Adapt documentation for timeframe

This commit is contained in:
Matthias 2019-11-02 20:34:06 +01:00
parent d801dec6aa
commit 334ac8b10c
3 changed files with 8 additions and 8 deletions

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@ -314,9 +314,9 @@ Please always check the mode of operation to select the correct method to get da
#### Possible options for DataProvider
- `available_pairs` - Property with tuples listing cached pairs with their intervals (pair, interval).
- `ohlcv(pair, ticker_interval)` - Currently cached ticker data for the pair, returns DataFrame or empty DataFrame.
- `historic_ohlcv(pair, ticker_interval)` - Returns historical data stored on disk.
- `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).
- `ohlcv(pair, timeframe)` - Currently cached ticker data for the pair, returns DataFrame or empty DataFrame.
- `historic_ohlcv(pair, timeframe)` - Returns historical data stored on disk.
- `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).
- `orderbook(pair, maximum)` - Returns latest orderbook data for the pair, a dict with bids/asks with a total of `maximum` entries.
- `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.
- `runmode` - Property containing the current runmode.
@ -327,7 +327,7 @@ Please always check the mode of operation to select the correct method to get da
if self.dp:
inf_pair, inf_timeframe = self.informative_pairs()[0]
informative = self.dp.get_pair_dataframe(pair=inf_pair,
ticker_interval=inf_timeframe)
timeframe=inf_timeframe)
```
!!! Warning "Warning about backtesting"

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@ -10,7 +10,7 @@ from pathlib import Path
# Customize these according to your needs.
# Define some constants
ticker_interval = "5m"
timeframe = "5m"
# Name of the strategy class
strategy_name = 'SampleStrategy'
# Path to user data
@ -29,7 +29,7 @@ pair = "BTC_USDT"
from freqtrade.data.history import load_pair_history
candles = load_pair_history(datadir=data_location,
ticker_interval=ticker_interval,
timeframe=timeframe,
pair=pair)
# Confirm success

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@ -26,7 +26,7 @@
"# Customize these according to your needs.\n",
"\n",
"# Define some constants\n",
"ticker_interval = \"5m\"\n",
"timeframe = \"5m\"\n",
"# Name of the strategy class\n",
"strategy_name = 'SampleStrategy'\n",
"# Path to user data\n",
@ -49,7 +49,7 @@
"from freqtrade.data.history import load_pair_history\n",
"\n",
"candles = load_pair_history(datadir=data_location,\n",
" ticker_interval=ticker_interval,\n",
" timeframe=timeframe,\n",
" pair=pair)\n",
"\n",
"# Confirm success\n",