def _on_review_stats_data(self, spawn_helper, piston_review_stats,
callback):
""" process stdout from the helper """
review_stats = self.REVIEW_STATS_CACHE
if self._cache_version_old and self._server_has_histogram(
piston_review_stats):
self.REVIEW_STATS_CACHE = {}
self.save_review_stats_cache_file()
self.refresh_review_stats(callback)
return
# convert to the format that s-c uses
for r in piston_review_stats:
s = ReviewStats(Application("", r.package_name))
s.ratings_average = float(r.ratings_average)
s.ratings_total = float(r.ratings_total)
if r.histogram:
s.rating_spread = json.loads(r.histogram)
else:
s.rating_spread = [0, 0, 0, 0, 0]
s.dampened_rating = calc_dr(s.rating_spread)
review_stats[s.app] = s
self.REVIEW_STATS_CACHE = review_stats
callback(review_stats)
self.emit("refresh-review-stats-finished", review_stats)
self.save_review_stats_cache_file()
def _on_review_stats_data(self, spawn_helper, piston_review_stats):
""" process stdout from the helper """
review_stats = self.REVIEW_STATS_CACHE
if self._cache_version_old and self._server_has_histogram(
piston_review_stats):
self.REVIEW_STATS_CACHE = {}
self.save_review_stats_cache_file()
self.refresh_review_stats()
return
# convert to the format that s-c uses
for r in piston_review_stats:
s = ReviewStats(Application("", r.package_name))
s.ratings_average = float(r.ratings_average)
s.ratings_total = float(r.ratings_total)
if r.histogram:
s.rating_spread = json.loads(r.histogram)
else:
s.rating_spread = [0, 0, 0, 0, 0]
s.dampened_rating = calc_dr(s.rating_spread)
review_stats[s.app] = s
self.REVIEW_STATS_CACHE = review_stats
self.emit("refresh-review-stats-finished", review_stats)
self.save_review_stats_cache_file()
def show_top_rated_apps():
# get the ratings
cache = get_pkg_info()
loader = get_review_loader(cache)
review_stats = loader.REVIEW_STATS_CACHE
# recalculate using different default power
results = {}
for i in [0.5, 0.4, 0.3, 0.2, 0.1, 0.05]:
for (key, value) in review_stats.iteritems():
value.dampened_rating = calc_dr(value.rating_spread, power=i)
top_rated = loader.get_top_rated_apps(quantity=25)
print "For power: %s" % i
for (i, key) in enumerate(top_rated):
item = review_stats[key]
print "%(rang)2i: %(pkgname)-25s avg=%(avg)1.2f total=%(total)03i dampened=%(dampened)1.5f spread=%(spread)s" % {
'rang' : i+1,
'pkgname' : item.app.pkgname,
'avg' : item.ratings_average,
'total' : item.ratings_total,
'spread' : item.rating_spread,
'dampened' : item.dampened_rating,
}
print
results[i] = top_rated[:]
def show_top_rated_apps():
# get the ratings
cache = get_pkg_info()
loader = get_review_loader(cache)
review_stats = loader.REVIEW_STATS_CACHE
# recalculate using different default power
results = {}
for i in [0.5, 0.4, 0.3, 0.2, 0.1, 0.05]:
for (key, value) in review_stats.iteritems():
value.dampened_rating = calc_dr(value.rating_spread, power=i)
top_rated = loader.get_top_rated_apps(quantity=25)
print "For power: %s" % i
for (i, key) in enumerate(top_rated):
item = review_stats[key]
print "%(rang)2i: %(pkgname)-25s avg=%(avg)1.2f total=%(total)03i dampened=%(dampened)1.5f spread=%(spread)s" % {
'rang': i + 1,
'pkgname': item.app.pkgname,
'avg': item.ratings_average,
'total': item.ratings_total,
'spread': item.rating_spread,
'dampened': item.dampened_rating,
}
print
results[i] = top_rated[:]
