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#!/usr/bin/env python
USER = "benosteen"
CACHE_FILE = "data.json"
rating_t =""""""
weight_t = """"""
import requests
from xml.etree import ElementTree as ET
import os
# stats stuff
import math
def average(s): return sum(s) * 1.0 / len(s)
def variance(s):
avg = average(s)
return map(lambda x: (x - avg)**2, s)
def std_deviation(s):
return math.sqrt(average(variance(s)))
# BGG stuff
def get_weight(objid):
gw = requests.get(weight_t % objid)
if gw.status_code == 200:
game_doc = ET.fromstring(gw.content)
weight = float(game_doc[0].find('statistics/ratings/averageweight').text)
return weight
# weight not found, bad xml, etc
return 0
def get_data():
r = requests.get(rating_t % USER)
if r.status_code == 200:
print("Got Collection list for %s" % USER)
collection_list = ET.fromstring(r.content)
items = []
for item in collection_list:
data = {'objectid': item.attrib['objectid'],
'rating' : float(item.find('stats/rating').attrib['value']),
'name' : item[0].text,
'weight' : get_weight(item.attrib['objectid']),
data['plays'] = float(item.find('numplays').text)
data['plays'] = 0
print("Got %s" % data['name'])
return items
print("Unable to get the collection list for %s" % USER)
return []
if __name__ == "__main__":
import json
if os.path.exists(CACHE_FILE):
with open(CACHE_FILE, "r") as fp:
d = json.load(fp)
data = get_data()
if data:
with open(CACHE_FILE, "w") as output:
json.dump(data, output)
d = data
weights = map(lambda x: x['weight'], d)
weighted_weights = [y for y in map(lambda x: x['weight'] * x['rating'], d) if y]
# number of plays can be 0, which is bad for log of course ;)
play_weighted_weights = []
most_played = ""
max_plays = 0
most_weighty = ""
max_weight = 0
plot_points = []
weighted_points = []
for item in d:
if item['weight'] > max_weight:
most_weighty = item
max_weight = item['weight']
if item['plays'] > max_plays:
most_plays = item
max_plays = item['plays']
ww = item['weight'] * item['rating']
if item['plays'] != 0:
play_weighted_weights.append(ww * math.log(item['plays'],2))
weighted_points.append((ww, item['plays']))
plot_points.append((item['weight'], item['plays']))
# play_weighted_weights = [y for y in map(lambda x: x['weight'] * x['rating'] * math.log(x['plays'],2), d) if y]
print("How does '%s' like their gaming?" % USER)
print("Weightiest game rated: %s at %s" % (most_weighty['name'], most_weighty['weight']))
print("Most played game: %s with a weight of %s" % (most_plays['name'], most_plays['weight']))
print("\nBy weights of rated games:")
print("Ave. weight: %s" % average(weights))
print("Std deviation: %s" % std_deviation(weights))
print("Majority of games (~68%%) are between %s and %s in weight" % (average(weights) - std_deviation(weights), average(weights) + std_deviation(weights)))
print("\nBy weight x rating:")
print("Ave. weight: %s" % average(weighted_weights))
print("Std deviation: %s" % std_deviation(weighted_weights))
print("\nBy weight x rating x log2(number of plays):")
print("Ave. weight: %s" % average(play_weighted_weights))
print("Std deviation: %s" % std_deviation(play_weighted_weights))
print("\n\nWeights (x) vs number of plays (y):")
print("(Paste into something like - add a 'Points' source)")
for point in plot_points:
print("%s,%s" % (point))
print("\n\nWeighted weights (x) vs number of plays (y):")
print("(Paste into something like - add a 'Points' source)")
for point in weighted_points:
print("%s,%s" % (point))
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