def api_init_model_ready(project_id): # noqa: F401
"""Check if trained model is available
"""
error_path = get_project_path(project_id) / "error.json"
if error_path.exists():
print("error on training")
with open(error_path, "r") as f:
error_message = json.load(f)
return jsonify(error_message), 400
if get_proba_path(project_id).exists():
logging.info("Model trained - go to review screen")
# read the file with project info
with open(get_project_file_path(project_id), "r") as fp:
project_info = json.load(fp)
project_info["projectInitReady"] = True
# update the file with project info
with open(get_project_file_path(project_id), "w") as fp:
json.dump(project_info, fp)
response = jsonify({'status': 1})
else:
response = jsonify({'status': 0})
response.headers.add('Access-Control-Allow-Origin', '*')
return response
def api_init_model_ready(project_id): # noqa: F401
"""Check if trained model is available
"""
error_path = get_project_path(project_id) / "error.json"
if error_path.exists():
logging.error("error on training")
with open(error_path, "r") as f:
error_message = json.load(f)
return jsonify(message=error_message), 400
try:
if get_proba_path(project_id).exists():
# read the file with project info
with open(get_project_file_path(project_id), "r") as fp:
project_info = json.load(fp)
project_info["projectInitReady"] = True
# update the file with project info
with open(get_project_file_path(project_id), "w") as fp:
json.dump(project_info, fp)
response = jsonify({'status': 1})
else:
response = jsonify({'status': 0})
except Exception as err:
logging.error(err)
return jsonify(message="Failed to initiate the project."), 500
response.headers.add('Access-Control-Allow-Origin', '*')
return response
def read_proba(project_id):
proba_fp = get_proba_path(project_id)
try:
with open(proba_fp, "r") as f:
proba = json.load(f)
proba = [float(x) for x in proba]
except FileNotFoundError:
proba = None
return proba
def api_init_model_ready(project_id): # noqa: F401
"""Check if trained model is available
"""
if get_proba_path(project_id).exists():
logging.info("Model trained - go to review screen")
response = jsonify({'status': 1})
else:
response = jsonify({'status': 0})
response.headers.add('Access-Control-Allow-Origin', '*')
return response
def write_proba(project_id, proba):
# get the proba file path location
proba_fp = get_proba_path(project_id)
# validate object
if not isinstance(proba, pd.DataFrame):
raise ValueError("Expect pandas.DataFrame with proba values.")
if proba.index.name != "record_id":
raise ValueError("Expect index with name 'record_id'.")
# write the file to a csv file
proba.to_csv(proba_fp)
def read_proba(project_id):
proba_fp = get_proba_path(project_id)
try:
return pd.read_csv(proba_fp, index_col="record_id")
except FileNotFoundError:
# try to read the legacy file
try:
return read_proba_legacy(project_id)
except FileNotFoundError:
# no proba.csv or proba.json found.
pass
return None
def write_proba(project_id, proba):
proba_fp = get_proba_path(project_id)
with open(proba_fp, "w") as f:
json.dump(proba, f)
