TravelScrum Hackathon Project Wanderer
pip install -r requirements.txt
cd python/location_recommendation && python recommend.py
This will train the model using the sample file in data/london_10k.csv and run the python flask server.
https://www.kaggle.com/amiralisa/context-aware-recommender/comments
Request files:
#user1.json
{
"_userId": "41087279@N00",
"email": "user1@gmail.com"
}
#user2.json
{
"_userId": "7344912@N05",
"email": "user2@gmail.com"
}
Make a Request
$ cd client
$ curl -H "Content-Type: application/json" --data @user1.json localhost:5000/api
{
"1":{
"location_id":766277,
"lat":51.5010986328,
"lon":-0.1703319997,
"pred":3.2272727273,
"covidSafetyRating":3
},
"2":{
"location_id":811547,
"lat":51.492931366,
"lon":-0.1475320011,
"pred":3.2272727273,
"covidSafetyRating":2
},
"0":{
"location_id":325510,
"lat":51.5133018494,
"lon":-0.0857840031,
"pred":2.9193942176,
"covidSafetyRating":2
}
$ curl -H "Content-Type: application/json" --data @user2.json localhost:5000/api
{
"0":{
"location_id":893200,
"lat":51.5032997131,
"lon":-0.1513399929,
"pred":1.5454545455,
"covidSafetyRating":2
},
"1":{
"location_id":811547,
"lat":51.492931366,
"lon":-0.1475320011,
"pred":1.5454545455,
"covidSafetyRating":3
},
"2":{
"location_id":787533,
"lat":51.4561386108,
"lon":-0.3416489959,
"pred":1.5454545455,
"covidSafetyRating":3
}
}
