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Freqtrade
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Producer/Consumer mode
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GitHub
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Home
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Quickstart with Docker
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Installation
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Linux/MacOS/Raspberry
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Windows
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Freqtrade Basics
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Configuration
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Strategy Customization
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Strategy Callbacks
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Stoploss
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Plugins
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Start the bot
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Control the bot
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Control the bot
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Telegram
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freqUI
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REST API
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Web Hook
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Data Downloading
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Backtesting
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Hyperopt
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FreqAI
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FreqAI
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Introduction
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Configuration
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Parameter table
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Feature engineering
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Running FreqAI
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Reinforcement Learning
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Developer guide
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Short / Leverage
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Utility Sub-commands
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Plotting
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< h1 id = "producer-consumer-mode" > Producer / Consumer mode< a class = "headerlink" href = "#producer-consumer-mode" title = "Permanent link" > ¶ < / a > < / h1 >
< p > freqtrade provides a mechanism whereby an instance (also called < code > consumer< / code > ) may listen to messages from an upstream freqtrade instance (also called < code > producer< / code > ) using the message websocket. Mainly, < code > analyzed_df< / code > and < code > whitelist< / code > messages. This allows the reuse of computed indicators (and signals) for pairs in multiple bots without needing to compute them multiple times.< / p >
< p > See < a href = "../rest-api/#message-websocket" > Message Websocket< / a > in the Rest API docs for setting up the < code > api_server< / code > configuration for your message websocket (this will be your producer).< / p >
< div class = "admonition note" >
< p class = "admonition-title" > Note< / p >
< p > We strongly recommend to set < code > ws_token< / code > to something random and known only to yourself to avoid unauthorized access to your bot.< / p >
< / div >
< h2 id = "configuration" > Configuration< a class = "headerlink" href = "#configuration" title = "Permanent link" > ¶ < / a > < / h2 >
< p > Enable subscribing to an instance by adding the < code > external_message_consumer< / code > section to the consumer's config file.< / p >
< div class = "highlight" > < pre > < span > < / span > < code > < span class = "p" > {< / span >
< span class = "w" > < / span > < span class = "c1" > //...< / span >
< span class = "w" > < / span > < span class = "nt" > " external_message_consumer" < / span > < span class = "p" > :< / span > < span class = "w" > < / span > < span class = "p" > {< / span >
< span class = "w" > < / span > < span class = "nt" > " enabled" < / span > < span class = "p" > :< / span > < span class = "w" > < / span > < span class = "kc" > true< / span > < span class = "p" > ,< / span >
< span class = "w" > < / span > < span class = "nt" > " producers" < / span > < span class = "p" > :< / span > < span class = "w" > < / span > < span class = "p" > [< / span >
< span class = "w" > < / span > < span class = "p" > {< / span >
< span class = "w" > < / span > < span class = "nt" > " name" < / span > < span class = "p" > :< / span > < span class = "w" > < / span > < span class = "s2" > " default" < / span > < span class = "p" > ,< / span > < span class = "w" > < / span > < span class = "c1" > // This can be any name you' d like, default is " default" < / span >
< span class = "w" > < / span > < span class = "nt" > " host" < / span > < span class = "p" > :< / span > < span class = "w" > < / span > < span class = "s2" > " 127.0.0.1" < / span > < span class = "p" > ,< / span > < span class = "w" > < / span > < span class = "c1" > // The host from your producer' s api_server config< / span >
< span class = "w" > < / span > < span class = "nt" > " port" < / span > < span class = "p" > :< / span > < span class = "w" > < / span > < span class = "mi" > 8080< / span > < span class = "p" > ,< / span > < span class = "w" > < / span > < span class = "c1" > // The port from your producer' s api_server config< / span >
< span class = "w" > < / span > < span class = "nt" > " secure" < / span > < span class = "p" > :< / span > < span class = "w" > < / span > < span class = "kc" > false< / span > < span class = "p" > ,< / span > < span class = "w" > < / span > < span class = "c1" > // Use a secure websockets connection, default false< / span >
< span class = "w" > < / span > < span class = "nt" > " ws_token" < / span > < span class = "p" > :< / span > < span class = "w" > < / span > < span class = "s2" > " sercet_Ws_t0ken" < / span > < span class = "w" > < / span > < span class = "c1" > // The ws_token from your producer' s api_server config< / span >
< span class = "w" > < / span > < span class = "p" > }< / span >
< span class = "w" > < / span > < span class = "p" > ],< / span >
< span class = "w" > < / span > < span class = "c1" > // The following configurations are optional, and usually not required< / span >
< span class = "w" > < / span > < span class = "c1" > // " wait_timeout" : 300,< / span >
< span class = "w" > < / span > < span class = "c1" > // " ping_timeout" : 10,< / span >
< span class = "w" > < / span > < span class = "c1" > // " sleep_time" : 10,< / span >
< span class = "w" > < / span > < span class = "c1" > // " remove_entry_exit_signals" : false,< / span >
< span class = "w" > < / span > < span class = "c1" > // " message_size_limit" : 8< / span >
< span class = "w" > < / span > < span class = "p" > }< / span >
< span class = "w" > < / span > < span class = "c1" > //...< / span >
< span class = "p" > }< / span >
< / code > < / pre > < / div >
< table >
< thead >
< tr >
< th > Parameter< / th >
< th > Description< / th >
< / tr >
< / thead >
< tbody >
< tr >
< td > < code > enabled< / code > < / td >
< td > < strong > Required.< / strong > Enable consumer mode. If set to false, all other settings in this section are ignored.< br > < em > Defaults to < code > false< / code > .< / em > < br > < strong > Datatype:< / strong > boolean .< / td >
< / tr >
< tr >
< td > < code > producers< / code > < / td >
< td > < strong > Required.< / strong > List of producers < br > < strong > Datatype:< / strong > Array.< / td >
< / tr >
< tr >
< td > < code > producers.name< / code > < / td >
< td > < strong > Required.< / strong > Name of this producer. This name must be used in calls to < code > get_producer_pairs()< / code > and < code > get_producer_df()< / code > if more than one producer is used.< br > < strong > Datatype:< / strong > string< / td >
< / tr >
< tr >
< td > < code > producers.host< / code > < / td >
< td > < strong > Required.< / strong > The hostname or IP address from your producer.< br > < strong > Datatype:< / strong > string< / td >
< / tr >
< tr >
< td > < code > producers.port< / code > < / td >
< td > < strong > Required.< / strong > The port matching the above host.< br > < em > Defaults to < code > 8080< / code > .< / em > < br > < strong > Datatype:< / strong > Integer< / td >
< / tr >
< tr >
< td > < code > producers.secure< / code > < / td >
< td > < strong > Optional.< / strong > Use ssl in websockets connection. Default False.< br > < strong > Datatype:< / strong > string< / td >
< / tr >
< tr >
< td > < code > producers.ws_token< / code > < / td >
< td > < strong > Required.< / strong > < code > ws_token< / code > as configured on the producer.< br > < strong > Datatype:< / strong > string< / td >
< / tr >
< tr >
< td > < / td >
< td > < strong > Optional settings< / strong > < / td >
< / tr >
< tr >
< td > < code > wait_timeout< / code > < / td >
< td > Timeout until we ping again if no message is received. < br > < em > Defaults to < code > 300< / code > .< / em > < br > < strong > Datatype:< / strong > Integer - in seconds.< / td >
< / tr >
< tr >
< td > < code > ping_timeout< / code > < / td >
< td > Ping timeout < br > < em > Defaults to < code > 10< / code > .< / em > < br > < strong > Datatype:< / strong > Integer - in seconds.< / td >
< / tr >
< tr >
< td > < code > sleep_time< / code > < / td >
< td > Sleep time before retrying to connect.< br > < em > Defaults to < code > 10< / code > .< / em > < br > < strong > Datatype:< / strong > Integer - in seconds.< / td >
< / tr >
< tr >
< td > < code > remove_entry_exit_signals< / code > < / td >
< td > Remove signal columns from the dataframe (set them to 0) on dataframe receipt.< br > < em > Defaults to < code > false< / code > .< / em > < br > < strong > Datatype:< / strong > Boolean.< / td >
< / tr >
< tr >
< td > < code > message_size_limit< / code > < / td >
< td > Size limit per message< br > < em > Defaults to < code > 8< / code > .< / em > < br > < strong > Datatype:< / strong > Integer - Megabytes.< / td >
< / tr >
< / tbody >
< / table >
< p > Instead of (or as well as) calculating indicators in < code > populate_indicators()< / code > 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.< / p >
< p > A consumer instance will then have a full copy of the analyzed dataframes without the need to calculate them itself.< / p >
< h2 id = "examples" > Examples< a class = "headerlink" href = "#examples" title = "Permanent link" > ¶ < / a > < / h2 >
< h3 id = "example-producer-strategy" > Example - Producer Strategy< a class = "headerlink" href = "#example-producer-strategy" title = "Permanent link" > ¶ < / a > < / h3 >
< p > A simple strategy with multiple indicators. No special considerations are required in the strategy itself.< / p >
< div class = "highlight" > < pre > < span > < / span > < code > < span class = "k" > class< / span > < span class = "nc" > ProducerStrategy< / span > < span class = "p" > (< / span > < span class = "n" > IStrategy< / span > < span class = "p" > ):< / span >
< span class = "c1" > #...< / span >
< span class = "k" > def< / span > < span class = "nf" > populate_indicators< / span > < span class = "p" > (< / span > < span class = "bp" > self< / span > < span class = "p" > ,< / span > < span class = "n" > dataframe< / span > < span class = "p" > :< / span > < span class = "n" > DataFrame< / span > < span class = "p" > ,< / span > < span class = "n" > metadata< / span > < span class = "p" > :< / span > < span class = "nb" > dict< / span > < span class = "p" > )< / span > < span class = "o" > -> < / span > < span class = "n" > DataFrame< / span > < span class = "p" > :< / span >
< span class = "w" > < / span > < span class = "sd" > " " " < / span >
< span class = "sd" > Calculate indicators in the standard freqtrade way which can then be broadcast to other instances< / span >
< span class = "sd" > " " " < / span >
< span class = "n" > dataframe< / span > < span class = "p" > [< / span > < span class = "s1" > ' rsi' < / span > < span class = "p" > ]< / span > < span class = "o" > =< / span > < span class = "n" > ta< / span > < span class = "o" > .< / span > < span class = "n" > RSI< / span > < span class = "p" > (< / span > < span class = "n" > dataframe< / span > < span class = "p" > )< / span >
< span class = "n" > bollinger< / span > < span class = "o" > =< / span > < span class = "n" > qtpylib< / span > < span class = "o" > .< / span > < span class = "n" > bollinger_bands< / span > < span class = "p" > (< / span > < span class = "n" > qtpylib< / span > < span class = "o" > .< / span > < span class = "n" > typical_price< / span > < span class = "p" > (< / span > < span class = "n" > dataframe< / span > < span class = "p" > ),< / span > < span class = "n" > window< / span > < span class = "o" > =< / span > < span class = "mi" > 20< / span > < span class = "p" > ,< / span > < span class = "n" > stds< / span > < span class = "o" > =< / span > < span class = "mi" > 2< / span > < span class = "p" > )< / span >
< span class = "n" > dataframe< / span > < span class = "p" > [< / span > < span class = "s1" > ' bb_lowerband' < / span > < span class = "p" > ]< / span > < span class = "o" > =< / span > < span class = "n" > bollinger< / span > < span class = "p" > [< / span > < span class = "s1" > ' lower' < / span > < span class = "p" > ]< / span >
< span class = "n" > dataframe< / span > < span class = "p" > [< / span > < span class = "s1" > ' bb_middleband' < / span > < span class = "p" > ]< / span > < span class = "o" > =< / span > < span class = "n" > bollinger< / span > < span class = "p" > [< / span > < span class = "s1" > ' mid' < / span > < span class = "p" > ]< / span >
< span class = "n" > dataframe< / span > < span class = "p" > [< / span > < span class = "s1" > ' bb_upperband' < / span > < span class = "p" > ]< / span > < span class = "o" > =< / span > < span class = "n" > bollinger< / span > < span class = "p" > [< / span > < span class = "s1" > ' upper' < / span > < span class = "p" > ]< / span >
< span class = "n" > dataframe< / span > < span class = "p" > [< / span > < span class = "s1" > ' tema' < / span > < span class = "p" > ]< / span > < span class = "o" > =< / span > < span class = "n" > ta< / span > < span class = "o" > .< / span > < span class = "n" > TEMA< / span > < span class = "p" > (< / span > < span class = "n" > dataframe< / span > < span class = "p" > ,< / span > < span class = "n" > timeperiod< / span > < span class = "o" > =< / span > < span class = "mi" > 9< / span > < span class = "p" > )< / span >
< span class = "k" > return< / span > < span class = "n" > dataframe< / span >
< span class = "k" > def< / span > < span class = "nf" > populate_entry_trend< / span > < span class = "p" > (< / span > < span class = "bp" > self< / span > < span class = "p" > ,< / span > < span class = "n" > dataframe< / span > < span class = "p" > :< / span > < span class = "n" > DataFrame< / span > < span class = "p" > ,< / span > < span class = "n" > metadata< / span > < span class = "p" > :< / span > < span class = "nb" > dict< / span > < span class = "p" > )< / span > < span class = "o" > -> < / span > < span class = "n" > DataFrame< / span > < span class = "p" > :< / span >
< span class = "w" > < / span > < span class = "sd" > " " " < / span >
< span class = "sd" > Populates the entry signal for the given dataframe< / span >
< span class = "sd" > " " " < / span >
< span class = "n" > dataframe< / span > < span class = "o" > .< / span > < span class = "n" > loc< / span > < span class = "p" > [< / span >
< span class = "p" > (< / span >
< span class = "p" > (< / span > < span class = "n" > qtpylib< / span > < span class = "o" > .< / span > < span class = "n" > crossed_above< / span > < span class = "p" > (< / span > < span class = "n" > dataframe< / span > < span class = "p" > [< / span > < span class = "s1" > ' rsi' < / span > < span class = "p" > ],< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > buy_rsi< / span > < span class = "o" > .< / span > < span class = "n" > value< / span > < span class = "p" > ))< / span > < span class = "o" > & < / span >
< span class = "p" > (< / span > < span class = "n" > dataframe< / span > < span class = "p" > [< / span > < span class = "s1" > ' tema' < / span > < span class = "p" > ]< / span > < span class = "o" > < =< / span > < span class = "n" > dataframe< / span > < span class = "p" > [< / span > < span class = "s1" > ' bb_middleband' < / span > < span class = "p" > ])< / span > < span class = "o" > & < / span >
< span class = "p" > (< / span > < span class = "n" > dataframe< / span > < span class = "p" > [< / span > < span class = "s1" > ' tema' < / span > < span class = "p" > ]< / span > < span class = "o" > > < / span > < span class = "n" > dataframe< / span > < span class = "p" > [< / span > < span class = "s1" > ' tema' < / span > < span class = "p" > ]< / span > < span class = "o" > .< / span > < span class = "n" > shift< / span > < span class = "p" > (< / span > < span class = "mi" > 1< / span > < span class = "p" > ))< / span > < span class = "o" > & < / span >
< span class = "p" > (< / span > < span class = "n" > dataframe< / span > < span class = "p" > [< / span > < span class = "s1" > ' volume' < / span > < span class = "p" > ]< / span > < span class = "o" > > < / span > < span class = "mi" > 0< / span > < span class = "p" > )< / span >
< span class = "p" > ),< / span >
< span class = "s1" > ' enter_long' < / span > < span class = "p" > ]< / span > < span class = "o" > =< / span > < span class = "mi" > 1< / span >
< span class = "k" > return< / span > < span class = "n" > dataframe< / span >
< / code > < / pre > < / div >
< div class = "admonition tip" >
< p class = "admonition-title" > FreqAI< / p >
< p > You can use this to setup < a href = "../freqai/" > FreqAI< / a > 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.< / p >
< / div >
< h3 id = "example-consumer-strategy" > Example - Consumer Strategy< a class = "headerlink" href = "#example-consumer-strategy" title = "Permanent link" > ¶ < / a > < / h3 >
< p > 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.< / p >
< div class = "highlight" > < pre > < span > < / span > < code > < span class = "k" > class< / span > < span class = "nc" > ConsumerStrategy< / span > < span class = "p" > (< / span > < span class = "n" > IStrategy< / span > < span class = "p" > ):< / span >
< span class = "c1" > #...< / span >
< span class = "n" > process_only_new_candles< / span > < span class = "o" > =< / span > < span class = "kc" > False< / span > < span class = "c1" > # required for consumers< / span >
< span class = "n" > _columns_to_expect< / span > < span class = "o" > =< / span > < span class = "p" > [< / span > < span class = "s1" > ' rsi_default' < / span > < span class = "p" > ,< / span > < span class = "s1" > ' tema_default' < / span > < span class = "p" > ,< / span > < span class = "s1" > ' bb_middleband_default' < / span > < span class = "p" > ]< / span >
< span class = "k" > def< / span > < span class = "nf" > populate_indicators< / span > < span class = "p" > (< / span > < span class = "bp" > self< / span > < span class = "p" > ,< / span > < span class = "n" > dataframe< / span > < span class = "p" > :< / span > < span class = "n" > DataFrame< / span > < span class = "p" > ,< / span > < span class = "n" > metadata< / span > < span class = "p" > :< / span > < span class = "nb" > dict< / span > < span class = "p" > )< / span > < span class = "o" > -> < / span > < span class = "n" > DataFrame< / span > < span class = "p" > :< / span >
< span class = "w" > < / span > < span class = "sd" > " " " < / span >
< span class = "sd" > Use the websocket api to get pre-populated indicators from another freqtrade instance.< / span >
< span class = "sd" > Use `self.dp.get_producer_df(pair)` to get the dataframe< / span >
< span class = "sd" > " " " < / span >
< span class = "n" > pair< / span > < span class = "o" > =< / span > < span class = "n" > metadata< / span > < span class = "p" > [< / span > < span class = "s1" > ' pair' < / span > < span class = "p" > ]< / span >
< span class = "n" > timeframe< / span > < span class = "o" > =< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > timeframe< / span >
< span class = "n" > producer_pairs< / span > < span class = "o" > =< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > dp< / span > < span class = "o" > .< / span > < span class = "n" > get_producer_pairs< / span > < span class = "p" > ()< / span >
< span class = "c1" > # You can specify which producer to get pairs from via:< / span >
< span class = "c1" > # self.dp.get_producer_pairs(" my_other_producer" )< / span >
< span class = "c1" > # This func returns the analyzed dataframe, and when it was analyzed< / span >
< span class = "n" > producer_dataframe< / span > < span class = "p" > ,< / span > < span class = "n" > _< / span > < span class = "o" > =< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > dp< / span > < span class = "o" > .< / span > < span class = "n" > get_producer_df< / span > < span class = "p" > (< / span > < span class = "n" > pair< / span > < span class = "p" > )< / span >
< span class = "c1" > # You can get other data if the producer makes it available:< / span >
< span class = "c1" > # self.dp.get_producer_df(< / span >
< span class = "c1" > # pair,< / span >
< span class = "c1" > # timeframe=" 1h" ,< / span >
< span class = "c1" > # candle_type=CandleType.SPOT,< / span >
< span class = "c1" > # producer_name=" my_other_producer" < / span >
< span class = "c1" > # )< / span >
< span class = "k" > if< / span > < span class = "ow" > not< / span > < span class = "n" > producer_dataframe< / span > < span class = "o" > .< / span > < span class = "n" > empty< / span > < span class = "p" > :< / span >
< span class = "c1" > # If you plan on passing the producer' s entry/exit signal directly,< / span >
< span class = "c1" > # specify ffill=False or it will have unintended results< / span >
< span class = "n" > merged_dataframe< / span > < span class = "o" > =< / span > < span class = "n" > merge_informative_pair< / span > < span class = "p" > (< / span > < span class = "n" > dataframe< / span > < span class = "p" > ,< / span > < span class = "n" > producer_dataframe< / span > < span class = "p" > ,< / span >
< span class = "n" > timeframe< / span > < span class = "p" > ,< / span > < span class = "n" > timeframe< / span > < span class = "p" > ,< / span >
< span class = "n" > append_timeframe< / span > < span class = "o" > =< / span > < span class = "kc" > False< / span > < span class = "p" > ,< / span >
< span class = "n" > suffix< / span > < span class = "o" > =< / span > < span class = "s2" > " default" < / span > < span class = "p" > )< / span >
< span class = "k" > return< / span > < span class = "n" > merged_dataframe< / span >
< span class = "k" > else< / span > < span class = "p" > :< / span >
< span class = "n" > dataframe< / span > < span class = "p" > [< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > _columns_to_expect< / span > < span class = "p" > ]< / span > < span class = "o" > =< / span > < span class = "mi" > 0< / span >
< span class = "k" > return< / span > < span class = "n" > dataframe< / span >
< span class = "k" > def< / span > < span class = "nf" > populate_entry_trend< / span > < span class = "p" > (< / span > < span class = "bp" > self< / span > < span class = "p" > ,< / span > < span class = "n" > dataframe< / span > < span class = "p" > :< / span > < span class = "n" > DataFrame< / span > < span class = "p" > ,< / span > < span class = "n" > metadata< / span > < span class = "p" > :< / span > < span class = "nb" > dict< / span > < span class = "p" > )< / span > < span class = "o" > -> < / span > < span class = "n" > DataFrame< / span > < span class = "p" > :< / span >
< span class = "w" > < / span > < span class = "sd" > " " " < / span >
< span class = "sd" > Populates the entry signal for the given dataframe< / span >
< span class = "sd" > " " " < / span >
< span class = "c1" > # Use the dataframe columns as if we calculated them ourselves< / span >
< span class = "n" > dataframe< / span > < span class = "o" > .< / span > < span class = "n" > loc< / span > < span class = "p" > [< / span >
< span class = "p" > (< / span >
< span class = "p" > (< / span > < span class = "n" > qtpylib< / span > < span class = "o" > .< / span > < span class = "n" > crossed_above< / span > < span class = "p" > (< / span > < span class = "n" > dataframe< / span > < span class = "p" > [< / span > < span class = "s1" > ' rsi_default' < / span > < span class = "p" > ],< / span > < span class = "bp" > self< / span > < span class = "o" > .< / span > < span class = "n" > buy_rsi< / span > < span class = "o" > .< / span > < span class = "n" > value< / span > < span class = "p" > ))< / span > < span class = "o" > & < / span >
< span class = "p" > (< / span > < span class = "n" > dataframe< / span > < span class = "p" > [< / span > < span class = "s1" > ' tema_default' < / span > < span class = "p" > ]< / span > < span class = "o" > < =< / span > < span class = "n" > dataframe< / span > < span class = "p" > [< / span > < span class = "s1" > ' bb_middleband_default' < / span > < span class = "p" > ])< / span > < span class = "o" > & < / span >
< span class = "p" > (< / span > < span class = "n" > dataframe< / span > < span class = "p" > [< / span > < span class = "s1" > ' tema_default' < / span > < span class = "p" > ]< / span > < span class = "o" > > < / span > < span class = "n" > dataframe< / span > < span class = "p" > [< / span > < span class = "s1" > ' tema_default' < / span > < span class = "p" > ]< / span > < span class = "o" > .< / span > < span class = "n" > shift< / span > < span class = "p" > (< / span > < span class = "mi" > 1< / span > < span class = "p" > ))< / span > < span class = "o" > & < / span >
< span class = "p" > (< / span > < span class = "n" > dataframe< / span > < span class = "p" > [< / span > < span class = "s1" > ' volume' < / span > < span class = "p" > ]< / span > < span class = "o" > > < / span > < span class = "mi" > 0< / span > < span class = "p" > )< / span >
< span class = "p" > ),< / span >
< span class = "s1" > ' enter_long' < / span > < span class = "p" > ]< / span > < span class = "o" > =< / span > < span class = "mi" > 1< / span >
< span class = "k" > return< / span > < span class = "n" > dataframe< / span >
< / code > < / pre > < / div >
< div class = "admonition tip" >
< p class = "admonition-title" > Using upstream signals< / p >
< p > By setting < code > remove_entry_exit_signals=false< / code > , you can also use the producer's signals directly. They should be available as < code > enter_long_default< / code > (assuming < code > suffix="default"< / code > was used) - and can be used as either signal directly, or as additional indicator.< / p >
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