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robcaulk
2022-09-25 20:53:36 +02:00
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4
docs/configuration.md
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@@ -225,14 +225,16 @@ Mandatory parameters are marked as **Required**, which means that they are requi
| `webhook.webhookexitcancel` | Payload to send on exit order cancel. Only required if `webhook.enabled` is `true`. See the [webhook documentation](webhook-config.md) for more details. <br> **Datatype:** String
| `webhook.webhookexitfill` | Payload to send on exit order filled. Only required if `webhook.enabled` is `true`. See the [webhook documentation](webhook-config.md) for more details. <br> **Datatype:** String
| `webhook.webhookstatus` | Payload to send on status calls. Only required if `webhook.enabled` is `true`. See the [webhook documentation](webhook-config.md) for more details. <br> **Datatype:** String
| | **Rest API / FreqUI**
| | **Rest API / FreqUI / Producer-Consumer**
| `api_server.enabled` | Enable usage of API Server. See the [API Server documentation](rest-api.md) for more details. <br> **Datatype:** Boolean
| `api_server.listen_ip_address` | Bind IP address. See the [API Server documentation](rest-api.md) for more details. <br> **Datatype:** IPv4
| `api_server.listen_port` | Bind Port. See the [API Server documentation](rest-api.md) for more details. <br>**Datatype:** Integer between 1024 and 65535
| `api_server.verbosity` | Logging verbosity. `info` will print all RPC Calls, while "error" will only display errors. <br>**Datatype:** Enum, either `info` or `error`. Defaults to `info`.
| `api_server.username` | Username for API server. See the [API Server documentation](rest-api.md) for more details. <br>**Keep it in secret, do not disclose publicly.**<br> **Datatype:** String
| `api_server.password` | Password for API server. See the [API Server documentation](rest-api.md) for more details. <br>**Keep it in secret, do not disclose publicly.**<br> **Datatype:** String
| `api_server.ws_token` | API token for the Message WebSocket. See the [API Server documentation](rest-api.md) for more details. <br>**Keep it in secret, do not disclose publicly.** <br> **Datatype:** String
| `bot_name` | Name of the bot. Passed via API to a client - can be shown to distinguish / name bots.<br> *Defaults to `freqtrade`*<br> **Datatype:** String
| `external_message_consumer` | Enable [Producer/Consumer mode](producer-consumer.md) for more details. <br> **Datatype:** Dict
| | **Other**
| `initial_state` | Defines the initial application state. If set to stopped, then the bot has to be explicitly started via `/start` RPC command. <br>*Defaults to `stopped`.* <br> **Datatype:** Enum, either `stopped` or `running`
| `force_entry_enable` | Enables the RPC Commands to force a Trade entry. More information below. <br> **Datatype:** Boolean

108
docs/data-download.md
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@@ -26,7 +26,7 @@ usage: freqtrade download-data [-h] [-v] [--logfile FILE] [-V] [-c PATH]
[--timerange TIMERANGE] [--dl-trades]
[--exchange EXCHANGE]
[-t TIMEFRAMES [TIMEFRAMES ...]] [--erase]
[--data-format-ohlcv {json,jsongz,hdf5}]
[--data-format-ohlcv {json,jsongz,hdf5,feather,parquet}]
[--data-format-trades {json,jsongz,hdf5}]
[--trading-mode {spot,margin,futures}]
[--prepend]
@@ -55,7 +55,7 @@ optional arguments:
list. Default: `1m 5m`.
--erase Clean all existing data for the selected
exchange/pairs/timeframes.
--data-format-ohlcv {json,jsongz,hdf5}
--data-format-ohlcv {json,jsongz,hdf5,feather,parquet}
Storage format for downloaded candle (OHLCV) data.
(default: `json`).
--data-format-trades {json,jsongz,hdf5}
@@ -76,7 +76,7 @@ Common arguments:
`userdir/config.json` or `config.json` whichever
exists). Multiple --config options may be used. Can be
set to `-` to read config from stdin.
-d PATH, --datadir PATH
-d PATH, --datadir PATH, --data-dir PATH
Path to directory with historical backtesting data.
--userdir PATH, --user-data-dir PATH
Path to userdata directory.
@@ -179,9 +179,11 @@ freqtrade download-data --exchange binance --pairs ETH/USDT XRP/USDT BTC/USDT --
Freqtrade currently supports 3 data-formats for both OHLCV and trades data:
* `json` (plain "text" json files)
* `jsongz` (a gzip-zipped version of json files)
* `hdf5` (a high performance datastore)
* `json` - plain "text" json files
* `jsongz` - a gzip-zipped version of json files
* `hdf5` - a high performance datastore
* `feather` - a dataformat based on Apache Arrow
* `parquet` - columnar datastore
By default, OHLCV data is stored as `json` data, while trades data is stored as `jsongz` data.
@@ -200,38 +202,74 @@ If the default data-format has been changed during download, then the keys `data
!!! Note
You can convert between data-formats using the [convert-data](#sub-command-convert-data) and [convert-trade-data](#sub-command-convert-trade-data) methods.
#### Dataformat comparison
The following comparisons have been made with the following data, and by using the linux `time` command.
```
Found 6 pair / timeframe combinations.
+----------+-------------+--------+---------------------+---------------------+
| Pair | Timeframe | Type | From | To |
|----------+-------------+--------+---------------------+---------------------|
| BTC/USDT | 5m | spot | 2017-08-17 04:00:00 | 2022-09-13 19:25:00 |
| ETH/USDT | 1m | spot | 2017-08-17 04:00:00 | 2022-09-13 19:26:00 |
| BTC/USDT | 1m | spot | 2017-08-17 04:00:00 | 2022-09-13 19:30:00 |
| XRP/USDT | 5m | spot | 2018-05-04 08:10:00 | 2022-09-13 19:15:00 |
| XRP/USDT | 1m | spot | 2018-05-04 08:11:00 | 2022-09-13 19:22:00 |
| ETH/USDT | 5m | spot | 2017-08-17 04:00:00 | 2022-09-13 19:20:00 |
+----------+-------------+--------+---------------------+---------------------+
```
Timings have been taken in a not very scientific way with the following command, which forces reading the data into memory.
``` bash
time freqtrade list-data --show-timerange --data-format-ohlcv <dataformat>
```
| Format | Size | timing |
|------------|-------------|-------------|
| `json` | 149Mb | 25.6s |
| `jsongz` | 39Mb | 27s |
| `hdf5` | 145Mb | 3.9s |
| `feather` | 72Mb | 3.5s |
| `parquet` | 83Mb | 3.8s |
Size has been taken from the BTC/USDT 1m spot combination for the timerange specified above.
To have a best performance/size mix, we recommend the use of either feather or parquet.
#### Sub-command convert data
```
usage: freqtrade convert-data [-h] [-v] [--logfile FILE] [-V] [-c PATH]
[-d PATH] [--userdir PATH]
[-p PAIRS [PAIRS ...]] --format-from
{json,jsongz,hdf5} --format-to
{json,jsongz,hdf5} [--erase]
[-t {1m,3m,5m,15m,30m,1h,2h,4h,6h,8h,12h,1d,3d,1w,2w,1M,1y} [{1m,3m,5m,15m,30m,1h,2h,4h,6h,8h,12h,1d,3d,1w,2w,1M,1y} ...]]
{json,jsongz,hdf5,feather,parquet} --format-to
{json,jsongz,hdf5,feather,parquet} [--erase]
[--exchange EXCHANGE]
[-t TIMEFRAMES [TIMEFRAMES ...]]
[--trading-mode {spot,margin,futures}]
[--candle-types {spot,,futures,mark,index,premiumIndex,funding_rate} [{spot,,futures,mark,index,premiumIndex,funding_rate} ...]]
[--candle-types {spot,futures,mark,index,premiumIndex,funding_rate} [{spot,futures,mark,index,premiumIndex,funding_rate} ...]]
optional arguments:
-h, --help show this help message and exit
-p PAIRS [PAIRS ...], --pairs PAIRS [PAIRS ...]
Limit command to these pairs. Pairs are space-
separated.
--format-from {json,jsongz,hdf5}
--format-from {json,jsongz,hdf5,feather,parquet}
Source format for data conversion.
--format-to {json,jsongz,hdf5}
--format-to {json,jsongz,hdf5,feather,parquet}
Destination format for data conversion.
--erase Clean all existing data for the selected
exchange/pairs/timeframes.
-t {1m,3m,5m,15m,30m,1h,2h,4h,6h,8h,12h,1d,3d,1w,2w,1M,1y} [{1m,3m,5m,15m,30m,1h,2h,4h,6h,8h,12h,1d,3d,1w,2w,1M,1y} ...], --timeframes {1m,3m,5m,15m,30m,1h,2h,4h,6h,8h,12h,1d,3d,1w,2w,1M,1y} [{1m,3m,5m,15m,30m,1h,2h,4h,6h,8h,12h,1d,3d,1w,2w,1M,1y} ...]
Specify which tickers to download. Space-separated
list. Default: `1m 5m`.
--exchange EXCHANGE Exchange name (default: `bittrex`). Only valid if no
config is provided.
--trading-mode {spot,margin,futures}
-t TIMEFRAMES [TIMEFRAMES ...], --timeframes TIMEFRAMES [TIMEFRAMES ...]
Specify which tickers to download. Space-separated
list. Default: `1m 5m`.
--trading-mode {spot,margin,futures}, --tradingmode {spot,margin,futures}
Select Trading mode
--candle-types {spot,,futures,mark,index,premiumIndex,funding_rate} [{spot,,futures,mark,index,premiumIndex,funding_rate} ...]
--candle-types {spot,futures,mark,index,premiumIndex,funding_rate} [{spot,futures,mark,index,premiumIndex,funding_rate} ...]
Select candle type to use
Common arguments:
@@ -245,7 +283,7 @@ Common arguments:
`userdir/config.json` or `config.json` whichever
exists). Multiple --config options may be used. Can be
set to `-` to read config from stdin.
-d PATH, --datadir PATH
-d PATH, --datadir PATH, --data-dir PATH
Path to directory with historical backtesting data.
--userdir PATH, --user-data-dir PATH
Path to userdata directory.
@@ -267,20 +305,24 @@ freqtrade convert-data --format-from json --format-to jsongz --datadir ~/.freqtr
usage: freqtrade convert-trade-data [-h] [-v] [--logfile FILE] [-V] [-c PATH]
[-d PATH] [--userdir PATH]
[-p PAIRS [PAIRS ...]] --format-from
{json,jsongz,hdf5} --format-to
{json,jsongz,hdf5} [--erase]
{json,jsongz,hdf5,feather,parquet}
--format-to
{json,jsongz,hdf5,feather,parquet}
[--erase] [--exchange EXCHANGE]
optional arguments:
-h, --help show this help message and exit
-p PAIRS [PAIRS ...], --pairs PAIRS [PAIRS ...]
Show profits for only these pairs. Pairs are space-
Limit command to these pairs. Pairs are space-
separated.
--format-from {json,jsongz,hdf5}
--format-from {json,jsongz,hdf5,feather,parquet}
Source format for data conversion.
--format-to {json,jsongz,hdf5}
--format-to {json,jsongz,hdf5,feather,parquet}
Destination format for data conversion.
--erase Clean all existing data for the selected
exchange/pairs/timeframes.
--exchange EXCHANGE Exchange name (default: `bittrex`). Only valid if no
config is provided.
Common arguments:
-v, --verbose Verbose mode (-vv for more, -vvv to get all messages).
@@ -293,7 +335,7 @@ Common arguments:
`userdir/config.json` or `config.json` whichever
exists). Multiple --config options may be used. Can be
set to `-` to read config from stdin.
-d PATH, --datadir PATH
-d PATH, --datadir PATH, --data-dir PATH
Path to directory with historical backtesting data.
--userdir PATH, --user-data-dir PATH
Path to userdata directory.
@@ -318,9 +360,9 @@ This command will allow you to repeat this last step for additional timeframes w
usage: freqtrade trades-to-ohlcv [-h] [-v] [--logfile FILE] [-V] [-c PATH]
[-d PATH] [--userdir PATH]
[-p PAIRS [PAIRS ...]]
[-t {1m,3m,5m,15m,30m,1h,2h,4h,6h,8h,12h,1d,3d,1w,2w,1M,1y} [{1m,3m,5m,15m,30m,1h,2h,4h,6h,8h,12h,1d,3d,1w,2w,1M,1y} ...]]
[-t TIMEFRAMES [TIMEFRAMES ...]]
[--exchange EXCHANGE]
[--data-format-ohlcv {json,jsongz,hdf5}]
[--data-format-ohlcv {json,jsongz,hdf5,feather,parquet}]
[--data-format-trades {json,jsongz,hdf5}]
optional arguments:
@@ -328,12 +370,12 @@ optional arguments:
-p PAIRS [PAIRS ...], --pairs PAIRS [PAIRS ...]
Limit command to these pairs. Pairs are space-
separated.
-t {1m,3m,5m,15m,30m,1h,2h,4h,6h,8h,12h,1d,3d,1w,2w,1M,1y} [{1m,3m,5m,15m,30m,1h,2h,4h,6h,8h,12h,1d,3d,1w,2w,1M,1y} ...], --timeframes {1m,3m,5m,15m,30m,1h,2h,4h,6h,8h,12h,1d,3d,1w,2w,1M,1y} [{1m,3m,5m,15m,30m,1h,2h,4h,6h,8h,12h,1d,3d,1w,2w,1M,1y} ...]
-t TIMEFRAMES [TIMEFRAMES ...], --timeframes TIMEFRAMES [TIMEFRAMES ...]
Specify which tickers to download. Space-separated
list. Default: `1m 5m`.
--exchange EXCHANGE Exchange name (default: `bittrex`). Only valid if no
config is provided.
--data-format-ohlcv {json,jsongz,hdf5}
--data-format-ohlcv {json,jsongz,hdf5,feather,parquet}
Storage format for downloaded candle (OHLCV) data.
(default: `json`).
--data-format-trades {json,jsongz,hdf5}
@@ -351,7 +393,7 @@ Common arguments:
`userdir/config.json` or `config.json` whichever
exists). Multiple --config options may be used. Can be
set to `-` to read config from stdin.
-d PATH, --datadir PATH
-d PATH, --datadir PATH, --data-dir PATH
Path to directory with historical backtesting data.
--userdir PATH, --user-data-dir PATH
Path to userdata directory.
@@ -371,7 +413,7 @@ You can get a list of downloaded data using the `list-data` sub-command.
```
usage: freqtrade list-data [-h] [-v] [--logfile FILE] [-V] [-c PATH] [-d PATH]
[--userdir PATH] [--exchange EXCHANGE]
[--data-format-ohlcv {json,jsongz,hdf5}]
[--data-format-ohlcv {json,jsongz,hdf5,feather,parquet}]
[-p PAIRS [PAIRS ...]]
[--trading-mode {spot,margin,futures}]
[--show-timerange]
@@ -380,13 +422,13 @@ optional arguments:
-h, --help show this help message and exit
--exchange EXCHANGE Exchange name (default: `bittrex`). Only valid if no
config is provided.
--data-format-ohlcv {json,jsongz,hdf5}
--data-format-ohlcv {json,jsongz,hdf5,feather,parquet}
Storage format for downloaded candle (OHLCV) data.
(default: `json`).
-p PAIRS [PAIRS ...], --pairs PAIRS [PAIRS ...]
Limit command to these pairs. Pairs are space-
separated.
--trading-mode {spot,margin,futures}
--trading-mode {spot,margin,futures}, --tradingmode {spot,margin,futures}
Select Trading mode
--show-timerange Show timerange available for available data. (May take
a while to calculate).
@@ -402,7 +444,7 @@ Common arguments:
`userdir/config.json` or `config.json` whichever
exists). Multiple --config options may be used. Can be
set to `-` to read config from stdin.
-d PATH, --datadir PATH
-d PATH, --datadir PATH, --data-dir PATH
Path to directory with historical backtesting data.
--userdir PATH, --user-data-dir PATH
Path to userdata directory.

163
docs/producer-consumer.md Normal file
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@@ -0,0 +1,163 @@
# Producer / Consumer mode
freqtrade provides a mechanism whereby an instance (also called `consumer`) may listen to messages from an upstream freqtrade instance (also called `producer`) using the message websocket. Mainly, `analyzed_df` and `whitelist` messages. This allows the reuse of computed indicators (and signals) for pairs in multiple bots without needing to compute them multiple times.
See [Message Websocket](rest-api.md#message-websocket) in the Rest API docs for setting up the `api_server` configuration for your message websocket (this will be your producer).
!!! Note
We strongly recommend to set `ws_token` to something random and known only to yourself to avoid unauthorized access to your bot.
## Configuration
Enable subscribing to an instance by adding the `external_message_consumer` section to the consumer's config file.
```json
{
//...
"external_message_consumer": {
"enabled": true,
"producers": [
{
"name": "default", // This can be any name you'd like, default is "default"
"host": "127.0.0.1", // The host from your producer's api_server config
"port": 8080, // The port from your producer's api_server config
"ws_token": "sercet_Ws_t0ken" // The ws_token from your producer's api_server config
}
],
// The following configurations are optional, and usually not required
// "wait_timeout": 300,
// "ping_timeout": 10,
// "sleep_time": 10,
// "remove_entry_exit_signals": false,
// "message_size_limit": 8
}
//...
}
```
| Parameter | Description |
|------------|-------------|
| `enabled` | **Required.** Enable consumer mode. If set to false, all other settings in this section are ignored.<br>*Defaults to `false`.*<br> **Datatype:** boolean .
| `producers` | **Required.** List of producers <br> **Datatype:** Array.
| `producers.name` | **Required.** Name of this producer. This name must be used in calls to `get_producer_pairs()` and `get_producer_df()` if more than one producer is used.<br> **Datatype:** string
| `producers.host` | **Required.** The hostname or IP address from your producer.<br> **Datatype:** string
| `producers.port` | **Required.** The port matching the above host.<br> **Datatype:** string
| `producers.ws_token` | **Required.** `ws_token` as configured on the producer.<br> **Datatype:** string
| | **Optional settings**
| `wait_timeout` | Timeout until we ping again if no message is received. <br>*Defaults to `300`.*<br> **Datatype:** Integer - in seconds.
| `wait_timeout` | Ping timeout <br>*Defaults to `10`.*<br> **Datatype:** Integer - in seconds.
| `sleep_time` | Sleep time before retrying to connect.<br>*Defaults to `10`.*<br> **Datatype:** Integer - in seconds.
| `remove_entry_exit_signals` | Remove signal columns from the dataframe (set them to 0) on dataframe receipt.<br>*Defaults to `10`.*<br> **Datatype:** Integer - in seconds.
| `message_size_limit` | Size limit per message<br>*Defaults to `8`.*<br> **Datatype:** Integer - Megabytes.
Instead of (or as well as) calculating indicators in `populate_indicators()` the follower instance listens on the connection to a producer instance's messages (or multiple producer instances in advanced configurations) and requests the producer's most recently analyzed dataframes for each pair in the active whitelist.
A consumer instance will then have a full copy of the analyzed dataframes without the need to calculate them itself.
## Examples
### Example - Producer Strategy
A simple strategy with multiple indicators. No special considerations are required in the strategy itself.
```py
class ProducerStrategy(IStrategy):
#...
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Calculate indicators in the standard freqtrade way which can then be broadcast to other instances
"""
dataframe['rsi'] = ta.RSI(dataframe)
bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=2)
dataframe['bb_lowerband'] = bollinger['lower']
dataframe['bb_middleband'] = bollinger['mid']
dataframe['bb_upperband'] = bollinger['upper']
dataframe['tema'] = ta.TEMA(dataframe, timeperiod=9)
return dataframe
def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Populates the entry signal for the given dataframe
"""
dataframe.loc[
(
(qtpylib.crossed_above(dataframe['rsi'], self.buy_rsi.value)) &
(dataframe['tema'] <= dataframe['bb_middleband']) &
(dataframe['tema'] > dataframe['tema'].shift(1)) &
(dataframe['volume'] > 0)
),
'enter_long'] = 1
return dataframe
```
!!! Tip "FreqAI"
You can use this to setup [FreqAI](freqai.md) on a powerful machine, while you run consumers on simple machines like raspberries, which can interpret the signals generated from the producer in different ways.
### Example - Consumer Strategy
A logically equivalent strategy which calculates no indicators itself, but will have the same analyzed dataframes available to make trading decisions based on the indicators calculated in the producer. In this example the consumer has the same entry criteria, however this is not necessary. The consumer may use different logic to enter/exit trades, and only use the indicators as specified.
```py
class ConsumerStrategy(IStrategy):
#...
process_only_new_candles = False # required for consumers
_columns_to_expect = ['rsi_default', 'tema_default', 'bb_middleband_default']
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Use the websocket api to get pre-populated indicators from another freqtrade instance.
Use `self.dp.get_producer_df(pair)` to get the dataframe
"""
pair = metadata['pair']
timeframe = self.timeframe
producer_pairs = self.dp.get_producer_pairs()
# You can specify which producer to get pairs from via:
# self.dp.get_producer_pairs("my_other_producer")
# This func returns the analyzed dataframe, and when it was analyzed
producer_dataframe, _ = self.dp.get_producer_df(pair)
# You can get other data if the producer makes it available:
# self.dp.get_producer_df(
# pair,
# timeframe="1h",
# candle_type=CandleType.SPOT,
# producer_name="my_other_producer"
# )
if not producer_dataframe.empty:
# If you plan on passing the producer's entry/exit signal directly,
# specify ffill=False or it will have unintended results
merged_dataframe = merge_informative_pair(dataframe, producer_dataframe,
timeframe, timeframe,
append_timeframe=False,
suffix="default")
return merged_dataframe
else:
dataframe[self._columns_to_expect] = 0
return dataframe
def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Populates the entry signal for the given dataframe
"""
# Use the dataframe columns as if we calculated them ourselves
dataframe.loc[
(
(qtpylib.crossed_above(dataframe['rsi_default'], self.buy_rsi.value)) &
(dataframe['tema_default'] <= dataframe['bb_middleband_default']) &
(dataframe['tema_default'] > dataframe['tema_default'].shift(1)) &
(dataframe['volume'] > 0)
),
'enter_long'] = 1
return dataframe
```
!!! Tip "Using upstream signals"
By setting `remove_entry_exit_signals=false`, you can also use the producer's signals directly. They should be available as `enter_long_default` (assuming `suffix="default"` was used) - and can be used as either signal directly, or as additional indicator.

75
docs/rest-api.md
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@@ -31,7 +31,8 @@ Sample configuration:
"jwt_secret_key": "somethingrandom",
"CORS_origins": [],
"username": "Freqtrader",
"password": "SuperSecret1!"
"password": "SuperSecret1!",
"ws_token": "sercet_Ws_t0ken"
},
```
@@ -66,7 +67,7 @@ secrets.token_hex()
!!! Danger "Password selection"
Please make sure to select a very strong, unique password to protect your bot from unauthorized access.
Also change `jwt_secret_key` to something random (no need to remember this, but it'll be used to encrypt your session, so it better be something unique!).
Also change `jwt_secret_key` to something random (no need to remember this, but it'll be used to encrypt your session, so it better be something unique!).
### Configuration with docker
@@ -93,7 +94,6 @@ Make sure that the following 2 lines are available in your docker-compose file:
!!! Danger "Security warning"
By using `8080:8080` in the docker port mapping, the API will be available to everyone connecting to the server under the correct port, so others may be able to control your bot.
## Rest API
### Consuming the API
@@ -274,7 +274,7 @@ reload_config
Reload configuration.
show_config
Returns part of the configuration, relevant for trading operations.
start
@@ -322,6 +322,73 @@ whitelist
```
### Message WebSocket
The API Server includes a websocket endpoint for subscribing to RPC messages from the freqtrade Bot.
This can be used to consume real-time data from your bot, such as entry/exit fill messages, whitelist changes, populated indicators for pairs, and more.
This is also used to setup [Producer/Consumer mode](producer-consumer.md) in Freqtrade.
Assuming your rest API is set to `127.0.0.1` on port `8080`, the endpoint is available at `http://localhost:8080/api/v1/message/ws`.
To access the websocket endpoint, the `ws_token` is required as a query parameter in the endpoint URL.
To generate a safe `ws_token` you can run the following code:
``` python
>>> import secrets
>>> secrets.token_urlsafe(25)
'hZ-y58LXyX_HZ8O1cJzVyN6ePWrLpNQv4Q'
```
You would then add that token under `ws_token` in your `api_server` config. Like so:
``` json
"api_server": {
"enabled": true,
"listen_ip_address": "127.0.0.1",
"listen_port": 8080,
"verbosity": "error",
"enable_openapi": false,
"jwt_secret_key": "somethingrandom",
"CORS_origins": [],
"username": "Freqtrader",
"password": "SuperSecret1!",
"ws_token": "hZ-y58LXyX_HZ8O1cJzVyN6ePWrLpNQv4Q" // <-----
},
```
You can now connect to the endpoint at `http://localhost:8080/api/v1/message/ws?token=hZ-y58LXyX_HZ8O1cJzVyN6ePWrLpNQv4Q`.
!!! Danger "Reuse of example tokens"
Please do not use the above example token. To make sure you are secure, generate a completely new token.
#### Using the WebSocket
Once connected to the WebSocket, the bot will broadcast RPC messages to anyone who is subscribed to them. To subscribe to a list of messages, you must send a JSON request through the WebSocket like the one below. The `data` key must be a list of message type strings.
``` json
{
"type": "subscribe",
"data": ["whitelist", "analyzed_df"] // A list of string message types
}
```
For a list of message types, please refer to the RPCMessageType enum in `freqtrade/enums/rpcmessagetype.py`
Now anytime those types of RPC messages are sent in the bot, you will receive them through the WebSocket as long as the connection is active. They typically take the same form as the request:
``` json
{
"type": "analyzed_df",
"data": {
"key": ["NEO/BTC", "5m", "spot"],
"df": {}, // The dataframe
"la": "2022-09-08 22:14:41.457786+00:00"
}
}
```
### OpenAPI interface
To enable the builtin openAPI interface (Swagger UI), specify `"enable_openapi": true` in the api_server configuration.

6
docs/strategy-advanced.md
View File

@@ -106,6 +106,12 @@ def custom_exit(self, pair: str, trade: Trade, current_time: datetime, current_r
!!! Note
`enter_tag` is limited to 100 characters, remaining data will be truncated.
!!! Warning
There is only one `enter_tag` column, which is used for both long and short trades.
As a consequence, this column must be treated as "last write wins" (it's just a dataframe column after all).
In fancy situations, where multiple signals collide (or if signals are deactivated again based on different conditions), this can lead to odd results with the wrong tag applied to an entry signal.
These results are a consequence of the strategy overwriting prior tags - where the last tag will "stick" and will be the one freqtrade will use.
## Exit tag
Similar to [Buy Tagging](#buy-tag), you can also specify a sell tag.