These are the specific steps to build this demo of faceted search navigation implemented with the stack: VueJS, Flask, MongoDB.
Everything assumes a MacOSX environment with brew, python, pip and virtualenvwrapper
$ brew install mongo
check if it works
$ mongo
MongoDB shell version v3.4.4
connecting to: mongodb://127.0.0.1:27017
MongoDB server version: 3.4.4
...
> show databases
> exit
This is a sample collection of 25K restaurants of NYC from mongo documentation.
- Download the dataset:
$ curl -O https://raw.githubusercontent.com/mongodb/docs-assets/primer-dataset/primer-dataset.json
- Import the dataset in 'test' database:
$ mongoimport --db test --collection restaurants --drop --file primer-dataset.json
- Check if it was imported well:
$ mongo
MongoDB shell version v3.4.4
connecting to: mongodb://127.0.0.1:27017
MongoDB server version: 3.4.4
...
> use test
> db.restaurants.findOne()
{
"_id" : ObjectId("596286ff0b13d7ec5826380f"),
"address" : {
"building" : "1007",
...
> db.restaurants.find().count()
25359
> db.restaurants.find({borough: 'Bronx'}).count()
2338
- Create index:
> db.restaurants.createIndex( { cuisine: -1, borough: -1, zipcode: -1 } )
> db.restaurants.createIndex( { name: "text" } )
> exit
- Remove downloaded dataset:
$ rm primer-dataset.json
Clone this repository and inside the folder:
- Make a virtualenv:
$ mkvirtualenv mongo-facets
- Install Python dependencies (Flask and PyMongo):
$ pip install -r requirements.txt
$ python server.py
And enjoy playing in the frontend at http://127.0.0.1:5000/ ! :D