def rate_limit_ip(ip, timestamp): """Return boolean whether the IP is rate limited""" key = 'ratelimit:{}:{}'.format(ip, timestamp) current = int(redis.get(key) or 0) if current >= conf.IP_RATE_LIMIT_MAX: log.warning('Rate limited {}'.format(ip)) statsd.incr('lisa.ratelimit') return True pipe = redis.pipeline() pipe.incr(key).expire(key, 60) pipe.execute() return False
def get_data_for_timestamp(timestamp): """ Return aggregate map and share data dict for a timestamp. """ issue_continents = get_issue_dict() issue_countries = get_issue_dict() data = { 'map_total': int(redis.get(rkeys.MAP_TOTAL) or 0), 'map_previous_total': int(redis.get(rkeys.MAP_TOTAL_SNAPSHOT) or 0), 'map_geo': [], 'share_total': int(redis.get(rkeys.SHARE_TOTAL) or 0), 'continent_issues': {}, 'issue_continents': issue_continents, 'country_issues': {}, 'issue_countries': issue_countries, } statsd.gauge('milhouse.map_total', data['map_total']) redis.set(rkeys.MAP_TOTAL_SNAPSHOT, data['map_total']) map_geo_key = rkeys.MAP_GEO.format(timestamp) geo_data = redis.hgetall(map_geo_key) for latlon, count in geo_data.iteritems(): lat, lon = latlon.split(':') data['map_geo'].append({ 'lat': float(lat), 'lon': float(lon), 'count': int(count), }) # CONTINENTS # continent_totals = redis.hgetall(rkeys.SHARE_CONTINENTS) continent_issues = data['continent_issues'] for continent, count in continent_totals.iteritems(): count = int(count) issues = redis.hgetall(rkeys.SHARE_CONTINENT_ISSUES.format(continent)) continent_issues[continent] = {} for issue, issue_count in issues.iteritems(): issue_count = int(issue_count) issue = data_types.types_map[issue] percent = get_percent(issue_count, count) continent_issues[continent][issue] = percent issue_continents[issue].append({ 'continent': continent, 'count': percent, }) # COUNTRIES # country_totals = redis.hgetall(rkeys.SHARE_COUNTRIES) country_issues = data['country_issues'] for country, count in country_totals.iteritems(): count = int(count) if count < conf.COUNTRY_MIN_SHARE: continue issues = redis.hgetall(rkeys.SHARE_COUNTRY_ISSUES.format(country)) country_issues[country] = {} for issue, issue_count in issues.iteritems(): issue_count = int(issue_count) issue = data_types.types_map[issue] percent = get_percent(issue_count, count) country_issues[country][issue] = percent issue_countries[issue].append({ 'country': country, 'count': percent, }) # GLOBAL # share_issues = redis.hgetall(rkeys.SHARE_ISSUES) share_total = data['share_total'] global_issues = country_issues['GLOBAL'] = {} for issue, count in share_issues.iteritems(): count = int(count) issue = data_types.types_map[issue] global_issues[issue] = get_percent(count, share_total) return data