def create_vocab(filename):
vocab_path = get_dir_cfg()['vocab_path']
filename = local_dir + vocab_path + filename + ".txt"
head, tail = os.path.split(filename)
logger.info('get from aws ' + tail)
# need to load the file from aws potentially
# get_aws_file(vocab_path, tail)
return filename
import logging
import os
import os.path
from service.config_service import get_dir_cfg
from util.file_utils import get_aws_file
logger = logging.getLogger(__name__)
local_dir = get_dir_cfg()['local']
TEAMS_FILE = 'team-vocab'
def create_vocab(filename, country):
vocab_path = get_dir_cfg()['vocab_path']
vocab_path = vocab_path.replace('<key>', country)
filename = local_dir + vocab_path + filename + ".txt"
head, tail = os.path.split(filename)
logger.info('get from aws ' + tail)
# need to load the file from aws potentially
get_aws_file(vocab_path, tail)
return filename
import predict.player_assists_prediction as player_assists_prediction
import predict.player_goals_prediction as player_goals_prediction
import predict.player_yellow_card_prediction as player_yellow_card_prediction
import threading
import traceback
import train.player_assists_train as player_assists_train
import train.player_goals_train as player_goals_train
import train.player_yellow_card_train as player_yellow_card_train
import util.classifier_utils as classifier_utils
from flask import Flask
from flask import request
from service.config_service import get_dir_cfg
app = Flask(__name__)
logging.basicConfig(filename=get_dir_cfg()['local'] + 'predictor.log',
level=logging.NOTSET)
logger = logging.getLogger(__name__)
local_dir = get_dir_cfg()['local']
if __name__ == "__main__":
app.run(host='0.0.0.0')
def set_init(init):
if init == 'true':
return True
else:
return False
import boto3
import csv
import logging
import os
import os.path
import time
from botocore.exceptions import ClientError
from service.config_service import get_dir_cfg
from service.index_service import process_index, read_index
logger = logging.getLogger(__name__)
s3_client = boto3.client('s3')
aws = get_dir_cfg()['aws']
aws_url = get_dir_cfg()['aws_url']
aws_bucket = get_dir_cfg()['aws_bucket']
local_dir = get_dir_cfg()['local']
def on_finish(tf_models_dir, aws_model_dir):
logger.info(' write index ' + tf_models_dir)
write_filenames_index(tf_models_dir)
try:
write_filenames_index(tf_models_dir + '/eval')
except Exception as e:
logger.info('eval dir not created')
logger.info(' put aws files ' + aws_model_dir)
def create_train_path():
train_path = get_dir_cfg()['train_path']
return train_path
import json
import logging
import predict.match_goals_prediction as match_goals_prediction
import predict.match_result_prediction as match_result_prediction
import threading
import traceback
import train.match_goals_train as match_goals_train
import train.match_result_train as match_result_train
from flask import Flask
from flask import request
from service.config_service import get_dir_cfg
app = Flask(__name__)
logging.basicConfig(filename=get_dir_cfg()['local'] + 'predictor.log', level=logging.NOTSET)
logger = logging.getLogger(__name__)
if __name__ == "__main__":
app.run(host='0.0.0.0')
# doesnt seem to do anything, should catch interrupted tho.
def process(thread):
try:
thread.start()
except Exception as e:
logger.error(traceback.format_exc())
# should handle errors at some point
def done_response():
def create_train_path(country):
train_path = get_dir_cfg()['train_path']
train_path = train_path.replace('<key>', country)
return train_path
