Class SpannerClient (3.45.0)

Cloud Spanner API

The Cloud Spanner API can be used to manage sessions and execute transactions on data stored in Cloud Spanner databases.

Returns the transport used by the client instance.

Instantiates the spanner client.

Releases underlying transport's resources.

Creates multiple new sessions.

This API can be used to initialize a session cache on the clients. See https://goo.gl/TgSFN2 for best practices on session cache management.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import spanner_v1

def sample_batch_create_sessions():
    # Create a client
    client = spanner_v1.SpannerClient()

    # Initialize request argument(s)
    request = spanner_v1.BatchCreateSessionsRequest(
        database="database_value",
        session_count=1420,
    )

    # Make the request
    response = client.batch_create_sessions(request=request)

    # Handle the response
    print(response)

Batches the supplied mutation groups in a collection of efficient transactions. All mutations in a group are committed atomically. However, mutations across groups can be committed non-atomically in an unspecified order and thus, they must be independent of each other. Partial failure is possible, i.e., some groups may have been committed successfully, while some may have failed. The results of individual batches are streamed into the response as the batches are applied.

BatchWrite requests are not replay protected, meaning that each mutation group may be applied more than once. Replays of non-idempotent mutations may have undesirable effects. For example, replays of an insert mutation may produce an already exists error or if you use generated or commit timestamp-based keys, it may result in additional rows being added to the mutation's table. We recommend structuring your mutation groups to be idempotent to avoid this issue.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import spanner_v1

def sample_batch_write():
    # Create a client
    client = spanner_v1.SpannerClient()

    # Initialize request argument(s)
    mutation_groups = spanner_v1.MutationGroup()
    mutation_groups.mutations.insert.table = "table_value"

    request = spanner_v1.BatchWriteRequest(
        session="session_value",
        mutation_groups=mutation_groups,
    )

    # Make the request
    stream = client.batch_write(request=request)

    # Handle the response
    for response in stream:
        print(response)

Begins a new transaction. This step can often be skipped: Read][google.spanner.v1.Spanner.Read], ExecuteSql][google.spanner.v1.Spanner.ExecuteSql] and Commit][google.spanner.v1.Spanner.Commit] can begin a new transaction as a side-effect.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import spanner_v1

def sample_begin_transaction():
    # Create a client
    client = spanner_v1.SpannerClient()

    # Initialize request argument(s)
    request = spanner_v1.BeginTransactionRequest(
        session="session_value",
    )

    # Make the request
    response = client.begin_transaction(request=request)

    # Handle the response
    print(response)

Commits a transaction. The request includes the mutations to be applied to rows in the database.

Commit might return an ABORTED error. This can occur at any time; commonly, the cause is conflicts with concurrent transactions. However, it can also happen for a variety of other reasons. If Commit returns ABORTED, the caller should re-attempt the transaction from the beginning, re-using the same session.

On very rare occasions, Commit might return UNKNOWN. This can happen, for example, if the client job experiences a 1+ hour networking failure. At that point, Cloud Spanner has lost track of the transaction outcome and we recommend that you perform another read from the database to see the state of things as they are now.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import spanner_v1

def sample_commit():
    # Create a client
    client = spanner_v1.SpannerClient()

    # Initialize request argument(s)
    request = spanner_v1.CommitRequest(
        transaction_id=b'transaction_id_blob',
        session="session_value",
    )

    # Make the request
    response = client.commit(request=request)

    # Handle the response
    print(response)

Returns a fully-qualified billing_account string.

Returns a fully-qualified folder string.

Returns a fully-qualified location string.

Returns a fully-qualified organization string.

Returns a fully-qualified project string.

Creates a new session. A session can be used to perform transactions that read and/or modify data in a Cloud Spanner database. Sessions are meant to be reused for many consecutive transactions.

Sessions can only execute one transaction at a time. To execute multiple concurrent read-write/write-only transactions, create multiple sessions. Note that standalone reads and queries use a transaction internally, and count toward the one transaction limit.

Active sessions use additional server resources, so it is a good idea to delete idle and unneeded sessions. Aside from explicit deletes, Cloud Spanner may delete sessions for which no operations are sent for more than an hour. If a session is deleted, requests to it return NOT_FOUND.

Idle sessions can be kept alive by sending a trivial SQL query periodically, e.g., "SELECT 1".

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import spanner_v1

def sample_create_session():
    # Create a client
    client = spanner_v1.SpannerClient()

    # Initialize request argument(s)
    request = spanner_v1.CreateSessionRequest(
        database="database_value",
    )

    # Make the request
    response = client.create_session(request=request)

    # Handle the response
    print(response)

Returns a fully-qualified database string.

Ends a session, releasing server resources associated with it. This will asynchronously trigger cancellation of any operations that are running with this session.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import spanner_v1

def sample_delete_session():
    # Create a client
    client = spanner_v1.SpannerClient()

    # Initialize request argument(s)
    request = spanner_v1.DeleteSessionRequest(
        name="name_value",
    )

    # Make the request
    client.delete_session(request=request)

Executes a batch of SQL DML statements. This method allows many statements to be run with lower latency than submitting them sequentially with ExecuteSql][google.spanner.v1.Spanner.ExecuteSql].

Statements are executed in sequential order. A request can succeed even if a statement fails. The ExecuteBatchDmlResponse.status][google.spanner.v1.ExecuteBatchDmlResponse.status] field in the response provides information about the statement that failed. Clients must inspect this field to determine whether an error occurred.

Execution stops after the first failed statement; the remaining statements are not executed.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import spanner_v1

def sample_execute_batch_dml():
    # Create a client
    client = spanner_v1.SpannerClient()

    # Initialize request argument(s)
    statements = spanner_v1.Statement()
    statements.sql = "sql_value"

    request = spanner_v1.ExecuteBatchDmlRequest(
        session="session_value",
        statements=statements,
        seqno=550,
    )

    # Make the request
    response = client.execute_batch_dml(request=request)

    # Handle the response
    print(response)

Executes an SQL statement, returning all results in a single reply. This method cannot be used to return a result set larger than 10 MiB; if the query yields more data than that, the query fails with a FAILED_PRECONDITION error.

Operations inside read-write transactions might return ABORTED. If this occurs, the application should restart the transaction from the beginning. See Transaction][google.spanner.v1.Transaction] for more details.

Larger result sets can be fetched in streaming fashion by calling ExecuteStreamingSql][google.spanner.v1.Spanner.ExecuteStreamingSql] instead.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import spanner_v1

def sample_execute_sql():
    # Create a client
    client = spanner_v1.SpannerClient()

    # Initialize request argument(s)
    request = spanner_v1.ExecuteSqlRequest(
        session="session_value",
        sql="sql_value",
    )

    # Make the request
    response = client.execute_sql(request=request)

    # Handle the response
    print(response)

Like ExecuteSql][google.spanner.v1.Spanner.ExecuteSql], except returns the result set as a stream. Unlike ExecuteSql][google.spanner.v1.Spanner.ExecuteSql], there is no limit on the size of the returned result set. However, no individual row in the result set can exceed 100 MiB, and no column value can exceed 10 MiB.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import spanner_v1

def sample_execute_streaming_sql():
    # Create a client
    client = spanner_v1.SpannerClient()

    # Initialize request argument(s)
    request = spanner_v1.ExecuteSqlRequest(
        session="session_value",
        sql="sql_value",
    )

    # Make the request
    stream = client.execute_streaming_sql(request=request)

    # Handle the response
    for response in stream:
        print(response)

Creates an instance of this client using the provided credentials file.

Creates an instance of this client using the provided credentials info.

Creates an instance of this client using the provided credentials file.

Return the API endpoint and client cert source for mutual TLS.

The client cert source is determined in the following order: (1) if GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is not "true", the client cert source is None. (2) if client_options.client_cert_source is provided, use the provided one; if the default client cert source exists, use the default one; otherwise the client cert source is None.

The API endpoint is determined in the following order: (1) if client_options.api_endpoint if provided, use the provided one. (2) if GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is "always", use the default mTLS endpoint; if the environment variable is "never", use the default API endpoint; otherwise if client cert source exists, use the default mTLS endpoint, otherwise use the default API endpoint.

More details can be found at https://google.aip.dev/auth/4114.

Gets a session. Returns NOT_FOUND if the session does not exist. This is mainly useful for determining whether a session is still alive.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import spanner_v1

def sample_get_session():
    # Create a client
    client = spanner_v1.SpannerClient()

    # Initialize request argument(s)
    request = spanner_v1.GetSessionRequest(
        name="name_value",
    )

    # Make the request
    response = client.get_session(request=request)

    # Handle the response
    print(response)

Lists all sessions in a given database.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import spanner_v1

def sample_list_sessions():
    # Create a client
    client = spanner_v1.SpannerClient()

    # Initialize request argument(s)
    request = spanner_v1.ListSessionsRequest(
        database="database_value",
    )

    # Make the request
    page_result = client.list_sessions(request=request)

    # Handle the response
    for response in page_result:
        print(response)

Parse a billing_account path into its component segments.

Parse a folder path into its component segments.

Parse a location path into its component segments.

Parse a organization path into its component segments.

Parse a project path into its component segments.

Parses a database path into its component segments.

Parses a session path into its component segments.

Creates a set of partition tokens that can be used to execute a query operation in parallel. Each of the returned partition tokens can be used by ExecuteStreamingSql][google.spanner.v1.Spanner.ExecuteStreamingSql] to specify a subset of the query result to read. The same session and read-only transaction must be used by the PartitionQueryRequest used to create the partition tokens and the ExecuteSqlRequests that use the partition tokens.

Partition tokens become invalid when the session used to create them is deleted, is idle for too long, begins a new transaction, or becomes too old. When any of these happen, it is not possible to resume the query, and the whole operation must be restarted from the beginning.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import spanner_v1

def sample_partition_query():
    # Create a client
    client = spanner_v1.SpannerClient()

    # Initialize request argument(s)
    request = spanner_v1.PartitionQueryRequest(
        session="session_value",
        sql="sql_value",
    )

    # Make the request
    response = client.partition_query(request=request)

    # Handle the response
    print(response)

Creates a set of partition tokens that can be used to execute a read operation in parallel. Each of the returned partition tokens can be used by StreamingRead][google.spanner.v1.Spanner.StreamingRead] to specify a subset of the read result to read. The same session and read-only transaction must be used by the PartitionReadRequest used to create the partition tokens and the ReadRequests that use the partition tokens. There are no ordering guarantees on rows returned among the returned partition tokens, or even within each individual StreamingRead call issued with a partition_token.

Partition tokens become invalid when the session used to create them is deleted, is idle for too long, begins a new transaction, or becomes too old. When any of these happen, it is not possible to resume the read, and the whole operation must be restarted from the beginning.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import spanner_v1

def sample_partition_read():
    # Create a client
    client = spanner_v1.SpannerClient()

    # Initialize request argument(s)
    request = spanner_v1.PartitionReadRequest(
        session="session_value",
        table="table_value",
    )

    # Make the request
    response = client.partition_read(request=request)

    # Handle the response
    print(response)

Reads rows from the database using key lookups and scans, as a simple key/value style alternative to ExecuteSql][google.spanner.v1.Spanner.ExecuteSql]. This method cannot be used to return a result set larger than 10 MiB; if the read matches more data than that, the read fails with a FAILED_PRECONDITION error.

Reads inside read-write transactions might return ABORTED. If this occurs, the application should restart the transaction from the beginning. See Transaction][google.spanner.v1.Transaction] for more details.

Larger result sets can be yielded in streaming fashion by calling StreamingRead][google.spanner.v1.Spanner.StreamingRead] instead.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import spanner_v1

def sample_read():
    # Create a client
    client = spanner_v1.SpannerClient()

    # Initialize request argument(s)
    request = spanner_v1.ReadRequest(
        session="session_value",
        table="table_value",
        columns=['columns_value1', 'columns_value2'],
    )

    # Make the request
    response = client.read(request=request)

    # Handle the response
    print(response)

Rolls back a transaction, releasing any locks it holds. It is a good idea to call this for any transaction that includes one or more Read][google.spanner.v1.Spanner.Read] or ExecuteSql][google.spanner.v1.Spanner.ExecuteSql] requests and ultimately decides not to commit.

Rollback returns OK if it successfully aborts the transaction, the transaction was already aborted, or the transaction is not found. Rollback never returns ABORTED.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import spanner_v1

def sample_rollback():
    # Create a client
    client = spanner_v1.SpannerClient()

    # Initialize request argument(s)
    request = spanner_v1.RollbackRequest(
        session="session_value",
        transaction_id=b'transaction_id_blob',
    )

    # Make the request
    client.rollback(request=request)

Returns a fully-qualified session string.

Like Read][google.spanner.v1.Spanner.Read], except returns the result set as a stream. Unlike Read][google.spanner.v1.Spanner.Read], there is no limit on the size of the returned result set. However, no individual row in the result set can exceed 100 MiB, and no column value can exceed 10 MiB.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import spanner_v1

def sample_streaming_read():
    # Create a client
    client = spanner_v1.SpannerClient()

    # Initialize request argument(s)
    request = spanner_v1.ReadRequest(
        session="session_value",
        table="table_value",
        columns=['columns_value1', 'columns_value2'],
    )

    # Make the request
    stream = client.streaming_read(request=request)

    # Handle the response
    for response in stream:
        print(response)