Merge pull request #2192 from freqtrade/rename_teststrat

Rename testStrategy to sample_strategy
This commit is contained in:
Matthias
2019-08-28 06:28:19 +02:00
committed by GitHub
10 changed files with 30 additions and 32 deletions

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@@ -79,18 +79,18 @@ freqtrade backtesting --datadir user_data/data/bittrex-20180101
#### With a (custom) strategy file
```bash
freqtrade -s TestStrategy backtesting
freqtrade -s SampleStrategy backtesting
```
Where `-s TestStrategy` refers to the class name within the strategy file `test_strategy.py` found in the `freqtrade/user_data/strategies` directory.
Where `-s SampleStrategy` refers to the class name within the strategy file `sample_strategy.py` found in the `freqtrade/user_data/strategies` directory.
#### Comparing multiple Strategies
```bash
freqtrade backtesting --strategy-list TestStrategy1 AwesomeStrategy --ticker-interval 5m
freqtrade backtesting --strategy-list SampleStrategy1 AwesomeStrategy --ticker-interval 5m
```
Where `TestStrategy1` and `AwesomeStrategy` refer to class names of strategies.
Where `SampleStrategy1` and `AwesomeStrategy` refer to class names of strategies.
#### Exporting trades to file
@@ -103,7 +103,7 @@ The exported trades can be used for [further analysis](#further-backtest-result-
#### Exporting trades to file specifying a custom filename
```bash
freqtrade backtesting --export trades --export-filename=backtest_teststrategy.json
freqtrade backtesting --export trades --export-filename=backtest_samplestrategy.json
```
#### Running backtest with smaller testset

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@@ -139,7 +139,7 @@ You can override strategy settings as demonstrated below.
# Define some constants
ticker_interval = "5m"
# Name of the strategy class
strategy_name = 'TestStrategy'
strategy_name = 'SampleStrategy'
# Path to user data
user_data_dir = 'user_data'
# Location of the strategy

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@@ -24,7 +24,7 @@ strategy file will be updated on Github. Put your custom strategy file
into the directory `user_data/strategies`.
Best copy the test-strategy and modify this copy to avoid having bot-updates override your changes.
`cp user_data/strategies/test_strategy.py user_data/strategies/awesome-strategy.py`
`cp user_data/strategies/sample_strategy.py user_data/strategies/awesome-strategy.py`
### Anatomy of a strategy
@@ -36,14 +36,14 @@ A strategy file contains all the information needed to build a good strategy:
- Minimal ROI recommended
- Stoploss strongly recommended
The bot also include a sample strategy called `TestStrategy` you can update: `user_data/strategies/test_strategy.py`.
You can test it with the parameter: `--strategy TestStrategy`
The bot also include a sample strategy called `SampleStrategy` you can update: `user_data/strategies/sample_strategy.py`.
You can test it with the parameter: `--strategy SampleStrategy`
```bash
freqtrade --strategy AwesomeStrategy
```
**For the following section we will use the [user_data/strategies/test_strategy.py](https://github.com/freqtrade/freqtrade/blob/develop/user_data/strategies/test_strategy.py)
**For the following section we will use the [user_data/strategies/sample_strategy.py](https://github.com/freqtrade/freqtrade/blob/develop/user_data/strategies/sample_strategy.py)
file as reference.**
!!! Note Strategies and Backtesting
@@ -109,9 +109,8 @@ def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame
return dataframe
```
!!! Note "Want more indicator examples?"
Look into the [user_data/strategies/test_strategy.py](https://github.com/freqtrade/freqtrade/blob/develop/user_data/strategies/test_strategy.py).<br/>
Look into the [user_data/strategies/sample_strategy.py](https://github.com/freqtrade/freqtrade/blob/develop/user_data/strategies/sample_strategy.py).
Then uncomment indicators you need.
### Buy signal rules
@@ -122,7 +121,7 @@ It's important to always return the dataframe without removing/modifying the col
This will method will also define a new column, `"buy"`, which needs to contain 1 for buys, and 0 for "no action".
Sample from `user_data/strategies/test_strategy.py`:
Sample from `user_data/strategies/sample_strategy.py`:
```python
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
@@ -152,7 +151,7 @@ It's important to always return the dataframe without removing/modifying the col
This will method will also define a new column, `"sell"`, which needs to contain 1 for sells, and 0 for "no action".
Sample from `user_data/strategies/test_strategy.py`:
Sample from `user_data/strategies/sample_strategy.py`:
```python
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: