Serialization¶

Graphio can serialize NodeSet and RelationshipSet objects to different formats. This can be used to store processed, graph-ready data in a file.

Graphio supports the following formats for both NodeSet and RelationshipSet objects:

combined CSV and JSON files (CSV file with all data and JSON file with metadata), can be deserialized again
CSV files with all data (useful for quick tests, cannot be fully deserialized again)
JSON files with all data (useful for quick tests with small datasets, contains redundant data)

Combined CSV and JSON files¶

The most useful serialization format stores the data in a CSV file and the metadata in a JSON file. This avoids redundancy and allows to deserialize the data again.

Data Format¶

Nodes¶

The JSON file with metadata contains at least the following information:

the labels (labels)
property keys used for MERGE operations (merge_keys)

The csv file contains the properties of one node per row, the header contains the property keys.

Example:

nodeset.json:

{
    "labels": [
        "Person"
    ],
    "merge_keys": [
        "name"
    ]
}

nodeset.csv:

name,age
Lisa,42
Bob,23

Relationships¶

The JSON file with metadata contains at least the following information:

start node labels
end node labels
start node property keys to MATCH the start node
end node property keys to MATCH the end node
relationship type

The csv file contains one relationship per row, the start node, end node, and relationship properties are indicated by header prefixes (start_, end_, rel_).

Example:

relset.json:

{
  "start_node_labels": ["Person"],
  "end_node_labels": ["Person"],
  "start_node_properties": ["name"],
  "end_node_properties": ["name"],
  "rel_type": "KNOWS"
}

relset.csv:

start_name,end_name,rel_since
Lisa,Bob,2018
Bob,Lisa,2018

Serialize to CSV and JSON¶

To serialize a NodeSet or RelationshipSet object use to_csv_json_set():

people = NodeSet(['Person'], merge_keys=['name']

people.add_node({'name': 'Lisa'})
people.add_node({'name': 'Bob'})

people.to_csv_json_set('people.json', 'people.csv')

knows = RelationshipSet('KNOWS', ['Person'], ['Person'], ['name'], ['name'])
knows.add_relationship({'name': 'Lisa'}, {'name': 'Bob'}, {'since': '2018'})

knows.to_csv_json_set('knows.json', 'knows.csv')

CSV files¶

Graphio can serialize NodeSet and RelationshipSet objects to CSV files in the same format as the CSV files in the combined CSV/JSON format. This can be useful for quick tests with small datasets.

See NodeSet.to_csv() and RelationshipSet.to_csv() for details:

people = NodeSet(['Person'], merge_keys=['name']

people.add_node({'name': 'Lisa'})
people.add_node({'name': 'Bob'})

people.to_csv('nodeset.csv')

knows = RelationshipSet('KNOWS', ['Person'], ['Person'], ['name'], ['name'])
knows.add_relationship({'name': 'Lisa'}, {'name': 'Bob'}, {'since': '2018'})

knows.to_csv('relset.csv')

Graphio can generate matching Cypher queries to load these CSV files to Neo4j:

# NodeSet CREATE query
people.create_csv_query('nodeset.csv')

# NodeSet MERGE query
people.merge_csv_query('nodeset.csv')

# RelationshipSet CREATE query
knows.create_csv_query('relset.csv')

JSON files¶

note:	Deserialization of simple JSON representations is currently not supported. Use the combined JSON/CSV format instead. The JSON serialization can still be useful to test small datasets.

NodeSet and RelationshipSet objects can be serialized to JSON:

people = NodeSet(['Person'], merge_keys=['name']

people.add_node({'name': 'Lisa'})

people.to_json('nodeset.json')

This will create a JSON file with full node descriptions:

nodeset.json:

{
  "labels": [
      "Person"
  ],
  "merge_keys": [
      "name"
  ],
  "nodes": [
      {
          "name": "Lisa"
      }
  ]
}

The same works with RelationshipSet objects:

person_like_food = RelationshipSet('LIKES', ['Person'], ['Food'], ['name'], ['type'])

person_like_food.add_relationship({'name': 'Lisa'}, {'type': 'Sushi'}, {'since': 'always'})

person_like_food.to_json('relset.json')