trades = analyze_trade_parallelism(trades, \"5m\")\n",
"\n",
"parallel_trades.plot()"
]
@ -324,22 +340,23 @@
"metadata": {},
"outputs": [],
"source": [
"from freqtrade.plot.plotting import generate_candlestick_graph\n",
"from freqtrade.plot.plotting import generate_candlestick_graph\n",
"\n",
"\n",
"# Limit graph period to keep plotly quick and reactive\n",
"\n",
"# Filter trades to one pair\n",
"trades_red = trades.loc[trades['pair'] == pair]\n",
"trades_red = trades.loc[trades[\"pair\"] == pair]\n",
"\n",
"data_red = data['2019-06-01':'2019-06-10']\n",
"data_red = data[\"2019-06-01\":\"2019-06-10\"]\n",
"# Generate candlestick graph\n",
"graph = generate_candlestick_graph(pair=pair,\n",
" data=data_red,\n",
" trades=trades_red,\n",
" indicators1=['sma20', 'ema50', 'ema55'],\n",
" indicators2=['rsi', 'macd', 'macdsignal', 'macdhist']\n",
" )\n",
"\n",
"\n"
"graph = generate_candlestick_graph(\n",
" pair=pair,\n",
" data=data_red,\n",
" trades=trades_red,\n",
" indicators1=[\"sma20\", \"ema50\", \"ema55\"],\n",
" indicators2=[\"rsi\", \"macd\", \"macdsignal\", \"macdhist\"],\n",
")"
]
},
{
@ -352,7 +369,7 @@
"# graph.show()\n",
"\n",
"# Render graph in a separate window\n",
"graph.show(renderer=\"browser\")\n"
"graph.show(renderer=\"browser\")"
]
},
{
@ -370,11 +387,12 @@
"source": [
"import plotly.figure_factory as ff\n",
"\n",
"\n",
"hist_data = [trades.profit_ratio]\n",
"group_labels = ['profit_ratio'] # name of the dataset\n",
"group_labels = [\"profit_ratio\"] # name of the dataset\n",
"\n",
"fig = ff.create_distplot(hist_data, group_labels, bin_size=0.01)\n",
"fig.show()\n"
"fig.show()"
]
},
{

2
requirements-dev.txt
View File

@ -7,7 +7,7 @@
-r docs/requirements-docs.txt
coveralls==4.0.1
ruff==0.5.7
ruff==0.6.1
mypy==1.11.1
pre-commit==3.8.0
pytest==8.3.2