def __init__(self, alpha, beta, x_plot=None, y_plot=None, verbose=False):
if len(alpha) <> len(beta):
raise ValueError("The two parameter lists must be of the same length")
alpha, beta = map(frac, alpha), map(frac, beta)
n = len(alpha)
if not(set([E(beta[j]) for j in range(n)]).isdisjoint(set([E(alpha[i]) for i in range(n)]))):
if verbose:
print "Warning the sets of eigenvalues are not disjoint, the flat bundle won't be minimal:"
print alpha, beta
alpha = map(lambda x: frac(x + random()/2**15), alpha)
beta = map(lambda x: frac(x + random()/2**15), beta)
if verbose:
print "Adding a little bit of noise"
print alpha, beta
self._dimension = len(alpha)
self._alpha = map(frac, alpha)
self._beta = map(frac, beta)
self._alpha.sort()
self._beta.sort()
self._i_alpha = [alpha.index(a) for a in self._alpha]
self._i_beta = [beta.index(b) for b in self._beta]
self.x_plot = x_plot
self.y_plot = y_plot
def __init__(self, alpha, beta, x_plot=None, y_plot=None, verbose=False):
if len(alpha) <> len(beta):
raise ValueError(
"The two parameter lists must be of the same length")
alpha, beta = map(frac, alpha), map(frac, beta)
n = len(alpha)
if not (set([E(beta[j]) for j in range(n)]).isdisjoint(
set([E(alpha[i]) for i in range(n)]))):
if verbose:
print "Warning the sets of eigenvalues are not disjoint, the flat bundle won't be minimal:"
print alpha, beta
alpha = map(lambda x: frac(x + random() / 2**15), alpha)
beta = map(lambda x: frac(x + random() / 2**15), beta)
if verbose:
print "Adding a little bit of noise"
print alpha, beta
self._dimension = len(alpha)
self._alpha = map(frac, alpha)
self._beta = map(frac, beta)
self._alpha.sort()
self._beta.sort()
self._i_alpha = [alpha.index(a) for a in self._alpha]
self._i_beta = [beta.index(b) for b in self._beta]
self.x_plot = x_plot
self.y_plot = y_plot
def ai_Mandarin1(phase, player, opponents, Ref): # This version ensures you have 1 gold before buying provinces
if phase == 'action':
if 'Mandarin' in player.hand:
return('Mandarin')
else: return(False)
elif phase == 'buy':
losing_play = Ref.supply['Province'] == 1 and player.score() + 6 < max( opponent.score() for opponent in opponents )
if Ref.feasible(player, 'Province') and not losing_play: return('Province') # buy Province
elif Ref.feasible(player, 'Duchy') and Ref.supply['Province'] <= 5: return('Duchy') # buy Duchy if there are fewer than 4 estates
elif Ref.feasible(player, 'Estate') and Ref.supply['Province'] == 1 and len(player.deck) >= 10: return('Estate') # buy Estate if only 1 province and cards in deck
elif Ref.feasible(player, 'Mandarin') and player.total('Mandarin') == 0: return('Mandarin')
elif Ref.feasible(player, 'Gold'): return('Gold') # buy Gold
elif Ref.feasible(player, 'Silver'): return('Silver') # buy Silver
else: return(False)
elif phase == 'mandarin': # Here choose a card to put back on top of the deck
if player.action == 0 and 'Mandarin' in player.hand: return 'Mandarin'
elif player.wealth() > 10 and 'Gold' in player.hand: return 'Gold'
elif player.wealth() >= 10 and 'Silver' in player.hand: return 'Silver'
elif player.wealth() >= 9 and 'Copper' in player.hand: return 'Copper'
elif 'Copper' in player.hand and player.wealth() == 7: return 'Copper'
elif 'Copper' in player.hand and player.wealth() == 4: return 'Copper'
elif list(set(Ref.strict_victory_cards) & set(player.hand)) != []:
union = list(set(Ref.strict_victory_cards) & set(player.hand))
return union[0]
elif 'Copper' in player.hand: return 'Copper'
elif 'Silver' in player.hand: return 'Silver'
else:
print "Error in Mandarin1 AI"
return 'Gold'
else: raise IOError
def getStateBySimbol(self, state, simbols): states = set([state]) for simbol in simbols: newStates = set([]) for state in states: try: newStates = newStates | set(self.delta[state][simbol]) except KeyError: pass states = newStates return states
def getStateBySimbol(self, state, simbols):
states = set([state])
for simbol in simbols:
newStates = set([])
for state in states:
try:
newStates = newStates | set(self.delta[state][simbol])
except KeyError:
pass
states = newStates
return states
def TotalClassList(self):
PythonClassList=set()
pythonFiles=self.AllFileList()
for filename in pythonFiles:
classList=self.PythonClassList(filename)
PythonClassList.update(classList)
return PythonClassList
def TotalFuncList(self):
PythonFuncList=set()
pythonFiles=self.AllFileList()
for filename in pythonFiles:
funcList=self.PythonFuncList(filename)
PythonFuncList.update(funcList)
return PythonFuncList
def NFAtoDFA(N):
q0 = frozenset(N.q0)
Q = set([q0])
unprocessedQ = Q.copy()
delta = {}
F = []
Sigma = N.alphabet()
while len(unprocessedQ) > 0:
qSet = unprocessedQ.pop()
delta[qSet] = {}
for a in Sigma:
nextStates = reduce(lambda x, y: x | y,
[N.getStateBySimbol(q, a) for q in qSet])
nextStates = frozenset(nextStates)
if (nextStates is not frozenset([])):
delta[qSet][a] = nextStates
if not nextStates in Q:
if (nextStates is not frozenset([])):
Q.add(nextStates)
unprocessedQ.add(nextStates)
for qSet in Q:
if len(qSet & N.F) > 0:
F.append(qSet)
M = DFA(delta, q0, F)
return M
def add(self, item, **ftuple):
"""Add an item to be matched on a flow tuple filter.
Flow tuple values may be lists.
"""
if 'src' in ftuple:
value = ftuple['src']
# XXX - handle lists of values
if not isinstance(value, list):
value = [ value ]
for v in value:
self.src.add(v.net(), v.bcast(), item)
else:
self.src_any.add(item)
if 'dst' in ftuple:
value = ftuple['dst']
# XXX - handle lists of values
if not isinstance(value, list):
value = [ value ]
for v in value:
self.dst.add(v.net(), v.bcast(), item)
else:
self.dst_any.add(item)
for k in self.__keys:
d = getattr(self, k)
value = ftuple.get(k, None)
# XXX - handle lists of values
if not isinstance(value, list):
value = [ value ]
for v in value:
if v not in d:
d[v] = set()
d[v].add(item)
def modified(date=None, etag=None):
try:
from __builtin__ import set
except ImportError:
# for python 2.3
from sets import Set as set
env = web.ctx.env
n = set(
[x.strip('" ') for x in env.get('HTTP_IF_NONE_MATCH', '').split(',')])
m = rbweb.net.parsehttpdate(
env.get('HTTP_IF_MODIFIED_SINCE', '').split(';')[0])
validate = False
if etag:
if '*' in n or etag in n:
validate = True
if date and m:
if date - datetime.timedelta(seconds=1) <= m:
validate = True
if date: lastmodified(date)
if etag: web.header('ETag', '"' + etag + '"')
if validate:
raise web.notmodified()
else:
return True
def subscribe(self, name, event, callback):
"""Subscribe to a handler's event.
Arguments:
name -- name of handler (or match pattern)
event -- name of event published by handler
callback -- callback to be invoked
"""
if '*' in name:
found = False
for x in fnmatch.filter(Handler._subclasses.iterkeys(), name):
if event in Handler._subclasses[x].events:
self.subscribe(x, event, callback)
found = True
if not found:
raise RuntimeError, 'no matching handlers found'
return
if name not in handlers:
if name != self.name:
# XXX - auto-instantiate handler
handlers[name] = Handler._subclasses[name]()
else:
handlers[name] = self
pub = handlers[name]
pub._register(event, callback)
if pub not in self.subscriptions:
self.subscriptions[pub] = set()
self.subscriptions[pub].add((event, callback))
def modified(date=None, etag=None):
try:
from __builtin__ import set
except ImportError:
# for python 2.3
from sets import Set as set
env=web.ctx.env
n = set([x.strip('" ') for x in env.get('HTTP_IF_NONE_MATCH', '').split(',')])
m = rbweb.net.parsehttpdate(env.get('HTTP_IF_MODIFIED_SINCE', '').split(';')[0])
validate = False
if etag:
if '*' in n or etag in n:
validate = True
if date and m:
if date-datetime.timedelta(seconds=1) <= m:
validate = True
if date: lastmodified(date)
if etag: web.header('ETag', '"' + etag + '"')
if validate:
raise web.notmodified()
else:
return True
def add(self, item, **ftuple):
"""Add an item to be matched on a flow tuple filter.
Flow tuple values may be lists.
"""
if 'src' in ftuple:
value = ftuple['src']
# XXX - handle lists of values
if not isinstance(value, list):
value = [value]
for v in value:
self.src.add(v.net(), v.bcast(), item)
else:
self.src_any.add(item)
if 'dst' in ftuple:
value = ftuple['dst']
# XXX - handle lists of values
if not isinstance(value, list):
value = [value]
for v in value:
self.dst.add(v.net(), v.bcast(), item)
else:
self.dst_any.add(item)
for k in self.__keys:
d = getattr(self, k)
value = ftuple.get(k, None)
# XXX - handle lists of values
if not isinstance(value, list):
value = [value]
for v in value:
if v not in d:
d[v] = set()
d[v].add(item)
def NFAtoDFA(N):
q0 = frozenset(N.q0)
Q = set([q0])
unprocessedQ = Q.copy()
delta = {}
F = []
Sigma = N.alphabet()
while len(unprocessedQ) > 0:
qSet = unprocessedQ.pop()
delta[qSet] = {}
for a in Sigma:
nextStates = reduce(lambda x,y: x | y, [N.getStateBySimbol(q,a) for q in qSet])
nextStates = frozenset(nextStates)
if (nextStates is not frozenset([])):
delta[qSet][a] = nextStates
if not nextStates in Q:
if (nextStates is not frozenset([])):
Q.add(nextStates)
unprocessedQ.add(nextStates)
for qSet in Q:
if len(qSet & N.F) > 0:
F.append(qSet)
M = DFA(delta, q0, F)
return M
def function_to_run(review):
ret_list = []
for _, row in review.iterrows():
_scores_ = {}
del row['_id']
tags = row['final']
if len(set(tags.keys())) > 0:
for key in tags.keys():
_scores_[key] = {}
word = key.split(" ")
for category in categories.keys():
cat = categories[category]
try:
_scores_[key][category] = sum(
word_vectors.n_similarity(word, cat))
except Exception as e:
break
pass
row['score'] = _scores_
ret_list.append(row)
if len(ret_list) > 10000:
df = pd.DataFrame(ret_list)
to_mongo_db(df, 'yelp_review_scored_pair_all_not_final')
print("Written to DB", len(ret_list), 'time from start',
(time.time() - start_time))
ret_list = []
df = pd.DataFrame(ret_list)
to_mongo_db(df, 'yelp_review_scored_pair_all_not_final')
print("Written to DB", len(ret_list), 'time from start',
(time.time() - start_time))
def __init__(self, file):
fileRead = open(file, 'r')
self.delta = dict()
definitions = fileRead.read().replace(' ',
'').replace('\n', '').replace(
'\t', '').split('.')
del definitions[-1]
for definition in definitions:
if (definition.split(':')[0][0] == 'T'):
transitionsString = definition.replace(
':=',
'=').split('T:')[1].replace('},',
'*').replace('}',
'*').split('*')
for transition in transitionsString:
if (transition != ''):
transition = transition.split('={')
state = transition[0][0]
simbol = transition[0][2]
targets = set(transition[1].split(','))
deltaAux = dict([(simbol, targets)])
if self.delta.has_key(state):
self.delta[state][simbol] = targets
else:
self.delta[state] = deltaAux
elif (definition.split(':')[0][0] == 'I'):
self.q0 = definition.split(':')[1].split(',')[0]
elif (definition.split(':')[0][0] == 'F'):
self.F = definition.split(':')[1].split(',')
fileRead.close()
def _handle_adjust(func, p0, adjust, noadjust):
if adjust is None and noadjust is None:
return slice(None)
Np = len(p0)
all_index = range(Np)
para, kwpara, varargs, varkw, defaults = getVarNames(func)
names = para
Npara = len(para)
if Npara < Np:
names += kwpara[:Np - Npara]
if isinstance(adjust, slice):
adjust = all_index(adjust)
if isinstance(noadjust, slice):
adjust = all_index(noadjust)
if adjust is None:
adjust = all_index
if noadjust is None:
noadjust = []
#s = set() # This fails when running under pyHegel (not on import).
s = __builtin__.set()
# cleanup adjust. Remove duplicates, handle named variables.
for a in adjust:
if isinstance(a, basestring):
s.add(names.index(a) -
1) # -1 to remove the x parameter of f(x, p1, ...)
else:
s.add(a)
# Now cleanup noadjust
sna = __builtin__.set()
for na in noadjust:
if isinstance(na, basestring):
sna.add(names.index(na) - 1)
else:
sna.add(na)
#Remove noadjust from adjust set
s = s - sna
adj = list(s)
adj.sort()
return adj
def get_users_for_business(business_id):
user_list = []
reviews = mongo_connection.db.yelp_reviews.find(
{'business_id': business_id}, {"user_id": 1})
tips = mongo_connection.db.yelp_tips.find({'business_id': business_id},
{"user_id": 1})
for user in reviews:
user_list.append(user['user_id'])
for user in tips:
user_list.append(user['user_id'])
user_list = list(set(user_list))
return user_list
def modified(date=None, etag=None):
"""
Checks to see if the page has been modified since the version in the
requester's cache.
When you publish pages, you can include `Last-Modified` and `ETag`
with the date the page was last modified and an opaque token for
the particular version, respectively. When readers reload the page,
the browser sends along the modification date and etag value for
the version it has in its cache. If the page hasn't changed,
the server can just return `304 Not Modified` and not have to
send the whole page again.
This function takes the last-modified date `date` and the ETag `etag`
and checks the headers to see if they match. If they do, it returns
`True`, or otherwise it raises NotModified error. It also sets
`Last-Modified` and `ETag` output headers.
"""
try:
from __builtin__ import set
except ImportError:
# for python 2.3
from sets import Set as set
n = set([
x.strip('" ')
for x in web.ctx.env.get('HTTP_IF_NONE_MATCH', '').split(',')
])
m = net.parsehttpdate(
web.ctx.env.get('HTTP_IF_MODIFIED_SINCE', '').split(';')[0])
validate = False
if etag:
if '*' in n or etag in n:
validate = True
if date and m:
# we subtract a second because
# HTTP dates don't have sub-second precision
if date - datetime.timedelta(seconds=1) <= m:
validate = True
if date: lastmodified(date)
if etag: web.header('ETag', '"' + etag + '"')
if validate:
raise web.notmodified()
else:
return True
def modified(date=None, etag=None):
"""
Checks to see if the page has been modified since the version in the
requester's cache.
When you publish pages, you can include `Last-Modified` and `ETag`
with the date the page was last modified and an opaque token for
the particular version, respectively. When readers reload the page,
the browser sends along the modification date and etag value for
the version it has in its cache. If the page hasn't changed,
the server can just return `304 Not Modified` and not have to
send the whole page again.
This function takes the last-modified date `date` and the ETag `etag`
and checks the headers to see if they match. If they do, it returns
`True`, or otherwise it raises NotModified error. It also sets
`Last-Modified` and `ETag` output headers.
"""
try:
from __builtin__ import set
except ImportError:
# for python 2.3
from sets import Set as set
n = set([x.strip('" ') for x in web.ctx.env.get('HTTP_IF_NONE_MATCH', '').split(',')])
m = net.parsehttpdate(web.ctx.env.get('HTTP_IF_MODIFIED_SINCE', '').split(';')[0])
validate = False
if etag:
if '*' in n or etag in n:
validate = True
if date and m:
# we subtract a second because
# HTTP dates don't have sub-second precision
if date - datetime.timedelta(seconds=1) <= m:
validate = True
if date:
lastmodified(date)
if etag:
web.header('ETag', '"' + etag + '"')
if validate:
raise web.notmodified()
else:
return True
def getPropertyValueListByPropertyTypeHandler(handlerName):
propertyTypeHandler = propertyApi.getPropertyHandlerIdByPropertyHandlerName(handlerName)
if propertyTypeHandler is not None:
handlerPropertyTypes = propertyApi.getPropertyTypesByHandlerId(propertyTypeHandler.data['id'])
else:
return
propertyValues = []
for propertyType in handlerPropertyTypes:
propertyTypeValues = propertyApi.getPropertyValuesByPropertyTypeId(propertyType.data['id'])
propertyValues = propertyValues + propertyTypeValues
attachements = []
for propertyValue in propertyValues:
appendNonEmptyValue(attachements,propertyValue.data['value'])
for propertyValueHistory in propertyValue.data['propertyValueHistory']:
appendNonEmptyValue(attachements, propertyValueHistory.value)
# Remove duplicates and return list
return list(set(attachements))
def get_user_friends(user_list):
users = mongo_connection.db.yelp_users.find(
{'user_id': {
"$in": user_list
}}, {
'friends': 1,
'user_id': 1
})
edges = []
for user in users:
friends = user['friends']
user_id = user['user_id']
for friend in friends:
edges.append((user_id, friend))
edges.append((friend, user_id))
edges = list(set(edges))
return edges
def FormattedClassList(self,silent=True):
PythonClassList=self.TotalClassList()
formattedClassList=set()
for filename in self.LyxFileList():
if not silent:
print(filename)
with open(filename,'r') as f:
lines=f.readlines()
for lineindex in range(len(lines)):
if lines[lineindex] == '\\begin_inset Flex PythonClass\n':
try:
classname=lines[lineindex+5].strip()
if classname in PythonClassList:
if not silent:
print('FOUND ONE: '+classname)
formattedClassList.add(classname)
else:
if not silent:
print('class not in list: '+classname)
except:
pass
return formattedClassList
def __init__(self, service, *args, **kwargs):
super(PrivacyPolicyForm, self).__init__(*args, **kwargs)
self.service = service
unq = set()
for sett in service.inputs.all():
for type in sett.types.all():
unq.add(type)
for type in service.output.types.all():
unq.add(type)
#removing the ones that are currently added
for rule in service.service_privacy_policy_rule_set.all():
unq.remove(rule.dataType)
choices = []
for type in unq:
choices.append((type, str(type)))
print(choices)
self.fields['type'].choices = choices
try:
self.fields['type'].initial = self.instance.dataType.name
except:
pass
def to_python(self, value):
striped = value.strip()
if striped[0] != '{' or striped[-1] != '}':
raise ValidationError(('set should start with { and end with }'))
striped = striped[1:-1]
splited = striped.split(',')
ret = set()
if len(splited) == 0 or (len(splited) == 1 and not splited[0].strip()):
if self.required:
raise ValidationError(('set can not be empty'))
else:
return ret
for val in splited:
striped = val.strip()
if not striped:
continue
if re.match('[a-zA-Z0-9_]\w*',striped) is None:
raise ValidationError(('invalid type name: "%(name)s"'),
params={'name': striped}
)
ret.add(striped)
return ret
def __init__(self, file):
fileRead = open(file, 'r')
self.delta = dict()
definitions = fileRead.read().replace(' ', '').replace('\n', '').replace('\t', '').split('.')
del definitions[-1]
for definition in definitions:
if (definition.split(':')[0][0] == 'T'):
transitionsString = definition.replace(':=','=').split('T:')[1].replace('},','*').replace('}','*').split('*')
for transition in transitionsString:
if (transition != ''):
transition = transition.split('={')
state = transition[0][0]
simbol = transition[0][2]
targets = set(transition[1].split(','))
deltaAux = dict([(simbol,targets)])
if self.delta.has_key(state):
self.delta[state][simbol] = targets
else:
self.delta[state] = deltaAux
elif (definition.split(':')[0][0] == 'I'):
self.q0 = definition.split(':')[1].split(',')[0]
elif (definition.split(':')[0][0] == 'F'):
self.F = definition.split(':')[1].split(',')
fileRead.close()
def tradefind_display(self,
qtype,
fromt,
to,
set=None,
age=24,
cashonhand=10000000.00,
minprofit=100000,
size=10000,
startat=0,
limit=50,
newsearch="0",
sort="jprofit",
prefer_sec="0"):
session = EVCstate()
t = display.template('tradefind_display.tmpl', session)
db = evec_func.db_con()
newsearch = int(newsearch)
if 'trade_results' not in session:
newsearch = 1
cur = db.cursor()
limit = int(limit)
prefer_sec = int(prefer_sec)
recalc_route = False
if sort not in ['jprofit', 'sprofit', 'profit', 'jumps']:
return
if set:
session['tf_age'] = age
session['tf_minprofit'] = minprofit
session['tf_size'] = size
session['tf_limit'] = limit
session['tf_sort'] = sort
session['tf_prefer_sec'] = prefer_sec
newsearch = 1
else:
if 'tf_age' in session:
age = session['tf_age']
if 'tf_minprofit' in session:
minprofit = session['tf_minprofit']
if 'tf_size' in session:
size = session['tf_size']
if 'tf_limit' in session:
limit = session['tf_limit']
if 'tf_sort' in session:
sort = session['tf_sort']
if 'tf_prefer_sec' in session:
prefer_sec = session['tf_prefer_sec']
else:
prefer_sec = 1
age_t = str(int(age)) + " hours"
size = str(int(size))
cashonhand = str(double(cashonhand))
sql_profit_size = """ (t.price - f.price)* min(""" + size + """, min(t.volremain,f.volremain) * types.size)/types.size """
sql_profit_jumps = """ '1' """
#sql_cash = """ f.price <= $(cashonhand)s """
sql_sec_limit = """ """
if prefer_sec:
sql_sec_limit = """ fsys.security > 0.4 AND tsys.security > 0.4 AND """
cur_f = db.cursor()
cur_t = db.cursor()
#####
# Warning: This is easily the worst piece of code I have ever written.
# I really am sorry.
#####
# Pure suck query
if qtype == "Systems" and newsearch:
cur.execute(
"""SELECT types.typeid,types.typename,fs.systemid,ts.systemid,fs.stationname,ts.stationname,t.price - f.price AS pricediff,
min(t.volremain,f.volremain),
(t.price - f.price)* min(t.volremain,f.volremain) AS profit,
""" + sql_profit_size + """ AS profit_size,
""" + sql_profit_jumps + """ AS profit_jumps,
t.price,f.price,
t.volremain,f.volremain
FROM
types, current_market AS f, current_market AS t, stations AS fs, stations AS ts, systems AS fsys, systems AS tsys
WHERE
""" + sql_sec_limit + """
ts.systemid = tsys.systemid AND fs.systemid = fsys.systemid AND
f.minvolume <= 1 AND t.minvolume <= 1 AND
f.bid = 0 AND t.bid = 1 AND f.systemid = %(fromt)s AND t.systemid = %(to)s AND t.typeid = f.typeid AND t.stationid = ts.stationid AND
f.stationid = fs.stationid AND
age(f.reportedtime) < %(age)s AND age(t.reportedtime) < %(age)s AND
""" + sql_profit_size + """ >= %(minprofit)s AND
types.size <= """ + size + """ AND
t.typeid = types.typeid
AND f.typeid = types.typeid
AND f.price < t.price""", {
'fromt': fromt,
'to': to,
'age': age_t,
'minprofit': minprofit,
})
cur_f.execute(
"SELECT systemid,(systemname || ' / ') || regionname FROM systems,regions WHERE systems.regionid = regions.regionid AND systemid = %s ORDER BY systemname",
[fromt])
cur_t.execute(
"SELECT systemid,(systemname || ' / ') || regionname FROM systems,regions WHERE systems.regionid = regions.regionid AND systemid = %s ORDER BY systemname",
[to])
elif qtype == "Regions" and newsearch:
cur.execute(
"""SELECT types.typeid,types.typename,fs.systemid,ts.systemid,fs.stationname,ts.stationname,t.price - f.price AS pricediff,
min(t.volremain,f.volremain),
(t.price - f.price)*min(t.volremain,f.volremain) AS profit,
""" + sql_profit_size + """ AS profit_size,
""" + sql_profit_jumps + """ AS profit_jumps,
t.price,f.price, t.volremain, f.volremain
FROM types, current_market AS f, current_market AS t, stations AS fs, stations AS ts, systems AS fsys, systems AS tsys
WHERE
""" + sql_sec_limit + """
ts.systemid = tsys.systemid AND fs.systemid = fsys.systemid AND
f.minvolume <= 1 AND t.minvolume <= 1 AND
f.bid = 0 AND t.bid = 1 AND f.regionid = %(fromt)s AND t.regionid = %(to)s AND t.typeid = f.typeid AND t.stationid = ts.stationid AND
f.stationid = fs.stationid AND
age(f.reportedtime) < %(age)s AND age(t.reportedtime) < %(age)s AND
""" + sql_profit_size + """ >= %(minprofit)s AND
types.size <= """ + size + """ AND
t.typeid = types.typeid
AND f.typeid = types.typeid
AND f.price < t.price""", {
'fromt': fromt,
'to': to,
'age': age_t,
'minprofit': minprofit,
})
cur_f.execute(
"SELECT regionid,regionname FROM regions WHERE regionid = %s ORDER BY regionname",
[fromt])
cur_t.execute(
"SELECT regionid,regionname FROM regions WHERE regionid = %s ORDER BY regionname",
[to])
elif qtype == "SystemToRegion" and newsearch:
cur.execute(
"""SELECT types.typeid,types.typename,fs.systemid,ts.systemid,fs.stationname,ts.stationname,t.price - f.price AS pricediff,
min(t.volremain,f.volremain),
(t.price - f.price)*min(t.volremain,f.volremain) AS profit,
""" + sql_profit_size + """ AS profit_size,
""" + sql_profit_jumps + """ AS profit_jumps,
t.price,f.price, t.volremain, f.volremain
FROM types, current_market AS f, current_market AS t, stations AS fs, stations AS ts, systems AS fsys, systems AS tsys
WHERE
""" + sql_sec_limit + """
ts.systemid = tsys.systemid AND fs.systemid = fsys.systemid AND
f.minvolume <= 1 AND t.minvolume <= 1 AND
f.bid = 0 AND t.bid = 1 AND f.systemid = %(fromt)s AND t.regionid = %(to)s AND t.typeid = f.typeid AND t.stationid = ts.stationid AND
f.stationid = fs.stationid AND
age(f.reportedtime) < %(age)s AND age(t.reportedtime) < %(age)s AND
""" + sql_profit_size + """ >= %(minprofit)s AND
types.size <= """ + size + """ AND
t.typeid = types.typeid
AND f.typeid = types.typeid
AND f.price < t.price""", {
'fromt': fromt,
'to': to,
'age': age_t,
'minprofit': minprofit,
})
cur_f.execute(
"SELECT systemid,(systemname || ' / ') || regionname FROM systems,regions WHERE systems.regionid = regions.regionid AND systemid = %s ORDER BY systemname",
[fromt])
cur_t.execute(
"SELECT regionid,regionname FROM regions WHERE regionid = %s ORDER BY regionname",
[to])
trades = []
time_net = 0.0
import __builtin__
from_set = __builtin__.set()
from_map = {}
from_to_map = {}
error_log = []
fromcache = 0
if newsearch:
r = cur.fetchone()
while r:
row = SorterDict('sortby')
row['typeid'] = r[0]
row['typename'] = r[1]
fr = int(r[2])
to2 = int(r[3])
row['fr'] = int(r[2])
row['to2'] = int(r[3])
row['fromstation'] = r[4]
row['tostation'] = r[5]
row['pricediff'] = r[6]
row['tradeable'] = format_long(long(r[7]))
row['profit'] = format_price(float(r[8]))
row['profit_num'] = float(r[8])
row['profit_size'] = float(r[9])
from_set.add(fr)
row['tprice'] = format_price(float(r[11]))
row['fprice'] = format_price(float(r[12]))
row['tvol'] = format_long(long(r[13]))
row['fvol'] = format_long(long(r[14]))
trades.append(row)
# Add to from_to_map - map source
if fr in from_to_map:
from_to_map[fr].add(row['to2'])
else:
from_to_map[fr] = __builtin__.set()
from_to_map[fr].add(row['to2'])
if fr in from_map:
from_map[fr].append(row)
else:
from_map[fr] = []
from_map[fr].append(row)
r = cur.fetchone()
# Now we try to compute distance
for compsys in from_set:
distance_map = {}
distance = 0
time_net_ = time.time()
for tosystem in from_to_map[compsys]:
load = urllib.urlopen(
'http://127.0.0.1:8081/api/distance/from/' +
str(int(compsys)) + '/to/' + str(int(tosystem)))
s = load.read()
load.close()
distance_map[tosystem] = json.loads(s)['distance']
time_net += time.time() - time_net_
for row in from_map[compsys]:
if row['fr'] == compsys:
if compsys == row['to2']:
distance = 0
else:
distance = distance_map[row['to2']]
ps = row['profit_size']
row['profit_size'] = format_price(ps)
if sort == "jprofit":
row['sortby'] = ps / (max(0, distance) + 1)
t.sort_nice = "Profit per jump"
elif sort == "sprofit":
row['sortby'] = ps
t.sort_nice = "Profit per trip"
elif sort == "profit":
row['sortby'] = row['profit_num']
t.sort_nice = "Profit"
elif sort == "jumps":
t.sort_nice = "Distance"
row['sortby'] = distance
row.reverse = True
row['profit_jumps'] = format_price(
float(ps / (1 + max(0, distance))))
row['distance'] = distance
time_sort = time.time()
trades.sort(reverse=True)
time_sort = time.time() - time_sort
#session['trade_results'] = trades
else:
trades = session['trade_results']
fromcache = 1
trade_num = len(trades)
trades = trades[int(startat):int(startat) + int(limit)]
t.fromcache = fromcache
t.num_trades = trade_num
t.trades = trades
t.fromt = fromt
t.to = to
t.qtype = qtype
t.age = age
t.minprofit = minprofit
t.size = size
t.startat = startat
t.limit = limit
t.sort = sort
t.prefer_sec = prefer_sec
t.fromname = cur_f.fetchone()[1]
t.toname = cur_t.fetchone()[1]
t.page = int((int(startat) + 1) / limit) + 1
t.next = int(startat) + limit
t.prev = max(0, int(startat) - limit)
db.close()
session.save()
return t.respond(
) + "Pathfinder time: %0.3fs, Sort time: %0.3fs, recompute set was %d elements long<br>" % (
time_net, time_sort, len(from_set))
def test_monodromy(self, nsteps_x, nsteps_y, save=False):
import os.path, csv
from csv import DictReader, DictWriter
import sage.all
from sage.matrix.special import identity_matrix
from sage.rings.complex_double import CDF
from sage.symbolic.constants import e
x_list = lin_space(self._xmin, self._xmax, nsteps_x)
y_list = lin_space(self._ymin, self._ymax, nsteps_y)
tab = [[self.section_f(x, y) for y in y_list] for x in x_list]
fieldnames = [
'Exp', 'i', 'j', 'x_plot', 'y_plot', 'dist_id', 'dist_ev'
]
f_name = self.f_name(nsteps_x, nsteps_y, -1, -1)
if os.path.isfile(f_name):
with open(f_name, 'r') as csvfile:
reader = csv.DictReader(csvfile, delimiter=',')
test = 1
for row in reader:
test = 0
if test:
last_i, last_j = 0, 0
else:
last_i, last_j = int(row['i']), int(row['j'])
else:
with open(f_name, 'w') as csvfile:
writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
writer.writeheader()
last_i, last_j = 0, 0
with open(f_name, 'a') as csvfile:
from cmath import exp, pi
from __builtin__ import set
from sage.misc.functional import numerical_approx
writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
if not ((last_i == nsteps_x - 1) and (last_i == nsteps_y - 1)):
for i in range(last_i, nsteps_x):
for j in range(last_j + 1 if i == last_i else 0, nsteps_y):
print i, j
M0, M1, MInfty = tab[i][j].monodromy_matrices()
n = tab[i][j]._dimension
beta = tab[i][j]._beta
dist_id = (M0 * M1 * MInfty -
identity_matrix(CDF, n)).norm()
ev = set(MInfty.eigenvalues())
d = []
for b in beta:
val = exp(-2 * 1j * pi * b)
c_val = min(ev, key=lambda z: (z - val).norm())
d.append((c_val - val).norm())
ev.remove(c_val)
dist_ev = max(d)
print max(dist_ev, dist_id)
writer.writerow({
'Exp': tab[i][j],
'i': i,
'j': j,
'x_plot': tab[i][j].x_plot,
'y_plot': tab[i][j].y_plot,
'dist_id': dist_id,
'dist_ev': dist_ev
})
return True
def test_monodromy(self, nsteps_x, nsteps_y, save=False):
import os.path, csv
from csv import DictReader, DictWriter
import sage.all
from sage.matrix.special import identity_matrix
from sage.rings.complex_double import CDF
from sage.symbolic.constants import e
x_list = lin_space(self._xmin, self._xmax, nsteps_x)
y_list = lin_space(self._ymin, self._ymax, nsteps_y)
tab = [[self.section_f(x,y) for y in y_list] for x in x_list]
fieldnames = ['Exp', 'i', 'j', 'x_plot', 'y_plot', 'dist_id', 'dist_ev']
f_name = self.f_name(nsteps_x, nsteps_y, -1, -1)
if os.path.isfile(f_name) :
with open(f_name, 'r') as csvfile :
reader= csv.DictReader(csvfile, delimiter=',')
test = 1
for row in reader :
test = 0
if test:
last_i, last_j = 0, 0
else:
last_i, last_j = int(row['i']), int(row['j'])
else :
with open(f_name, 'w') as csvfile :
writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
writer.writeheader()
last_i, last_j = 0, 0
with open(f_name, 'a') as csvfile :
from cmath import exp, pi
from __builtin__ import set
from sage.misc.functional import numerical_approx
writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
if not ((last_i == nsteps_x-1) and (last_i == nsteps_y-1)):
for i in range(last_i,nsteps_x):
for j in range(last_j+1 if i == last_i else 0, nsteps_y):
print i,j
M0, M1, MInfty = tab[i][j].monodromy_matrices()
n = tab[i][j]._dimension
beta = tab[i][j]._beta
dist_id = (M0*M1*MInfty - identity_matrix(CDF,n)).norm()
ev = set(MInfty.eigenvalues())
d = []
for b in beta:
val = exp(-2*1j*pi*b)
c_val = min(ev, key=lambda z: (z-val).norm())
d.append((c_val-val).norm())
ev.remove(c_val)
dist_ev = max(d)
print max(dist_ev, dist_id)
writer.writerow({'Exp' : tab[i][j], 'i' : i, 'j' : j,
'x_plot' : tab[i][j].x_plot, 'y_plot' : tab[i][j].y_plot,
'dist_id' : dist_id, 'dist_ev' : dist_ev})
return True
def __init__(self, delta, q0, F): self.delta = delta self.q0 = q0 self.F = set(F)
def _register(self, event, callback):
"""Register subscription from another handler."""
if event not in self.callbacks:
self.callbacks[event] = set()
self.callbacks[event].add(callback)
def __get_all_modules__(path=convert_to_unicode(sys.path[0])):
'''
This method provides a generic way to determine all modules in \
current package or folder. It is useful for "__init__.py" files.
**path** - Current working directory.
Examples:
>>> __get_all_modules__() # doctest: +ELLIPSIS
[...]
>>> from boostnode.extension.file import Handler as FileHandler
>>> location = FileHandler(
... __test_folder__.path + '__get_all_modules__',
... make_directory=True)
>>> a = FileHandler(location.path + 'a.py')
>>> a.content = ''
>>> FileHandler(
... location.path + 'b.pyc', make_directory=True
... ) # doctest: +ELLIPSIS
Object of "Handler" with path "...__get_all_modu...b.pyc..." (type: ...
>>> __get_all_modules__(__test_folder__.path + '__get_all_modules__')
['a']
>>> a.remove_file()
True
>>> __get_all_modules__(__test_folder__.path + '__get_all_modules__')
[]
>>> __get_all_modules__('')
['highPerformanceModification']
'''
# # python3.5
# # if not path:
# # path = os.getcwd()
# # return builtins.list(builtins.set(builtins.map(
# # lambda name: name[:name.rfind('.')],
# # builtins.filter(
# # lambda name: (
# # (name.endswith('.py') or name.endswith('.pyc')) and
# # not name.startswith('__init__.') and os.path.isfile(
# # '%s%s%s' % (path, os.sep, name))),
# # os.listdir(
# # path[:-(builtins.len(os.path.basename(path)) + 1)] if
# # os.path.isfile(path) else path)))))
if not path:
path = os.getcwd()
return builtins.list(builtins.set(builtins.map(
lambda name: name[:name.rfind('.')],
builtins.filter(
lambda name: (
(name.endswith('.py') or name.endswith('.pyc')) and
not name.startswith('__init__.') and os.path.isfile(
convert_to_string('%s%s%s' % (path, os.sep, name)))),
builtins.map(
lambda name: convert_to_unicode(name), os.listdir(
path[:-(builtins.len(os.path.basename(path)) + 1)] if
os.path.isfile(path) else path))))))
import os, __builtin__
plugin_list = __builtin__.set()
for module in os.listdir(os.path.dirname(__file__)):
if module == '__init__.py' or module[-3:] != '.py':
continue
__import__(module[:-3], locals(), globals())
plugin_list.add(module[:-3])
del module
def __init__(self):
self.src, self.src_any = itree.Itree(), set()
self.dst, self.dst_any = itree.Itree(), set()
for k in self.__keys:
setattr(self, k, {None: set()})
def tradefind_display(self, qtype, fromt, to, set = None, age = 24, cashonhand = 10000000.00, minprofit = 100000, size = 10000, startat = 0, limit = 10, newsearch = "0", sort = "jprofit", prefer_sec = "0"):
mapserver = Pyro.core.getProxyForURI("PYROLOC://localhost:7766/mapserver")
session = EVCstate()
t = display.template('tradefind_display.tmpl', session)
db = evec_func.db_con()
newsearch = int(newsearch)
if 'trade_results' not in session:
newsearch = 1
cur = db.cursor()
limit = int(limit)
prefer_sec = int(prefer_sec)
recalc_route = False
if sort not in ['jprofit', 'sprofit', 'profit', 'jumps']:
return
if set:
session['tf_age'] = age
session['tf_minprofit'] = minprofit
session['tf_size'] = size
session['tf_limit'] = limit
session['tf_sort'] = sort
session['tf_prefer_sec'] = prefer_sec
newsearch = 1
else:
if 'tf_age' in session:
age = session['tf_age']
if 'tf_minprofit' in session:
minprofit = session['tf_minprofit']
if 'tf_size' in session:
size = session['tf_size']
if 'tf_limit' in session:
limit = session['tf_limit']
if 'tf_sort' in session:
sort = session['tf_sort']
if 'tf_prefer_sec' in session:
prefer_sec = session['tf_prefer_sec']
else:
prefer_sec = 1
age_t = str(int(age)) + " hours"
size = str(int(size))
cashonhand = str(double(cashonhand))
sql_profit_size = """ (t.price - f.price)* min(""" + size + """, min(t.volremain,f.volremain) * types.size)/types.size """
sql_profit_jumps = """ '1' """
#sql_cash = """ f.price <= $(cashonhand)s """
sql_sec_limit = """ """
if prefer_sec:
sql_sec_limit = """ fsys.security > 0.4 AND tsys.security > 0.4 AND """
cur_f = db.cursor()
cur_t = db.cursor()
# Pure suck query
if qtype == "Systems" and newsearch:
cur.execute("""SELECT types.typeid,types.typename,fs.systemid,ts.systemid,fs.stationname,ts.stationname,t.price - f.price AS pricediff,
min(t.volremain,f.volremain),
(t.price - f.price)* min(t.volremain,f.volremain) AS profit,
""" + sql_profit_size + """ AS profit_size,
""" + sql_profit_jumps + """ AS profit_jumps,
t.price,f.price,
t.volremain,f.volremain
FROM
types, current_market AS f, current_market AS t, stations AS fs, stations AS ts, systems AS fsys, systems AS tsys
WHERE
""" + sql_sec_limit + """
ts.systemid = tsys.systemid AND fs.systemid = fsys.systemid AND
f.bid = 0 AND t.bid = 1 AND f.systemid = %(fromt)s AND t.systemid = %(to)s AND t.typeid = f.typeid AND t.stationid = ts.stationid AND
f.stationid = fs.stationid AND
age(f.reportedtime) < %(age)s AND age(t.reportedtime) < %(age)s AND
""" + sql_profit_size + """ >= %(minprofit)s AND
types.size <= """ + size + """ AND
t.typeid = types.typeid
AND f.typeid = types.typeid
AND f.price < t.price""",
{'fromt':fromt, 'to':to, 'age':age_t, 'minprofit':minprofit,})
cur_f.execute("SELECT systemid,(systemname || ' / ') || regionname FROM systems,regions WHERE systems.regionid = regions.regionid AND systemid = %s ORDER BY systemname", [fromt])
cur_t.execute("SELECT systemid,(systemname || ' / ') || regionname FROM systems,regions WHERE systems.regionid = regions.regionid AND systemid = %s ORDER BY systemname", [to])
elif qtype == "Regions" and newsearch:
cur.execute("""SELECT types.typeid,types.typename,fs.systemid,ts.systemid,fs.stationname,ts.stationname,t.price - f.price AS pricediff,
min(t.volremain,f.volremain),
(t.price - f.price)*min(t.volremain,f.volremain) AS profit,
"""+ sql_profit_size + """ AS profit_size,
""" + sql_profit_jumps + """ AS profit_jumps,
t.price,f.price, t.volremain, f.volremain
FROM types, current_market AS f, current_market AS t, stations AS fs, stations AS ts, systems AS fsys, systems AS tsys
WHERE
""" + sql_sec_limit + """
ts.systemid = tsys.systemid AND fs.systemid = fsys.systemid AND
f.bid = 0 AND t.bid = 1 AND f.regionid = %(fromt)s AND t.regionid = %(to)s AND t.typeid = f.typeid AND t.stationid = ts.stationid AND
f.stationid = fs.stationid AND
age(f.reportedtime) < %(age)s AND age(t.reportedtime) < %(age)s AND
""" + sql_profit_size + """ >= %(minprofit)s AND
types.size <= """ + size + """ AND
t.typeid = types.typeid
AND f.typeid = types.typeid
AND f.price < t.price""",
{'fromt':fromt, 'to':to, 'age':age_t, 'minprofit':minprofit, })
cur_f.execute("SELECT regionid,regionname FROM regions WHERE regionid = %s ORDER BY regionname", [fromt])
cur_t.execute("SELECT regionid,regionname FROM regions WHERE regionid = %s ORDER BY regionname", [to])
elif qtype == "SystemToRegion" and newsearch:
cur.execute("""SELECT types.typeid,types.typename,fs.systemid,ts.systemid,fs.stationname,ts.stationname,t.price - f.price AS pricediff,
min(t.volremain,f.volremain),
(t.price - f.price)*min(t.volremain,f.volremain) AS profit,
""" + sql_profit_size + """ AS profit_size,
""" + sql_profit_jumps + """ AS profit_jumps,
t.price,f.price, t.volremain, f.volremain
FROM types, current_market AS f, current_market AS t, stations AS fs, stations AS ts, systems AS fsys, systems AS tsys
WHERE
""" + sql_sec_limit + """
ts.systemid = tsys.systemid AND fs.systemid = fsys.systemid AND
f.bid = 0 AND t.bid = 1 AND f.systemid = %(fromt)s AND t.regionid = %(to)s AND t.typeid = f.typeid AND t.stationid = ts.stationid AND
f.stationid = fs.stationid AND
age(f.reportedtime) < %(age)s AND age(t.reportedtime) < %(age)s AND
""" + sql_profit_size + """ >= %(minprofit)s AND
types.size <= """ + size + """ AND
t.typeid = types.typeid
AND f.typeid = types.typeid
AND f.price < t.price""",
{'fromt':fromt, 'to':to, 'age':age_t, 'minprofit':minprofit, })
cur_f.execute("SELECT systemid,(systemname || ' / ') || regionname FROM systems,regions WHERE systems.regionid = regions.regionid AND systemid = %s ORDER BY systemname", [fromt])
cur_t.execute("SELECT regionid,regionname FROM regions WHERE regionid = %s ORDER BY regionname", [to])
elif qtype == "Global" and newsearch:
cur.execute("""SELECT types.typeid,types.typename,fs.systemid,ts.systemid,fs.stationname,ts.stationname,t.price - f.price AS pricediff,
min(t.volremain,f.volremain),
(t.price - f.price)*min(t.volremain,f.volremain) AS profit,
"""+ sql_profit_size + """ AS profit_size,
""" + sql_profit_jumps + """ AS profit_jumps,
t.price,f.price
FROM types, current_market AS f, current_market AS t, stations AS fs, stations AS ts, systems AS fsys, systems AS tsys
WHERE
""" + sql_sec_limit + """
ts.systemid = tsys.systemid AND fs.systemid = fsys.systemid AND
f.bid = 0 AND t.bid = 1 AND t.typeid = f.typeid AND t.stationid = ts.stationid AND
f.stationid = fs.stationid AND
age(f.reportedtime) < %(age)s AND age(t.reportedtime) < %(age)s AND
""" + sql_profit_size + """ >= %(minprofit)s AND
types.size <= """ + size + """ AND
t.typeid = types.typeid
AND f.typeid = types.typeid
AND f.price < t.price""",
# ORDER BY profit_size DESC LIMIT %(limit)s OFFSET %(startat)s""",
{'age':age_t, 'minprofit':minprofit})
cur_f.execute("SELECT regionid,regionname FROM regions WHERE regionid = %s ORDER BY regionname", [fromt])
cur_t.execute("SELECT regionid,regionname FROM regions WHERE regionid = %s ORDER BY regionname", [to])
trades = []
time_net = 0.0
import __builtin__
from_set = __builtin__.set()
from_map = {}
from_to_map = {}
error_log = []
fromcache = 0
if newsearch:
r = cur.fetchone()
while r:
row = SorterDict('sortby')
row['typeid'] = r[0]
row['typename'] = r[1]
fr = int(r[2])
to2 = int(r[3])
row['fr'] = int(r[2])
row['to2'] = int(r[3])
row['fromstation'] = r[4]
row['tostation'] = r[5]
row['pricediff'] = r[6]
row['tradeable'] = format_long(long(r[7]))
row['profit'] = format_price(float(r[8]))
row['profit_size'] = float(r[9])
from_set.add(fr)
row['tprice'] = format_price(float(r[11]))
row['fprice'] = format_price(float(r[12]))
row['tvol'] = format_long(long(r[13]))
row['fvol'] = format_long(long(r[14]))
trades.append(row)
# Add to from_to_map - map source
if fr in from_to_map:
from_to_map[fr].add(row['to2'])
else:
from_to_map[fr] = __builtin__.set()
from_to_map[fr].add(row['to2'])
if fr in from_map:
from_map[fr].append(row)
else:
from_map[fr] = []
from_map[fr].append(row)
r = cur.fetchone()
# Now we try to compute distance
for compsys in from_set:
distance_map = {}
distance = 0
time_net_ = time.time()
distance_map = mapserver.route_comp(compsys, list(from_to_map[compsys]))
time_net += time.time() - time_net_
for row in from_map[compsys]:
if row['fr'] == compsys:
if compsys == row['to2']:
distance = 0
else:
distance = distance_map[row['to2']]
ps = row['profit_size']
row['profit_size'] = format_price(ps)
if sort == "jprofit":
row['sortby'] = ps/(max(0,distance)+1)
t.sort_nice = "Profit per jump"
elif sort == "sprofit":
row['sortby'] = ps
t.sort_nice = "Profit per trip"
elif sort == "profit":
row['sortby'] = row['profit']
t.sort_nice = "Profit"
elif sort == "jumps":
t.sort_nice = "Distance"
row['sortby'] = distance
row.reverse= True
row['profit_jumps'] = format_price(float(ps/(1+max(0,distance))))
row['distance'] = distance
time_sort = time.time()
trades.sort(reverse=True)
time_sort = time.time() - time_sort
#session['trade_results'] = trades
else:
trades = session['trade_results']
fromcache = 1
trade_num = len(trades)
trades = trades[int(startat):int(startat)+int(limit)]
t.fromcache = fromcache
t.num_trades = trade_num
t.trades = trades
t.fromt = fromt
t.to = to
t.qtype = qtype
t.age = age
t.minprofit = minprofit
t.size = size
t.startat = startat
t.limit = limit
t.sort = sort
t.prefer_sec = prefer_sec
t.fromname = cur_f.fetchone()[1]
t.toname = cur_t.fetchone()[1]
t.page = int((int(startat) + 1) / limit) + 1
t.next = int(startat) +limit
t.prev = max(0,int(startat) - limit)
db.close()
session.save()
return t.respond() +"Pathfinder time: %0.3fs, Sort time: %0.3fs, recompute set was %d elements long<br>" % (time_net, time_sort, len(from_set))
def tradefind_display(
self,
qtype,
fromt,
to,
set=None,
age=24,
cashonhand=10000000.00,
minprofit=100000,
size=10000,
startat=0,
limit=50,
newsearch="0",
sort="jprofit",
prefer_sec="0",
):
session = EVCstate()
t = display.template("tradefind_display.tmpl", session)
db = evec_func.db_con()
newsearch = int(newsearch)
if "trade_results" not in session:
newsearch = 1
cur = db.cursor()
limit = int(limit)
prefer_sec = int(prefer_sec)
recalc_route = False
if sort not in ["jprofit", "sprofit", "profit", "jumps"]:
return
if set:
session["tf_age"] = age
session["tf_minprofit"] = minprofit
session["tf_size"] = size
session["tf_limit"] = limit
session["tf_sort"] = sort
session["tf_prefer_sec"] = prefer_sec
newsearch = 1
else:
if "tf_age" in session:
age = session["tf_age"]
if "tf_minprofit" in session:
minprofit = session["tf_minprofit"]
if "tf_size" in session:
size = session["tf_size"]
if "tf_limit" in session:
limit = session["tf_limit"]
if "tf_sort" in session:
sort = session["tf_sort"]
if "tf_prefer_sec" in session:
prefer_sec = session["tf_prefer_sec"]
else:
prefer_sec = 1
age_t = str(int(age)) + " hours"
size = str(int(size))
cashonhand = str(double(cashonhand))
sql_profit_size = (
""" (t.price - f.price)* min(""" + size + """, min(t.volremain,f.volremain) * types.size)/types.size """
)
sql_profit_jumps = """ '1' """
# sql_cash = """ f.price <= $(cashonhand)s """
sql_sec_limit = """ """
if prefer_sec:
sql_sec_limit = """ fsys.security > 0.4 AND tsys.security > 0.4 AND """
cur_f = db.cursor()
cur_t = db.cursor()
#####
# Warning: This is easily the worst piece of code I have ever written.
# I really am sorry.
#####
# Pure suck query
if qtype == "Systems" and newsearch:
cur.execute(
"""SELECT types.typeid,types.typename,fs.systemid,ts.systemid,fs.stationname,ts.stationname,t.price - f.price AS pricediff,
min(t.volremain,f.volremain),
(t.price - f.price)* min(t.volremain,f.volremain) AS profit,
"""
+ sql_profit_size
+ """ AS profit_size,
"""
+ sql_profit_jumps
+ """ AS profit_jumps,
t.price,f.price,
t.volremain,f.volremain
FROM
types, current_market AS f, current_market AS t, stations AS fs, stations AS ts, systems AS fsys, systems AS tsys
WHERE
"""
+ sql_sec_limit
+ """
ts.systemid = tsys.systemid AND fs.systemid = fsys.systemid AND
f.minvolume <= 1 AND t.minvolume <= 1 AND
f.bid = 0 AND t.bid = 1 AND f.systemid = %(fromt)s AND t.systemid = %(to)s AND t.typeid = f.typeid AND t.stationid = ts.stationid AND
f.stationid = fs.stationid AND
age(f.reportedtime) < %(age)s AND age(t.reportedtime) < %(age)s AND
"""
+ sql_profit_size
+ """ >= %(minprofit)s AND
types.size <= """
+ size
+ """ AND
t.typeid = types.typeid
AND f.typeid = types.typeid
AND f.price < t.price""",
{"fromt": fromt, "to": to, "age": age_t, "minprofit": minprofit},
)
cur_f.execute(
"SELECT systemid,(systemname || ' / ') || regionname FROM systems,regions WHERE systems.regionid = regions.regionid AND systemid = %s ORDER BY systemname",
[fromt],
)
cur_t.execute(
"SELECT systemid,(systemname || ' / ') || regionname FROM systems,regions WHERE systems.regionid = regions.regionid AND systemid = %s ORDER BY systemname",
[to],
)
elif qtype == "Regions" and newsearch:
cur.execute(
"""SELECT types.typeid,types.typename,fs.systemid,ts.systemid,fs.stationname,ts.stationname,t.price - f.price AS pricediff,
min(t.volremain,f.volremain),
(t.price - f.price)*min(t.volremain,f.volremain) AS profit,
"""
+ sql_profit_size
+ """ AS profit_size,
"""
+ sql_profit_jumps
+ """ AS profit_jumps,
t.price,f.price, t.volremain, f.volremain
FROM types, current_market AS f, current_market AS t, stations AS fs, stations AS ts, systems AS fsys, systems AS tsys
WHERE
"""
+ sql_sec_limit
+ """
ts.systemid = tsys.systemid AND fs.systemid = fsys.systemid AND
f.minvolume <= 1 AND t.minvolume <= 1 AND
f.bid = 0 AND t.bid = 1 AND f.regionid = %(fromt)s AND t.regionid = %(to)s AND t.typeid = f.typeid AND t.stationid = ts.stationid AND
f.stationid = fs.stationid AND
age(f.reportedtime) < %(age)s AND age(t.reportedtime) < %(age)s AND
"""
+ sql_profit_size
+ """ >= %(minprofit)s AND
types.size <= """
+ size
+ """ AND
t.typeid = types.typeid
AND f.typeid = types.typeid
AND f.price < t.price""",
{"fromt": fromt, "to": to, "age": age_t, "minprofit": minprofit},
)
cur_f.execute("SELECT regionid,regionname FROM regions WHERE regionid = %s ORDER BY regionname", [fromt])
cur_t.execute("SELECT regionid,regionname FROM regions WHERE regionid = %s ORDER BY regionname", [to])
elif qtype == "SystemToRegion" and newsearch:
cur.execute(
"""SELECT types.typeid,types.typename,fs.systemid,ts.systemid,fs.stationname,ts.stationname,t.price - f.price AS pricediff,
min(t.volremain,f.volremain),
(t.price - f.price)*min(t.volremain,f.volremain) AS profit,
"""
+ sql_profit_size
+ """ AS profit_size,
"""
+ sql_profit_jumps
+ """ AS profit_jumps,
t.price,f.price, t.volremain, f.volremain
FROM types, current_market AS f, current_market AS t, stations AS fs, stations AS ts, systems AS fsys, systems AS tsys
WHERE
"""
+ sql_sec_limit
+ """
ts.systemid = tsys.systemid AND fs.systemid = fsys.systemid AND
f.minvolume <= 1 AND t.minvolume <= 1 AND
f.bid = 0 AND t.bid = 1 AND f.systemid = %(fromt)s AND t.regionid = %(to)s AND t.typeid = f.typeid AND t.stationid = ts.stationid AND
f.stationid = fs.stationid AND
age(f.reportedtime) < %(age)s AND age(t.reportedtime) < %(age)s AND
"""
+ sql_profit_size
+ """ >= %(minprofit)s AND
types.size <= """
+ size
+ """ AND
t.typeid = types.typeid
AND f.typeid = types.typeid
AND f.price < t.price""",
{"fromt": fromt, "to": to, "age": age_t, "minprofit": minprofit},
)
cur_f.execute(
"SELECT systemid,(systemname || ' / ') || regionname FROM systems,regions WHERE systems.regionid = regions.regionid AND systemid = %s ORDER BY systemname",
[fromt],
)
cur_t.execute("SELECT regionid,regionname FROM regions WHERE regionid = %s ORDER BY regionname", [to])
trades = []
time_net = 0.0
import __builtin__
from_set = __builtin__.set()
from_map = {}
from_to_map = {}
error_log = []
fromcache = 0
if newsearch:
r = cur.fetchone()
while r:
row = SorterDict("sortby")
row["typeid"] = r[0]
row["typename"] = r[1]
fr = int(r[2])
to2 = int(r[3])
row["fr"] = int(r[2])
row["to2"] = int(r[3])
row["fromstation"] = r[4]
row["tostation"] = r[5]
row["pricediff"] = format_price(r[6])
row["tradeable"] = format_long(r[7])
row["profit"] = format_price(r[8])
row["profit_num"] = float(r[8])
row["profit_size"] = float(r[9])
from_set.add(fr)
row["tprice"] = format_price(r[11])
row["fprice"] = format_price(r[12])
row["tvol"] = format_long(r[13])
row["fvol"] = format_long(r[14])
trades.append(row)
# Add to from_to_map - map source
if fr in from_to_map:
from_to_map[fr].add(row["to2"])
else:
from_to_map[fr] = __builtin__.set()
from_to_map[fr].add(row["to2"])
if fr in from_map:
from_map[fr].append(row)
else:
from_map[fr] = []
from_map[fr].append(row)
r = cur.fetchone()
# Now we try to compute distance
for compsys in from_set:
distance_map = {}
distance = 0
time_net_ = time.time()
for tosystem in from_to_map[compsys]:
load = urllib.urlopen(
"http://127.0.0.1:8081/api/distance/from/" + str(int(compsys)) + "/to/" + str(int(tosystem))
)
s = load.read()
load.close()
distance_map[tosystem] = json.loads(s)["distance"]
time_net += time.time() - time_net_
for row in from_map[compsys]:
if row["fr"] == compsys:
if compsys == row["to2"]:
distance = 0
else:
distance = distance_map[row["to2"]]
ps = row["profit_size"]
row["profit_size"] = format_price(ps)
if sort == "jprofit":
row["sortby"] = ps / (max(0, distance) + 1)
t.sort_nice = "Profit per jump"
elif sort == "sprofit":
row["sortby"] = ps
t.sort_nice = "Profit per trip"
elif sort == "profit":
row["sortby"] = row["profit_num"]
t.sort_nice = "Profit"
elif sort == "jumps":
t.sort_nice = "Distance"
row["sortby"] = distance
row.reverse = True
row["profit_jumps"] = format_price(ps / (1 + max(0, distance)))
row["distance"] = distance
time_sort = time.time()
trades.sort(reverse=True)
time_sort = time.time() - time_sort
# session['trade_results'] = trades
else:
trades = session["trade_results"]
fromcache = 1
trade_num = len(trades)
trades = trades[int(startat) : int(startat) + int(limit)]
t.fromcache = fromcache
t.num_trades = trade_num
t.trades = trades
t.fromt = fromt
t.to = to
t.qtype = qtype
t.age = age
t.minprofit = minprofit
t.size = size
t.startat = startat
t.limit = limit
t.sort = sort
t.prefer_sec = prefer_sec
t.fromname = cur_f.fetchone()[1]
t.toname = cur_t.fetchone()[1]
t.page = int((int(startat) + 1) / limit) + 1
t.next = int(startat) + limit
t.prev = max(0, int(startat) - limit)
db.close()
session.save()
return t.respond() + "Pathfinder time: %0.3fs, Sort time: %0.3fs, recompute set was %d elements long<br>" % (
time_net,
time_sort,
len(from_set),
)
def alphabet(self):
sigma = reduce(lambda a, b: set(a) | set(b),
[x.keys() for x in self.delta.values()])
return sigma
def clean_set(self):
sett = self.cleaned_data['set']
if not set(sett.types.all()).isdisjoint(self.service.output.types.all()):
raise ValidationError("input set must be disjoint from output set")
return sett
def __init__(self):
self.src, self.src_any = itree.Itree(), set()
self.dst, self.dst_any = itree.Itree(), set()
for k in self.__keys:
setattr(self, k, { None: set() })
def alphabet(self): sigma = reduce(lambda a,b:set(a) | set(b), [x.keys() for x in self.delta.values()]) return sigma
def __init__(self, delta, q0, F):
self.delta = delta
self.q0 = q0
self.F = set(F)
def states(self): d = set([self.q0]) | set(self.delta.keys()) | reduce(lambda a,b:a | b, reduce(lambda a,b:a + b, [x.values() for x in self.delta.values()])) return d
def states(self):
d = set([self.q0]) | set(self.delta.keys()) | reduce(
lambda a, b: a | b,
reduce(lambda a, b: a + b,
[x.values() for x in self.delta.values()]))
return d
def as_set(iterable):
return builtins.set(iterable)