merge pull request #11 from mukeshmk/ui

WIP: restructured the application and added UI

app.py

@@ -1,11 +1,11 @@
-import os
-from config import *
-from constants import *
-from flask import Flask, request, jsonify
+from flask import Flask, render_template
 from flask_sqlalchemy import SQLAlchemy
 from flask_marshmallow import Marshmallow
 
-app = Flask(__name__)
+from src.config import *
+from src.utils.constants import METRIC
+
+app = Flask(__name__, template_folder='src/templates', static_folder='src/static')
 
 if ENV == 'dev':
     app.debug = True
@@ -21,112 +21,21 @@
 # Init ma
 ma = Marshmallow(app)
 
-from data_models.Metrics import *
-from data_models.Params import *
-from data_models.MetaFeatures import *
-
-# Create a Metric
-@app.route(METRIC, methods=[POST])
-def add_metric():
-    algorithm_name = request.json['algorithm_name']
-    dataset_hash = request.json['dataset_hash'].replace("\x00", "")
-    metric_name = request.json['metric_name']
-    metric_value = request.json['metric_value']
-
-    target_type = request.json['target_type']
-
-    new_metric = Metric(algorithm_name, dataset_hash, metric_name, metric_value, target_type)
-
-    db.session.add(new_metric)
-    db.session.commit()
-
-    params = request.json['params']
-    if(params != ""):
-        for param in params:
-            new_params = Params(new_metric.id, param['param_name'], param['param_value'])
-            db.session.add(new_params)
-    db.session.commit()
-
-    data_meta_features = request.json['data_meta_features']
-    if(data_meta_features != ""):
-        for feat in data_meta_features:
-            new_feat = MetaFeature(new_metric.id, feat['feat_name'], feat['feat_value'])
-            db.session.add(new_feat)
-    db.session.commit()
-
-    return metric_schema.jsonify(new_metric)
-
-
-
-# Get All Metrics
-@app.route(METRIC, methods=[GET])
-def get_metrics():
-    all_metrics = Metric.query.all()
-    result = metrics_schema.dump(all_metrics)
-    if len(result) > 0:
-        return jsonify(result)
-    else:
-        return jsonify('No Metric')
-
-
-# Get Single Metric
-@app.route(METRIC + VAR_ID, methods=[GET])
-def get_metric(id):
-    metric = Metric.query.get(id)
-    return metric_schema.jsonify(metric)
-
-
-# Update a Metric
-@app.route(METRIC + VAR_ID, methods=[PUT])
-def update_metric(id):
-    metric = Metric.query.get(id)
-
-    metric.algorithm_name = request.json['algorithm_name']
-    metric.dataset_hash = request.json['dataset_hash'].replace("\x00", "")
-    metric.metric_name = request.json['metric_name']
-    metric.metric_value = request.json['metric_value']
-
-    db.session.commit()
-
-    return metric_schema.jsonify(metric)
-
-
-# Delete Metric
-@app.route(METRIC + VAR_ID, methods=[DEL])
-def delete_metric(id):
-    metric = Metric.query.get(id)
-    db.session.delete(metric)
-    db.session.commit()
-
-    return metric_schema.jsonify(metric)
-
-# Retrieve all metric that matches the dataset_hash
-@app.route(METRIC + RETRIEVE + ALL, methods=[POST])
-def retrieve_algorithm_list():
-    dataset_hash = request.json['dataset_hash'].replace("\x00", "")
-
-    all_metrics = Metric.query.filter_by(dataset_hash=dataset_hash).all()
-
-    return metrics_schema.jsonify(all_metrics)
-
-
-# Retrieve metric that best matches the dataset_hash
-@app.route(METRIC + RETRIEVE + MIN, methods=[POST])
-def retrieve_algorithm_best_min():
-    dataset_hash = request.json['dataset_hash'].replace("\x00", "")
-
-    metric = Metric.query.filter_by(dataset_hash=dataset_hash).order_by(Metric.metric_value.asc()).first()
+from src.api import metrics_api
 
-    return metric_schema.jsonify(metric)
+app.register_blueprint(metrics_api, url_prefix=METRIC)
 
-# Retrieve metric that best matches the dataset_hash
-@app.route(METRIC + RETRIEVE + MAX, methods=[POST])
-def retrieve_algorithm_best_max():
-    dataset_hash = request.json['dataset_hash'].replace("\x00", "")
+# added route for index.html webpage
+@app.route('/')
+@app.route('/index.html')
+def index():
+    return render_template('index.html')
 
-    metric = Metric.query.filter_by(dataset_hash=dataset_hash).order_by(Metric.metric_value.desc()).first()
+# added route for api-description webpage
+@app.route('/api-description.html')
+def apidescription():
+    return render_template('api-description.html')
 
-    return metric_schema.jsonify(metric)
 
 # Run Server
 if __name__ == '__main__':

src/api.py

@@ -0,0 +1,114 @@
+from flask import Blueprint, Flask, request, jsonify
+
+from src.utils.constants import *
+
+metrics_api = Blueprint('metrics_api', __name__)
+
+from src.data_models.Metrics import *
+from src.data_models.Params import *
+from src.data_models.MetaFeatures import *
+
+from app import db
+
+# Create a Metric
+@metrics_api.route('', methods=[POST])
+def add_metric():
+    algorithm_name = request.json['algorithm_name']
+    dataset_hash = request.json['dataset_hash'].replace("\x00", "")
+    metric_name = request.json['metric_name']
+    metric_value = request.json['metric_value']
+
+    target_type = request.json['target_type']
+
+    new_metric = Metric(algorithm_name, dataset_hash, metric_name, metric_value, target_type)
+
+    db.session.add(new_metric)
+    db.session.commit()
+
+    params = request.json['params']
+    if(params != ""):
+        for param in params:
+            new_params = Params(new_metric.id, param['param_name'], param['param_value'])
+            db.session.add(new_params)
+    db.session.commit()
+
+    data_meta_features = request.json['data_meta_features']
+    if(data_meta_features != ""):
+        for feat in data_meta_features:
+            new_feat = MetaFeature(new_metric.id, feat['feat_name'], feat['feat_value'])
+            db.session.add(new_feat)
+    db.session.commit()
+
+    return metric_schema.jsonify(new_metric)
+
+
+
+# Get All Metrics
+@metrics_api.route('', methods=[GET])
+def get_metrics():
+    all_metrics = Metric.query.all()
+    result = metrics_schema.dump(all_metrics)
+    if len(result) > 0:
+        return jsonify(result)
+    else:
+        return jsonify('No Metric')
+
+
+# Get Single Metric
+@metrics_api.route(VAR_ID, methods=[GET])
+def get_metric(id):
+    metric = Metric.query.get(id)
+    return metric_schema.jsonify(metric)
+
+
+# Update a Metric
+@metrics_api.route(VAR_ID, methods=[PUT])
+def update_metric(id):
+    metric = Metric.query.get(id)
+
+    metric.algorithm_name = request.json['algorithm_name']
+    metric.dataset_hash = request.json['dataset_hash'].replace("\x00", "")
+    metric.metric_name = request.json['metric_name']
+    metric.metric_value = request.json['metric_value']
+
+    db.session.commit()
+
+    return metric_schema.jsonify(metric)
+
+
+# Delete Metric
+@metrics_api.route(VAR_ID, methods=[DEL])
+def delete_metric(id):
+    metric = Metric.query.get(id)
+    db.session.delete(metric)
+    db.session.commit()
+
+    return metric_schema.jsonify(metric)
+
+# Retrieve all metric that matches the dataset_hash
+@metrics_api.route(RETRIEVE + ALL, methods=[POST])
+def retrieve_algorithm_list():
+    dataset_hash = request.json['dataset_hash'].replace("\x00", "")
+
+    all_metrics = Metric.query.filter_by(dataset_hash=dataset_hash).all()
+
+    return metrics_schema.jsonify(all_metrics)
+
+
+# Retrieve metric that best matches the dataset_hash
+@metrics_api.route(RETRIEVE + MIN, methods=[POST])
+def retrieve_algorithm_best_min():
+    dataset_hash = request.json['dataset_hash'].replace("\x00", "")
+
+    metric = Metric.query.filter_by(dataset_hash=dataset_hash).order_by(Metric.metric_value.asc()).first()
+
+    return metric_schema.jsonify(metric)
+
+# Retrieve metric that best matches the dataset_hash
+@metrics_api.route(RETRIEVE + MAX, methods=[POST])
+def retrieve_algorithm_best_max():
+    dataset_hash = request.json['dataset_hash'].replace("\x00", "")
+
+    metric = Metric.query.filter_by(dataset_hash=dataset_hash).order_by(Metric.metric_value.desc()).first()
+
+    return metric_schema.jsonify(metric)

data_models/MetaFeatures.py → src/data_models/MetaFeatures.py

@@ -1,5 +1,5 @@
 from app import db, ma
-from constants import TABLE_META_FEATURES
+from src.utils.constants import TABLE_META_FEATURES
 
 
 # Meta Feature Class/Model

data_models/Metrics.py → src/data_models/Metrics.py

@@ -1,7 +1,7 @@
 from app import db, ma
-from data_models.Params import ParamSchema
-from data_models.MetaFeatures import MetaFeatureSchema
-from constants import TABLE_METRIC, CLASS_PARAM, CLASS_META_FEATURE
+from src.data_models.Params import ParamSchema
+from src.data_models.MetaFeatures import MetaFeatureSchema
+from src.utils.constants import TABLE_METRIC, CLASS_PARAM, CLASS_META_FEATURE
 
 # Metric Class/Model
 class Metric(db.Model):

data_models/Params.py → src/data_models/Params.py

@@ -1,5 +1,5 @@
 from app import db, ma
-from constants import TABLE_PARAM
+from src.utils.constants import TABLE_PARAM
 
 
 # Param Class/Model

fmlearn.py → src/fmlearn.py

@@ -1,9 +1,9 @@
 import pandas as pd
-import utils
-
 from sklearn.model_selection import train_test_split
 from sklearn.neighbors import KNeighborsRegressor
 
+from src.utils import utils
+
 def kmc():
     df = utils.get_df_from_db()
     df.fillna(0, inplace=True)
@@ -27,7 +27,7 @@ def kmc():
 
     print(y_test.to_string(header=False))
     y_pred = pd.DataFrame(y_pred)
-    print(y_pred.to_string(header=False))
+    return y_pred.to_string(header=False)
 
 if __name__ == "__main__":
-    kmc()
+    kmc()