Batches

Create / interact with a batch of updates / deletes.

Batches provide the ability to execute multiple operations in a single request to the Cloud Datastore API.

See https://cloud.google.com/datastore/docs/concepts/entities#Datastore_Batch_operations

class google.cloud.datastore.batch.Batch(client)

Bases: object

An abstraction representing a collected group of updates / deletes.

Used to build up a bulk mutation.

For example, the following snippet of code will put the two save operations and the delete operation into the same mutation, and send them to the server in a single API request:

>>> from google.cloud import datastore
>>> client = datastore.Client()
>>> batch = client.batch()
>>> batch.put(entity1)
>>> batch.put(entity2)
>>> batch.delete(key3)
>>> batch.commit()

You can also use a batch as a context manager, in which case commit() will be called automatically if its block exits without raising an exception:

>>> with batch:
...     batch.put(entity1)
...     batch.put(entity2)
...     batch.delete(key3)

By default, no updates will be sent if the block exits with an error:

>>> with batch:
...     do_some_work(batch)
...     raise Exception()  # rolls back

Parameters:client (google.cloud.datastore.client.Client) – The client used to connect to datastore.

begin()

Begins a batch.

This method is called automatically when entering a with statement, however it can be called explicitly if you don’t want to use a context manager.

Overridden by google.cloud.datastore.transaction.Transaction.

Raises:ValueError if the batch has already begun.

commit()

Commits the batch.

This is called automatically upon exiting a with statement, however it can be called explicitly if you don’t want to use a context manager.

Raises:ValueError if the batch is not in progress.

connection

Getter for connection over which the batch will run.

Return type:google.cloud.datastore.connection.Connection Returns:The connection over which the batch will run.

current()

Return the topmost batch / transaction, or None.

delete(key)

Remember a key to be deleted during commit().

Parameters:key (google.cloud.datastore.key.Key) – the key to be deleted. Raises:ValueError if the batch is not in progress, if key is not complete, or if the key’s project does not match ours.

mutations

Getter for the changes accumulated by this batch.

Every batch is committed with a single commit request containing all the work to be done as mutations. Inside a batch, calling put() with an entity, or delete() with a key, builds up the request by adding a new mutation. This getter returns the protobuf that has been built-up so far.

Return type:iterable Returns:The list of _generated.datastore_pb2.Mutation protobufs to be sent in the commit request.

namespace

Getter for namespace in which the batch will run.

Return type:str Returns:The namespace in which the batch will run.

project

Getter for project in which the batch will run.

Return type:str Returns:The project in which the batch will run.

put(entity)

Remember an entity’s state to be saved during commit().

Note

Any existing properties for the entity will be replaced by those currently set on this instance. Already-stored properties which do not correspond to keys set on this instance will be removed from the datastore.

Note

Property values which are “text” (‘unicode’ in Python2, ‘str’ in Python3) map to ‘string_value’ in the datastore; values which are “bytes” (‘str’ in Python2, ‘bytes’ in Python3) map to ‘blob_value’.

When an entity has a partial key, calling commit() sends it as an insert mutation and the key is completed. On return, the key for the entity passed in is updated to match the key ID assigned by the server.

Parameters:entity (google.cloud.datastore.entity.Entity) – the entity to be saved. Raises:ValueError if the batch is not in progress, if entity has no key assigned, or if the key’s project does not match ours.

rollback()

Rolls back the current batch.

Marks the batch as aborted (can’t be used again).

Overridden by google.cloud.datastore.transaction.Transaction.

Raises:ValueError if the batch is not in progress.