def predict():
"""
basic predict function for the API
"""
## input checking
if not request.json:
print("ERROR: API (predict): did not receive request data")
return jsonify([])
if 'country' not in request.json:
print(
"ERROR API (predict): received request, but no 'country' found within"
)
return jsonify([])
## set the test flag
test = False
if 'mode' in request.json and request.json['mode'] == 'test':
test = True
## extract the query parameters
country = request.json['country']
year = request.json['year']
month = request.json['month']
day = request.json['day']
## load model
data_dir = os.path.join("data", "cs-train")
all_data, all_models = model_load(data_dir=data_dir)
model = all_models[country]
if not model:
print("ERROR: model is not available")
return jsonify([])
_result = model_predict(country, year, month, day, test=test)
result = {}
## convert numpy objects to ensure they are serializable
for key, item in _result.items():
if isinstance(item, np.ndarray):
result[key] = item.tolist()
else:
result[key] = item
return (jsonify(result))
def train():
"""
basic predict function for the API
the 'mode' give you the ability to toggle between a test version and a production verion of training
"""
test = False
if 'mode' in request.json:
if request.json['mode'] == 'test':
test = True
print("... training model")
data_dir = os.path.join(THIS_DIR, "data", "cs-train")
try:
model_train(data_dir, test=test)
print("... training complete")
# reload models and data after re-train
print("... reloading models in cache")
global_data, global_models = model_load(training=False)
return (jsonify(True))
except Exception as e:
print("ERROR API (train): model_train returned: {}".format(str(e)))
return jsonify([]), 400
import socketserver, sys
from pprint import pprint
import json
from utils import option
from utils.convert import convert_File
from model.model import model_load
opt = option.Options()
IP = opt.host_ip
PORT = int(opt.host_port)
py2java_path = opt.py2java_path
model = model_load()
class SingleTCPHandler(socketserver.BaseRequestHandler):
"One instance per connection. Override handle(self) to customize action."
def handle(self):
# self.request is the client connection
data = self.request.recv(1024) # clip input at 1Kb
text = data.decode('utf-8')
# pprint(json.loads(text))
inObj = json.loads(text)
# input check
pprint(inObj)
isSuccess = False
output_path = ""
try:
def startup():
global global_data, global_models
print(".. loading models")
global_data, global_models = model_load(training=False)
print(".. all models loaded")
return redirect(url_for('landing'))