def run_model(model_id, input_dict, output_names):
"""
Load the model, set the inputs and return the calculated outputs
TODO get this working roughly following these steps
- Get serialised model from S3
- Load model with koala
- Extract inputs from payload
- Set the inputs in the model
- Extract required outputs from payload (all outputs if none specifically requested)
- Get the required outputs from the model
- Build and return response
"""
# see if compiled model compiled
try:
compliled_string = bucket.Object(
'compiled_models/{}'.format(model_id)).get()['Body'].read()
except botocore.exceptions.ClientError as err:
return err.response['Error']['Code']
# XXX HACK Workaround needed for koala spreadsheet loading API
# - need to write the file to a temp location for koala to read it...
# - FIX: update koala.Spreadsheet / koala.serialize to take the file contents in directly
if not os.path.exists('/tmp'):
os.mkdir('/tmp')
dummy_file_name = '/tmp/temp_{}.gzip'.format(model_id)
with open(dummy_file_name, 'wb') as f:
f.write(compliled_string)
sheet = Spreadsheet.load(dummy_file_name)
for name, value in input_dict.iteritems():
sheet.set_value(name, value)
results = {}
for name in output_names:
output_value = sheet.evaluate(name)
if isinstance(output_value, ExcelError):
output_value = str(output_value)
results[name] = output_value
# Cleanup previous workaround
os.remove(dummy_file_name)
if not os.listdir('/tmp'):
os.rmdir('/tmp')
return results
from koala.ExcelCompiler import ExcelCompiler
from koala.Spreadsheet import Spreadsheet
filename = "./examples/basic.xlsx"
print(filename)
### Graph Generation ###
c = ExcelCompiler(filename)
sp = c.gen_graph()
## Graph Serialization ###
print("Serializing to disk...")
sp.dump(filename.replace("xlsx", "gzip"))
### Graph Loading ###
print("Reading from disk...")
sp = Spreadsheet.load(filename.replace("xlsx", "gzip"))
### Graph Evaluation ###
sp.set_value('Sheet1!A1', 10)
print('New D1 value: %s' % str(sp.evaluate('Sheet1!D1')))
from koala.ExcelCompiler import ExcelCompiler
from koala.Spreadsheet import Spreadsheet
file = "./examples/basic.xlsx"
print file
### Graph Generation ###
c = ExcelCompiler(file)
sp = c.gen_graph()
## Graph Serialization ###
print "Serializing to disk..."
sp.dump(file.replace("xlsx", "gzip"))
### Graph Loading ###
print "Reading from disk..."
sp = Spreadsheet.load(file.replace("xlsx", "gzip"))
### Graph Evaluation ###
sp.set_value('Sheet1!A1', 10)
print 'New D1 value: %s' % str(sp.evaluate('Sheet1!D1'))