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Add description and example for dp.ticker() to the docs

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hroff-1902 2020-05-15 16:35:48 +03:00 committed by GitHub
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docs/strategy-customization.md
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@ -367,9 +367,10 @@ Please always check the mode of operation to select the correct method to get da
- [`current_whitelist()`](#current_whitelist) - Returns a current list of whitelisted pairs. Useful for accessing dynamic whitelists (ie. VolumePairlist)
- [`get_pair_dataframe(pair, timeframe)`](#get_pair_dataframepair-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).
- `historic_ohlcv(pair, timeframe)` - Returns historical data stored on disk.
- `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.
- `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 the Market data structure.
- `ohlcv(pair, timeframe)` - Currently cached candle (OHLCV) data for the pair, returns DataFrame or empty DataFrame.
- [`orderbook(pair, maximum)`](#orderbookpair-maximum) - Returns latest orderbook data for the pair, a dict with bids/asks with a total of `maximum` entries.
- `ticker(pair)` - Returns current ticker data for the pair. See [ccxt documentation](https://github.com/ccxt/ccxt/wiki/Manual#price-tickers) for more details on the Ticker data structure.
- `runmode` - Property containing the current runmode.
#### Example Usages:
@ -451,6 +452,17 @@ if self.dp:
The order book is not part of the historic data which means backtesting and hyperopt will not work if this
method is used.
#### *ticker(pair)*
``` python
if self.dp:
if self.dp.runmode.value in ('live', 'dry_run'):
ticker = self.dp.ticker(metadata['pair'])
dataframe['last_price'] = ticker['last']
dataframe['volume24h'] = ticker['quoteVolume']
dataframe['vwap'] = ticker['vwap']
```
***
### Additional data (Wallets)