Merge remote-tracking branch 'origin/develop' into add-metric-tracker

This commit is contained in:
robcaulk
2022-10-14 19:00:49 +02:00
72 changed files with 570 additions and 341 deletions

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@@ -215,16 +215,18 @@ Mandatory parameters are marked as **Required**, which means that they are requi
| `telegram.balance_dust_level` | Dust-level (in stake currency) - currencies with a balance below this will not be shown by `/balance`. <br> **Datatype:** float
| `telegram.reload` | Allow "reload" buttons on telegram messages. <br>*Defaults to `True`.<br> **Datatype:** boolean
| `telegram.notification_settings.*` | Detailed notification settings. Refer to the [telegram documentation](telegram-usage.md) for details.<br> **Datatype:** dictionary
| `telegram.allow_custom_messages` | Enable the sending of Telegram messages from strategies via the dataprovider.send_msg() function. <br> **Datatype:** Boolean
| | **Webhook**
| `webhook.enabled` | Enable usage of Webhook notifications <br> **Datatype:** Boolean
| `webhook.url` | URL for the webhook. Only required if `webhook.enabled` is `true`. See the [webhook documentation](webhook-config.md) for more details. <br> **Datatype:** String
| `webhook.webhookentry` | Payload to send on entry. Only required if `webhook.enabled` is `true`. See the [webhook documentation](webhook-config.md) for more details. <br> **Datatype:** String
| `webhook.webhookentrycancel` | Payload to send on entry order cancel. Only required if `webhook.enabled` is `true`. See the [webhook documentation](webhook-config.md) for more details. <br> **Datatype:** String
| `webhook.webhookentryfill` | Payload to send on entry order filled. Only required if `webhook.enabled` is `true`. See the [webhook documentation](webhook-config.md) for more details. <br> **Datatype:** String
| `webhook.webhookexit` | Payload to send on exit. Only required if `webhook.enabled` is `true`. See the [webhook documentation](webhook-config.md) for more details. <br> **Datatype:** String
| `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
| `webhook.entry` | Payload to send on entry. Only required if `webhook.enabled` is `true`. See the [webhook documentation](webhook-config.md) for more details. <br> **Datatype:** String
| `webhook.entry_cancel` | Payload to send on entry order cancel. Only required if `webhook.enabled` is `true`. See the [webhook documentation](webhook-config.md) for more details. <br> **Datatype:** String
| `webhook.entry_fill` | Payload to send on entry order filled. Only required if `webhook.enabled` is `true`. See the [webhook documentation](webhook-config.md) for more details. <br> **Datatype:** String
| `webhook.exit` | Payload to send on exit. Only required if `webhook.enabled` is `true`. See the [webhook documentation](webhook-config.md) for more details. <br> **Datatype:** String
| `webhook.exit_cancel` | 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.exit_fill` | 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.status` | 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
| `webhook.allow_custom_messages` | Enable the sending of Webhook messages from strategies via the dataprovider.send_msg() function. <br> **Datatype:** Boolean
| | **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

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@@ -66,11 +66,11 @@ We will keep a compatibility layer for 1-2 versions (so both `buy_tag` and `ente
#### Naming changes
Webhook terminology changed from "sell" to "exit", and from "buy" to "entry".
Webhook terminology changed from "sell" to "exit", and from "buy" to "entry", removing "webhook" in the process.
* `webhookbuy` -> `webhookentry`
* `webhookbuyfill` -> `webhookentryfill`
* `webhookbuycancel` -> `webhookentrycancel`
* `webhooksell` -> `webhookexit`
* `webhooksellfill` -> `webhookexitfill`
* `webhooksellcancel` -> `webhookexitcancel`
* `webhookbuy`, `webhookentry` -> `entry`
* `webhookbuyfill`, `webhookentryfill` -> `entry_fill`
* `webhookbuycancel`, `webhookentrycancel` -> `entry_cancel`
* `webhooksell`, `webhookexit` -> `exit`
* `webhooksellfill`, `webhookexitfill` -> `exit_fill`
* `webhooksellcancel`, `webhookexitcancel` -> `exit_cancel`

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@@ -204,14 +204,44 @@ If this value is set, FreqAI will initially use the predictions from the trainin
## Using different prediction models
FreqAI has multiple example prediction model libraries that are ready to be used as is via the flag `--freqaimodel`. These libraries include `Catboost`, `LightGBM`, and `XGBoost` regression, classification, and multi-target models, and can be found in `freqai/prediction_models/`. However, it is possible to customize and create your own prediction models using the `IFreqaiModel` class. You are encouraged to inherit `fit()`, `train()`, and `predict()` to let these customize various aspects of the training procedures.
FreqAI has multiple example prediction model libraries that are ready to be used as is via the flag `--freqaimodel`. These libraries include `CatBoost`, `LightGBM`, and `XGBoost` regression, classification, and multi-target models, and can be found in `freqai/prediction_models/`.
### Setting classifier targets
Regression and classification models differ in what targets they predict - a regression model will predict a target of continuous values, for example what price BTC will be at tomorrow, whilst a classifier will predict a target of discrete values, for example if the price of BTC will go up tomorrow or not. This means that you have to specify your targets differently depending on which model type you are using (see details [below](#setting-model-targets)).
FreqAI includes a variety of classifiers, such as the `CatboostClassifier` via the flag `--freqaimodel CatboostClassifier`. If you elects to use a classifier, the classes need to be set using strings. For example:
All of the aforementioned model libraries implement gradient boosted decision tree algorithms. They all work on the principle of ensemble learning, where predictions from multiple simple learners are combined to get a final prediction that is more stable and generalized. The simple learners in this case are decision trees. Gradient boosting refers to the method of learning, where each simple learner is built in sequence - the subsequent learner is used to improve on the error from the previous learner. If you want to learn more about the different model libraries you can find the information in their respective docs:
* CatBoost: https://catboost.ai/en/docs/
* LightGBM: https://lightgbm.readthedocs.io/en/v3.3.2/#
* XGBoost: https://xgboost.readthedocs.io/en/stable/#
There are also numerous online articles describing and comparing the algorithms. Some relatively light-weight examples would be [CatBoost vs. LightGBM vs. XGBoost — Which is the best algorithm?](https://towardsdatascience.com/catboost-vs-lightgbm-vs-xgboost-c80f40662924#:~:text=In%20CatBoost%2C%20symmetric%20trees%2C%20or,the%20same%20depth%20can%20differ.) and [XGBoost, LightGBM or CatBoost — which boosting algorithm should I use?](https://medium.com/riskified-technology/xgboost-lightgbm-or-catboost-which-boosting-algorithm-should-i-use-e7fda7bb36bc). Keep in mind that the performance of each model is highly dependent on the application and so any reported metrics might not be true for your particular use of the model.
Apart from the models already available in FreqAI, it is also possible to customize and create your own prediction models using the `IFreqaiModel` class. You are encouraged to inherit `fit()`, `train()`, and `predict()` to customize various aspects of the training procedures. You can place custom FreqAI models in `user_data/freqaimodels` - and freqtrade will pick them up from there based on the provided `--freqaimodel` name - which has to correspond to the class name of your custom model.
Make sure to use unique names to avoid overriding built-in models.
### Setting model targets
#### Regressors
If you are using a regressor, you need to specify a target that has continuous values. FreqAI includes a variety of regressors, such as the `CatboostRegressor`via the flag `--freqaimodel CatboostRegressor`. An example of how you could set a regression target for predicting the price 100 candles into the future would be
```python
df['&s-close_price'] = df['close'].shift(-100)
```
If you want to predict multiple targets, you need to define multiple labels using the same syntax as shown above.
#### Classifiers
If you are using a classifier, you need to specify a target that has discrete values. FreqAI includes a variety of classifiers, such as the `CatboostClassifier` via the flag `--freqaimodel CatboostClassifier`. If you elects to use a classifier, the classes need to be set using strings. For example, if you want to predict if the price 100 candles into the future goes up or down you would set
```python
df['&s-up_or_down'] = np.where( df["close"].shift(-100) > df["close"], 'up', 'down')
```
Additionally, the example classifier models do not accommodate multiple labels, but they do allow multi-class classification within a single label column.
If you want to predict multiple targets you must specify all labels in the same label column. You could, for example, add the label `same` to define where the price was unchanged by setting
```python
df['&s-up_or_down'] = np.where( df["close"].shift(-100) > df["close"], 'up', 'down')
df['&s-up_or_down'] = np.where( df["close"].shift(-100) == df["close"], 'same', df['&s-up_or_down'])
```

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@@ -43,7 +43,7 @@ Mandatory parameters are marked as **Required** and have to be set in one of the
| `test_size` | The fraction of data that should be used for testing instead of training. <br> **Datatype:** Positive float < 1.
| `shuffle` | Shuffle the training data points during training. Typically, to not remove the chronological order of data in time-series forecasting, this is set to `False`. <br> **Datatype:** Boolean. <br> Defaut: `False`.
| | **Model training parameters**
| `model_training_parameters` | A flexible dictionary that includes all parameters available by the selected model library. For example, if you use `LightGBMRegressor`, this dictionary can contain any parameter available by the `LightGBMRegressor` [here](https://lightgbm.readthedocs.io/en/latest/pythonapi/lightgbm.LGBMRegressor.html) (external website). If you select a different model, this dictionary can contain any parameter from that model. <br> **Datatype:** Dictionary.
| `model_training_parameters` | A flexible dictionary that includes all parameters available by the selected model library. For example, if you use `LightGBMRegressor`, this dictionary can contain any parameter available by the `LightGBMRegressor` [here](https://lightgbm.readthedocs.io/en/latest/pythonapi/lightgbm.LGBMRegressor.html) (external website). If you select a different model, this dictionary can contain any parameter from that model. A list of the currently available models can be found [here](freqai-configuration.md#using-different-prediction-models). <br> **Datatype:** Dictionary.
| `n_estimators` | The number of boosted trees to fit in the training of the model. <br> **Datatype:** Integer.
| `learning_rate` | Boosting learning rate during training of the model. <br> **Datatype:** Float.
| `n_jobs`, `thread_count`, `task_type` | Set the number of threads for parallel processing and the `task_type` (`gpu` or `cpu`). Different model libraries use different parameter names. <br> **Datatype:** Float.

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@@ -142,6 +142,19 @@ dataframe['outlier'] = np.where(dataframe['DI_values'] > self.di_max.value/10, 1
This specific hyperopt would help you understand the appropriate `DI_values` for your particular parameter space.
## Using Tensorboard
CatBoost models benefit from tracking training metrics via Tensorboard. You can take advantage of the FreqAI integration to track training and evaluation performance across all coins and across all retrainings. Tensorboard is activated via the following command:
```bash
cd freqtrade
tensorboard --logdir user_data/models/unique-id
```
where `unique-id` is the `identifier` set in the `freqai` configuration file. This command must be run in a separate shell if you wish to view the output in your browser at 127.0.0.1:6060 (6060 is the default port used by Tensorboard).
![tensorboard](assets/tensorboard.jpg)
## Setting up a follower
You can indicate to the bot that it should not train models, but instead should look for models trained by a leader with a specific `identifier` by defining:

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@@ -43,19 +43,25 @@ Note : `forcesell`, `forcebuy`, `emergencysell` are changed to `force_exit`, `fo
* `order_time_in_force` buy -> entry, sell -> exit.
* `order_types` buy -> entry, sell -> exit.
* `unfilledtimeout` buy -> entry, sell -> exit.
* `ignore_buying_expired_candle_after` -> moved to root level instead of "ask_strategy/exit_pricing"
* Terminology changes
* Sell reasons changed to reflect the new naming of "exit" instead of sells. Be careful in your strategy if you're using `exit_reason` checks and eventually update your strategy.
* `sell_signal` -> `exit_signal`
* `custom_sell` -> `custom_exit`
* `force_sell` -> `force_exit`
* `emergency_sell` -> `emergency_exit`
* Order pricing
* `bid_strategy` -> `entry_pricing`
* `ask_strategy` -> `exit_pricing`
* `ask_last_balance` -> `price_last_balance`
* `bid_last_balance` -> `price_last_balance`
* Webhook terminology changed from "sell" to "exit", and from "buy" to entry
* `webhookbuy` -> `webhookentry`
* `webhookbuyfill` -> `webhookentryfill`
* `webhookbuycancel` -> `webhookentrycancel`
* `webhooksell` -> `webhookexit`
* `webhooksellfill` -> `webhookexitfill`
* `webhooksellcancel` -> `webhookexitcancel`
* `webhookbuy` -> `entry`
* `webhookbuyfill` -> `entry_fill`
* `webhookbuycancel` -> `entry_cancel`
* `webhooksell` -> `exit`
* `webhooksellfill` -> `exit_fill`
* `webhooksellcancel` -> `exit_cancel`
* Telegram notification settings
* `buy` -> `entry`
* `buy_fill` -> `entry_fill`
@@ -443,6 +449,7 @@ Please refer to the [pricing documentation](configuration.md#prices-used-for-ord
"use_order_book": true,
"order_book_top": 1,
"bid_last_balance": 0.0
"ignore_buying_expired_candle_after": 120
}
}
```
@@ -466,6 +473,7 @@ after:
"use_order_book": true,
"order_book_top": 1,
"price_last_balance": 0.0
}
},
"ignore_buying_expired_candle_after": 120
}
```

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@@ -77,6 +77,7 @@ Example configuration showing the different settings:
"enabled": true,
"token": "your_telegram_token",
"chat_id": "your_telegram_chat_id",
"allow_custom_messages": true,
"notification_settings": {
"status": "silent",
"warning": "on",
@@ -115,6 +116,7 @@ Example configuration showing the different settings:
`show_candle` - show candle values as part of entry/exit messages. Only possible values are `"ohlc"` or `"off"`.
`balance_dust_level` will define what the `/balance` command takes as "dust" - Currencies with a balance below this will be shown.
`allow_custom_messages` completely disable strategy messages.
`reload` allows you to disable reload-buttons on selected messages.
## Create a custom keyboard (command shortcut buttons)

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@@ -10,37 +10,37 @@ Sample configuration (tested using IFTTT).
"webhook": {
"enabled": true,
"url": "https://maker.ifttt.com/trigger/<YOUREVENT>/with/key/<YOURKEY>/",
"webhookentry": {
"entry": {
"value1": "Buying {pair}",
"value2": "limit {limit:8f}",
"value3": "{stake_amount:8f} {stake_currency}"
},
"webhookentrycancel": {
"entry_cancel": {
"value1": "Cancelling Open Buy Order for {pair}",
"value2": "limit {limit:8f}",
"value3": "{stake_amount:8f} {stake_currency}"
},
"webhookentryfill": {
"entry_fill": {
"value1": "Buy Order for {pair} filled",
"value2": "at {open_rate:8f}",
"value3": ""
},
"webhookexit": {
"exit": {
"value1": "Exiting {pair}",
"value2": "limit {limit:8f}",
"value3": "profit: {profit_amount:8f} {stake_currency} ({profit_ratio})"
},
"webhookexitcancel": {
"exit_cancel": {
"value1": "Cancelling Open Exit Order for {pair}",
"value2": "limit {limit:8f}",
"value3": "profit: {profit_amount:8f} {stake_currency} ({profit_ratio})"
},
"webhookexitfill": {
"exit_fill": {
"value1": "Exit Order for {pair} filled",
"value2": "at {close_rate:8f}.",
"value3": ""
},
"webhookstatus": {
"status": {
"value1": "Status: {status}",
"value2": "",
"value3": ""
@@ -57,7 +57,7 @@ You can set the POST body format to Form-Encoded (default), JSON-Encoded, or raw
"enabled": true,
"url": "https://<YOURSUBDOMAIN>.cloud.mattermost.com/hooks/<YOURHOOK>",
"format": "json",
"webhookstatus": {
"status": {
"text": "Status: {status}"
}
},
@@ -88,17 +88,30 @@ Optional parameters are available to enable automatic retries for webhook messag
"url": "https://<YOURHOOKURL>",
"retries": 3,
"retry_delay": 0.2,
"webhookstatus": {
"status": {
"status": "Status: {status}"
}
},
```
Custom messages can be sent to Webhook endpoints via the `self.dp.send_msg()` function from within the strategy. To enable this, set the `allow_custom_messages` option to `true`:
```json
"webhook": {
"enabled": true,
"url": "https://<YOURHOOKURL>",
"allow_custom_messages": true,
"strategy_msg": {
"status": "StrategyMessage: {msg}"
}
},
```
Different payloads can be configured for different events. Not all fields are necessary, but you should configure at least one of the dicts, otherwise the webhook will never be called.
### Webhookentry
### Entry
The fields in `webhook.webhookentry` are filled when the bot executes a long/short. Parameters are filled using string.format.
The fields in `webhook.entry` are filled when the bot executes a long/short. Parameters are filled using string.format.
Possible parameters are:
* `trade_id`
@@ -118,9 +131,9 @@ Possible parameters are:
* `current_rate`
* `enter_tag`
### Webhookentrycancel
### Entry cancel
The fields in `webhook.webhookentrycancel` are filled when the bot cancels a long/short order. Parameters are filled using string.format.
The fields in `webhook.entry_cancel` are filled when the bot cancels a long/short order. Parameters are filled using string.format.
Possible parameters are:
* `trade_id`
@@ -139,9 +152,9 @@ Possible parameters are:
* `current_rate`
* `enter_tag`
### Webhookentryfill
### Entry fill
The fields in `webhook.webhookentryfill` are filled when the bot filled a long/short order. Parameters are filled using string.format.
The fields in `webhook.entry_fill` are filled when the bot filled a long/short order. Parameters are filled using string.format.
Possible parameters are:
* `trade_id`
@@ -160,9 +173,9 @@ Possible parameters are:
* `current_rate`
* `enter_tag`
### Webhookexit
### Exit
The fields in `webhook.webhookexit` are filled when the bot exits a trade. Parameters are filled using string.format.
The fields in `webhook.exit` are filled when the bot exits a trade. Parameters are filled using string.format.
Possible parameters are:
* `trade_id`
@@ -184,9 +197,9 @@ Possible parameters are:
* `open_date`
* `close_date`
### Webhookexitfill
### Exit fill
The fields in `webhook.webhookexitfill` are filled when the bot fills a exit order (closes a Trade). Parameters are filled using string.format.
The fields in `webhook.exit_fill` are filled when the bot fills a exit order (closes a Trade). Parameters are filled using string.format.
Possible parameters are:
* `trade_id`
@@ -209,9 +222,9 @@ Possible parameters are:
* `open_date`
* `close_date`
### Webhookexitcancel
### Exit cancel
The fields in `webhook.webhookexitcancel` are filled when the bot cancels a exit order. Parameters are filled using string.format.
The fields in `webhook.exit_cancel` are filled when the bot cancels a exit order. Parameters are filled using string.format.
Possible parameters are:
* `trade_id`
@@ -234,9 +247,9 @@ Possible parameters are:
* `open_date`
* `close_date`
### Webhookstatus
### Status
The fields in `webhook.webhookstatus` are used for regular status messages (Started / Stopped / ...). Parameters are filled using string.format.
The fields in `webhook.status` are used for regular status messages (Started / Stopped / ...). Parameters are filled using string.format.
The only possible value here is `{status}`.
@@ -280,7 +293,6 @@ You can configure this as follows:
}
```
The above represents the default (`exit_fill` and `entry_fill` are optional and will default to the above configuration) - modifications are obviously possible.
Available fields correspond to the fields for webhooks and are documented in the corresponding webhook sections.
@@ -288,3 +300,13 @@ Available fields correspond to the fields for webhooks and are documented in the
The notifications will look as follows by default.
![discord-notification](assets/discord_notification.png)
Custom messages can be sent from a strategy to Discord endpoints via the dataprovider.send_msg() function. To enable this, set the `allow_custom_messages` option to `true`:
```json
"discord": {
"enabled": true,
"webhook_url": "https://discord.com/api/webhooks/<Your webhook URL ...>",
"allow_custom_messages": true,
},
```