from arango import Arango # Initialize ArangoDB connection a = Arango(host="localhost", port=8529)

# List the database names a.databases a.databases["user"] a.databases["system"] # Get information on the default database ("_system") a.name # equivalent to a.db("_system").name a.collections # equivalent to a.db("_system").collections a.id # equivalent to a.db("_system").id a.path # equivalent to a.db("_system").path a.is_system # equivalent to a.db("_system").is_system # Get information on a specific database a.db("db01").collections a.db("db02").id a.db("db03").path a.db("dbXX").is_system # Create a new database a.add_database("my_db") # Remove a database a.remove_database("my_db") # Working with database "_system" a.add_collection("my_col") a.col("my_col").add_document({"value" : 1}) a.{whatever} # Working with database "my_db" a.db("my_db").add_collection("my_col") a.db("my_db").col("my_col").add_document({"value": 1}) a.db("my_db").{whatever}

my_db = a.db("my_db") # List the AQL functions defined in database "my_db" my_db.aql_functions # Add a new AQL function my_db.add_aql_function( "myfunctions::temperature::ctof", "function (celsius) { return celsius * 1.8 + 32; }" ) # Remove an AQL function my_db.remove_aql_function("myfunctions::temperature::ctof")

# Retrieve the execution plan without actually executing it my_db.explain_query("FOR doc IN my_col RETURN doc") # Validate the AQL query without actually executing it my_db.validate_query("FOR doc IN my_col RETURN doc") # Execute the AQL query and iterate through the AQL cursor cursor = my_db.execute_query( "FOR d IN my_col FILTER d.value == @val RETURN d", bind_vars={"val": "foobar"} ) for doc in cursor: # the cursor is deleted when the generator is exhausted print doc

my_db = a.db("my_db") # List the collection names in "my_db" my_db.collections my_db.collections["user"] my_db.collecitons["system"] my_db.collections["all"] # Add a new collection my_db.add_collection("new_col") # Add a new edge collection my_db.add_collection("new_ecol", is_edge=True) # Rename a collection my_db.rename_collection("new_col", "my_col") # Remove a collection from the database my_db.remove_collection("my_col") # Retrieve collection information my_col = a.db("my_db").col("my_col") len(my_col) == my_col.count my_col.properties my_col.id my_col.status my_col.key_options my_col.wait_for_sync my_col.journal_size my_col.is_system my_col.is_edge my_col.do_compact my_col.figures my_col.revision # Modify collection properties (only the modifiable ones) my_col.wait_for_sync = False my_col.journal_size = new_journal_size # Load the collection into memory my_col.load() # Unload the collection from memory my_col.unload() # Rotate the collection journal my_col.rotate_journal() # Return the checksum of the collection my_col.checksum(with_rev=True, with_data=True) # Remove all documents in the collection my_col.truncate() # Check if a document exists in the collection my_col.contains("a_document_key") "a_document_key" in my_col

my_col = a.collection("my_col") # or a.col("mycol") # List the indexes in collection "my_col" my_col.indexes # Add a unique hash index on attributes "attr1" and "attr2" my_col.add_hash_index(fields=["attr1", "attr2"], unique=True) # Add a cap constraint my_col.add_cap_constraint(size=10, byte_size=40000) # Add a unique skiplist index on attributes "attr1" and "attr2" my_col.add_skiplist_index(["attr1", "attr2"], unique=True) # Examples of adding a geo-spatial index on 1 (or 2) coordinate attributes my_col.add_geo_index(fields=["coordinates"]) my_col.add_geo_index(fields=["longitude", "latitude"]) # Add a fulltext index on attribute "attr1" my_col.add_fulltext_index(fields=["attr1"], min_length=10)

my_col = a.db("my_db").collection("my_col") # Retrieve a document by its key my_col.get_document("doc01") # Add a new document ("_key" attribute is optional) my_col.add_document({"_key": "doc01", "value": 1}) # Replace a document my_col.replace_document("doc01", {"value": 2}) # Update a document my_col.update_document("doc01", {"another_value": 3}) # Remove a document my_col.remove_document("doc01") # Iterate through the documents in a collection and update them for doc in my_col: new_value = doc["value"] + 1 my_col.update_document(doc["_key"], {"new_value": new_value})

# Return the first 5 documents in collection "my_col" my_col.first(5) # Return the last 3 documents my_col.last(3) # Return all documents (cursor generator object) my_col.all() list(my_col.all()) # Return a random document my_col.any() # Return first document whose "value" is 1 my_col.get_first_example({"value": 1}) # Return all documents whose "value" is 1 my_col.get_by_example({"value": 1}) # Update all documents whose "value" is 1 with a new attribute my_col.update_by_example( {"value": 1}, new_value={"new_attr": 1} ) # Return all documents within a radius around a given coordinate (requires geo-index) my_col.within(latitude=100, longitude=20, radius=15) # Return all documents near a given coordinate (requires geo-index) my_col.near(latitude=100, longitude=20)

my_db = a.db("my_db") # List all the graphs in the database my_db.graphs # Add a new graph my_graph = my_db.add_graph("my_graph") # Add new vertex collections to a graph my_db.add_collection("vcol01") my_db.add_collection("vcol02") my_graph.add_vertex_collection("vcol01") my_graph.add_vertex_collection("vcol02") # Add a new edge definition to a graph my_db.add_collection("ecol01", is_edge=True) my_graph.add_edge_definition( edge_collection="ecol01", from_vertex_collections=["vcol01"], to_vertex_collections=["vcol02"], ) # Retrieve graph information my_graph.properties my_graph.id my_graph.revision my_graph.edge_definitions my_graph.vertex_collections my_graph.orphan_collections

# Add new vertices (again if "_key" is not given it's auto-generated) my_graph.add_vertex("vcol01", {"_key": "v01", "value": 1}) my_graph.add_vertex("vcol02", {"_key": "v01", "value": 1}) # Replace a vertex my_graph.replace_vertex("vol01/v01", {"value": 2}) # Update a vertex my_graph.update_vertex("vol02/v01", {"new_value": 3}) # Remove a vertex my_graph.remove_vertex("vol01/v01")

# Add a new edge my_graph.add_edge( "ecol01", # edge collection name { "_key": "e01", "_from": "vcol01/v01", # must abide the edge definition "_to": "vcol02/v01", # must abide the edge definition "foo": 1, "bar": 2, } ) # Replace an edge my_graph.replace_edge("ecol01/e01", {"baz": 2}) # Update an edge my_graph.update_edge("ecol01/e01", {"foo": 3}) # Remove an edge my_graph.remove_edge("ecol01/e01")

my_graph = a.db("my_db").graph("my_graph") # Execute a graph traversal results = my_graph.execute_traversal( start_vertex="vcol01/v01", direction="outbound", strategy="depthfirst" ) # Return the visited nodes in order results.get("visited") # Return the paths traversed in order results.get("paths")

# NOTE: only (add/update/replace/remove) methods for (documents/vertices/edges) are supported at the moment # Execute a batch request for managing documents my_db.execute_batch([ ( my_col.add_document, # method name [{"_key": "doc04", "value": 1}], # args {"wait_for_sync": True} # kwargs ), ( my_col.update_document, ["doc01", {"value": 2}], {"wait_for_sync": True} ), ( my_col.replace_document, ["doc02", {"new_value": 3}], {"wait_for_sync": True} ), ( my_col.remove_document, ["doc03"], {"wait_for_sync": True} ), ( my_col.add_document, [{"_key": "doc05", "value": 5}], {"wait_for_sync": True} ), ]) # Execute a batch request for managing vertexes self.db.execute_batch([ ( my_graph.add_vertex, ["vcol01", {"_key": "v01", "value": 1}], {"wait_for_sync": True} ), ( my_graph.add_vertex, ["vcol01", {"_key": "v02", "value": 2}], {"wait_for_sync": True} ), ( my_graph.add_vertex, ["vcol01", {"_key": "v03", "value": 3}], {"wait_for_sync": True} ), ])

# Execute a transaction action = """  function () {  var db = require('internal').db;  db.col01.save({ _key: 'doc01'});  db.col02.save({ _key: 'doc02'});  return 'success!';  } """ res = my_db.execute_transaction( action=action, read_collections=["col01", "col02"], write_collections=["col01", "col02"], wait_for_sync=True, lock_timeout=10000 )