README

This Neo4j-based node / react web app displays movie and person data in a manner similar to IMDB. It is designed to serve as a template for further development projects. Feel encouraged to fork and update this repo!

The Model

Nodes

• Movie
• Person
• Genre
• Keyword

Relationships

• (:Person)-[:ACTED_IN {role:"some role"}]->(:Movie)
• (:Person)-[:DIRECTED]->(:Movie)
• (:Person)-[:WRITER_OF]->(:Movie)
• (:Person)-[:PRODUCED]->(:Movie)
• (:MOVIE)-[:HAS_GENRE]->(:Genre)

Database Setup

Unix Video Instructions

• Download Neo4j Community Edition: .tar Version
• video instructions start here
• Set your NEO4J_HOME variable: `export NEO4J_HOME=/path/to/neo4j-community
• From this project's root directory, run the import script:

$NEO4J_HOME/bin/neo4j-import --into $NEO4J_HOME/data/databases/graph.db --nodes:Person csv/person_node.csv --nodes:Movie csv/movie_node.csv --nodes:Genre csv/genre_node.csv --nodes:Keyword csv/keyword_node.csv --relationships:ACTED_IN csv/acted_in_rels.csv --relationships:DIRECTED csv/directed_rels.csv --relationships:HAS_GENRE csv/has_genre_rels.csv --relationships:HAS_KEYWORD csv/has_keyword_rels.csv --relationships:PRODUCED csv/produced_rels.csv --relationships:WRITER_OF csv/writer_of_rels.csv --delimiter ";" --array-delimiter "|" --id-type INTEGER

If you see Input error: Directory 'neo4j-community-3.0.3/data/databases/graph.db' already contains a database, delete the graph.db directory and try again.

• Start the database: $NEO4J_HOME/bin/neo4j console
• Add constraints to your database: $NEO4J_HOME/bin/neo4j-shell < setup.cql

Windows

Download Neo4j Community Edition

neo4j-import does not come with Neo4j-Desktop (.exe on Windows, .dmg on OSX). To get around this issue, find your OS here and try using the alternate import command for your system. Update the Neo4j version in the snippet with whatever you're using, and replacing "$@" or %\* with:

--into database/ --nodes:Person csv/person_node.csv --nodes:Movie csv/movie_node.csv --nodes:Genre csv/genre_node.csv --nodes:Keyword csv/keyword_node.csv --relationships:ACTED_IN csv/acted_in_rels.csv --relationships:DIRECTED csv/directed_rels.csv --relationships:HAS_GENRE csv/has_genre_rels.csv --relationships:HAS_KEYWORD csv/has_keyword_rels.csv --relationships:PRODUCED csv/produced_rels.csv --relationships:WRITER_OF csv/writer_of_rels.csv --delimiter ";" --array-delimiter "|" --id-type INTEGER

For example, this would be the alternate command for Windows on Neo4j 3.0.3:

"C:\Program Files\Neo4j Community\jre\bin\java" -cp "C:\Program Files\Neo4j Community\bin\neo4j-desktop-3.0.3.jar" org.neo4j.tooling.ImportTool --into database/ --nodes:Person csv/person_node.csv --nodes:Movie csv/movie_node.csv --nodes:Genre csv/genre_node.csv --nodes:Keyword csv/keyword_node.csv --relationships:ACTED_IN csv/acted_in_rels.csv --relationships:DIRECTED csv/directed_rels.csv --relationships:HAS_GENRE csv/has_genre_rels.csv --relationships:HAS_KEYWORD csv/has_keyword_rels.csv --relationships:PRODUCED csv/produced_rels.csv --relationships:WRITER_OF csv/writer_of_rels.csv --delimiter ";" --array-delimiter "|" --id-type INTEGER

Use the GUI to select and start your database.

Start the Database!

• Start Neo4j if you haven't already!
• Set your username and password
• You should see a database populated with Movie, Genre, Keyword, and Person nodes.

Node API

From the root directory of this project:

• cd api
• npm install
• in config.js, update the credentials for your database as needed
• node app.js starts the API
• Take a look at the docs at http://localhost:3000/docs

Alternative: Flask API

From the root directory of this project:

• cd flask-api
• pip install -r requirements.txt (you should be using a virtualenv)
• set your neo4j database username export MOVIE_DATABASE_USERNAME=myusername
• set your neo4j database password export MOVIE_DATABASE_PASSWORD=mypassword
• export FLASK_APP=app.py
• flask run starts the API
• Take a look at the docs at http://localhost:5000/docs

Frontend

From the root directory of this project, set up and start the frontend with:

• cd web
• npm install (if package.json changed)
• bower install to install the styles
• update config.settings.js file ** if you are using the Node API: cp config/settings.example.js config/settings.js ** if you are using the flask api then edit config/settings.js and change the apiBaseURL to http://localhost:5000/api/v0
• gulp starts the app on http://localhost:4000/

Ratings and Recommendations

Load some fake users and ratings

If you're running the app locally, you might want to tweak or explore ratings without having a robust community of users. In the /csv directory, note that there is a file called ratings.csv. This file contains some pseudo-randomly generated users and ratings. Load the users and ratings:

Move ratings.csv into the import directory of your database either by dragging and dropping or using

cp csv/ratings.csv $NEO4J_HOME/import/ratings.csv


Assuming your database is running, paste the following query into the Neo4j browser:

LOAD CSV WITH HEADERS FROM 'file:///ratings.csv' AS line
MATCH (m:Movie {id:toInt(line.movie_id)})  
MERGE (u:User {id:line.user_id, username:line.user_username}) // user ids are strings
MERGE (u)-[r:RATED]->(m)
SET r.rating = toInt(line.rating)
RETURN m.title, r.rating, u.username

If you don't want to use the browser, you can uncomment out the above query in setup.cql and run it again using $NEO4J_HOME/bin/neo4j-shell < setup.cql

User-Centric, User-Based Recommendations

Based on my similarity to other users, user Sherman might be interested in movies rated highly by users with similar ratings as himself.

MATCH (me:User {username:'Sherman'})-[my:RATED]->(m:Movie)
MATCH (other:User)-[their:RATED]->(m)
WHERE me <> other
AND abs(my.rating - their.rating) < 2
WITH other,m
MATCH (other)-[otherRating:RATED]->(movie:Movie)
WHERE movie <> m
WITH avg(otherRating.rating) AS avgRating, movie
RETURN movie
ORDER BY avgRating desc
LIMIT 25

Movie-Centric, Keyword-Based Recommendations

Site visitors interested in movies like Elysium will likely be interested in movies with similar keywords.

MATCH (m:Movie {title:'Elysium'})
MATCH (m)-[:HAS_KEYWORD]->(k:Keyword)
MATCH (movie:Movie)-[r:HAS_KEYWORD]->(k)
WHERE m <> movie
WITH movie, count(DISTINCT r) AS commonKeywords
RETURN movie
ORDER BY commonKeywords DESC
LIMIT 25

User-Centric, Keyword-Based Recommendations

Sherman has seen many movies, and is looking for movies similar to the ones he has already watched.

MATCH (u:User {username:'Sherman'})-[:RATED]->(m:Movie)
MATCH (m)-[:HAS_KEYWORD]->(k:Keyword)
MATCH (movie:Movie)-[r:HAS_KEYWORD]->(k)
WHERE m <> movie
WITH movie, count(DISTINCT r) AS commonKeywords
RETURN movie
ORDER BY commonKeywords DESC
LIMIT 25

Contributing

Flask API

The flask API is located in the flask-api folder. The application code is in the app.py file.

Create Endpoint

The API itself is created using the Flask-RESTful library. The API endpoints are documented using swagger with the flask-restful-swagger-2 library.

To add a new API endpoint there are 3 steps:

1. Create a new Flask-RESTful resource class
2. Create an endpoint method including the swagger docs decorator.
3. Add the new resource to the API at the bottom of the file.