Merged readme + Scrap that Multithreading for now

user_data/hyperopts/MoniGoManiHyperOpt.py → Legacy MoniGoMani/user_data/hyperopts/MoniGoManiHyperOpt.py

@@ -1,18 +1,12 @@
-# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
-
-# --- Do not remove these libs ---
-from typing import Any, Callable, Dict, List
-
+# --- Do not remove these libs --------------------------------------
 import numpy as np  # noqa
 import pandas as pd  # noqa
-# --------------------------------
-# Add your lib to import here
-import talib.abstract as ta  # noqa
 from pandas import DataFrame
-from skopt.space import Categorical, Dimension, Integer, Real  # noqa
-
 import freqtrade.vendor.qtpylib.indicators as qtpylib
 from freqtrade.optimize.hyperopt_interface import IHyperOpt
+from skopt.space import Categorical, Dimension, Integer, Real  # noqa
+from typing import Any, Callable, Dict, List
+# -------------------------------------------------------------------
 
 
 class MoniGoManiHyperOpt(IHyperOpt):

user_data/strategies/MoniGoMani.py → Legacy MoniGoMani/user_data/strategies/MoniGoMani.py

@@ -1,18 +1,14 @@
-# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
-
-# --- Do not remove these libs ---
+# --- Do not remove these libs ----------------------------------------------------------------------
 import numpy as np  # noqa
 import pandas as pd  # noqa
-# --------------------------------
-# Add your lib to import here
-import talib.abstract as ta
 from pandas import DataFrame
-
+from freqtrade.strategy import IStrategy
+import freqtrade.vendor.qtpylib.indicators as qtpylib
+import talib.abstract as ta
 # ^ TA-Lib Autofill mostly broken in JetBrains Products,
 # ta._ta_lib.<function_name> can temporarily be used while writing as a workaround
 # Then change back to ta.<function_name> so IDE won't nag about accessing a protected member of TA-Lib
-import freqtrade.vendor.qtpylib.indicators as qtpylib
-from freqtrade.strategy import IStrategy
+# ----------------------------------------------------------------------------------------------------
 
 
 class MoniGoMani(IStrategy):

user_data/strategies/MoniGoManiHyperOpted.py → Legacy MoniGoMani/user_data/strategies/MoniGoManiHyperOpted.py

@@ -1,18 +1,14 @@
-# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
-
-# --- Do not remove these libs ---
+# --- Do not remove these libs ----------------------------------------------------------------------
 import numpy as np  # noqa
 import pandas as pd  # noqa
-# --------------------------------
-# Add your lib to import here
-import talib.abstract as ta
 from pandas import DataFrame
-
+from freqtrade.strategy import IStrategy
+import freqtrade.vendor.qtpylib.indicators as qtpylib
+import talib.abstract as ta
 # ^ TA-Lib Autofill mostly broken in JetBrains Products,
 # ta._ta_lib.<function_name> can temporarily be used while writing as a workaround
 # Then change back to ta.<function_name> so IDE won't nag about accessing a protected member of TA-Lib
-import freqtrade.vendor.qtpylib.indicators as qtpylib
-from freqtrade.strategy import IStrategy
+# ----------------------------------------------------------------------------------------------------
 
 
 class MoniGoManiHyperOpted(IStrategy):

README.md

@@ -1,7 +1,7 @@
 ```
     ####################################################################################
     ####                                                                            ####
-    ###                         MoniGoMani v0.8.0 by Rikj000                         ###
+    ###                         MoniGoMani v0.8.1 by Rikj000                         ###
     ##                          ----------------------------                          ##
     #               Isn't that what we all want? Our money to go many?                 #
     #          Well that's what this Freqtrade strategy hopes to do for you!           #
@@ -24,15 +24,26 @@
     ####################################################################################
 ```
 
-**WARNING: MoniGoMani should always be HyperOpted unless you really know what you are doing when manually allocating weights!**   
-**MoniGoManiHyperOpted already has a decent hyperopt applied to it!**   
+**WARNING: MoniGoManiHyperStrategy should always be HyperOpted unless you really know what you are doing when manually allocating weights!**   
+**MoniGoManiHyperStrategy found in releases already has a decent hyperopt applied to it for BTC pairs!**   
+**When changing anything in `config.json` please [re-optimize](https://github.com/Rikj000/MoniGoMani/blob/main/VERYQUICKSTART.md#how-to-optimize-monigomani)!**   
 
-# **Current `MoniGoMani` status @ `v0.8.0`** with:
-- *(new)* [Auto-HyperOptable Strategy](https://github.com/freqtrade/freqtrade/pull/4596) Support \**(No more need for legacy MoniGoMani, legacy MoniGoManiHyperOpt and \*\*MoniGoManiHyperOpted strategy classes and hyperopted parameters can be easily pasted to strategy and be loaded)*
+# **Current `MoniGoMani` status @ `v0.8.1`**   
+
+## The idea / Theory:   
+MoniGoMani derives iteself from other strategies by it's use of something I called "weighted signals".   
+Each signal has it's own weight allocated to it & a total buy/sell signal needed is defined too.   
+MGM (MoniGoMani) will loop through all signals, if they trigger it will add up the weight and eventually it will check if it's bigger then what's needed in total, if it is it will buy/sell.   
+The beauty lies in using MGM in combination with hyperopting (= backtesting a timeframe a lot of times to find the most ideal values), since all weighted signals have been made hyperoptable it can be used to find the most "ideal" weight divisions.   
+Also will it teach us what works where & what doesn't since MoniGoMani first detects Downwards/Sideways/Upwards trends and then does all of the above individually for each kind of trend (Creating basically 3 individual strategies, 1 for each kind of trend).   
+
+## Feature List:   
+- *(new)* [Auto-HyperOptable Strategy](https://github.com/freqtrade/freqtrade/pull/4596)! \**(No more need for legacy MoniGoMani, legacy MoniGoManiHyperOpt and MoniGoManiHyperOpted strategy classes)*   
 - All Configurable & HyperOptable settings are easily copy/paste-able from the HyperOpt Results
 - Configurable & HyperOptable Buy/Sell Signal Weight Influence Tables for Downwards/Sideways/Upwards trends
 - Configurable & HyperOptable Total Buy/Sell Signal Percentages for Downwards/Sideways/Upwards trends
 - Turn On/Off Trading on Downwards/Sideways/Upwards trends for Buys/Sells *(HyperOptable)*
+- Settings to Enable/Disable HyperOpting for individual `buy_params` & `sell_params` through [HyperOpt Setting Overrides](https://github.com/Rikj000/MoniGoMani/blob/main/VERYQUICKSTART.md#hyperopt-setting-overrides)
 - Turn On/Off **All** Individual Weighted Signal DataFrame entries for easy debugging in an IDE or better speed while dry/live running or hyperopting
 - Each Table has 9 Buy & 9 Sell signals implemented each Configurable & HyperOptable:
   - ADX + Strong Up/Strong Down
@@ -45,51 +56,50 @@
   - Bollinger Band Re-Entrance
   - VWAP Cross
 - Total Overall Signal Importance Calculator for Total Average Signal Importance Calculation upon the HyperOpt Results
-- Main/Sub Plot Configurations for all indicators used *(Handy for FreqUI but requires Docker `freqtrade:develop_plot` & `technical` dependencies)*
+- Main/Sub Plot Configurations for all indicators used *(Handy in FreqUI)*   
 
-*\*Legacy versions will still be maintained until this feature gets merged in Freqtrade, then their support will stop*   
-*\*\*MoniGoManiHyperOpted will keep on receiving maintenance since it's more lightweight than MoniGoManiHyperStrategy, thus should be better for dry/live-runs*   
+*\*Support/Updates for Legacy versions stopped since Auto-HyperOptable Strategies are merged into the official Freqtrade Development Branch!*   
+***Please switch to the new MoniGoManiHyperStrategy!***   
 
 ## Go-To Commands:
 For Hyper Opting *(the new [MoniGoManiHyperStrategy.py](https://github.com/Rikj000/MoniGoMani/blob/main/user_data/strategies/MoniGoManiHyperStrategy.py))*:
 ```bash
 freqtrade hyperopt -c ./user_data/config.json -c ./user_data/config-private.json --hyperopt-loss SortinoHyperOptLossDaily --spaces all -s MoniGoManiHyperStrategy -e 1000 --timerange 20210101-20210316
 ```
-For Hyper Opting *(the legacy [MoniGoMani.py](https://github.com/Rikj000/MoniGoMani/blob/main/user_data/strategies/MoniGoMani.py) + legacy [MoniGoManiHyperOpt.py](https://github.com/Rikj000/MoniGoMani/blob/main/user_data/hyperopts/MoniGoManiHyperOpt.py))*:
-```bash
-freqtrade hyperopt -c ./user_data/config.json -c ./user_data/config-private.json --hyperopt-loss SortinoHyperOptLossDaily --spaces all --hyperopt MoniGoManiHyperOpt -s MoniGoMani -e 1000 --timerange 20210101-20210316
-```
-For Back Testing *(the new [MoniGoManiHyperStrategy.py](https://github.com/Rikj000/MoniGoMani/blob/main/user_data/strategies/MoniGoManiHyperStrategy.py) or [MoniGoManiHyperOpted.py](https://github.com/Rikj000/MoniGoMani/blob/main/user_data/strategies/MoniGoManiHyperOpted.py) or legacy [MoniGoMani.py](https://github.com/Rikj000/MoniGoMani/blob/main/user_data/strategies/MoniGoMani.py))*:
+For Back Testing *(the new [MoniGoManiHyperStrategy.py](https://github.com/Rikj000/MoniGoMani/blob/main/user_data/strategies/MoniGoManiHyperStrategy.py) or legacy [MoniGoManiHyperOpted.py](https://github.com/Rikj000/MoniGoMani/blob/main/Legacy%20MoniGoMani/user_data/strategies/MoniGoManiHyperOpted.py) or legacy [MoniGoMani.py](https://github.com/Rikj000/MoniGoMani/blob/main/Legacy%20MoniGoMani/user_data/strategies/MoniGoMani.py))*:
 ```bash
 freqtrade backtesting -s MoniGoManiHyperStrategy -c ./user_data/config.json -c ./user_data/config-private.json --timerange 20210101-20210316
 ```
 For Total Average Signal Importance Calculation *(with the [Total-Overall-Signal-Importance-Calculator.py](https://github.com/Rikj000/MoniGoMani/blob/main/user_data/Total-Overall-Signal-Importance-Calculator.py))*:
 ```bash
 python ./user_data/Total-Overall-Signal-Importance-Calculator.py -sc BTC
 ```
+For Hyper Opting *(the legacy [MoniGoMani.py](https://github.com/Rikj000/MoniGoMani/blob/main/Legacy%20MoniGoMani/user_data/strategies/MoniGoMani.py) + legacy [MoniGoManiHyperOpt.py](https://github.com/Rikj000/MoniGoMani/blob/main/Legacy%20MoniGoMani/user_data/hyperopts/MoniGoManiHyperOpt.py))*:
+```bash
+freqtrade hyperopt -c ./user_data/config.json -c ./user_data/config-private.json --hyperopt-loss SortinoHyperOptLossDaily --spaces all --hyperopt MoniGoManiHyperOpt -s MoniGoMani -e 1000 --timerange 20210101-20210316
+```
 
-### **ChangeLog**:  
-[View the ChangeLog](https://github.com/Rikj000/MoniGoMani/blob/main/CHANGELOG.md)
-
-### **Planned**:   
+## **Planned**:   
 *Ordered by current schedule/priority*
-- Try to get fewer points in the code where the DataFrame gets accessed for speed improvements
-- [MultiThreaded DataFrame indicator checking](https://www.machinelearningplus.com/python/parallel-processing-python/) if possible for speed improvements
-- Settings to enable/disable HyperOpting for individual `buy_params` & `sell_params`
-- If open trade's trend changed for X candles & X% of open trades is making losses (indication of clogged with bad trades, both settings hyperoptable) => Send out sell signal for open trades making losses (To try to unclog the bot & attempt to continue the profit climb :rocket:)   
+- If open trade's trend changed for X candles (hyperoptable), check if trade is making losses & send sell signal if it is (To try to unclog the bot & attempt to continue the profit climb :rocket:)   
 - **Other & Better indicators!** MoniGoMani has been designed so signals can easily be inserted / swapped out   
 Please use the `Total-Overall-Signal-Importance-Calculator.py` (added in `v0.7.1`) to find out which signals do best and report your results to the Discord server, so we can improve! :rocket:
 - Individual `BTC_config.json` & `USDT_config.json` files, as well as individual `BTC_MoniGoManiHyperOpted.py` & `USDT_MoniGoManiHyperOpted.py` releases
+- Try to get fewer points in the code where the DataFrame gets accessed for speed improvements
+- [MultiThreaded DataFrame indicator checking](https://www.machinelearningplus.com/python/parallel-processing-python/) if possible for speed improvements
+
+## **ChangeLog**:  
+[View the ChangeLog](https://github.com/Rikj000/MoniGoMani/blob/main/CHANGELOG.md)
 
-### Got Test Results / Ideas / Config Improvements?
+## Got Test Results / Ideas / Config Improvements?
 - Feel free to join [**CryptoStonksShallRise**](https://discord.gg/xFZ9bB6vEz) on Discord there you can follow/participate in the official channels:
   - `#moni-go-mani-updates`
   - `#moni-go-mani-testing`
   - `#moni-go-mani-setup-releases`
 
-### Need help getting started?
+## Need help getting started?
 [View the VeryQuickStart](https://github.com/Rikj000/MoniGoMani/blob/main/VERYQUICKSTART.md)
 
-### **Freqtrade**:   
+## **Freqtrade**:   
 The Bot that makes this strategy possible: https://github.com/freqtrade/freqtrade   
 Big thank you to **xmatthias** and everyone who helped on it!