Affichage graph des données / sélection des indicateurs

src/app.py

@@ -1,4 +1,4 @@
-from flask import Flask, jsonify, abort, render_template, send_from_directory
+from flask import Flask, jsonify, abort, render_template, send_from_directory,request
 import pandas as pd
 import json
 import zipfile
@@ -102,14 +102,59 @@ def read_json(filename):
 def read_feather(filename):
     path = os.path.join(FREQTRADE_USERDATA_DIR + "/data/binance/", filename)
     try:
-        print(path)
-        df = pd.read_feather(path)
-        print(df)
-        return df.to_json(orient="records")
+        dataframe = pd.read_feather(path)
+        # dataframe['min'] = talib.MIN(dataframe['close'], timeperiod=200)
+        # dataframe['min12'] = talib.MIN(dataframe['close'], timeperiod=12)
+        #
+        # dataframe['min50'] = talib.MIN(dataframe['close'], timeperiod=50)
+        # dataframe['min200'] = talib.MIN(dataframe['close'], timeperiod=200)
+        # dataframe['max200'] = talib.MAX(dataframe['close'], timeperiod=200)
+
+        return dataframe.to_json(orient="records")
     except Exception as e:
         print(e)
         return jsonify({"error": str(e)}), 500
 
+@app.route('/get_chart_data')
+def get_chart_data():
+    filename = request.args.get('filename', '')
+    path = os.path.join(FREQTRADE_USERDATA_DIR + "/data/binance/", filename)
+    print(path)
+    indicators = request.args.get('indicators', '').split(',')
+    df = pd.read_feather(path)
+    print(df)
+
+    # # Calculs conditionnels
+    # if 'sma' in indicators:
+    #     df['sma'] = df['close'].rolling(window=20).mean()
+    # if 'rsi' in indicators:
+    #     delta = df['close'].diff()
+    #     gain = delta.where(delta > 0, 0)
+    #     loss = -delta.where(delta < 0, 0)
+    #     avg_gain = gain.rolling(14).mean()
+    #     avg_loss = loss.rolling(14).mean()
+    #     rs = avg_gain / avg_loss
+    #     df['rsi'] = 100 - (100 / (1 + rs))
+    # if 'bollinger' in indicators:
+    #     sma = df['close'].rolling(window=20).mean()
+    #     std = df['close'].rolling(window=20).std()
+    #     df['bb_upper'] = sma + 2 * std
+    #     df['bb_lower'] = sma - 2 * std
+    #
+    # df = df.dropna()
+
+    # Simplifier les données pour le JSON
+    # chart_data = {
+    #     'date': df['date'].astype(str).tolist(),
+    #     'close': df['close'].tolist(),
+    #     'sma': df.get('sma', pd.Series()).tolist(),
+    #     'rsi': df.get('rsi', pd.Series()).tolist(),
+    #     'bb_upper': df.get('bb_upper', pd.Series()).tolist(),
+    #     'bb_lower': df.get('bb_lower', pd.Series()).tolist(),
+    # }
+
+    return df.to_json(orient="records") #jsonify(chart_data)
+
 
 if __name__ == '__main__':
     app.run(debug=True, host='0.0.0.0', port=5000)