Adapt documentation for timeframe
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@ -314,9 +314,9 @@ Please always check the mode of operation to select the correct method to get da
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#### Possible options for DataProvider
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#### Possible options for DataProvider
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- `available_pairs` - Property with tuples listing cached pairs with their intervals (pair, interval).
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- `available_pairs` - Property with tuples listing cached pairs with their intervals (pair, interval).
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- `ohlcv(pair, ticker_interval)` - Currently cached ticker data for the pair, returns DataFrame or empty DataFrame.
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- `ohlcv(pair, timeframe)` - Currently cached ticker data for the pair, returns DataFrame or empty DataFrame.
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- `historic_ohlcv(pair, ticker_interval)` - Returns historical data stored on disk.
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- `historic_ohlcv(pair, timeframe)` - Returns historical data stored on disk.
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- `get_pair_dataframe(pair, ticker_interval)` - This is a universal method, which returns either historical data (for backtesting) or cached live data (for the Dry-Run and Live-Run modes).
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- `get_pair_dataframe(pair, timeframe)` - This is a universal method, which returns either historical data (for backtesting) or cached live data (for the Dry-Run and Live-Run modes).
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- `orderbook(pair, maximum)` - Returns latest orderbook data for the pair, a dict with bids/asks with a total of `maximum` entries.
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- `orderbook(pair, maximum)` - Returns latest orderbook data for the pair, a dict with bids/asks with a total of `maximum` entries.
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- `market(pair)` - Returns market data for the pair: fees, limits, precisions, activity flag, etc. See [ccxt documentation](https://github.com/ccxt/ccxt/wiki/Manual#markets) for more details on Market data structure.
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- `market(pair)` - Returns market data for the pair: fees, limits, precisions, activity flag, etc. See [ccxt documentation](https://github.com/ccxt/ccxt/wiki/Manual#markets) for more details on Market data structure.
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- `runmode` - Property containing the current runmode.
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- `runmode` - Property containing the current runmode.
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@ -327,7 +327,7 @@ Please always check the mode of operation to select the correct method to get da
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if self.dp:
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if self.dp:
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inf_pair, inf_timeframe = self.informative_pairs()[0]
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inf_pair, inf_timeframe = self.informative_pairs()[0]
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informative = self.dp.get_pair_dataframe(pair=inf_pair,
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informative = self.dp.get_pair_dataframe(pair=inf_pair,
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ticker_interval=inf_timeframe)
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timeframe=inf_timeframe)
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```
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```
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!!! Warning "Warning about backtesting"
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!!! Warning "Warning about backtesting"
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@ -10,7 +10,7 @@ from pathlib import Path
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# Customize these according to your needs.
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# Customize these according to your needs.
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# Define some constants
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# Define some constants
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ticker_interval = "5m"
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timeframe = "5m"
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# Name of the strategy class
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# Name of the strategy class
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strategy_name = 'SampleStrategy'
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strategy_name = 'SampleStrategy'
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# Path to user data
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# Path to user data
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@ -29,7 +29,7 @@ pair = "BTC_USDT"
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from freqtrade.data.history import load_pair_history
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from freqtrade.data.history import load_pair_history
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candles = load_pair_history(datadir=data_location,
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candles = load_pair_history(datadir=data_location,
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ticker_interval=ticker_interval,
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timeframe=timeframe,
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pair=pair)
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pair=pair)
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# Confirm success
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# Confirm success
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@ -26,7 +26,7 @@
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"# Customize these according to your needs.\n",
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"# Customize these according to your needs.\n",
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"\n",
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"\n",
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"# Define some constants\n",
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"# Define some constants\n",
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"ticker_interval = \"5m\"\n",
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"timeframe = \"5m\"\n",
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"# Name of the strategy class\n",
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"# Name of the strategy class\n",
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"strategy_name = 'SampleStrategy'\n",
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"strategy_name = 'SampleStrategy'\n",
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"# Path to user data\n",
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"# Path to user data\n",
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@ -49,7 +49,7 @@
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"from freqtrade.data.history import load_pair_history\n",
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"from freqtrade.data.history import load_pair_history\n",
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"\n",
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"\n",
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"candles = load_pair_history(datadir=data_location,\n",
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"candles = load_pair_history(datadir=data_location,\n",
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" ticker_interval=ticker_interval,\n",
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" timeframe=timeframe,\n",
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" pair=pair)\n",
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" pair=pair)\n",
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"\n",
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"\n",
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"# Confirm success\n",
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"# Confirm success\n",
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