python-arango

Python-Arango

Python driver for ArangoDB, a scalable multi-model database natively supporting documents, graphs and search.

If you're interested in using asyncio, please check python-arango-async.

Requirements

• ArangoDB version 3.11+
• Python version 3.9+

Installation

pip install python-arango --upgrade

Getting Started

Here is a simple usage example:

from arango import ArangoClient

# Initialize the client for ArangoDB.
client = ArangoClient(hosts="http://localhost:8529")

# Connect to "_system" database as root user.
sys_db = client.db("_system", username="root", password="passwd")

# Create a new database named "test".
sys_db.create_database("test")

# Connect to "test" database as root user.
db = client.db("test", username="root", password="passwd")

# Create a new collection named "students".
students = db.create_collection("students")

# Add a persistent index to the collection.
students.add_index({'type': 'persistent', 'fields': ['name'], 'unique': True})

# Insert new documents into the collection.
students.insert({"name": "jane", "age": 39})
students.insert({"name": "josh", "age": 18})
students.insert({"name": "judy", "age": 21})

# Execute an AQL query and iterate through the result cursor.
cursor = db.aql.execute("FOR doc IN students RETURN doc")
student_names = [document["name"] for document in cursor]

Another example with graphs:

from arango import ArangoClient

# Initialize the client for ArangoDB.
client = ArangoClient(hosts="http://localhost:8529")

# Connect to "test" database as root user.
db = client.db("test", username="root", password="passwd")

# Create a new graph named "school".
graph = db.create_graph("school")

# Create a new EnterpriseGraph [Enterprise Edition]
eegraph = db.create_graph(
    name="school",
    smart=True)

# Create vertex collections for the graph.
students = graph.create_vertex_collection("students")
lectures = graph.create_vertex_collection("lectures")

# Create an edge definition (relation) for the graph.
edges = graph.create_edge_definition(
    edge_collection="register",
    from_vertex_collections=["students"],
    to_vertex_collections=["lectures"]
)

# Insert vertex documents into "students" (from) vertex collection.
students.insert({"_key": "01", "full_name": "Anna Smith"})
students.insert({"_key": "02", "full_name": "Jake Clark"})
students.insert({"_key": "03", "full_name": "Lisa Jones"})

# Insert vertex documents into "lectures" (to) vertex collection.
lectures.insert({"_key": "MAT101", "title": "Calculus"})
lectures.insert({"_key": "STA101", "title": "Statistics"})
lectures.insert({"_key": "CSC101", "title": "Algorithms"})

# Insert edge documents into "register" edge collection.
edges.insert({"_from": "students/01", "_to": "lectures/MAT101"})
edges.insert({"_from": "students/01", "_to": "lectures/STA101"})
edges.insert({"_from": "students/01", "_to": "lectures/CSC101"})
edges.insert({"_from": "students/02", "_to": "lectures/MAT101"})
edges.insert({"_from": "students/02", "_to": "lectures/STA101"})
edges.insert({"_from": "students/03", "_to": "lectures/CSC101"})

# Traverse the graph in outbound direction, breath-first.
query = """
    FOR v, e, p IN 1..3 OUTBOUND 'students/01' GRAPH 'school'
    OPTIONS { bfs: true, uniqueVertices: 'global' }
    RETURN {vertex: v, edge: e, path: p}
    """
cursor = db.aql.execute(query)

Please see the documentation for more details.