stable/docs/bot-usage.md

# 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](docs/configuration.md#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](https://github.com/freqtrade/freqtrade/blob/develop/docs/bot-optimization.md).