From 942840da2d0c902fcbb8a9a43cf53dfc3f0feeb0 Mon Sep 17 00:00:00 2001
From: Matthias <xmatthias@outlook.com>
Date: Sun, 13 Nov 2022 15:22:44 +0100
Subject: [PATCH] Improve setting wording to keep future possibilities open

---
 config_examples/config_full.example.json | 1 +
 docs/configuration.md                    | 2 +-
 docs/freqai-parameter-table.md           | 2 +-
 freqtrade/freqai/data_kitchen.py         | 2 +-
 4 files changed, 4 insertions(+), 3 deletions(-)

diff --git a/config_examples/config_full.example.json b/config_examples/config_full.example.json
index 5a5096f81..b60957b58 100644
--- a/config_examples/config_full.example.json
+++ b/config_examples/config_full.example.json
@@ -204,6 +204,7 @@
     "strategy_path": "user_data/strategies/",
     "recursive_strategy_search": false,
     "add_config_files": [],
+    "reduce_df_footprint": false,
     "dataformat_ohlcv": "json",
     "dataformat_trades": "jsongz"
 }
diff --git a/docs/configuration.md b/docs/configuration.md
index 1fda27893..d50b798f8 100644
--- a/docs/configuration.md
+++ b/docs/configuration.md
@@ -253,7 +253,7 @@ Mandatory parameters are marked as **Required**, which means that they are requi
 | `add_config_files` | Additional config files. These files will be loaded and merged with the current config file. The files are resolved relative to the initial file.<br> *Defaults to `[]`*. <br> **Datatype:** List of strings
 | `dataformat_ohlcv` | Data format to use to store historical candle (OHLCV) data. <br> *Defaults to `json`*. <br> **Datatype:** String
 | `dataformat_trades` | Data format to use to store historical trades data. <br> *Defaults to `jsongz`*. <br> **Datatype:** String
-| `convert_df_to_32bit` | Recast all numeric columns to float32/int32, with the objective of reducing ram/disk usage and decreasing train/inference timing. (Currently only affects FreqAI use-cases) <br> **Datatype:** Boolean. <br> Default: `False`.
+| `reduce_df_footprint` | Recast all numeric columns to float32/int32, with the objective of reducing ram/disk usage and decreasing train/inference timing, as well as memory usage. (Currently only affects FreqAI use-cases) <br> **Datatype:** Boolean. <br> Default: `False`.
 
 ### Parameters in the strategy
 
diff --git a/docs/freqai-parameter-table.md b/docs/freqai-parameter-table.md
index 7ba54c1eb..c027a12b1 100644
--- a/docs/freqai-parameter-table.md
+++ b/docs/freqai-parameter-table.md
@@ -50,4 +50,4 @@ Mandatory parameters are marked as **Required** and have to be set in one of the
 |  |  **Extraneous parameters**
 | `keras` | If the selected model makes use of Keras (typical for Tensorflow-based prediction models), this flag needs to be activated so that the model save/loading follows Keras standards. <br> **Datatype:** Boolean. <br> Default: `False`.
 | `conv_width` | The width of a convolutional neural network input tensor. This replaces the need for shifting candles (`include_shifted_candles`) by feeding in historical data points as the second dimension of the tensor. Technically, this parameter can also be used for regressors, but it only adds computational overhead and does not change the model training/prediction. <br> **Datatype:** Integer. <br> Default: `2`.
-| `convert_df_to_32bit` | Recast all numeric columns to float32/int32, with the objective of reducing ram/disk usage and decreasing train/inference timing. This parameter is set in the main level of the Freqtrade configuration file (not inside FreqAI). <br> **Datatype:** Boolean. <br> Default: `False`.
+| `reduce_df_footprint` | Recast all numeric columns to float32/int32, with the objective of reducing ram/disk usage and decreasing train/inference timing. This parameter is set in the main level of the Freqtrade configuration file (not inside FreqAI). <br> **Datatype:** Boolean. <br> Default: `False`.
diff --git a/freqtrade/freqai/data_kitchen.py b/freqtrade/freqai/data_kitchen.py
index 5b2457eb8..d717858d2 100644
--- a/freqtrade/freqai/data_kitchen.py
+++ b/freqtrade/freqai/data_kitchen.py
@@ -1276,7 +1276,7 @@ class FreqaiDataKitchen:
 
         dataframe = self.remove_special_chars_from_feature_names(dataframe)
 
-        if self.config.get('convert_df_to_32bit', False):
+        if self.config.get('reduce_df_footprint', False):
             dataframe = reduce_dataframe_footprint(dataframe)
 
         return dataframe