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Switch sequence of information documentation

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Matthias
2024-03-03 12:58:10 +01:00
parent c1ae110080
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docs/strategy-advanced.md
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@@ -11,42 +11,6 @@ The call sequence of the methods described here is covered under [bot execution
!!! Tip !!! Tip
Start off with a strategy template containing all available callback methods by running `freqtrade new-strategy --strategy MyAwesomeStrategy --template advanced` Start off with a strategy template containing all available callback methods by running `freqtrade new-strategy --strategy MyAwesomeStrategy --template advanced`
## Storing information (Non-Persistent)
!!! Warning "Deprecated"
This method of storing information is deprecated and we do advise against using non-persistent storage.
Please use the below [Persistent Storing Information Section](#storing-information-persistent) instead.
It's content has therefore been collapsed.
??? Abstract "Storing information"
Storing information can be accomplished by creating a new dictionary within the strategy class.
The name of the variable can be chosen at will, but should be prefixed with `custom_` to avoid naming collisions with predefined strategy variables.
```python
class AwesomeStrategy(IStrategy):
# Create custom dictionary
custom_info = {}
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
# Check if the entry already exists
if not metadata["pair"] in self.custom_info:
# Create empty entry for this pair
self.custom_info[metadata["pair"]] = {}
if "crosstime" in self.custom_info[metadata["pair"]]:
self.custom_info[metadata["pair"]]["crosstime"] += 1
else:
self.custom_info[metadata["pair"]]["crosstime"] = 1
```
!!! Warning
The data is not persisted after a bot-restart (or config-reload). Also, the amount of data should be kept smallish (no DataFrames and such), otherwise the bot will start to consume a lot of memory and eventually run out of memory and crash.
!!! Note
If the data is pair-specific, make sure to use pair as one of the keys in the dictionary.
## Storing information (Persistent) ## Storing information (Persistent)
Freqtrade allows storing/retrieving user custom information associated with a specific trade in the database. Freqtrade allows storing/retrieving user custom information associated with a specific trade in the database.
@@ -135,6 +99,42 @@ The above is a simple example - there are simpler ways to retrieve trade data li
"value" can be any type (both in setting and receiving) - but must be json serializable. "value" can be any type (both in setting and receiving) - but must be json serializable.
## Storing information (Non-Persistent)
!!! Warning "Deprecated"
This method of storing information is deprecated and we do advise against using non-persistent storage.
Please use [Persistent Storage](#storing-information-persistent) instead.
It's content has therefore been collapsed.
??? Abstract "Storing information"
Storing information can be accomplished by creating a new dictionary within the strategy class.
The name of the variable can be chosen at will, but should be prefixed with `custom_` to avoid naming collisions with predefined strategy variables.
```python
class AwesomeStrategy(IStrategy):
# Create custom dictionary
custom_info = {}
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
# Check if the entry already exists
if not metadata["pair"] in self.custom_info:
# Create empty entry for this pair
self.custom_info[metadata["pair"]] = {}
if "crosstime" in self.custom_info[metadata["pair"]]:
self.custom_info[metadata["pair"]]["crosstime"] += 1
else:
self.custom_info[metadata["pair"]]["crosstime"] = 1
```
!!! Warning
The data is not persisted after a bot-restart (or config-reload). Also, the amount of data should be kept smallish (no DataFrames and such), otherwise the bot will start to consume a lot of memory and eventually run out of memory and crash.
!!! Note
If the data is pair-specific, make sure to use pair as one of the keys in the dictionary.
## Dataframe access ## Dataframe access
You may access dataframe in various strategy functions by querying it from dataprovider. You may access dataframe in various strategy functions by querying it from dataprovider.