def index(path):
"""
Wildcard view api to allow access to a specified page if the
page exists
Args:
path (str): path to different html
Returns:
view: flask view for the requested HTML
"""
if not current_user.is_authenticated:
print('not logged in')
return redirect(url_for('login'))
content = None
data = None
data = Project.from_user(current_user.user_id)
print(data)
try:
# try to match the pages defined in -> pages/<input file>
return render_template('pages/' + path, data=data)
except:
return "404 Not Found"
def predictions_dashboard(project_id):
if not current_user.is_authenticated:
print('not logged in')
return redirect(url_for('login'))
content = None
data = None
model_info = None
data = Project.from_user(current_user.user_id)
if Project.check_auth(current_user.user_id, int(project_id)):
project_specific_data = Project.get_one(current_user.user_id,
int(project_id))
if project_specific_data[0]['model_available']:
model_info = Database.find_one(
collection="models",
query={"project_id": project_specific_data[0]['project_id']})
print(model_info)
try:
# try to match the pages defined in -> pages/<input file>
return render_template('pages/prediction_dashboard.html',
data=data,
project_specific_data=project_specific_data,
model_info=model_info)
except:
return render_template('pages/error-404.html')
def start_train(project_id):
if not current_user.is_authenticated:
print('not logged in')
return redirect(url_for('login'))
content = None
data = None
data = Project.from_user(current_user.user_id)
project_specific_data = []
html = None
titles = None
if Project.check_auth(current_user.user_id, int(project_id)):
project_specific_data = Project.get_one(current_user.user_id,
int(project_id))
if project_specific_data[0]['model_available']:
return jsonify(result='trained')
q.enqueue(DLModel.train_model,
project_specific_data[0]['dataset'][0]['name'],
int(project_id), app.config['UPLOAD_FOLDER'])
Database.update_one(collection='projects',
query=[{
'project_id': int(project_id)
}, {
"$set": {
"in_training": True
}
}])
return jsonify(result='done')
else:
return jsonify(result='error')
def explore_data(project_id, dataset_id):
if not current_user.is_authenticated:
print('not logged in')
return redirect(url_for('login'))
content = None
data = None
data = Project.from_user(current_user.user_id)
if Project.check_auth(current_user.user_id, int(project_id)):
project_specific_data = Project.get_one(current_user.user_id,
int(project_id))
table_data, titles, numerical_vals = Analysis.get_coloums_stat(
app.config['UPLOAD_FOLDER'] + 'dataset/' + dataset_id)
try:
# try to match the pages defined in -> pages/<input file>
return render_template('pages/explore_data.html',
data=data,
project_specific_data=project_specific_data,
numerical_vals=numerical_vals,
table_data=table_data,
titles=titles,
active_dataset=dataset_id)
except:
return render_template('pages/error-404.html')
def start_train(project_id):
"""
STRICT API To allow ADMIN user to force sart training for the Deep Leanring Model
Allows an ADMIN user to start traning the user Deep LEarning model
customer's activities. \n\n
API/URL must be accessed with GET request and supply project_id the URL\n
method: GET\n
Args:
project_id (str): ID of the poject/Customer need to be sent in url. It is made to do so via Front end href
Returns:
response: JSON object
On Success \n
response = {
'result': 'done'
}
\n
On Fail:\n
response = {
'result': 'error'
}
\n
"""
if not current_user.is_authenticated:
print('not logged in')
return redirect(url_for('login'))
content = None
data = None
data = Project.from_user(current_user.user_id)
project_specific_data = []
html = None
titles = None
if Project.check_auth(current_user.user_id, int(project_id)):
project_specific_data = Project.get_one(current_user.user_id,
int(project_id))
if project_specific_data[0]['model_available']:
return jsonify(result='trained')
q.enqueue(DLModel.train_model,
project_specific_data[0]['dataset'][0]['name'],
int(project_id), app.config['UPLOAD_FOLDER'])
Database.update_one(collection='projects',
query=[{
'project_id': int(project_id)
}, {
"$set": {
"in_training": True
}
}])
return jsonify(result='done')
else:
return jsonify(result='error')
def project_dashboard(project_id):
"""
Admin Dashboard \n
ALlows ADMIN to access project/CUSTOMER user
ALlows ADMIN to access project/CUSTOMER user dashboard
with all the admin tools to vefiy user pipeline
this allows admin to oversee if the user data is present or not
Allow to see the status of user Deep Learning model.\n\n
method: GET\n
API/URL must be accessed with GET request and supply project_id in the URL\n
Args:
project_id (str): ID of the poject need to be sent in url. It is made to do so via Front end href
Returns:
view: a url VIEW the project's/CUSTOMER's required params such as
Dataset, dataset voliation if present, Deep leanring model status,
Deep learning model metrics, predication metreics. OR if the user is
not logged in or CUSTOMER user does not exists then 404 redirect
"""
if not current_user.is_authenticated:
print('not logged in')
return redirect(url_for('login'))
content = None
data = None
data = Project.from_user(current_user.user_id)
project_specific_data = []
html = None
titles = None
model_info = None
if Project.check_auth(current_user.user_id, int(project_id)):
project_specific_data = Project.get_one(current_user.user_id,
int(project_id))
print(project_specific_data)
if project_specific_data[0]['model_available']:
model_info = Database.find_one(
collection="models",
query={"project_id": project_specific_data[0]['project_id']})
print(model_info)
try:
# try to match the pages defined in -> pages/<input file>
return render_template('pages/project_dashboard.html',
data=data,
project_specific_data=project_specific_data,
model_info=model_info)
except:
return render_template('pages/error-404.html')
def create_project():
if not current_user.is_authenticated:
print('not logged in')
return redirect(url_for('login'))
data = Project.from_user(current_user.user_id)
all_data = []
html = None
project_id = None
titles = None
if request.method == 'POST':
f_1 = request.files['file_1']
f_2 = request.files['file_2']
filename_one = str(uuid.uuid4())[:8] + "." + f_1.filename.rsplit(
'.', 1)[1].lower()
if not f_2:
f_2 = f_1
filename_two = str(uuid.uuid4())[:8] + "." + f_2.filename.rsplit(
'.', 1)[1].lower()
f_1.save(app.config['UPLOAD_FOLDER'] + "dataset/" +
secure_filename(filename_one))
f_2.save(app.config['UPLOAD_FOLDER'] + "dataset/" +
secure_filename(filename_two))
dataset = [{
'name': filename_one,
'type': 'Forecasting Timeseries Data',
'file_attributes': [0, 0],
'datasetID': filename_one,
'status': 'Active'
}, {
'name': filename_two,
'type': 'Item Attributes',
'file_attributes': [0, 0],
'datasetID': filename_two,
'status': 'Active'
}]
pname = request.form['pname']
ptype = request.form['ptype']
user_id = current_user.user_id
project_id = int(str(uuid.uuid4().int)[:6])
date = str(datetime.datetime.utcnow())
#project_id, user_id, pname, ptype, dataset, date
new_project = Project(project_id, user_id, pname, ptype, dataset, date)
new_project.save_to_mongo()
return redirect(url_for('project_dashboard', project_id=project_id))
def predictions_dashboard(project_id):
"""
Predictions Dashboard \n
To allow ADMIN user see all necessary metrics for the project/CUSTOMER user
Allows an ADMIN user visualize the Deep Learning model's performance, along side
customer's activities.\n\n
method: GET\n
API/URL must be accessed with GET request and supply project_id in the URL\n
Args:
project_id (str): ID of the poject need to be sent in url. It is made to do so via Front end href
Returns:
view: a url VIEW the project's/CUSTOMER's all required prediction values and visulization data
give user login status. If project CUSTOMER not found then redirect 404.
"""
if not current_user.is_authenticated:
print('not logged in')
return redirect(url_for('login'))
content = None
data = None
model_info = None
data = Project.from_user(current_user.user_id)
if Project.check_auth(current_user.user_id, int(project_id)):
project_specific_data = Project.get_one(current_user.user_id,
int(project_id))
if project_specific_data[0]['model_available']:
model_info = Database.find_one(
collection="models",
query={"project_id": project_specific_data[0]['project_id']})
print(model_info)
try:
# try to match the pages defined in -> pages/<input file>
return render_template('pages/prediction_dashboard.html',
data=data,
project_specific_data=project_specific_data,
model_info=model_info)
except:
return render_template('pages/error-404.html')
def dataset_raw_data(project_id, dataset_id):
"""
RAW Data exploaration\n
Allows an ADMIN user to explore user dataset
through its dashboard and see all the raw not pruned data
user login status. If dataset not found then redirect 404.\n\n
method: GET\n
API/URL must be accessed with GET request and supply project_id and dataset_id in the URL\n
Args:
project_id (str): ID of the poject need to be sent in url. It is made to do so via Front end href
dataset_id (str): ID of the dataset need to be sent in url. It is made to do so via Frontend href
Returns:
view: A flask view for the raw data html
"""
if not current_user.is_authenticated:
print('not logged in')
return redirect(url_for('login'))
content = None
data = None
data = Project.from_user(current_user.user_id)
if Project.check_auth(current_user.user_id, int(project_id)):
project_specific_data = Project.get_one(current_user.user_id,
int(project_id))
print(project_specific_data)
table_html, titles = Analysis.get_data_head(app.config['UPLOAD_FOLDER'] +
'dataset/' + dataset_id)
try:
# try to match the pages defined in -> pages/<input file>
return render_template('pages/raw_data.html',
data=data,
project_specific_data=project_specific_data,
tables=table_html,
titles=titles,
active_dataset=dataset_id)
except:
return render_template('pages/error-404.html')
def index(path):
if not current_user.is_authenticated:
print('not logged in')
return redirect(url_for('login'))
content = None
data = None
data = Project.from_user(current_user.user_id)
print(data)
try:
# try to match the pages defined in -> pages/<input file>
return render_template('pages/' + path, data=data)
except:
return "404 Not Found"
def dataset_schema(project_id):
if not current_user.is_authenticated:
print('not logged in')
return redirect(url_for('login'))
content = None
data = None
data = Project.from_user(current_user.user_id)
if Project.check_auth(current_user.user_id, int(project_id)):
project_specific_data = Project.get_one(current_user.user_id, int(project_id))
print(project_specific_data)
try:
# try to match the pages defined in -> pages/<input file>
return render_template( 'pages/dataset_schema.html', data=data, project_specific_data=project_specific_data)
except:
return render_template( 'pages/error-404.html' )
def customer_dashboard(project_id):
if not current_user.is_authenticated:
print('not logged in')
return redirect(url_for('login'))
content = None
data = None
data = Project.from_user(current_user.user_id)
project_specific_data = []
html = None
titles = None
model_info = None
if Project.check_auth(current_user.user_id, int(project_id)):
project_specific_data = Project.get_one(current_user.user_id,
int(project_id))
print(project_specific_data)
if project_specific_data[0]['model_available']:
model_info = Database.find_one(
collection="models",
query={"project_id": project_specific_data[0]['project_id']})
print(model_info)
try:
# try to match the pages defined in -> pages/<input file>
responseObject = {
"data": data,
"project_specific_data": project_specific_data,
"model_info": model_info
}
return make_response(jsonify(responseObject)), 201
except:
responseObject = {
'status': 'fail',
'message': 'Some error occurred with database. Please try again.'
}
return make_response(jsonify(responseObject)), 201
def create_project_sample():
if not current_user.is_authenticated:
print('not logged in')
return redirect(url_for('login'))
data = Project.from_user(current_user.user_id)
if request.method == 'POST':
dataset = [
{
'name': 'sample.csv',
'type': 'Forecasting Timeseries Data',
'file_attributes': [0, 0],
'datasetID': 'sample.csv',
'status': 'Active'
},
{
'name': 'sample.csv',
'type': 'Item Attributes',
'file_attributes': [0, 0],
'datasetID': 'sample1.csv',
'status': 'Active'
},
]
pname = "Sample Project"
#if pname is None or len(pname) == 0:
# pname = "Sample"
ptype = request.form['ptype']
user_id = current_user.user_id
project_id = int(str(uuid.uuid4().int)[:6])
date = str(datetime.datetime.utcnow())
#project_id, user_id, pname, ptype, dataset, date
new_project = Project(project_id, user_id, pname, ptype, dataset, date)
new_project.save_to_mongo()
return redirect(url_for('project_dashboard', project_id=project_id))
def dataset_schema(project_id):
"""
Data Schema mapping\n
To allow ADMIN user to set data schema for AUTOML
Allows an ADMIN user to change/set data schema for AUTOML\n\n
method: GET\n
API/URL must be accessed with GET request and supply project_id in the URL\n
Args:
project_id (str): ID of the poject need to be sent in url. It is made to do so via Front end href
Returns:
view: a url VIEW the project's data schema mapping after verfying
user login status. If project not found then redirect 404.
"""
if not current_user.is_authenticated:
print('not logged in')
return redirect(url_for('login'))
content = None
data = None
data = Project.from_user(current_user.user_id)
if Project.check_auth(current_user.user_id, int(project_id)):
project_specific_data = Project.get_one(current_user.user_id,
int(project_id))
print(project_specific_data)
try:
# try to match the pages defined in -> pages/<input file>
return render_template('pages/dataset_schema.html',
data=data,
project_specific_data=project_specific_data)
except:
return render_template('pages/error-404.html')
def customer_dashboard(project_id):
"""
STRICT api for mobile team and customer web Ui team to use
Retunrs all CUSTOEMR deeplearning model satas. Data set for the CUSTOMER USER
if any error occurs then JSON will contain error message. \n\n
API/URL must be accessed with GET request and supply project_id the URL\n
method: GET\n
Args:
project_id (str): ID of the poject/Customer need to be sent in url. It is made to do so via Front end href
Returns:
response: JSON object
On Success \n
response = {
"data":data,
"project_specific_data":project_specific_data,
"model_info":model_info
}
\n
On Fail:\n
response = {
'status': 'fail',
'message': 'Some error occurred with database. Please try again.'
}
\n
"""
if not current_user.is_authenticated:
print('not logged in')
return redirect(url_for('login'))
content = None
data = None
data = Project.from_user(current_user.user_id)
project_specific_data = []
html = None
titles = None
model_info = None
if Project.check_auth(current_user.user_id, int(project_id)):
project_specific_data = Project.get_one(current_user.user_id,
int(project_id))
print(project_specific_data)
if project_specific_data[0]['model_available']:
model_info = Database.find_one(
collection="models",
query={"project_id": project_specific_data[0]['project_id']})
print(model_info)
try:
# try to match the pages defined in -> pages/<input file>
responseObject = {
"data": data,
"project_specific_data": project_specific_data,
"model_info": model_info
}
return make_response(jsonify(responseObject)), 201
except:
responseObject = {
'status': 'fail',
'message': 'Some error occurred with database. Please try again.'
}
return make_response(jsonify(responseObject)), 201
def create_project():
"""
Create customer user via ADMIN dashboard
Allows an ADMIN user to create customer
through its dashboard and set all DATA required
MANUALLY. It created the user and saves all the files
required in necessary order.\n\n
method: POST\n
POST: API usage, acts a api to craete customer user\n
params should be in a FLASK FORM json format (Form data).\n\n
Args:
form_data: data retrived from Flask form from the frontend
file_1: Data set for the user specifying feature file needed to for time series forecasting
file_2: optional file for attributes
Returns:
redirect: url for the newely creadted user or redirects to root.
form_data = {
'name': type=str
'lname': type=str)
'gender': type=str
'phone': type=str
'address': type=str
'city': type=str
'zipcode': type=str
'state': type=str
'username': type=str
'password': type=str
'email': type=str
}
file_1 = file upload from CSV
file_2 = file upload from CSV optional
"""
if not current_user.is_authenticated:
print('not logged in')
return redirect(url_for('login'))
data = Project.from_user(current_user.user_id)
all_data = []
html = None
project_id = None
titles = None
if request.method == 'POST':
f_1 = request.files['file_1']
f_2 = request.files['file_2']
filename_one = str(uuid.uuid4())[:8] + "." + f_1.filename.rsplit(
'.', 1)[1].lower()
if not f_2:
f_2 = f_1
filename_two = str(uuid.uuid4())[:8] + "." + f_2.filename.rsplit(
'.', 1)[1].lower()
f_1.save(app.config['UPLOAD_FOLDER'] + "dataset/" +
secure_filename(filename_one))
f_2.save(app.config['UPLOAD_FOLDER'] + "dataset/" +
secure_filename(filename_two))
dataset = [{
'name': filename_one,
'type': 'Forecasting Timeseries Data',
'file_attributes': [0, 0],
'datasetID': filename_one,
'status': 'Active'
}, {
'name': filename_two,
'type': 'Item Attributes',
'file_attributes': [0, 0],
'datasetID': filename_two,
'status': 'Active'
}]
pname = request.form['pname']
ptype = request.form['ptype']
user_id = current_user.user_id
project_id = int(str(uuid.uuid4().int)[:6])
date = str(datetime.datetime.utcnow())
#project_id, user_id, pname, ptype, dataset, date
new_project = Project(project_id, user_id, pname, ptype, dataset, date)
new_project.save_to_mongo()
return redirect(url_for('project_dashboard', project_id=project_id))