Python and neo4j - fuck the jvm

A lightning talk I gave at pyBelfast on the 30th Jan 2019 re: python, neo4j and an idea I have.

Transcript

1. Python & neo4j -
   Fuck the jvm Stephen McCullough / Pybelfast Jan 2019
   

   View Slide

2. About me.. cos it is all
   about me, me, me!!!!
   • Lead Developer @ Futrli - we’re hiring
   
   • I co-organise pyBelfast, BelfastRuby and
   BelfastElixir
   
   • I’ll try and behave and not curse…
   
   • You can find me on the inter web on most
   things as @swmcc apart from twitter!
   

   View Slide

3. Python & neo4j - Fuck the jvm
   • First off… I don’t mean “Fuck the jvm”
   • It is an incendiary title
   • I find graph databases interesting/fun
   • I don’t want to have to learn a new language to play
   with something
   • Python has a nice eco system around it for neo4j
   • Standing on others shoulders - Grant Dickerson
   

   View Slide

4. What is a graph DB?
   • Composed of nodes (vertices) & relationships (edges)
   • Completely different paradigm from relationship databases
   • It focuses on the relationships between values and
   commonalities among a ‘set’ of values
   • Designed to treat the relationships between the data as
   equally important to the data itself
   • Intended to hold data without constricting it to a pre-
   defined model
   

   View Slide

5. Use cases for a graph db
   • Fraud Detection & Analytics Solution
   • Ecomm fraud, insurance fraud, link analysis
   • Knowledge Graph
   • Asset management, Inventory
   • Recommendation Engines
   • Product recommendations, social recommendations
   • Identity & Access management
   • Cross referencing of business objects
   

   View Slide

6. Knowledge Graph
   • It represents a knowledge domain.
   • Connects things of different types in a systematic way.
   • Encodes knowledge arranged in a network of nodes
   and links rather than tables of rows and columns
   • Grow a semantic network of facts about “things” and
   can use it for data integration, knowledge discovery,
   and in-depth analyses.
   

   View Slide

7. For example
   • Homer Simpson (is friends with) with Kenny & Carl
   • Kenny (is friends with) Carl
   

   View Slide

8. Nodes
   • A node is a “vertex between edges that may hold data”
   • Or as I call it “a wee box of data stores”
   • [name: Homer]
   • [name: Lenny]
   • [name: Carl]
   

   View Slide

9. What does it look like?
   

   View Slide

10. Cypher
    • Cypher is a graph query language supported by neo4j
    • Based on pattern matching and a SQL-like syntax
    • …. when I was doing this before I didn’t use it much
    • I used Gremlin
    • DSL for Groovy
    • Wanted to use either ruby or python for an idea I’ve had
    since 2013
    

    View Slide

11. Is python fit enough?
    • I tried this out with ruby in 2013
    • It didn’t go well, as you can imagine.
    • There were libraries but most weren’t fit for purpose
    • Reason that I went to Groovy
    • However its now 2019 and there is a very well supported “official” packages for python
    • Neo4j-python-driver
    • https://github.com/neo4j-examples/movies-python-bolt
    • Py2neo
    • https://py2neo.org/v4/
    

    View Slide

12. Example Code
    from py2neo import Node
    nicole = Node("Person", name="Nicole", age=24)
    drew = Node("Person", name="Drew", age=20)
    mtdew = Node("Drink", name="Mountain Dew", calories=9000)
    cokezero = Node("Drink", name="Coke Zero", calories=0)
    coke = Node("Manufacturer", name="Coca Cola")
    pepsi = Node("Manufacturer", name="Pepsi")
    graph.create(nicole | drew | mtdew | cokezero | coke | pepsi)
    from scripts.vis import draw
    options = {"Person": "name", "Drink": "name", "Manufacturer": "name"}
    draw(graph, options)
    from py2neo import Relationship
    graph.create(Relationship(nicole, "LIKES", cokezero))
    graph.create(Relationship(nicole, "LIKES", mtdew))
    graph.create(Relationship(drew, "LIKES", mtdew))
    graph.create(Relationship(coke, "MAKES", cokezero))
    graph.create(Relationship(pepsi, "MAKES", mtdew))
    draw(graph, options)
    

    View Slide

13. View Slide

14. The Wire
    

    View Slide

15. The GRROM
    

    View Slide

16. View Slide

17. The Nodes - The Wire
    • All have common attributes:
    • Name
    • First / Last Appearance
    • Title
    • Section
    • Relationship between nodes
    

    View Slide

18. Joe

    “Proposition Joe”
    Stewart
    name: Joe Stewart
    
    alias: Prop Joe
    
    first_apperance: 1.09
    
    last_apperance: 5.04
    
    section: The Street
    
    rank: Kingpin
    
    affiliation: [east-side, new day co-
    op]
    

    View Slide

19. Russell

    “Stringer”
    Bell
    name: Russell Bell
    
    alias: Stringer
    
    first_apperance: 1.01
    
    last_apperance: 3.12
    
    section: The Street
    
    rank: Street Boss
    
    affiliation: [west-side, new-day co-
    op, b&b properties]
    

    View Slide

20. Cedric
    Daniels
    name: Cedric Daniels
    
    alias:
    
    first_apperance: 1.01
    
    last_apperance: 5.10
    
    section: The Law
    
    rank: [Lieutenant, Major, Colonel,
    Chief Deputy Ops, Commissioner, ]
    
    affiliation: [police, lawyer]
    

    View Slide

21. View Slide

22. Why do this???
    • It doesn’t remind me of my day to day to work:
    • Not taking a section of a monolith and making a ‘micro
    service’ out of it
    • Not creating an API so that a front end can use it and
    display information
    • Nothing at all to do with my work
    • It is FUCKING FUN (for me at least).
    

    View Slide

23. Going to do the following
    • Possibly come back at some stage and give you an
    actual talk on this, if there is interest
    • Will blog about it
    • Want to help me, please get in touch
    

    View Slide