stable/docs/bot-usage.md

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# Bot usage
This page explains the difference parameters of the bot and how to run
it.
## Table of Contents
- [Bot commands](#bot-commands)
- [Backtesting commands](#backtesting-commands)
- [Hyperopt commands](#hyperopt-commands)
## Bot commands
```
usage: main.py [-h] [-c PATH] [-v] [--version] [--dynamic-whitelist [INT]]
[--dry-run-db]
{backtesting,hyperopt} ...
Simple High Frequency Trading Bot for crypto currencies
positional arguments:
{backtesting,hyperopt}
backtesting backtesting module
hyperopt hyperopt module
optional arguments:
-h, --help show this help message and exit
-c PATH, --config PATH
specify configuration file (default: config.json)
-v, --verbose be verbose
--version show program's version number and exit
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-dd PATH, --datadir PATH
Path is from where backtesting and hyperopt will load the
ticker data files (default freqdata/tests/testdata).
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--dynamic-whitelist [INT]
dynamically generate and update whitelist based on 24h
BaseVolume (Default 20 currencies)
--dry-run-db Force dry run to use a local DB
"tradesv3.dry_run.sqlite" instead of memory DB. Work
only if dry_run is enabled.
```
### 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 --dynamic-whitelist?
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 --dry-run-db?
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 `--dry-run-db`. This command will use a separate database file
`tradesv3.dry_run.sqlite`
```bash
python3 ./freqtrade/main.py -c config.json --dry-run-db
```
## Backtesting commands
Backtesting also uses the config specified via `-c/--config`.
```
usage: freqtrade backtesting [-h] [-l] [-i INT] [--realistic-simulation]
[-r]
optional arguments:
-h, --help show this help message and exit
-l, --live using live data
-i INT, --ticker-interval INT
specify ticker interval in minutes (default: 5)
--realistic-simulation
uses max_open_trades from config to simulate real
world limitations
-r, --refresh-pairs-cached
refresh the pairs files in tests/testdata with
the latest data from Bittrex. Use it if you want
to run your backtesting with up-to-date data.
```
### 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.
**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
It is possible to use hyperopt for trading strategy optimization.
Hyperopt uses an internal json config return by `hyperopt_optimize_conf()`
located in `freqtrade/optimize/hyperopt_conf.py`.
```
usage: freqtrade hyperopt [-h] [-e INT] [--use-mongodb]
optional arguments:
-h, --help show this help message and exit
-e INT, --epochs INT specify number of epochs (default: 100)
--use-mongodb parallelize evaluations with mongodb (requires mongod
in PATH)
```
## A parameter missing in the configuration?
All parameters for `main.py`, `backtesting`, `hyperopt` are referenced
in [misc.py](https://github.com/gcarq/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
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[optimize your bot](https://github.com/gcarq/freqtrade/blob/develop/docs/bot-optimization.md).