def _parse_sites(self, sheet):
"""
Sub method of _parse_sheet() that parses only the 'sites' sheet
Parameters
----------
sheet: GSpread worksheet
sheet containing metadata about sites
"""
records = sheet.get_all_records()
for r in records:
if r['Key'] == '':
continue
new_site = Site(hp=self,
key=r['Key'],
size=r['House size'],
inhabitants=r['Number of inhabitants'],
postcode=r['postcode'],
construction_year=r['construction year'],
k_level=r['K-level'],
e_level=r['E-level'],
epc_cert=r['EPC certificate'])
self.sites.append(new_site)
print('{} Sites created'.format(len(self.sites)))
def place_site(self,
new_site_type,
level,
player_table,
required_zone_types=None):
def is_valid_site_hex(curr_hex):
if curr_hex.active_group != None:
return False
if curr_hex.hex_type.name not in new_site_type.legal_terrain:
return False
if curr_hex.has_site():
return False
if required_zone_types != None and self.get_zone(
curr_hex.x,
curr_hex.y).zone_type.name not in required_zone_types:
return False
neighbors = self.get_neighbors(curr_hex.x, curr_hex.y)
return not any([neighbor.has_site() for neighbor in neighbors])
site_hex = self.get_random_hex(is_valid_site_hex)
if site_hex == None:
return None
site_hex.site = Site(site_hex, new_site_type, level,
player_table[new_site_type.owner_name])
site_hex.site.initialize()
return site_hex
def load_sites(self):
"""
Sets self.sites as a dict of site objects, keyed by site name
"""
sites = userapi.sites(self.session)
self.sites = {}
self.sitemap = {}
for uuid, properties in sites.iteritems():
settings = siteapi.settings(self.session, uuid)
settings['uuid'] = uuid
name = settings['name']
self.sites[name] = Site(self.session, settings)
self.sitemap[uuid] = name
def get_sum_by_site(cls, page=1, limit=10):
sites = Site.get_pagination(page, limit)
total = Site.objects.count()
items = []
for site in sites:
q = cls.objects.filter(site_id=site.id).values_list(
'dataA', 'dataB')
# the results are a collection of tupples [(d1, d2), (d3, d4) ... (dn, dm)]
# so we should be able to use the transpose to get [(d1, d3, ..., dn), (d2, d4, ..., dm)]
# then sum each group
dataA, dataB = map(sum, zip(*list(q)))
items.append(cls(site=site, dataA=dataA, dataB=dataB))
return items, total
def get_avg_sql_by_site(cls, page=1, limit=10):
table_name = cls.objects.model._meta.db_table
ids = Site.get_ids(page, limit)
total = Site.objects.count()
query = ' SELECT' \
' 0 AS id,' \
' `site_id`,' \
' AVG(`dataA`) AS dataA,' \
' AVG(`dataB`) AS dataB' \
' FROM' \
' `{}`' \
' WHERE `site_id` IN({})' \
' GROUP BY `site_id`' \
' ORDER BY `site_id` DESC'
query = query.format(table_name, ",".join(map(str, ids)))
return list(cls.objects.raw(query)), total
def __init__(self, siteId, name, baseUrl):
Site.__init__(self, siteId, name, baseUrl)