Pgraphs NPM | npm.io

pgraphs

Property Graph Exchange Format (PG) converters

This package implements parsers and serializers to convert between labeled property graph formats and databases.

Background

A property graph (also known as labeled property graph) is an abstract data structure consisting of nodes and (possibly directed) edges between these nodes. Nodes and edges can each have labels and properties. Property graph formats and databases slightly differ in their data model by restrictions, support of data types etc.

This package implements the Property Graph Exchange Format (PG), aimed to be a superset of common models, with parsers and serializers from and to various formats.

Install

Default installation requires node >= 18.0.0 (or node >= 20.0.0 for development).

npm install -g pgraphs

To connect to Neo4J databases, also install:

npm install -g neo4j-driver-lite

Browser bundles have not been created yet.

Alternatively install as Docker image (see Docker usage below):

docker pull ghcr.io/pg-format/pgraphs

Usage

CLI

Command pgraph is installed with this package:

Usage: pgraph [options] [<source> [<target>]]

Convert between property graph formats and databases.

Options:
  -f, --from [format]   source format
  -t, --to [format]     target format
  -i, --id [key]        copy node id to property
  --html                generate HTML label
  -s, --scale [factor]  scale spatial properties x,y,width,height,pos
  -e, --errors          verbose error messages
  -q, --quiet           don't warn when graph is reduced
  -h, --help            show usage information
  -V, --version         show the version number

Supported conversion formats:
  pg         from/to PG format (default source format)
  json       from/to PG-JSON
  jsonl      from/to PG-JSONL (default target format)
  cypher     from/to Cypher CREATE statements
  neo4j      from/to Neo4J database (via Cypher query)
  dot        from/to GraphViz DOT
  tgf        from/to Trivial Graph Format
  canvas     from/to JSON Canvas (experimental)
  graphology from/to Graphology import/export
  ncol       from/to NCOL file format
  xml        to GraphML
  yarspg     to YARS-PG 5.0.0 without data types
  yarspg3    to YARS-PG 3.0.0 with optional labels
  csv        to OpenCypher/Neo4J CSV files
  neptune    to Neptune CSV import (aka Gremlin load data format)
  mmd        to Meermaid Flowchart (experimental)
  gexf       to Graph Exchange XML Format (GEXF)

Docker

Command pgraph is executable when installed as Docker image this way:

docker run -it --rm ghcr.io/pg-format/pgraphs

The long command can be abbreviated for instance with an alias:

alias pgraph='docker run -it --rm ghcr.io/pg-format/pgraphs'

Note that the command cannot access file outside of the Docker image by default, so usage is limited to reading/writing from/to standard input/output:

# this won't work
docker run -i ghcr.io/pg-format/pgraphs graph.pg graph.jsonl

# this will
<graph.pg docker run -i ghcr.io/pg-format/pgraphs > graph.jsonl

API

Programming API may still change. Try this or look at the sources:

import { pgformat, ParsingError } from "pgraphs"

const graph = {
  nodes: [ ... ],
  edges: [ ... ] 
}

try {
  const pgstring = pgformat.pg.serialize(graph)
  const graph = pgformat.pg.parse(pgstring)
} catch (ParsingError e) {
  console.log(`Parsing failed in line ${e.line}`)
}

Formats

Many formats and conventions exist to store labeled property graphs. Each format comes with a syntax and a limited or extended data model of property graphs: not every feature can be expressed in every format! The following table lists all formats and systems known by know and whether they can be read and/or written from with this package:

read	write	format or database
yes	yes	PG format
yes	yes	PG-JSON
yes	yes	PG-JSONL
yes	yes	Cypher CREATE
yes	yes	Neo4J or compatible
yes	yes	Trivial Graph Format (TGF)
yes	yes	GraphViz DOT
yes	yes	JSON Canvas
yes	yes	Graphology
yes	yes	NCOL
	yes	GraphML
	yes	GEXF
	yes	YARS-PG
	yes	OpenCypher/Neo4J CSV
	yes	Amazon Neptune CSV
	yes	Mermaid

The repository of pgraphs contains a CSV file and equivalent pg file listing these and more graph formats with their capabilities to store selected graph features.

PG format

PG format was first proposed by Hirokazu Chiba, Ryota Yamanaka, and Shota Matsumoto (2019, 2022). A revision is currently taking place to get to a final specification.

The following graph in PG format with two nodes and two edges uses features such as multiple labels, and property values, numbers and boolean values:

101 :person name:Alice name:Carol country:"United States"
102 :person :student  name:Bob  country:Japan
101 -- 102  :same_school  :same_class  since:2012
101 -> 102  :likes  since:2015  engaged:false

PG JSON and JSONL

The same graph in PG-JSON and in PG-JSONL:

{
  "nodes": [{
    "id": "101", "labels": [ "person" ],
    "properties": { "name": [ "Alice", "Carol" ], "country": [ "United States" ] }
   },{
    "id": "102", "labels": [ "person", "student" ],
    "properties": { "name": [ "Bob" ], "country": [ "Japan" ] }
  }],
  "edges": [{
    "from": "101", "to": "102", "undirected": true,
    "labels": [ "same_school", "same_class" ], "properties": { "since": [ 2012 ] }
   },{
    "from": "101", "to": "102",
    "labels": [ "likes" ], "properties": { "engaged": [ false ], "since": [ 2015 ] }
  }]
}

{"id":"101","labels":["person"],"properties":{"name":["Alice","Carol"],"country":["United States"]}}
{"id":"102","labels":["person","student"],"properties":{"name":["Bob"],"country":["Japan"]}}
{"from":"101","to":"102","labels":["same_school","same_class"],"properties":{"since":[2012]},"undirected":true}
{"from":"101","to":"102","labels":["likes"],"properties":{"since":[2015],"engaged":[false]}}

There is also a JSON Schema for PG-JSON. and a JSON Schema for PG-JSONL.

GraphViz DOT

When exported to GraphViz DOT format, labels are ignored and edges become either all undirected or stay all directed.

graph {
  101 [country="United States" name=Alice];
  102 [country=Japan name=Bob];
  101 -- 102 [since=2012];
  101 -- 102 [since=2015];
}

Graphviz can generate image files from DOT, so pgraph can be used to create diagrams from any other graph source:

pgraph graph.pg -t dot | dot -Tsvg -o graph.svg

With option --html the full labels and properties of nodes and edges are converted to HTML labels, resulting in the following diagram:

npm.io

GraphML

When exported to GraphML, labels are ignored and all values are converted to strings:

<?xml version="1.0" encoding="UTF-8"?>
<graphml xmlns="http://graphml.graphdrawing.org/xmlns">
  <graph edgedefault="undirected">
    <node id="101">
      <data key="country">United States</data>
      <data key="name">Alice</data>
      <data key="name">Carol</data>
    </node>
    <node id="102">
      <data key="country">Japan</data>
      <data key="name">Bob</data>
    </node>
    <edge source="101" target="102">
      <data key="since">2012</data>
    </edge>
    <edge source="101" target="102">
      <data key="engaged">false</data>
      <data key="since">2015</data>
    </edge>
  </graph>
</graphml>

GEXF

When exported to GEXF 1.3, labels but the first edge label and multi-edges of same label are ignored. Export of properties as GEXF attributes has not been implemented yet, so this export format is experimental.

Cypher CREATE

The example graph in Cypher language with CREATE statements. The undirected edge is ignored because Cypher only supports directed edges:

CREATE (`101`:person {name:["Alice","Carol"], country:"United States"})
CREATE (`102`:person:student {name:"Bob", country:"Japan"})
CREATE (`101`)-[:likes {since:2015, engaged:false}]->(`102`)

Further differences between PG data model and Cypher include no support of null in property values and mixed types in repeated property values.

YARS-PG

Export to YARS-PG 5.0.0 is limited to nodes and edges without schema, so all property values are mapped to strings:

(node1{"person"}["country":"United States","name":["Alice","Carol"]])
(node2{"person","student"}["country":"Japan","name":"Bob"])
(node1)-["same_school"]["since":"2012"]-(node2)
(node1)-["likes"]["engaged":"false","since":"2015"]-(node2)

YARS-PG 3.0.0 supported data types without a schema but labels were mandatory. The exported format variant lifts this restriction, so the graph in this format is very similar to PG format:

<"101">{"person"}["country":"United States","name":["Alice","Carol"]]
<"102">{"person","student"}["country":"Japan","name":"Bob"]
("101")-["same_school"]["since":2012]-("102")
("101")-["likes"]["engaged":false,"since":2015]-("102")

CSV

Property graphs can be stored in form of separate CSV files for nodes and edges, respectively. An nearly common form these files is supported by Neo4J as CSV header format and by Amazon Neptune as OpenCypher CSV format. pgraph creates four files in csv format using the output as base name (with optional directory):

base + .nodes.headers and base + .nodes.csv with node data
base + .edges.header, and base + .edges.csv with edge data

The example graph is serialized as following, in four files:

:START_ID,:END_ID,:TYPE,since:int,engaged:boolean

101,102,same_school,2012
101,102,likes,2015,false

:ID,:LABEL,name:string[],country:string

101,person,Alice�Carol,United States
102,person;student,Bob,Japan

Repeated labels and property values are separated by a NULL-Byte (shown as � above) as array delimited to allow using arbitrary characters in these values and NULL-Bytes are removed from string values (see this Neo4J feature request). Configuration of this character to some other value is not supported yet.

Imported into a Neo4J database and exported again is serialized as following in PG. Thus conversion of property graphs between PG and Neo4J or Neptune should be round-trip apart from identifiers, undirected edges, semicolon, and support of additional data types:

1 :person country:"United States" name:Alice name:Carol
2 :person :student country:Japan name:Bob
1 -> 2 :same_school since:2012
1 -> 2 :likes engaged:false since:2015

Neptune CSV

Amazon Neptune graph database also supports import of property graph data in a CSV format called Gremlin load data format (but only by Amazon, not by Apache TinkerPop community). This CSV format is very similar to the more common CSV format but it also allows to escape the semicolon used as array delimiter as \;.

The example graph is serialized as following, in two files:

~id,~label,name:String[],country:String
101,person,Alice;Carol,United States
102,person;student,Bob,Japan

~id,~from,~to,~label,since:Int,engaged:Bool
0,101,102,same_school,2012
1,101,102,likes,2015,false

TGF

The Trivial Graph Format (TGF) is a text-based format to exchange labeled graphs. It does not support properties, multiple labels nor line breaks in labels. The example graph is serialized as following:

1 person
2 person
#
1 2 same_school
1 2 likes

Parsed back from TGF and serialized as PG format, this is equivalent to:

1 :person
2 :person
1 -> 2 :same_school
1 -> 2 :likes

JSON Canvas

The spatial hypertext JSON Canvas format can store a spatial graph with nodes of text (in Markdown), links, or files. Each node requires a position and size at least. The corresponding properties (width, height, x, y) are not included in the example graph but GraphViz can be used to generate them. As GraphViz uses dpi instead of pixel, the numbers should be scaled with pgraph option --scale. This command line pipeline generates a JSON Canvas from the example graph:

pgraph examples/example.pg -t dot | dot | pgraph -f dot -s 4 -t canvas

To transform a DOT file graph.dot into JSON Canvas:

dot graph.dot | pgraph -f dot -s 4 -t canvas > graph.canvas

JSON Canvas can be read as well, but not all features are supported.

Mermaid

Export to Mermaid is experimental and may lead to syntactically invalid Marmaid files because there is no formal specification and because some characters cannot be escaped. Mermaid supports HTML in names of nodes and edges (property name) but HTML attributes must be single-quoted (<a href='...' instead of <a href="...") and numeric character entities cannot be used.

By default the example graph is exported to this Mermaid diagram source:

flowchart LR
    101["Alice"]
    102["Bob"]
    101 --- 102
    101 --> 102

mermaid-cli can be used to generate image files from Mermaid diagram files or from any other graph source:

pgraph graph.pg --html -t mmd | mmdc -i - -o graph.svg

With option --html the full labels and properties of nodes and edges are converted to HTML labels, resulting in the following diagram:

npm.io

NCOL

The NCOL file format is used to visualize very large undirected graphs with Large Graph Layout software. The graph is eventually reduced to simple edges with optional weight, but extensions exist for coloring and node labels (not supported by this library).

Databases

pgraphs can directly connect to some graph databases for import and/or export.

Neo4J

Format neo4j requires to install node package neo4j-driver (done automatically by calling npm install unless pgraphs package is installed as dependency of another project) and expects a JSON file with Neo4J database Bolt-API URI and credentials as source or target. Use the following for a default installation on your local machine:

{
  "uri": "neo4j://localhost",
  "user": "",
  "password": ""
}

Reading from a database uses a Cypher MATCH query. Writing into a database uses the list of Cypher CREATE queries as exported with Cypher target format, so the following should be equivalent:

pgraphs graph.pg query.cypher and manually execute query query.cypher
pgraphs -t neo4j pgraph.pg neo4j.json

Reading from and writing to other graph database systems supporting Cypher and Bolt protocol (Memgraph, Kuzú, FalkorDB, TuGraph...) may be possible but has not been tested so far.

For larger graphs better export in CSV format to multiple files and bulk import the CSV files with neo4j-admin database import and these options:

--delimiter=","
--array-delimiter="\0" (NULL-Byte)

Cypher command LOAD CSV will not work because it expects an additional MERGE clause and node/edges must have uniform labels.

The pgraphs git repository contains shell scripts in directory neo4j to run a local Neo4J instance with Docker and to bulk import CSV files from local directly ./import.

License

Licensed under the MIT License.

A first version of the PG model and its serializations PG format and PG-JSON have been proposed by Hirokazu Chiba, Ryota Yamanaka, and Shota Matsumoto (2019, 2022).