Add Coindesk, Lunarcrush and Alternative.me services

Evaluator/Social/news_evaluator/__init__.py

@@ -1 +1 @@
-from .news import TwitterNewsEvaluator
+from .news import TwitterNewsEvaluator, CryptoNewsEvaluator

Evaluator/Social/news_evaluator/config/CryptoNewsEvaluator.json

@@ -0,0 +1,3 @@
+{
+    "language": "en"
+}

Evaluator/Social/news_evaluator/metadata.json

@@ -1,6 +1,6 @@
 {
   "version": "1.2.0",
   "origin_package": "OctoBot-Default-Tentacles",
-  "tentacles": ["TwitterNewsEvaluator"],
-  "tentacles-requirements": ["text_analysis", "twitter_service_feed"]
+  "tentacles": ["TwitterNewsEvaluator", "CryptoNewsEvaluator"],
+  "tentacles-requirements": ["text_analysis", "twitter_service_feed", "coindesk_service_feed"]
 }

Evaluator/Social/news_evaluator/news.py

@@ -16,12 +16,11 @@
 
 import octobot_commons.constants as commons_constants
 import octobot_commons.enums as commons_enums
-
 import octobot_commons.tentacles_management as tentacles_management
 import octobot_services.constants as services_constants
 import octobot_evaluators.evaluators as evaluators
-from tentacles.Evaluator.Util.text_analysis import TextAnalysis
 import tentacles.Services.Services_feeds as Services_feeds
+import tentacles.Evaluator.Util as EvaluatorUtil
 
 
 # disable inheritance to disable tentacle visibility. Disabled as starting from feb 9 2023, API is now paid only
@@ -177,4 +176,64 @@ def _get_config_elements(self, config_cryptocurrencies, key):
         return {}
 
     async def prepare(self):
-        self.sentiment_analyser = tentacles_management.get_single_deepest_child_class(TextAnalysis)()
+        self.sentiment_analyser = tentacles_management.get_single_deepest_child_class(EvaluatorUtil.TextAnalysis)()
+
+
+NEWS_CONFIG_LANGUAGE = "language"
+
+# Should use any feed available to fetch crypto news (coindesk, etc.)
+class CryptoNewsEvaluator(evaluators.SocialEvaluator):
+    SERVICE_FEED_CLASS = Services_feeds.CoindeskServiceFeed
+
+    def __init__(self, tentacles_setup_config):
+        evaluators.SocialEvaluator.__init__(self, tentacles_setup_config)
+        self.stats_analyser = None   
+        self.language = None
+
+    def init_user_inputs(self, inputs: dict) -> None:
+        self.language = self.UI.user_input(NEWS_CONFIG_LANGUAGE,
+                               commons_enums.UserInputTypes.TEXT,
+                               self.language, inputs,
+                               title="Language to use to fetch crypto news.",
+                               options=["en", "fr"])
+        self.feed_config = {
+            services_constants.CONFIG_COINDESK_TOPICS: [services_constants.COINDESK_TOPIC_NEWS],
+            services_constants.CONFIG_COINDESK_LANGUAGE: self.language
+        }
+
+    @classmethod
+    def get_is_cryptocurrencies_wildcard(cls) -> bool:
+        """
+        :return: True if the evaluator is not cryptocurrency dependant else False
+        """
+        return True
+
+    @classmethod
+    def get_is_cryptocurrency_name_wildcard(cls) -> bool:
+        """
+        :return: True if the evaluator is not cryptocurrency name dependant else False
+        """
+        return True
+
+    async def _feed_callback(self, data):
+        if self._is_interested_by_this_notification(data[services_constants.FEED_METADATA]):
+            latest_news = self.get_data_cache(self.get_current_exchange_time(), key=services_constants.COINDESK_TOPIC_NEWS)
+            if latest_news is not None and len(latest_news) > 0:
+                sentiment_sum = 0
+                news_count = 0
+                for news in latest_news:
+                    sentiment = news.sentiment
+                    sentiment_sum += 0 if sentiment is None else -1 if sentiment == "NEGATIVE" else 1 if sentiment == "POSITIVE" else 0
+                    news_count += 1
+
+                if news_count > 0:  
+                    self.eval_note = sentiment_sum / news_count
+                    await self.evaluation_completed(eval_time=self.get_current_exchange_time())
+                else:
+                    self.debug(f"No news found")
+
+    def _is_interested_by_this_notification(self, notification_description):
+        return notification_description == services_constants.COINDESK_TOPIC_NEWS
+
+    async def prepare(self):
+        self.sentiment_analyser = tentacles_management.get_single_deepest_child_class(EvaluatorUtil.TextAnalysis)()

Evaluator/Social/news_evaluator/resources/CryptoNewsEvaluator.md

@@ -0,0 +1,7 @@
+Analyzes overall crypto market sentiment through cryptocurrency news articles.
+
+This evaluator interprets aggregated news signals (e.g., article headlines, content,
+and sentiment classifications) to produce a normalized score
+indicating bullish or bearish market sentiment based on recent news coverage.
+
+Data source: ([CoinDesk Data API](https://developers.coindesk.com/documentation/data-api/news))

Evaluator/Social/sentiment_evaluator/__init__.py

@@ -0,0 +1 @@
+from .sentiment import FearAndGreedIndexEvaluator, SocialScoreEvaluator

Evaluator/Social/sentiment_evaluator/config/FearAndGreedIndexEvaluator.json

@@ -0,0 +1,3 @@
+{
+  "trend_averages" : [40, 30, 20, 15, 10]
+}

Evaluator/Social/sentiment_evaluator/config/SocialScoreEvaluator.json

@@ -0,0 +1,2 @@
+{
+}

Evaluator/Social/sentiment_evaluator/metadata.json

@@ -0,0 +1,6 @@
+{
+  "version": "1.2.0",
+  "origin_package": "OctoBot-Default-Tentacles",
+  "tentacles": ["FearAndGreedIndexEvaluator", "SocialScoreEvaluator"],
+  "tentacles-requirements": ["alternative_me_service_feed", "lunarcrush_service_feed"]
+}

Evaluator/Social/sentiment_evaluator/resources/FearAndGreedIndexEvaluator.md

@@ -0,0 +1,7 @@
+Analyzes overall crypto market sentiment through a Fear & Greed Index.
+
+This evaluator interprets aggregated market signals (e.g., volatility, volume/momentum,
+social media sentiment, dominance, and trends) to produce a normalized score
+indicating prevailing fear or greed.
+
+Data source: ([alternative.me](https://alternative.me/crypto/fear-and-greed-index/))

Evaluator/Social/sentiment_evaluator/resources/SocialScoreEvaluator.md

@@ -0,0 +1,7 @@
+Analyzes cryptocurrency-specific social sentiment through LunarCrush social metrics.
+
+This evaluator interprets aggregated social signals (e.g., social volume, social engagement,
+social dominance, and community sentiment) to produce a normalized score
+indicating bullish or bearish social sentiment for a specific cryptocurrency.
+
+Data source: ([LunarCrush](https://lunarcrush.com/faq/what-metrics-are-available-on-lunarcrush))

Evaluator/Social/sentiment_evaluator/sentiment.py

@@ -0,0 +1,111 @@
+#  Drakkar-Software OctoBot-Tentacles
+#  Copyright (c) Drakkar-Software, All rights reserved.
+#
+#  This library is free software; you can redistribute it and/or
+#  modify it under the terms of the GNU Lesser General Public
+#  License as published by the Free Software Foundation; either
+#  version 3.0 of the License, or (at your option) any later version.
+#
+#  This library is distributed in the hope that it will be useful,
+#  but WITHOUT ANY WARRANTY; without even the implied warranty of
+#  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+#  Lesser General Public License for more details.
+#
+#  You should have received a copy of the GNU Lesser General Public
+#  License along with this library.
+import octobot_commons.enums as commons_enums
+import octobot_commons.tentacles_management as tentacles_management
+import octobot_evaluators.evaluators as evaluators
+import octobot_services.constants as services_constants
+import tentacles.Evaluator.Util as EvaluatorUtil
+import tentacles.Services.Services_feeds as Services_feeds
+
+CONFIG_TREND_AVERAGES = "trend_averages"
+
+class FearAndGreedIndexEvaluator(evaluators.SocialEvaluator):
+    SERVICE_FEED_CLASS = Services_feeds.AlternativeMeServiceFeed
+
+    def __init__(self, tentacles_setup_config):
+        evaluators.SocialEvaluator.__init__(self, tentacles_setup_config)
+        self.stats_analyser = None
+        self.history_data = None
+        self.feed_config = {
+            services_constants.CONFIG_ALTERNATIVE_ME_TOPICS: [services_constants.ALTERNATIVE_ME_TOPIC_FEAR_AND_GREED]
+        }
+        self.trend_averages = [40, 30, 20, 15, 10]
+
+    def init_user_inputs(self, inputs: dict) -> None:
+        self.trend_averages = self.UI.user_input(CONFIG_TREND_AVERAGES,
+                                                 commons_enums.UserInputTypes.OBJECT_ARRAY,
+                                                 self.trend_averages, inputs,
+                                                 title="Averages to use to compute the trend evaluation.")
+
+    @classmethod
+    def get_is_cryptocurrencies_wildcard(cls) -> bool:
+        """
+        :return: True if the evaluator is not cryptocurrency dependant else False
+        """
+        return True
+
+    @classmethod
+    def get_is_cryptocurrency_name_wildcard(cls) -> bool:
+        """
+        :return: True if the evaluator is not cryptocurrency name dependant else False
+        """
+        return True
+
+    async def _feed_callback(self, data):
+        if self._is_interested_by_this_notification(data[services_constants.FEED_METADATA]):
+            fear_and_greed_history = self.get_data_cache(self.get_current_exchange_time(), key=services_constants.ALTERNATIVE_ME_TOPIC_FEAR_AND_GREED)
+            if fear_and_greed_history is not None and len(fear_and_greed_history) > 0:
+                fear_and_greed_history_values = [item.value for item in fear_and_greed_history]
+                self.eval_note = self.stats_analyser.get_trend(fear_and_greed_history_values, self.trend_averages)
+                await self.evaluation_completed(eval_time=self.get_current_exchange_time())
+
+    def _is_interested_by_this_notification(self, notification_description):
+        return notification_description == services_constants.ALTERNATIVE_ME_TOPIC_FEAR_AND_GREED
+
+    async def prepare(self):
+        self.stats_analyser = tentacles_management.get_single_deepest_child_class(EvaluatorUtil.TrendAnalysis)()
+
+class SocialScoreEvaluator(evaluators.SocialEvaluator):
+    SERVICE_FEED_CLASS = Services_feeds.LunarCrushServiceFeed
+
+    def __init__(self, tentacles_setup_config):
+        evaluators.SocialEvaluator.__init__(self, tentacles_setup_config)
+        self.stats_analyser = None
+
+    def init_user_inputs(self, inputs: dict) -> None:
+        self.feed_config = {
+            services_constants.CONFIG_LUNARCRUSH_COINS: [self.cryptocurrency]
+        }
+
+    @classmethod
+    def get_is_cryptocurrencies_wildcard(cls) -> bool:
+        """
+        :return: True if the evaluator is not cryptocurrency dependant else False
+        """
+        return False
+
+    @classmethod
+    def get_is_cryptocurrency_name_wildcard(cls) -> bool:
+        """
+        :return: True if the evaluator is not cryptocurrency name dependant else False
+        """
+        return False
+
+    async def _feed_callback(self, data):
+        if self._is_interested_by_this_notification(data[services_constants.FEED_METADATA]):
+            coin, _ = data[services_constants.FEED_METADATA].split(";")
+            coin_data = self.get_data_cache(self.get_current_exchange_time(), key=f"{coin};{services_constants.LUNARCRUSH_COIN_METRICS}")
+            if coin_data is not None and len(coin_data) > 0:
+                self.eval_note = coin_data[-1].sentiment
+                await self.evaluation_completed(cryptocurrency=self.cryptocurrency, eval_time=self.get_current_exchange_time())
+
+    def _is_interested_by_this_notification(self, notification_description):
+        try:
+            coin, topic = notification_description.split(";")
+            return coin == self.cryptocurrency and topic == services_constants.LUNARCRUSH_COIN_METRICS
+        except KeyError:
+            pass
+        return False

Evaluator/Social/trends_evaluator/__init__.py

@@ -1 +1 @@
-from .trends import GoogleTrendsEvaluator
+from .trends import GoogleTrendsEvaluator, MarketCapEvaluator

Evaluator/Social/trends_evaluator/config/MarketCapEvaluator.json

@@ -0,0 +1,4 @@
+{
+    "trend_averages" : [40, 30, 20, 15, 10]
+  }
+

Evaluator/Social/trends_evaluator/metadata.json

@@ -1,6 +1,6 @@
 {
   "version": "1.2.0",
   "origin_package": "OctoBot-Default-Tentacles",
-  "tentacles": ["GoogleTrendsEvaluator"],
-  "tentacles-requirements": ["statistics_analysis", "google_service_feed"]
+  "tentacles": ["GoogleTrendsEvaluator", "MarketCapEvaluator"],
+  "tentacles-requirements": ["statistics_analysis", "google_service_feed", "coindesk_service_feed"]
 }

Evaluator/Social/trends_evaluator/resources/MarketCapEvaluator.md

@@ -0,0 +1,7 @@
+Analyzes overall crypto market trends through total market capitalization data.
+
+This evaluator interprets aggregated market cap signals (e.g., historical market cap values,
+trend changes, and long-term averages) to produce a normalized score
+indicating bullish or bearish market trends based on capitalization movements.
+
+Data source: ([CoinDesk Data API](https://developers.coindesk.com/documentation/data-api/overview_v1_latest_marketcap_all_tick))

Evaluator/Social/trends_evaluator/trends.py

@@ -23,7 +23,6 @@
 import tentacles.Evaluator.Util as EvaluatorUtil
 import tentacles.Services.Services_feeds as Services_feeds
 
-
 class GoogleTrendsEvaluator(evaluators.SocialEvaluator):
     SERVICE_FEED_CLASS = Services_feeds.GoogleServiceFeed
 
@@ -81,3 +80,50 @@ def _build_trend_topics(self):
 
     async def prepare(self):
         self.stats_analyser = tentacles_management.get_single_deepest_child_class(EvaluatorUtil.StatisticAnalysis)()
+
+CONFIG_TREND_AVERAGES = "trend_averages"
+
+class MarketCapEvaluator(evaluators.SocialEvaluator):
+    SERVICE_FEED_CLASS = Services_feeds.CoindeskServiceFeed
+
+    def __init__(self, tentacles_setup_config):
+        evaluators.SocialEvaluator.__init__(self, tentacles_setup_config)
+        self.stats_analyser = None
+        self.feed_config = {
+            services_constants.CONFIG_COINDESK_TOPICS: [services_constants.COINDESK_TOPIC_MARKETCAP]
+        }
+        self.trend_averages = [40, 30, 20, 15, 10]
+
+    def init_user_inputs(self, inputs: dict) -> None:
+        self.trend_averages = self.UI.user_input(CONFIG_TREND_AVERAGES,
+                                                 commons_enums.UserInputTypes.OBJECT_ARRAY,
+                                                 self.trend_averages, inputs,
+                                                 title="Averages to use to compute the trend evaluation.")
+
+    @classmethod
+    def get_is_cryptocurrencies_wildcard(cls) -> bool:
+        """
+        :return: True if the evaluator is not cryptocurrency dependant else False
+        """
+        return True
+
+    @classmethod
+    def get_is_cryptocurrency_name_wildcard(cls) -> bool:
+        """
+        :return: True if the evaluator is not cryptocurrency name dependant else False
+        """
+        return True
+
+    async def _feed_callback(self, data):
+        if self._is_interested_by_this_notification(data[services_constants.FEED_METADATA]):
+            marketcap_data = self.get_data_cache(self.get_current_exchange_time(), key=services_constants.COINDESK_TOPIC_MARKETCAP)
+            if marketcap_data is not None and len(marketcap_data) > 0:
+                marketcap_history = [item.close for item in marketcap_data]
+                self.eval_note = self.stats_analyser.get_trend(marketcap_history, self.trend_averages)
+                await self.evaluation_completed(eval_time=self.get_current_exchange_time())
+
+    def _is_interested_by_this_notification(self, notification_description):
+        return notification_description == services_constants.COINDESK_TOPIC_MARKETCAP
+
+    async def prepare(self):
+        self.stats_analyser = tentacles_management.get_single_deepest_child_class(EvaluatorUtil.TrendAnalysis)()

Evaluator/Strategies/mixed_strategies_evaluator/mixed_strategies.py

@@ -78,7 +78,9 @@ def init_user_inputs(self, inputs: dict) -> None:
                                default_config[self.BACKGROUND_SOCIAL_EVALUATORS],
                                inputs, other_schema_values={"minItems": 0, "uniqueItems": True},
                             options=["RedditForumEvaluator", "TwitterNewsEvaluator",
-                                     "TelegramSignalEvaluator", "GoogleTrendsEvaluator"],
+                                     "TelegramSignalEvaluator", "GoogleTrendsEvaluator", 
+                                     "FearAndGreedIndexEvaluator", "SocialScoreEvaluator", 
+                                     "CryptoNewsEvaluator", "MarketCapEvaluator"],
                             title="Social evaluator to consider as background evaluators: they won't trigger technical "
                                   "evaluators re-evaluation when updated. Avoiding unnecessary updates increases "
                                   "performances.")

Services/Services_bases/alternative_me_service/__init__.py

@@ -0,0 +1 @@
+from .alternative_me import AlternativeMeService

Services/Services_bases/alternative_me_service/alternative_me.py

@@ -0,0 +1,42 @@
+#  Drakkar-Software OctoBot-Tentacles
+#  Copyright (c) Drakkar-Software, All rights reserved.
+#
+#  This library is free software; you can redistribute it and/or
+#  modify it under the terms of the GNU Lesser General Public
+#  License as published by the Free Software Foundation; either
+#  version 3.0 of the License, or (at your option) any later version.
+#
+#  This library is distributed in the hope that it will be useful,
+#  but WITHOUT ANY WARRANTY; without even the implied warranty of
+#  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+#  Lesser General Public License for more details.
+#
+#  You should have received a copy of the GNU Lesser General Public
+#  License along with this library.
+import octobot_services.constants as services_constants
+import octobot_services.services as services
+
+
+class AlternativeMeService(services.AbstractService):
+    @staticmethod
+    def is_setup_correctly(config):
+        return True
+
+    @staticmethod
+    def get_is_enabled(config):
+        return True
+
+    def has_required_configuration(self):
+        return True
+
+    def get_endpoint(self) -> None:
+        return None
+
+    def get_type(self) -> None:
+        return services_constants.CONFIG_ALTERNATIVE_ME
+
+    async def prepare(self) -> None:
+        pass
+
+    def get_successful_startup_message(self):
+        return "", True