def next(self):
while True:
if (self.e1 == None) and (self.e2 == None):
raise StopIteration()
# No more db1 events
if self.e1 == None:
diff = EventDiff(both=[], db1=None, db2=[self.e2])
self.e2 = __builtin__.next(self.events2, None)
return diff
# No more db2 events
if self.e2 == None:
diff = EventDiff(both=[], db1=[self.e1], db2=None)
self.e1 = __builtin__.next(self.events1, None)
return diff
# Collect all events for the lowest of two timestamps
if self.e2.timestamp >= self.e1.timestamp:
timestamp = self.e1.timestamp
else:
timestamp = self.e2.timestamp
el1 = []
el2 = []
while (self.e1 <> None) and (self.e1.timestamp == timestamp):
el1.append(self.e1)
self.e1 = __builtin__.next(self.events1, None)
while (self.e2 <> None) and (self.e2.timestamp == timestamp):
el2.append(self.e2)
self.e2 = __builtin__.next(self.events2, None)
diff = compare_event_lists(self.db1, self.db2, el1, el2)
diff.timestamp = timestamp
return diff
def __init__(self, db1, db2, events1, events2):
self.db1 = db1
self.db2 = db2
self.events1 = iter(events1)
self.events2 = iter(events2)
self.e1 = __builtin__.next(self.events1, None)
self.e2 = __builtin__.next(self.events2, None)
def parse_csv_file(self):
with open(self.file_path, "rb", 1) as csv_file:
dialect = csv.Sniffer().sniff(csv_file.read(1024))
has_header = csv.Sniffer().has_header(csv_file.read(1024))
csv_file.seek(0)
if not has_header:
raise Exception('Not a correct CSV file')
csv_data = csv.reader(csv_file, dialect)
company_names = next(csv_data)[2:] # Extract the Companies name
for name in company_names:
self.output[name] = {'price': 0, 'year': 'year', 'month': 'month'}
for row in csv_data:
year, month = row[:2]
for name, price in zip(company_names, map(int, row[2:])):
if self.output[name]['price'] < price:
self.output[name] = {'price':price, 'year': year, 'month': month}
self.result = '\nCompany name\tYear\tMonth\tMax Price\n\n'
for company_name , analysis_dict in self.output.items():
self.result += '%s\t%s\t%s\t%d\n' % (company_name, analysis_dict['year'], analysis_dict['month'], analysis_dict['price'])
def parse_csv_file(self):
with open(self.file_path, "rb", 1) as csv_file:
dialect = csv.Sniffer().sniff(csv_file.read(1024))
has_header = csv.Sniffer().has_header(csv_file.read(1024))
csv_file.seek(0)
if not has_header:
raise Exception('Not a correct CSV file')
csv_data = csv.reader(csv_file, dialect)
company_names = next(csv_data)[2:] # Extract the Companies name
for name in company_names:
self.output[name] = {
'price': 0,
'year': 'year',
'month': 'month'
}
for row in csv_data:
year, month = row[:2]
for name, price in zip(company_names, map(int, row[2:])):
if self.output[name]['price'] < price:
self.output[name] = {
'price': price,
'year': year,
'month': month
}
self.result = '\nCompany name\tYear\tMonth\tMax Price\n\n'
for company_name, analysis_dict in self.output.items():
self.result += '%s\t%s\t%s\t%d\n' % (
company_name, analysis_dict['year'],
analysis_dict['month'], analysis_dict['price'])
def first(iterable):
try:
return builtins.next(iter(iterable))
except StopIteration:
return None
def next(self):
return __builtin__.next(self.iter)