DEV Community: Benoît Durand

MongoDB Atlas Hackathon Submission - CookReview

Benoît Durand — Wed, 07 Dec 2022 17:12:37 +0000

My submission for the MongoDB Atlas Hackathon consist in a web application called CookReview that let you find restaurants in the USA based on full text search on previous customer reviews. Thanks to community you can find more information on the restaurant that you can not find on other websites (e.g Price/Quality ratio, events, atmosphere)

Category Submission:

Event tought this project is built using a FARM stack, this project more found itself in the Search No More Category since it's heavily depends on MongoDB Atlas Search Feature.

Atlas search is used here for 3 differents use case:

Full text search based on user input

When a user search for a restaurant a query is ran to find related information that should match the user input, if it's found then the score is boosted Doc by a factor 3, since it's a perfect match.

In the case of user clicking on Vegan and New York City, those two parameters are putted in a must condition signifying that the query MUST match those two parameters. We can not recommand a non-vegan restaurant or a restaurant outside of New York to a user that search for those.

Another way to optmize the query result was to use the Synonyms feature Docs of Atlas search by providing a collection of equivalent words to enhance the query result. For that I created two different collections

To enhance geographical user input, a collection containing all the US State and their ISO abbreviation, such that when a user input a full state name, Atlas Search can make the link to a postal code.

To add more words with the same meaning such as café and coffee, etc

Smart chose of icons based on restaurant information

Another usage I made of Atlas Search was to find the best icon corresponding to a restaurant name and type so I dont have to do it

To put that in use I wrote this simple query

[
    {
        "$search": {
            "index": "default",
            "text": {
                "query": <RESTAURANT_INFO>,
                "path": {
                    "wildcard": "*"
                }
            }
        }
    },
    {
        "$limit": 3
    },
    {
        "$project": {
            "id": {
                "$toString": "$_id"
            },
            "_id": 0,
            "Name": 1,
            "filename": 1,
            "score": {
                "$meta": "searchScore"
            }

        }
    }
]

Into this collection where each svg icon is linked to a word describing it.

Here is an example where chosen icon is a sushi

Autocomplete of restaurant name

Using MongoDB Atlas Seach autocomplete feature I was able to quickly make an autocomplete system based on restaurant name

[
    {
        "$search": {
            "index": "reviews",
            "autocomplete": {
                "query": "",
                "path": "Name"
            }
        }
    },
    {
        "$limit": 3
    },
    {
        "$project": {
            "id": {
                "$toString": "$_id"
            },
            "_id": 0,
            "Name": 1
        }
    }
]

App Link

http://cookreview.duranbe.tech

Source Code

https://github.com/duranbe/restaurants-reviews

Story behind the project

The original idea came to me by browsing Kaggle. As a Machine Learning graduate and incoming Software Engineer I wanted to build a data-driven application.

How I built it

When building this project I learned more about MongoDB, and Atlas Search feature that gives a lot of options to developper and a solve a lots of problems, such as an autocomplete feature.

I also learned more about React and Tailwind, as it is the first big project I am working on with these technology.

Ressources

MongoDB Atlas Search : https://www.mongodb.com/docs/atlas/atlas-search/atlas-search-overview/
React : https://reactjs.org
Tailwind : https://tailwindcss.com
DrawKit (Illustrations) : https://www.drawkit.com
Fast API : https://fastapi.tiangolo.com

Importing a csv to MongoDB Atlas on Debian with mongoimport

Benoît Durand — Sat, 26 Nov 2022 09:53:28 +0000

In those times of MongoDB Atlas Hackathon I thought it will be useful to share with the community the process to upload csv/tsv files to MongoDB Atlas service, as it can be use in case a building a data-driven service.

NB : This tutorial is mainly targeted to Debian User.

Pre Requisites :

Debian Linux Installed
a MongoDB Atlas database cluster

Installing MongoDB Database Tools 🌱

To upload our csv file the first thing we need is to install MongoDB Database Tools on our machine. This will allow us to use the mongoimport tool and bunch of others mongodb related tools such as :

mongodump
mongorestore
bsondump
mongoimport
mongoexport
mongostat
mongotop
mongofiles

To do that you need to select your operating system and download the package here
In case you are like me on Debian or WSL you can directly use one of these commands :

Debian 11

wget https://fastdl.mongodb.org/tools/db/mongodb-database-tools-debian11-x86_64-100.6.1.deb 
sudo apt install ./mongodb-database-tools-debian11-x86_64-100.6.1.deb

Debian 10

wget https://fastdl.mongodb.org/tools/db/mongodb-database-tools-debian10-x86_64-100.6.1.deb
sudo apt install ./mongodb-database-tools-debian10-x86_64-100.6.1.deb

And then all the mentionned tools should be installed !

Upload a csv file using the mongoimport command 🌱🌱

The mongoimport command can be use with the following syntax :

mongoimport <options> <connection-string> <file>
Where the connection-string is your mongodb cluster connection string, in the following format :
mongodb+srv://<username>:<password>@<host>/<database>or
mongodb://<username>:<password>@<host>/<database>
The file arguments is the path of the csv you want to upload, such as imdb_data.csv

Options are bunch of others configurations you can use such as

--headerline : To make mongodb use the first line of the csv as the fields reference
--collection=<collection_name>: To define which collections to use in your db, otherwise mongo will create one using the name of the csv file

To get a detail of all the options you can refer the help using mongoimport --help

In my case I used the following command to make sure things were done right :

mongoimport \
--uri=mongodb+srv://USERNAME:PASSWORD@HOST \
--db=DB\
--type=csv \
--headerline  \
--DATA.csv \

And that's it ! You can comment below your thought and issues 👇

Explore Seattle City Bikes trips

Benoît Durand — Wed, 05 Jan 2022 19:32:15 +0000

Overview

If like me you had the chance to live in a big city or a capital, you certainly came across these bikes :

Theses bike sharing services are pretty popular nowadays and as a user I'm a pretty big fan of them. That's why as a Data Science student I chose to dig and play a bit with the data I could find about them.

The project consist in a small one-page dashboard to analyze and predicts the cycle share trips of the Pronto Cycle Share system, that was operating between 2014 and 2016 in Seattle, USA.

This project was built with FastAPI, MongoDB, Docker, Bootstrap and Chartjs.

Project can be accessed at the following url :
Pronto Dashboard

Submission Category:

This project belongs to the Prime Time category.

Link to Code

duranbe / bike-sharing

Dashboard on Pronto Bikes Data 🚴‍♂️ for MongoDB Atlas Hackathon

Bike Sharing

Pronto Bike Sharing Dashboard

Overview

The project consist in a small one-page dashboard to analyze and predicts the cycle share trips of the Pronto Cycle Share system, that was operating between 2014 and 2016 in Seattle, USA.

It was created for the DEV.TO and MongoDB atlashackathon

Dev post : https://dev.to/duranbe/explore-and-predict-seattle-city-bikes-trips-cac

This project was built with FastAPI, MongoDB, Docker, Bootstrap and Chartjs.

Setting up the project

This project is built with Docker 🐋,

First step is to build the image

docker build . -t bike-sharing

Then create a container, map the network port and the .env file

docker run --name bike-sharing-container -p 80:80 --env-file .env bike-sharing

To stop and delete the container

docker rm --force bike-sharing-container

Ressources

View on GitHub

DEV Community: Benoît Durand

MongoDB Atlas Hackathon Submission - CookReview

Category Submission:

Full text search based on user input

Smart chose of icons based on restaurant information

Autocomplete of restaurant name

App Link

Source Code

Story behind the project

How I built it

Ressources

Importing a csv to MongoDB Atlas on Debian with mongoimport

Installing MongoDB Database Tools 🌱

Debian 11

Debian 10

Upload a csv file using the mongoimport command 🌱🌱

Explore Seattle City Bikes trips

Overview

Submission Category:

Link to Code

duranbe / bike-sharing

Dashboard on Pronto Bikes Data 🚴‍♂️ for MongoDB Atlas Hackathon

Bike Sharing

Overview

Setting up the project

Ressources

Additional Resources / Info