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.