adelorenzo/stable
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Do not use ticker where it's not a ticker

Browse Source
This commit is contained in:
hroff-1902
2020-03-08 13:35:31 +03:00
parent 77944175e2
commit 3208faf7ed
43 changed files with 459 additions and 452 deletions
Download Patch File Download Diff File Expand all files Collapse all files

17
docs/strategy-customization.md
View File

@@ -84,7 +84,7 @@ def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame
Performance Note: For the best performance be frugal on the number of indicators
you are using. Let uncomment only the indicator you are using in your strategies
or your hyperopt configuration, otherwise you will waste your memory and CPU usage.
:param dataframe: Raw data from the exchange and parsed by parse_ticker_dataframe()
:param dataframe: Dataframe with data from the exchange
:param metadata: Additional information, like the currently traded pair
:return: a Dataframe with all mandatory indicators for the strategies
"""
@@ -284,13 +284,14 @@ If your exchange supports it, it's recommended to also set `"stoploss_on_exchang
For more information on order_types please look [here](configuration.md#understand-order_types).
### Ticker interval
### Timeframe (ticker interval)
This is the set of candles the bot should download and use for the analysis.
Common values are `"1m"`, `"5m"`, `"15m"`, `"1h"`, however all values supported by your exchange should work.
Please note that the same buy/sell signals may work with one interval, but not the other.
This setting is accessible within the strategy by using `self.ticker_interval`.
Please note that the same buy/sell signals may work well with one timeframe, but not with the others.
This setting is accessible within the strategy methods as the `self.ticker_interval` attribute.
### Metadata dict
@@ -335,14 +336,14 @@ 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, timeframe)` - Currently cached ticker data for the pair, returns DataFrame or empty DataFrame.
- `ohlcv(pair, timeframe)` - Currently cached candle (OHLCV) 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.
#### Example: fetch live ohlcv / historic data for the first informative pair
#### Example: fetch live / historical candle (OHLCV) data for the first informative pair
``` python
if self.dp:
@@ -377,8 +378,8 @@ if self.dp:
``` python
if self.dp:
for pair, ticker in self.dp.available_pairs:
print(f"available {pair}, {ticker}")
for pair, timeframe in self.dp.available_pairs:
print(f"available {pair}, {timeframe}")
```
#### Get data for non-tradeable pairs