def validate(prices):
raw = DataEngine.getData(prices).strip()
raw = csv.reader(io.StringIO(raw))
data = {}
for row in raw:
if len(row) == 0:
continue
elif len(row) > 2 or len(row) == 1:
raise DataEngineException('Rows must have exactly 2 columns')
elif len(row) == 2:
try:
data[row[0].strip()] = [float(row[1])] + [None] * 7
except:
raise DataEngineException(
'The first column must be a string, the second column must be a number'
)
elif len(row) == 8:
try:
data[row[0].strip()] = []
for item in row[1:]:
if item == None:
data[row[0].strip()].append(item)
else:
data[row[0].strip()].append(float(item))
except:
raise DataEngineException(
'The first column must be a string, the other 8 columns must be numbers'
)
else:
raise DataEngineException(
'Prices for goods must either be in a single currency or have 8 currencies defined'
)
return data
def validate(prices):
raw = DataEngine.getData(prices).strip()
raw = csv.reader(io.StringIO(raw))
data = {}
for row in raw:
if len(row) == 0:
continue
elif len(row) > 2 or len(row) == 1:
raise DataEngineException('Rows must have exactly 2 columns')
elif len(row) == 2:
try:
data[row[0].strip()] = [float(row[1])]+[None]*7
except:
raise DataEngineException('The first column must be a string, the second column must be a number')
elif len(row) == 8:
try:
data[row[0].strip()] = []
for item in row[1:]:
if item == None:
data[row[0].strip()].append(item)
else:
data[row[0].strip()].append(float(item))
except:
raise DataEngineException('The first column must be a string, the other 8 columns must be numbers')
else:
raise DataEngineException('Prices for goods must either be in a single currency or have 8 currencies defined')
return data
def validate(prices):
raw = DataEngine.getData(prices).strip()
try:
data = json.loads(raw)
except:
raise DataEngineException('JSON data failed to be parsed')
if 'prices' not in data:
raise DataEngineException('Sim data must have prices key')
if 'metric' not in data:
raise DataEngineException('Sim data must have metric key')
if type(data['metric']) != int:
raise DataEngineException('Metric must be an integer between 0 and 31')
for k in data['prices']:
if type(k) != str:
raise DataEngineException('Keys must be strings')
if type(data['prices'][k]) not in (int, list, float):
raise DataEngineException('Values must be arrays or numbers')
if type(data['prices'][k]) == list:
if len(data['prices'][k]) != 8:
raise DataEngineException('Array values must have exactly 8 elements')
if any(map(lambda i: type(i) not in [int, float, type(None)], data['prices'][k])):
raise DataEngineException('Array values must be all numbers or null')
return data
def validate(prices):
raw = DataEngine.getData(prices).strip()
raw = csv.reader(io.StringIO(raw))
rows = list(raw)
if len(rows) < 2:
raise DataEngineException('Must contain at least two rows')
if len(rows[0]) < 2:
raise DataEngineException('Must contain at least two columns')
try:
metric = rows[0][0]
if 'metricString' in metric:
metric = int(metric[12:])-1
elif 'metricNumber' in metric:
metric = int(metric[12:])+8-1
elif metric.lower().strip() == 'country':
metric = metric.lower().strip()
else:
assert(False)
assert((type(metric)==int and metric<32 and metric>-1) or (metric=='country'))
except:
raise DataEngineException('Metric name not valid/recognized')
if type(metric) == int:
if metric<8:
progress = list(map(lambda p: p.strip().lower(), rows[0][1:]))
else:
try:
progress = []
for p in rows[0][1:]:
if p.strip().lower() == 'default':
progress.append('default')
else:
progress.append(float(p))
except:
raise DataEngineException('Numberic progress metric must have numeric progress values for the columns')
elif type(metric) == str:
progress = list(map(lambda p: p.strip().lower(), rows[0][1:]))
data = dict(map(lambda p: (p, {}), progress))
if any(map(lambda p: p.lower() == 'default', progress)) == False:
raise DataEngineException('Missing default pricing column')
for row in rows[1:]:
# Remove trailing spaces
row = list(map(lambda r: r.strip(), row))
if len(row) != len(row[0]):
raise DataEngineException('All rows must contain the same number of elements')
for i, value in enumerate(row[1:]):
try:
data[progress[i]][row[0]] = [float(value)] + [None]*7
except:
raise DataEngineException('The first column must be a tring, all other columns must be good prices encoded as numbers')
return {'metric':metric, 'data':data}
def validate(prices):
raw = DataEngine.getData(prices).strip()
try:
data = json.loads(raw)
except:
raise DataEngineException('JSON data failed to be parsed')
return data
def validate(prices):
raw = DataEngine.getData(prices).strip()
try:
data = json.loads(raw)
except:
raise DataEngineException('JSON data failed to be parsed')
return data
def validate(prices):
raw = DataEngine.getData(prices).strip()
try:
data = json.loads(raw)
except:
raise DataEngineException('JSON data failed to be parsed')
for k in data:
if type(k) != str:
raise DataEngineException('Keys must be strings')
if type(data[k]) not in (int, list, float):
raise DataEngineException('Values must be arrays or numbers')
if type(data[k]) == list:
if len(data[k]) != 8:
raise DataEngineException('Array values must have exactly 8 elements')
if any(map(lambda i: type(i) not in [int, float, type(None)], data[k])):
raise DataEngineException('Array values must be all numbers or null')
return data
def validate(prices):
raw = DataEngine.getData(prices).strip()
raw = csv.reader(io.StringIO(raw))
rows = list(raw)
if len(rows) < 2:
raise DataEngineException('Must contain at least two rows')
if len(rows[0]) < 2:
raise DataEngineException('Must contain at least two columns')
try:
metric = rows[0][0]
if 'metricString' in metric:
metric = int(metric[12:]) - 1
elif 'metricNumber' in metric:
metric = int(metric[12:]) + 8 - 1
elif metric.lower().strip() == 'country':
metric = metric.lower().strip()
else:
assert (False)
assert ((type(metric) == int and metric < 32 and metric > -1)
or (metric == 'country'))
except:
raise DataEngineException('Metric name not valid/recognized')
if type(metric) == int:
if metric < 8:
progress = list(map(lambda p: p.strip().lower(), rows[0][1:]))
else:
try:
progress = []
for p in rows[0][1:]:
if p.strip().lower() == 'default':
progress.append('default')
else:
progress.append(float(p))
except:
raise DataEngineException(
'Numberic progress metric must have numeric progress values for the columns'
)
elif type(metric) == str:
progress = list(map(lambda p: p.strip().lower(), rows[0][1:]))
data = dict(map(lambda p: (p, {}), progress))
if any(map(lambda p: p.lower() == 'default', progress)) == False:
raise DataEngineException('Missing default pricing column')
for row in rows[1:]:
# Remove trailing spaces
row = list(map(lambda r: r.strip(), row))
if len(row) != len(row[0]):
raise DataEngineException(
'All rows must contain the same number of elements')
for i, value in enumerate(row[1:]):
try:
data[progress[i]][row[0]] = [float(value)] + [None] * 7
except:
raise DataEngineException(
'The first column must be a tring, all other columns must be good prices encoded as numbers'
)
return {'metric': metric, 'data': data}