stable/docs/bot-usage.md
2018-12-31 11:04:22 +01:00

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# Start the bot
This page explains the different parameters of the bot and how to run it.
## Bot commands
```
usage: main.py [-h] [-v] [--version] [-c PATH] [-d PATH] [-s NAME]
[--strategy-path PATH] [--customhyperopt NAME]
[--dynamic-whitelist [INT]] [--db-url PATH]
{backtesting,edge,hyperopt} ...
Simple High Frequency Trading Bot for crypto currencies
positional arguments:
{backtesting,edge,hyperopt}
backtesting backtesting module
edge edge module
hyperopt hyperopt module
optional arguments:
-h, --help show this help message and exit
-v, --verbose verbose mode (-vv for more, -vvv to get all messages)
--version show program\'s version number and exit
-c PATH, --config PATH
specify configuration file (default: config.json)
-d PATH, --datadir PATH
path to backtest data
-s NAME, --strategy NAME
specify strategy class name (default: DefaultStrategy)
--strategy-path PATH specify additional strategy lookup path
--customhyperopt NAME
specify hyperopt class name (default:
DefaultHyperOpts)
--dynamic-whitelist [INT]
dynamically generate and update whitelist based on 24h
BaseVolume (default: 20) DEPRECATED.
--db-url PATH Override trades database URL, this is useful if
dry_run is enabled or in custom deployments (default:
None)
```
### How to use a different config file?
The bot allows you to select which config file you want to use. Per
default, the bot will load the file `./config.json`
```bash
python3 ./freqtrade/main.py -c path/far/far/away/config.json
```
### How to use **--strategy**?
This parameter will allow you to load your custom strategy class.
Per default without `--strategy` or `-s` the bot will load the
`DefaultStrategy` included with the bot (`freqtrade/strategy/default_strategy.py`).
The bot will search your strategy file within `user_data/strategies` and `freqtrade/strategy`.
To load a strategy, simply pass the class name (e.g.: `CustomStrategy`) in this parameter.
**Example:**
In `user_data/strategies` you have a file `my_awesome_strategy.py` which has
a strategy class called `AwesomeStrategy` to load it:
```bash
python3 ./freqtrade/main.py --strategy AwesomeStrategy
```
If the bot does not find your strategy file, it will display in an error
message the reason (File not found, or errors in your code).
Learn more about strategy file in [optimize your bot](https://github.com/freqtrade/freqtrade/blob/develop/docs/bot-optimization.md).
### How to use **--strategy-path**?
This parameter allows you to add an additional strategy lookup path, which gets
checked before the default locations (The passed path must be a folder!):
```bash
python3 ./freqtrade/main.py --strategy AwesomeStrategy --strategy-path /some/folder
```
#### How to install a strategy?
This is very simple. Copy paste your strategy file into the folder
`user_data/strategies` or use `--strategy-path`. And voila, the bot is ready to use it.
### How to use **--dynamic-whitelist**?
!!! danger "DEPRECATED"
Dynamic-whitelist is deprecated. Please move your configurations to the configuration as outlined [here](/configuration/#dynamic-pairlists)
Per default `--dynamic-whitelist` will retrieve the 20 currencies based
on BaseVolume. This value can be changed when you run the script.
**By Default**
Get the 20 currencies based on BaseVolume.
```bash
python3 ./freqtrade/main.py --dynamic-whitelist
```
**Customize the number of currencies to retrieve**
Get the 30 currencies based on BaseVolume.
```bash
python3 ./freqtrade/main.py --dynamic-whitelist 30
```
**Exception**
`--dynamic-whitelist` must be greater than 0. If you enter 0 or a
negative value (e.g -2), `--dynamic-whitelist` will use the default
value (20).
### How to use **--db-url**?
When you run the bot in Dry-run mode, per default no transactions are
stored in a database. If you want to store your bot actions in a DB
using `--db-url`. This can also be used to specify a custom database
in production mode. Example command:
```bash
python3 ./freqtrade/main.py -c config.json --db-url sqlite:///tradesv3.dry_run.sqlite
```
## Backtesting commands
Backtesting also uses the config specified via `-c/--config`.
```
usage: main.py backtesting [-h] [-i TICKER_INTERVAL] [--timerange TIMERANGE]
[--eps] [--dmmp] [-l] [-r]
[--strategy-list STRATEGY_LIST [STRATEGY_LIST ...]]
[--export EXPORT] [--export-filename PATH]
optional arguments:
-h, --help show this help message and exit
-i TICKER_INTERVAL, --ticker-interval TICKER_INTERVAL
specify ticker interval (1m, 5m, 30m, 1h, 1d)
--timerange TIMERANGE
specify what timerange of data to use.
--eps, --enable-position-stacking
Allow buying the same pair multiple times (position
stacking)
--dmmp, --disable-max-market-positions
Disable applying `max_open_trades` during backtest
(same as setting `max_open_trades` to a very high
number)
-l, --live using live data
-r, --refresh-pairs-cached
refresh the pairs files in tests/testdata with the
latest data from the exchange. Use it if you want to
run your backtesting with up-to-date data.
--strategy-list STRATEGY_LIST [STRATEGY_LIST ...]
Provide a commaseparated list of strategies to
backtest Please note that ticker-interval needs to be
set either in config or via command line. When using
this together with --export trades, the strategy-name
is injected into the filename (so backtest-data.json
becomes backtest-data-DefaultStrategy.json
--export EXPORT export backtest results, argument are: trades Example
--export=trades
--export-filename PATH
Save backtest results to this filename requires
--export to be set as well Example --export-
filename=user_data/backtest_data/backtest_today.json
(default: user_data/backtest_data/backtest-
result.json)
```
### How to use **--refresh-pairs-cached** parameter?
The first time your run Backtesting, it will take the pairs you have
set in your config file and download data from Bittrex.
If for any reason you want to update your data set, you use
`--refresh-pairs-cached` to force Backtesting to update the data it has.
!!! Note
Use it only if you want to update your data set. You will not be able to come back to the previous version.
To test your strategy with latest data, we recommend continuing using
the parameter `-l` or `--live`.
## Hyperopt commands
To optimize your strategy, you can use hyperopt parameter hyperoptimization
to find optimal parameter values for your stategy.
```
usage: freqtrade hyperopt [-h] [-i TICKER_INTERVAL] [--eps] [--dmmp]
[--timerange TIMERANGE] [-e INT]
[-s {all,buy,roi,stoploss} [{all,buy,roi,stoploss} ...]]
optional arguments:
-h, --help show this help message and exit
-i TICKER_INTERVAL, --ticker-interval TICKER_INTERVAL
specify ticker interval (1m, 5m, 30m, 1h, 1d)
--eps, --enable-position-stacking
Allow buying the same pair multiple times (position
stacking)
--dmmp, --disable-max-market-positions
Disable applying `max_open_trades` during backtest
(same as setting `max_open_trades` to a very high
number)
--timerange TIMERANGE
specify what timerange of data to use.
--hyperopt PATH specify hyperopt file (default:
freqtrade/optimize/default_hyperopt.py)
-e INT, --epochs INT specify number of epochs (default: 100)
-s {all,buy,roi,stoploss} [{all,buy,roi,stoploss} ...], --spaces {all,buy,roi,stoploss} [{all,buy,roi,stoploss} ...]
Specify which parameters to hyperopt. Space separate
list. Default: all
```
## Edge commands
To know your trade expectacny and winrate against historical data, you can use Edge.
```
usage: main.py edge [-h] [-i TICKER_INTERVAL] [--timerange TIMERANGE] [-r]
[--stoplosses STOPLOSS_RANGE]
optional arguments:
-h, --help show this help message and exit
-i TICKER_INTERVAL, --ticker-interval TICKER_INTERVAL
specify ticker interval (1m, 5m, 30m, 1h, 1d)
--timerange TIMERANGE
specify what timerange of data to use.
-r, --refresh-pairs-cached
refresh the pairs files in tests/testdata with the
latest data from the exchange. Use it if you want to
run your edge with up-to-date data.
--stoplosses STOPLOSS_RANGE
defines a range of stoploss against which edge will
assess the strategythe format is "min,max,step"
(without any space).example:
--stoplosses=-0.01,-0.1,-0.001
```
To understand edge and how to read the results, please read the [edge documentation](edge.md).
## A parameter missing in the configuration?
All parameters for `main.py`, `backtesting`, `hyperopt` are referenced
in [misc.py](https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/misc.py#L84)
## Next step
The optimal strategy of the bot will change with time depending of the market trends. The next step is to
[optimize your bot](bot-optimization.md).