Podcast Search GraphQL API With Neo4j And The Podcast Index
By: William Lyon
Tags: GraphQL, Grandstack, JavaScript, Neo4j, Podcast

Podcast Search GraphQL API With Neo4j And The Podcast Index

A few weeks ago I was complaining about the podcast app I was using. There was some problem with updating my playlists and I was grumpy because the app wasn’t pulling down any episodes. My wife suggested I just build my own podcast application and use that instead. She was just trying to get me to shut up and stop complaining, but I thought that actually sounded like a fun project. So this week on the Neo4j livestream we kicked off a new project: building a podcast application with GRANDstack!

In this first week, we went over the graph data model we’ll need for this application and started building the GraphQL API for the project, focusing on implementing podcast search functionality using the Podcast Index API. This blog post covers what we built in that stream, but you can watch the recording of the stream here

Graph Data Modeling

When beginning a new project I always like to start with a data modeling exercise. In my mind graph data modeling is an iterative process that begins as soon as you start defining the business requirements of the application. The steps of the graph data modeling iterative process:

Identify the entities. These become nodes. How are these entities connected? These connections become relationships. What attributes describe the entities? These become node properties. What attributes are specific to how entities are connected? These become relationship properties.

Once you have an initial model, work through the business requirements, and try to identify a traversal through the graph model that fulfills the requirement. If you can’t traverse the graph to answer the necessary question, you may need to update the graph model.

After going through this process initially, we ended up with a graph model that looks like this (created using the Arrows graph diagramming tool.)

Podcast Search

The first feature I wanted to implement is podcast search since that’s the first thing our users will want to do. Our GRANDstack application will be powered by a GraphQL API so we want to expose this podcast search functionality in our GraphQL API. We’ll make use of GRANDstack’s @cypher schema directive functionality for adding custom logic to implement this podcast search functionality, but instead of searching a Neo4j database, we'll query a 3rd party API endpoint to search for podcasts.

Podcast Index

We don’t want to maintain an index of all possible podcasts in existence, instead, we’ll use a 3rd party API to enable searching for podcasts, in this case, a service called the Podcast Index. The Podcast Index is committed to maintaining an open API of podcasts for the preservation of free speech. In line with its goal, anyone can register for an API token and begin building an application using its API.

Searching Endpoint

Looking at the API docs for the Podcast Index we can see there is an API endpoint for searching for podcasts. To use this endpoint we include a single query parameter which is our search term:

/api/1.0/search/byterm?q=neo4j

{

"status": "true",

"feeds": [

{

"id": 969306,

"title": "Graphistania: Podcast for Neo4j Graph Database community",

"url": "http://feeds.soundcloud.com/users/soundcloud:users:141739624/sounds.rss",

"originalUrl": "http://feeds.soundcloud.com/users/soundcloud:users:141739624/sounds.rss",

"link": "http://blog.bruggen.com",

"description": "Podcast by The Neo4j Graph Database Community",

"author": "The Neo4j Graph Database Community",

"ownerName": "Graphistania",

"image": "http://i1.sndcdn.com/avatars-000135096101-qekfg1-original.png",

"artwork": "http://i1.sndcdn.com/avatars-000135096101-qekfg1-original.png",

"lastUpdateTime": 1606220307,

"lastCrawlTime": 1607132366,

"lastParseTime": 1606220308,

"lastGoodHttpStatusTime": 1607132366,

"lastHttpStatus": 200,

"contentType": "application/rss+xml; charset=utf-8",

"itunesId": 975377379,

"generator": null,

"language": "en",

"type": 0,

"dead": 0,

"crawlErrors": 0,

"parseErrors": 0,

"categories": {

"102": "Technology"

},

"locked": 0,

"imageUrlHash": 775621088

}

],

"count": 1,

"query": "neo4j",

"description": "Found matching feeds."

}

Authorization Headers

According to the Podcast Index API documentation, each request need to be authenticated using “Amazon style” request authorization token headers. This means that each request must include the following headers:

User-Agent - to identify our application "GRANDcast.FM"

- to identify our application "GRANDcast.FM" X-Auth-Date - the current unix epoch time, expressed in seconds.

- the current unix epoch time, expressed in seconds. X-Auth-Key - our API key. We can get a free API key simply by registering.

- our API key. We can get a free API key simply by registering. Authorization - a SHA1 hash of our API key, API secret, and the current unix epoch time concatenated together

Since we want to use the @cypher schema directive to query the Podcast Index, we'll need to format and parse the request to this API using Cypher. How can we make a HTTP request, format the request headers, and parse a JSON response with Cypher?

APOC to the Rescue

Fortunately, the APOC standard library for Neo4j has some helpful procedures and functions that will enable us to query the Podcast Index API with Cypher. We’ll make use of the following APOC procedures and functions:

apoc.load.jsonParams - load data from a JSON URL, including passing a request payload and our authorization headers

- load data from a JSON URL, including passing a request payload and our authorization headers apoc.static.get - reading static values such as API credentials from a config file so we don't have to check our secrets into version control

- reading static values such as API credentials from a config file so we don't have to check our secrets into version control apoc.util.sha1 - compute the SHA1 hash of a string. We'll use this to compute the hash for the Authorization token in our request.

- compute the SHA1 hash of a string. We'll use this to compute the hash for the token in our request. apoc.text.urlencode - encode text so it can be safely used in a URL. We use this URL encode the search term parameter.

- encode text so it can be safely used in a URL. We use this URL encode the search term parameter. apoc.map.values - convert a map into a list of values. We'll use this to work with the categories data for podcast search results.

First, we’ll add our API credentials from Podcast Index to apoc.conf :

apoc.static.podcastkey=<YOUR_API_KEY_HERE>

apoc.static.podcastsecret=<YOUR_API_SECRET_HERE>

We’ll now be able to reference these values using the apoc.static.get() function.

Putting everything together the Cypher query to search for podcasts using the Podcast Index API endpoint looks like this:

WITH toString(timestamp()/1000) AS timestamp

WITH {

`User-Agent`: "GRANDstackFM",

`X-Auth-Date`: timestamp,

`X-Auth-Key`: apoc.static.get('podcastkey'),

`Authorization`: apoc.util.sha1([apoc.static.get('podcastkey') + apoc.static.get('podcastsecret') + timestamp])

} AS headers

CALL apoc.load.jsonParams("https://api.podcastindex.org/api/1.0/search/byterm?q=" + apoc.text.urlencode($searchTerm), headers, '', '') YIELD value

RETURN value

GraphQL API

Now that we’re able to use Cypher to search for podcasts it’s time to start building our GraphQL API. We’ll use the create-grandstack-app command line tool to quickly create the skeleton for our GraphQL server application.

create-grandstack-app

The create-grandstack-app CLI is a utility for creating GRANDstack applications based on the GRANDstack starter project. Here we'll use it to create the GraphQL server application, but not the frontend since we're not ready to start thinking about the client application yet.

npx create-grandstack-app grandstack.fm

This command will fetch the latest release of the GRANDstack Starter project and ask us a few questions about how to connect to our Neo4j database.

We now have a functional GraphQL server application in the grandcast.fm/ directory that can serve a GraphQL endpoint backed by our local Neo4j database. Since we selected the API-Only option we don't yet have a frontend for the application.

@cypher GraphQL Schema Directive

Now it’s time to edit the GraphQL type definitions of our GraphQL server application. We want to:

create a Query field podcastSearch that returns a list of PodcastSearchResult objects

field that returns a list of objects add the Cypher query we wrote above as a @cypher schema directive, defining the logic for this podcastSearch field

schema directive, defining the logic for this field the podcastSearch field will take a String argument searchTerm that will be passed as a Cypher parameter to the indicated Cypher query

We’ll replace the template type definitions found in grandstack.fm/api/src/schema.graphql with the following:

type Query {

podcastSearch(searchTerm: String!): [PodcastSearchResult]

@cypher(

statement: """

WITH toString(timestamp()/1000) AS timestamp

WITH {

`User-Agent`: "GRANDstackFM",

`X-Auth-Date`: timestamp,

`X-Auth-Key`: apoc.static.get('podcastkey'),

`Authorization`: apoc.util.sha1([apoc.static.get('podcastkey')+apoc.static.get('podcastsecret') +timestamp])

} AS headers

CALL apoc.load.jsonParams("https://api.podcastindex.org/api/1.0/search/byterm?q=" + apoc.text.urlencode($searchTerm), headers, '', '') YIELD value

UNWIND value.feeds AS feed

RETURN {

itunesId: feed.itunesId,

title: feed.title,

description: feed.description,

feedURL: feed.url,

artwork: feed.artwork,

categories: apoc.map.values(feed.categories, keys(feed.categories))

}

"""

)

} type PodcastSearchResult {

itunesId: String

title: String

description: String

feedURL: String

artwork: String

categories: [String]

}

Next, in src/index.js we'll add the PodcastSearchResult to the types to be excluded from the schema augmentation process. Since this type represents results from the Podcast Index API call we don't want to generate query and mutation operations for this type. We'll also comment out the init(driver) line to initialize the database, saving that for later.

We’ll leave the rest of the file untouched:

import { typeDefs } from './graphql-schema';

import { ApolloServer } from 'apollo-server-express';

import express from 'express';

import neo4j from 'neo4j-driver';

import { makeAugmentedSchema } from 'neo4j-graphql-js';

import dotenv from 'dotenv';

import { initializeDatabase } from './initialize'; // set environment variables from .env

dotenv.config(); const app = express(); /*

* Create an executable GraphQL schema object from GraphQL type definitions

* including autogenerated queries and mutations.

* Optionally a config object can be included to specify which types to include

* in generated queries and/or mutations. Read more in the docs:

* https://grandstack.io/docs/neo4j-graphql-js-api.html#makeaugmentedschemaoptions-graphqlschema

*/ const schema = makeAugmentedSchema({

typeDefs,

config: {

query: {

exclude: ['PodcastSearchResult']

},

mutation: {

exclude: ['PodcastSearchResult']

}

}

}); /*

* Create a Neo4j driver instance to connect to the database

* using credentials specified as environment variables

* with fallback to defaults

*/

const driver = neo4j.driver(

process.env.NEO4J_URI || 'bolt://localhost:7687',

neo4j.auth.basic(

process.env.NEO4J_USER || 'neo4j',

process.env.NEO4J_PASSWORD || 'neo4j'

),

{

encrypted: process.env.NEO4J_ENCRYPTED ? 'ENCRYPTION_ON' : 'ENCRYPTION_OFF'

}

); /*

* Perform any database initialization steps such as

* creating constraints or ensuring indexes are online

*

*/

const init = async (driver) => {

await initializeDatabase(driver);

}; /*

* We catch any errors that occur during initialization

* to handle cases where we still want the API to start

* regardless, such as running with a read only user.

* In this case, ensure that any desired initialization steps

* have occurred

*/ //init(driver) /*

* Create a new ApolloServer instance, serving the GraphQL schema

* created using makeAugmentedSchema above and injecting the Neo4j driver

* instance into the context object so it is available in the

* generated resolvers to connect to the database.

*/

const server = new ApolloServer({

context: { driver, neo4jDatabase: process.env.NEO4J_DATABASE },

schema: schema,

introspection: true,

playground: true

}); // Specify host, port and path for GraphQL endpoint

const port = process.env.GRAPHQL_SERVER_PORT || 4001;

const path = process.env.GRAPHQL_SERVER_PATH || '/graphql';

const host = process.env.GRAPHQL_SERVER_HOST || '0.0.0.0'; /*

* Optionally, apply Express middleware for authentication, etc

* This also also allows us to specify a path for the GraphQL endpoint

*/

server.applyMiddleware({ app, path }); app.listen({ host, port, path }, () => {

console.log(`GraphQL server ready at http://${host}:${port}${path}`);

});

Querying with GraphQL

We can now start our GraphQL server application and start searching for podcasts:



...

Successfully compiled 6 files with Babel (411ms).

GraphQL server ready at ➜ npm run start...Successfully compiled 6 files with Babel (411ms).GraphQL server ready at http://0.0.0.0:4001/graphql

Now our GraphQL server application is running locally at localhost:4001/graphql . If we open up a web browser and navigate to that URL we'll see the GraphQL Playground tool. GraphQL Playground allows us to view the results of introspection of our GraphQL endpoint. This allows us to see the entry points for the GraphQL schema (the Query , Mutation , and Subscription fields) as well as the types, fields, and how the types are connected, essentially the schema of the API.

Let’s query the GraphQL endpoint to find podcasts using the search term “Neo4j”:

{

podcastSearch(searchTerm: "Neo4j") {

title

description

artwork

feedURL

itunesId

categories

}

}

We now have a GraphQL API to enable our users to search for podcasts. Next, we’ll need to enable users to subscribe to podcasts and for that to work we’ll need to think about how to add users and enable them to log in and authenticate. So that’s what we’ll focus on next time.

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