Don't use class for plotting

This will allow easy usage of the methods from jupter notebooks

freqtrade/plot/plotting.py

@@ -1,6 +1,6 @@
 import logging
 from pathlib import Path
-from typing import Any, Dict, List, Optional
+from typing import Dict, List, Optional
 
 import pandas as pd
 
@@ -23,37 +23,43 @@ except ImportError:
     exit(1)
 
 
-class FTPlots():
+def init_plotscript(config):
+    """
+    Initialize objects needed for plotting
+    :return: Dict with tickers, trades, pairs and strategy
+    """
+    exchange: Optional[Exchange] = None
 
-    def __init__(self, config: Dict[str, Any]):
-        self._config = config
-        self.exchange: Optional[Exchange] = None
+    # Exchange is only needed when downloading data!
+    if config.get("live", False) or config.get("refresh_pairs", False):
+        exchange = ExchangeResolver(config.get('exchange', {}).get('name'),
+                                    config).exchange
 
-        # Exchange is only needed when downloading data!
-        if self._config.get("live", False) or self._config.get("refresh_pairs", False):
-            self.exchange = ExchangeResolver(self._config.get('exchange', {}).get('name'),
-                                             self._config).exchange
+    strategy = StrategyResolver(config).strategy
+    if "pairs" in config:
+        pairs = config["pairs"].split(',')
+    else:
+        pairs = config["exchange"]["pair_whitelist"]
 
-        self.strategy = StrategyResolver(self._config).strategy
-        if "pairs" in self._config:
-            self.pairs = self._config["pairs"].split(',')
-        else:
-            self.pairs = self._config["exchange"]["pair_whitelist"]
+    # Set timerange to use
+    timerange = Arguments.parse_timerange(config["timerange"])
 
-        # Set timerange to use
-        self.timerange = Arguments.parse_timerange(self._config["timerange"])
+    tickers = history.load_data(
+        datadir=Path(str(config.get("datadir"))),
+        pairs=pairs,
+        ticker_interval=config['ticker_interval'],
+        refresh_pairs=config.get('refresh_pairs', False),
+        timerange=timerange,
+        exchange=exchange,
+        live=config.get("live", False),
+    )
 
-        self.tickers = history.load_data(
-            datadir=Path(str(self._config.get("datadir"))),
-            pairs=self.pairs,
-            ticker_interval=self._config['ticker_interval'],
-            refresh_pairs=self._config.get('refresh_pairs', False),
-            timerange=self.timerange,
-            exchange=self.exchange,
-            live=self._config.get("live", False),
-        )
-
-        self.trades = load_trades(self._config)
+    trades = load_trades(config)
+    return {"tickers": tickers,
+            "trades": trades,
+            "pairs": pairs,
+            "strategy": strategy,
+            }
 
 
 def add_indicators(fig, row, indicators: List[str], data: pd.DataFrame) -> tools.make_subplots:

scripts/plot_dataframe.py

@@ -21,7 +21,7 @@ import pandas as pd
 from freqtrade.arguments import ARGS_PLOT_DATAFRAME, Arguments
 from freqtrade.data.btanalysis import extract_trades_of_period
 from freqtrade.optimize import setup_configuration
-from freqtrade.plot.plotting import (FTPlots, generate_candlestick_graph,
+from freqtrade.plot.plotting import (init_plotscript, generate_candlestick_graph,
                                      store_plot_file,
                                      generate_plot_filename)
 from freqtrade.state import RunMode
@@ -54,17 +54,18 @@ def analyse_and_plot_pairs(config: Dict[str, Any]):
     -Generate plot files
     :return: None
     """
-    plot = FTPlots(config)
+    plot_elements = init_plotscript(config)
+    trades = plot_elements['trades']
 
     pair_counter = 0
-    for pair, data in plot.tickers.items():
+    for pair, data in plot_elements["tickers"].items():
         pair_counter += 1
         logger.info("analyse pair %s", pair)
         tickers = {}
         tickers[pair] = data
-        dataframe = generate_dataframe(plot.strategy, tickers, pair)
+        dataframe = generate_dataframe(plot_elements["strategy"], tickers, pair)
 
-        trades_pair = plot.trades.loc[plot.trades['pair'] == pair]
+        trades_pair = trades.loc[trades['pair'] == pair]
         trades_pair = extract_trades_of_period(dataframe, trades_pair)
 
         fig = generate_candlestick_graph(

scripts/plot_profit.py

@@ -10,7 +10,7 @@ from typing import Any, Dict, List
 
 from freqtrade.arguments import ARGS_PLOT_PROFIT, Arguments
 from freqtrade.optimize import setup_configuration
-from freqtrade.plot.plotting import FTPlots, generate_profit_graph, store_plot_file
+from freqtrade.plot.plotting import init_plotscript, generate_profit_graph, store_plot_file
 from freqtrade.state import RunMode
 
 logger = logging.getLogger(__name__)
@@ -23,13 +23,14 @@ def plot_profit(config: Dict[str, Any]) -> None:
     But should be somewhat proportional, and therefor useful
     in helping out to find a good algorithm.
     """
-    plot = FTPlots(config)
-
-    trades = plot.trades[plot.trades['pair'].isin(plot.pairs)]
+    plot_elements = init_plotscript(config)
+    trades = plot_elements['trades']
+    # Filter trades to relevant pairs
+    trades = trades[trades['pair'].isin(plot_elements["pairs"])]
 
     # Create an average close price of all the pairs that were involved.
     # this could be useful to gauge the overall market trend
-    fig = generate_profit_graph(plot.pairs, plot.tickers, trades)
+    fig = generate_profit_graph(plot_elements["pairs"], plot_elements["tickers"], trades)
     store_plot_file(fig, filename='freqtrade-profit-plot.html', auto_open=True)