Merge branch 'develop' into 'master'

Fix xvfb-related issues

See merge request !6

CHANGELOG

+V 0.5.1:
+  - Fixed xvfb-related issues
 V 0.5.0:
   - Gives neural network more data
 V 0.4.0:

Dockerfile

@@ -10,4 +10,4 @@ ADD . bot
 RUN cd bot && python3 setup.py install
 
 WORKDIR bot
-CMD ["xvfb-run", "multi-betbot", "-v"]
+CMD ["docker_start.sh", "-v"]

betbot/neural/data/FootballDataFetcher.py

@@ -19,11 +19,13 @@ LICENSE"""
 
 import os
 import csv
+import time
 import requests
 import dryscrape
 from datetime import datetime
 from io import StringIO
 from bs4 import BeautifulSoup
+from webkit_server import InvalidResponseError
 from typing import List, Tuple, Dict, Optional
 from betbot.neural.data.vector.InputVector import InputVector
 from betbot.neural.data.vector.OutputVector import OutputVector
@@ -154,7 +156,19 @@ class FootballDataFetcher(DataFetcher):
         ]
         current_matches = [x for x in _current_matches if x is not None]
         if len(current_matches) == 0:
-            current_matches = self.load_oddsportal_matches()
+            retry = 0
+            while retry < 3:
+                retry += 1
+                try:
+                    current_matches = self.load_oddsportal_matches()
+                except InvalidResponseError:
+                    self.logger.warning("Failed to fetch data from oddsportal")
+                    if retry < 3:
+                        self.logger.info("Retrying...")
+                        time.sleep(15)
+                    else:
+                        self.logger.warning("Couldn't fetch data")
+                        return []
 
         _all_matches = [
             Match.from_football_data(x)

betbot/neural/keras/BetPredictorTrainer.py

@@ -47,7 +47,6 @@ class BetPredictorTrainer(Trainer):
         for i, expected in enumerate(expected_output):
             predicted = [float(round(x)) for x in predictions[i]]
 
-            print(f"{predicted}|{expected}|{predictions[i]}")
             if int(predicted[0]) == int(predicted[1]):
                 draws += 1
 
@@ -72,7 +71,11 @@ class BetPredictorTrainer(Trainer):
 
         score = points / len(predictions)
         accuracy = 100 * score / 15
-        print(f"Winner Accuracy: {100 * correct_winners / len(predictions)}%")
-        print(f"Correct Accuracy: {100 * correct_results / len(predictions)}%")
-        print(f"Draw Percentage: {100 * draws / len(predictions)}%")
+        self.logger.info(f"Winner Accuracy: "
+                         f"{100 * correct_winners / len(predictions)}%")
+        self.logger.info(f"Correct Accuracy: "
+                         f"{100 * correct_results / len(predictions)}%")
+        self.logger.info(f"Draw Percentage: "
+                         f"{100 * draws / len(predictions)}%")
+        self.logger.info(f"Average Points: {score} ({accuracy}%)")
         return score, accuracy

betbot/prediction/MatchHistoryNNPredictor.py

@@ -40,7 +40,7 @@ class TableHistoryNNPredictor(Predictor):
         super().__init__()
         self.model_data_path = os.path.join(self.model_dir, self.name())
         trainer = MatchHistoryTrainer(self.model_data_path)
-        self.model = trainer.load_trained_model(minimum_accuracy=41.0)
+        self.model = trainer.load_trained_model(minimum_accuracy=41.5)
 
     @classmethod
     def name(cls) -> str:

bin/docker_start.sh

+#!/bin/bash
+
+Xvfb :00 &
+export DISPLAY=:00
+multi-betbot "$@"

version

-0.5.0
\ No newline at end of file
+0.5.1
\ No newline at end of file