def plot_sentiment(item,name_plot):
sent_points = get_item_sentiment(item['item_id'])
trace0 = Scatter(x=sent_points[0],y=sent_points[1],
mode='markers', markers=Marker(size=8),
name='reviews sentiment score')
trace1 = Scatter(x=sent_points[0],y=[0]*len(sent_points[1]),
name = "neutral line")
data = ([trace0,trace1])
layout = Layout(xaxis=XAxis(title='Time Line',autorange=True),
yaxis=YAxis(title='Sentiment score on product',autorange=True),
legend=Legend(y=0.5,yref='paper',font=Font(size=10,)), )
fig = Figure(data=data, layout=layout)
plot_url = py.plot(fig, filename=name_plot)
return plot_url
def plot_sentiment(item, name_plot):
sent_points = get_item_sentiment(item['item_id'])
trace0 = Scatter(x=sent_points[0],
y=sent_points[1],
mode='markers',
markers=Marker(size=8),
name='reviews sentiment score')
trace1 = Scatter(x=sent_points[0],
y=[0] * len(sent_points[1]),
name="neutral line")
data = ([trace0, trace1])
layout = Layout(
xaxis=XAxis(title='Time Line', autorange=True),
yaxis=YAxis(title='Sentiment score on product', autorange=True),
legend=Legend(y=0.5, yref='paper', font=Font(size=10, )),
)
fig = Figure(data=data, layout=layout)
plot_url = py.plot(fig, filename=name_plot)
return plot_url
def recommendation():
"""
When a POST request with json data is made to this url,
read the data from json, find the beauty product, then
return the response
"""
data = flask.request.json
priority_concern = data["priority"][0]
other_concerns = data["others"][0].split(",")
list_of_concern = data["priority"] + data["skin_type"] + other_concerns
list_of_concern = list(set(list_of_concern))
#print list_of_concern
recommended_15_items = list_of_15(priority_concern, list_of_concern)
item_ids = [i['item_id'] for i in recommended_15_items]
recommended_5_items = list_of_5(item_ids)
recommended_5 = add_price.add_price(recommended_5_items)
#####------Trying to add price and distance into my data---------------
#recommended_items = add_price.add_price(recommended_5_items)
unsorted_recommended_items = add_distance(data['extra_info'],
recommended_5)
sorted_recommended_items = sorted(unsorted_recommended_items,
key=lambda k: k['distance'],
reverse=True)
recommended_items = sorted_recommended_items[:3]
# plot1 = plot_sentiment(recommended_items[0],'sentiment plot 1')
# plot2 = plot_sentiment(recommended_items[1],'sentiment plot 2')
# plot3 = plot_sentiment(recommended_items[2],'sentiment plot 3')
graph_data1 = get_item_sentiment(recommended_items[0]['item_id'])
new_data1 = np.asarray(graph_data1).T.tolist()
graph_data2 = get_item_sentiment(recommended_items[1]['item_id'])
new_data2 = np.asarray(graph_data2).T.tolist()
graph_data3 = get_item_sentiment(recommended_items[2]['item_id'])
new_data3 = np.asarray(graph_data3).T.tolist()
####-------Result to be return to html----------------------------------
results = {
1: [
recommended_items[0]['name'],
round(recommended_items[0]['star_rating_ave'],
3), recommended_items[0]['number_of_reviews'],
recommended_items[0]['reviews_summary'],
recommended_items[0]['price']
],
2: [
recommended_items[1]['name'],
round(recommended_items[1]['star_rating_ave'],
3), recommended_items[1]['number_of_reviews'],
recommended_items[1]['reviews_summary'],
recommended_items[1]['price']
],
3: [
recommended_items[2]['name'],
round(recommended_items[2]['star_rating_ave'],
3), recommended_items[2]['number_of_reviews'],
recommended_items[2]['reviews_summary'],
recommended_items[2]['price']
],
"graph_data1":
new_data1,
"graph_data2":
new_data2,
"graph_data3":
new_data3
}
return flask.jsonify(results)
def recommendation():
"""
When a POST request with json data is made to this url,
read the data from json, find the beauty product, then
return the response
"""
data = flask.request.json
priority_concern = data["priority"][0]
other_concerns = data["others"][0].split(",")
list_of_concern = data["priority"]+ data["skin_type"] + other_concerns
list_of_concern = list(set(list_of_concern))
#print list_of_concern
recommended_15_items = list_of_15(priority_concern,list_of_concern)
item_ids = [i['item_id'] for i in recommended_15_items]
recommended_5_items = list_of_5(item_ids)
recommended_5 = add_price.add_price(recommended_5_items)
#####------Trying to add price and distance into my data---------------
#recommended_items = add_price.add_price(recommended_5_items)
unsorted_recommended_items = add_distance(data['extra_info'], recommended_5)
sorted_recommended_items = sorted(unsorted_recommended_items,key=lambda k: k['distance'],reverse=True)
recommended_items = sorted_recommended_items[:3]
# plot1 = plot_sentiment(recommended_items[0],'sentiment plot 1')
# plot2 = plot_sentiment(recommended_items[1],'sentiment plot 2')
# plot3 = plot_sentiment(recommended_items[2],'sentiment plot 3')
graph_data1 = get_item_sentiment(recommended_items[0]['item_id'])
new_data1 = np.asarray(graph_data1).T.tolist()
graph_data2 = get_item_sentiment(recommended_items[1]['item_id'])
new_data2 = np.asarray(graph_data2).T.tolist()
graph_data3 = get_item_sentiment(recommended_items[2]['item_id'])
new_data3 = np.asarray(graph_data3).T.tolist()
####-------Result to be return to html----------------------------------
results = {1:[recommended_items[0]['name'],round(recommended_items[0]['star_rating_ave'],3),
recommended_items[0]['number_of_reviews'],recommended_items[0]['reviews_summary'],
recommended_items[0]['price']],
2:[recommended_items[1]['name'],round(recommended_items[1]['star_rating_ave'],3),
recommended_items[1]['number_of_reviews'],recommended_items[1]['reviews_summary'],
recommended_items[1]['price']],
3:[recommended_items[2]['name'],round(recommended_items[2]['star_rating_ave'],3),
recommended_items[2]['number_of_reviews'],recommended_items[2]['reviews_summary'],
recommended_items[2]['price']],
"graph_data1":new_data1,"graph_data2":new_data2,"graph_data3":new_data3 }
return flask.jsonify(results)
