Cursors

Many operations provided by the driver (e.g. executing AQL queries) return result cursors to batch the network communication between ArangoDB server and the client. Each HTTP request from a cursor fetches the next batch of results (usually documents). Depending on the query, the total number of items in the result set may or may not be known in advance.

Example:

from arangoasync import ArangoClient
from arangoasync.auth import Auth

# Initialize the client for ArangoDB.
async with ArangoClient(hosts="http://localhost:8529") as client:
    auth = Auth(username="root", password="passwd")

    # Connect to "test" database as root user.
    db = await client.db("test", auth=auth)

    # Set up some test data to query against.
    await db.collection("students").insert_many([
        {"_key": "Abby", "age": 22},
        {"_key": "John", "age": 18},
        {"_key": "Mary", "age": 21},
        {"_key": "Suzy", "age": 23},
        {"_key": "Dave", "age": 20}
    ])

    # Execute an AQL query which returns a cursor object.
    cursor = await db.aql.execute(
        "FOR doc IN students FILTER doc.age > @val RETURN doc",
        bind_vars={"val": 17},
        batch_size=2,
        count=True
    )

    # Get the cursor ID.
    cid = cursor.id

    # Get the items in the current batch.
    batch = cursor.batch

    # Check if the current batch is empty.
    is_empty = cursor.empty()

    # Get the total count of the result set.
    cnt = cursor.count

    # Flag indicating if there are more to be fetched from server.
    has_more = cursor.has_more

    # Flag indicating if the results are cached.
    is_cached = cursor.cached

    # Get the cursor statistics.
    stats = cursor.statistics

    # Get the performance profile.
    profile = cursor.profile

    # Get any warnings produced from the query.
    warnings = cursor.warnings

    # Return the next item from the cursor. If current batch is depleted, the
    # next batch is fetched from the server automatically.
    await cursor.next()

    # Return the next item from the cursor. If current batch is depleted, an
    # exception is thrown. You need to fetch the next batch manually.
    cursor.pop()

    # Fetch the next batch and add them to the cursor object.
    await cursor.fetch()

    # Delete the cursor from the server.
    await cursor.close()

See arangoasync.cursor.Cursor for API specification.

Cursors can be used together with a context manager to ensure that the resources get freed up when the cursor is no longer needed. Asynchronous iteration is also supported, allowing you to iterate over the cursor results without blocking the event loop.

Example:

from arangoasync import ArangoClient
from arangoasync.auth import Auth
from arangoasync.exceptions import CursorCloseError

# Initialize the client for ArangoDB.
async with ArangoClient(hosts="http://localhost:8529") as client:
    auth = Auth(username="root", password="passwd")

    # Connect to "test" database as root user.
    db = await client.db("test", auth=auth)

    # Set up some test data to query against.
    await db.collection("students").insert_many([
        {"_key": "Abby", "age": 22},
        {"_key": "John", "age": 18},
        {"_key": "Mary", "age": 21},
        {"_key": "Suzy", "age": 23},
        {"_key": "Dave", "age": 20}
    ])

    # Execute an AQL query which returns a cursor object.
    cursor = await db.aql.execute(
        "FOR doc IN students FILTER doc.age > @val RETURN doc",
        bind_vars={"val": 17},
        batch_size=2,
        count=True
    )

    # Iterate over the cursor in an async context manager.
    async with cursor as ctx:
        async for student in ctx:
            print(student)

    # The cursor is automatically closed when exiting the context manager.
    try:
        await cursor.close()
    except CursorCloseError:
        print(f"Cursor already closed!")

If the fetched result batch is depleted while you are iterating over a cursor (or while calling the method arangoasync.cursor.Cursor.next()), the driver automatically sends an HTTP request to the server in order to fetch the next batch (just-in-time style). To control exactly when the fetches occur, you can use methods like arangoasync.cursor.Cursor.fetch() and arangoasync.cursor.Cursor.pop() instead.

Example:

from arangoasync import ArangoClient
from arangoasync.auth import Auth

# Initialize the client for ArangoDB.
async with ArangoClient(hosts="http://localhost:8529") as client:
    auth = Auth(username="root", password="passwd")

    # Connect to "test" database as root user.
    db = await client.db("test", auth=auth)

    # Set up some test data to query against.
    await db.collection("students").insert_many([
        {"_key": "Abby", "age": 22},
        {"_key": "John", "age": 18},
        {"_key": "Mary", "age": 21}
    ])

    # You can manually fetch and pop for finer control.
    cursor = await db.aql.execute("FOR doc IN students RETURN doc", batch_size=1)
    while cursor.has_more: # Fetch until nothing is left on the server.
        await cursor.fetch()
    while not cursor.empty(): # Pop until nothing is left on the cursor.
        student = cursor.pop()
        print(student)

You can use the allow_retry parameter of arangoasync.aql.AQL.execute() to automatically retry the request if the cursor encountered any issues during the previous fetch operation. Note that this feature causes the server to cache the last batch. To allow re-fetching of the very last batch of the query, the server cannot automatically delete the cursor. Once you have successfully received the last batch, you should call arangoasync.cursor.Cursor.close(), or use a context manager to ensure the cursor is closed properly.

Example:

from arangoasync import ArangoClient
from arangoasync.auth import Auth
from arangoasync.typings import QueryProperties

# Initialize the client for ArangoDB.
async with ArangoClient(hosts="http://localhost:8529") as client:
    auth = Auth(username="root", password="passwd")

    # Connect to "test" database as root user.
    db = await client.db("test", auth=auth)

    # Set up some test data to query against.
    await db.collection("students").insert_many([
        {"_key": "Abby", "age": 22},
        {"_key": "John", "age": 18},
        {"_key": "Mary", "age": 21}
    ])

    cursor = await db.aql.execute(
        "FOR doc IN students RETURN doc",
        batch_size=1,
        options=QueryProperties(allow_retry=True)
    )

    while cursor.has_more:
        try:
            await cursor.fetch()
        except ConnectionError:
            # Retry the request.
            continue

    while not cursor.empty():
        student = cursor.pop()
        print(student)

    # Delete the cursor from the server.
    await cursor.close()

For more information about various query properties, see arangoasync.typings.QueryProperties.