Getting started with Spanner in Python

Objectives

This tutorial walks you through the following steps using the Spannerclient library for Python:

Costs

This tutorial uses Spanner, which is a billable component of theGoogle Cloud. For information on the cost of using Spanner, seePricing.

Before you begin

Complete the steps described inSet up, which cover creating andsetting a default Google Cloud project, enabling billing, enabling theCloud Spanner API, and setting up OAuth 2.0 to get authentication credentials to usethe Cloud Spanner API.

In particular, make sure that you rungcloud authapplication-default loginto set up your local development environment with authenticationcredentials.

Note: If you don't plan to keep the resources that you create in this tutorial,consider creating a new Google Cloud project instead of selecting an existingproject. After you finish the tutorial, you can delete the project, removing allresources associated with the project.

Prepare your local Python environment

  1. Follow the instructionsinSetting Up a Python Development Environment.

  2. Clone the sample app repository to your local machine:

    gitclonehttps://github.com/googleapis/python-spanner

    Alternatively, you candownload the sample as a zip file and extract it.

  3. Change to the directory that contains the Spanner sample code:

    cdpython-spanner/samples/samples

  4. Create an isolated Python environment, and install dependencies:

    virtualenvenvsourceenv/bin/activatepipinstall-rrequirements.txt

Create an instance

When you first use Spanner, you must create an instance, which is anallocation of resources that are used by Spanner databases. When youcreate an instance, you choose aninstance configuration, which determineswhere your data is stored, and also the number of nodes to use, which determinesthe amount of serving and storage resources in your instance.

SeeCreate an instanceto learn how to create a Spanner instance using any of thefollowing methods. You can name your instancetest-instance to use it withother topics in this document that reference an instance namedtest-instance.

  • The Google Cloud CLI
  • The Google Cloud console
  • A client library (C++, C#, Go, Java, Node.js, PHP, Python, or Ruby)

Look through sample files

The samples repository contains a sample that shows how to use Spannerwith Python.

Take a look through thesnippets.py file, which shows how to useSpanner. The code shows how to create and use a new database. The datauses the example schema shown in theSchema and data model page.

Create a database

GoogleSQL

pythonsnippets.pytest-instance--database-idexample-dbcreate_database

PostgreSQL

pythonpg_snippets.pytest-instance--database-idexample-dbcreate_database

You should see:

Createddatabaseexample-dboninstancetest-instance
The following code creates a database and two tables in the database.Note: The subsequent code samples use these two tables. If you don't executethis code, then create the tables by using the Google Cloud console or thegcloud CLI. For more information, see theexample schema.

GoogleSQL

defcreate_database(instance_id,database_id):"""Creates a database and tables for sample data."""fromgoogle.cloud.spanner_admin_database_v1.typesimportspanner_database_adminspanner_client=spanner.Client()database_admin_api=spanner_client.database_admin_apirequest=spanner_database_admin.CreateDatabaseRequest(parent=database_admin_api.instance_path(spanner_client.project,instance_id),create_statement=f"CREATE DATABASE `{database_id}`",extra_statements=["""CREATE TABLE Singers (            SingerId     INT64 NOT NULL,            FirstName    STRING(1024),            LastName     STRING(1024),            SingerInfo   BYTES(MAX),            FullName   STRING(2048) AS (                ARRAY_TO_STRING([FirstName, LastName], " ")            ) STORED        ) PRIMARY KEY (SingerId)""","""CREATE TABLE Albums (            SingerId     INT64 NOT NULL,            AlbumId      INT64 NOT NULL,            AlbumTitle   STRING(MAX)        ) PRIMARY KEY (SingerId, AlbumId),        INTERLEAVE IN PARENT Singers ON DELETE CASCADE""",],)operation=database_admin_api.create_database(request=request)print("Waiting for operation to complete...")database=operation.result(OPERATION_TIMEOUT_SECONDS)print("Created database{} on instance{}".format(database.name,database_admin_api.instance_path(spanner_client.project,instance_id),))

PostgreSQL

defcreate_database(instance_id,database_id):"""Creates a PostgreSql database and tables for sample data."""fromgoogle.cloud.spanner_admin_database_v1.typesimportspanner_database_adminspanner_client=spanner.Client()database_admin_api=spanner_client.database_admin_apirequest=spanner_database_admin.CreateDatabaseRequest(parent=database_admin_api.instance_path(spanner_client.project,instance_id),create_statement=f'CREATE DATABASE "{database_id}"',database_dialect=DatabaseDialect.POSTGRESQL,)operation=database_admin_api.create_database(request=request)print("Waiting for operation to complete...")database=operation.result(OPERATION_TIMEOUT_SECONDS)create_table_using_ddl(database.name)print("Created database{} on instance{}".format(database_id,instance_id))defcreate_table_using_ddl(database_name):fromgoogle.cloud.spanner_admin_database_v1.typesimportspanner_database_adminspanner_client=spanner.Client()request=spanner_database_admin.UpdateDatabaseDdlRequest(database=database_name,statements=["""CREATE TABLE Singers (  SingerId   bigint NOT NULL,  FirstName  character varying(1024),  LastName   character varying(1024),  SingerInfo bytea,  FullName   character varying(2048)    GENERATED ALWAYS AS (FirstName || ' ' || LastName) STORED,  PRIMARY KEY (SingerId)  )""","""CREATE TABLE Albums (  SingerId     bigint NOT NULL,  AlbumId      bigint NOT NULL,  AlbumTitle   character varying(1024),  PRIMARY KEY (SingerId, AlbumId)  ) INTERLEAVE IN PARENT Singers ON DELETE CASCADE""",],)operation=spanner_client.database_admin_api.update_database_ddl(request)operation.result(OPERATION_TIMEOUT_SECONDS)

The next step is to write data to your database.

Create a database client

Before you can do reads or writes, you must create aClient. Youcan think of aClient as a database connection: all of your interactions withSpanner must go through aClient. Typically you create aClient whenyour application starts up, then you re-use thatClient to read, write, andexecute transactions. The following code shows how to create a client.

# Imports the Google Cloud Client Library.fromgoogle.cloudimportspanner# Your Cloud Spanner instance ID.# instance_id = "my-instance-id"## Your Cloud Spanner database ID.# database_id = "my-database-id"# Instantiate a client.spanner_client=spanner.Client()# Get a Cloud Spanner instance by ID.instance=spanner_client.instance(instance_id)# Get a Cloud Spanner database by ID.database=instance.database(database_id)# Execute a simple SQL statement.withdatabase.snapshot()assnapshot:results=snapshot.execute_sql("SELECT 1")forrowinresults:print(row)

Read more in theClientreference.

Write data with DML

You can insert data using Data Manipulation Language (DML) in a read-writetransaction.

You use theexecute_update() method to execute a DML statement.

# instance_id = "your-spanner-instance"# database_id = "your-spanner-db-id"spanner_client=spanner.Client()instance=spanner_client.instance(instance_id)database=instance.database(database_id)definsert_singers(transaction):row_ct=transaction.execute_update("INSERT INTO Singers (SingerId, FirstName, LastName) VALUES ""(12, 'Melissa', 'Garcia'), ""(13, 'Russell', 'Morales'), ""(14, 'Jacqueline', 'Long'), ""(15, 'Dylan', 'Shaw')")print("{} record(s) inserted.".format(row_ct))database.run_in_transaction(insert_singers)

Run the sample using theinsert_with_dml argument.

pythonsnippets.pytest-instance--database-idexample-dbinsert_with_dml

You should see:

4record(s)inserted.
Note: There are limits to commit size. SeeCRUD limitfor more information.

Write data with mutations

You can also insert data usingmutations.

You write data using aBatchobject. ABatch object is a container for mutation operations. A mutationrepresents a sequence of inserts, updates, and deletes that Spannerapplies atomically to different rows and tables in a Spanner database.

Theinsert()method in theBatch class adds one or more insert mutations to thebatch. All mutations in a single batch are applied atomically.

This code shows how to write the data using mutations:

definsert_data(instance_id,database_id):"""Inserts sample data into the given database.    The database and table must already exist and can be created using    `create_database`.    """spanner_client=spanner.Client()instance=spanner_client.instance(instance_id)database=instance.database(database_id)withdatabase.batch()asbatch:batch.insert(table="Singers",columns=("SingerId","FirstName","LastName"),values=[(1,"Marc","Richards"),(2,"Catalina","Smith"),(3,"Alice","Trentor"),(4,"Lea","Martin"),(5,"David","Lomond"),],)batch.insert(table="Albums",columns=("SingerId","AlbumId","AlbumTitle"),values=[(1,1,"Total Junk"),(1,2,"Go, Go, Go"),(2,1,"Green"),(2,2,"Forever Hold Your Peace"),(2,3,"Terrified"),],)print("Inserted data.")

Run the sample using theinsert_data argument.

pythonsnippets.pytest-instance--database-idexample-dbinsert_data

You should see:

Inserteddata.
Note: There are limits to commit size. SeeCRUD limitfor more information.

Query data using SQL

Spanner supports a SQL interface for reading data, which you canaccess on the command line using the Google Cloud CLI orprogrammatically usingthe Spanner client library for Python.

On the command line

Execute the following SQL statement to read the values of all columns from theAlbums table:

gcloudspannerdatabasesexecute-sqlexample-db--instance=test-instance \--sql='SELECT SingerId, AlbumId, AlbumTitle FROM Albums'
Note: For the GoogleSQL reference, seeQuery syntax in GoogleSQLand for PostgreSQL reference, seePostgreSQL lexical structure and syntax.

The result shows:

SingerIdAlbumIdAlbumTitle11TotalJunk12Go,Go,Go21Green22ForeverHoldYourPeace23Terrified

Use the Spanner client library for Python

In addition to executing a SQL statement on the command line, you can issue thesame SQL statement programmatically using the Spanner client library forPython.

Use theexecute_sql()method of aSnapshot object torun the SQL query. To get aSnapshot object, call thesnapshot()method of theDatabaseclass in awith statement.

Here's how to issue the query and access the data:

defquery_data(instance_id,database_id):"""Queries sample data from the database using SQL."""spanner_client=spanner.Client()instance=spanner_client.instance(instance_id)database=instance.database(database_id)withdatabase.snapshot()assnapshot:results=snapshot.execute_sql("SELECT SingerId, AlbumId, AlbumTitle FROM Albums")forrowinresults:print("SingerId:{}, AlbumId:{}, AlbumTitle:{}".format(*row))

Run the sample using thequery_data argument.

pythonsnippets.pytest-instance--database-idexample-dbquery_data

You should see the following result:

SingerId:2,AlbumId:2,AlbumTitle:ForeverHoldYourPeaceSingerId:1,AlbumId:2,AlbumTitle:Go,Go,GoSingerId:2,AlbumId:1,AlbumTitle:GreenSingerId:2,AlbumId:3,AlbumTitle:TerrifiedSingerId:1,AlbumId:1,AlbumTitle:TotalJunk

Query using a SQL parameter

If your application has a frequently executed query, you can improve its performanceby parameterizing it. The resulting parametric query can be cached and reused, whichreduces compilation costs. For more information, seeUse query parameters to speed up frequently executed queries.

Here is an example of using a parameter in theWHERE clause toquery records containing a specific value forLastName.

# instance_id = "your-spanner-instance"# database_id = "your-spanner-db-id"spanner_client=spanner.Client()instance=spanner_client.instance(instance_id)database=instance.database(database_id)withdatabase.snapshot()assnapshot:results=snapshot.execute_sql("SELECT SingerId, FirstName, LastName FROM Singers ""WHERE LastName = @lastName",params={"lastName":"Garcia"},param_types={"lastName":spanner.param_types.STRING},)forrowinresults:print("SingerId:{}, FirstName:{}, LastName:{}".format(*row))

Run the sample using the query_data_with_parameter argument.

pythonsnippets.pytest-instance--database-idexample-dbquery_data_with_parameter

You should see the following result:

SingerId:12,FirstName:Melissa,LastName:Garcia

Read data using the read API

In addition to Spanner's SQL interface, Spanner also supports aread interface.

Use theread()method of aSnapshotobject to read rows from the database.To get aSnapshot object, call thesnapshot()method of theDatabaseclass in awith statement.Use aKeySetobject to define a collection of keys and key ranges to read.

Here's how to read the data:

defread_data(instance_id,database_id):"""Reads sample data from the database."""spanner_client=spanner.Client()instance=spanner_client.instance(instance_id)database=instance.database(database_id)withdatabase.snapshot()assnapshot:keyset=spanner.KeySet(all_=True)results=snapshot.read(table="Albums",columns=("SingerId","AlbumId","AlbumTitle"),keyset=keyset)forrowinresults:print("SingerId:{}, AlbumId:{}, AlbumTitle:{}".format(*row))

Run the sample using theread_data argument.

pythonsnippets.pytest-instance--database-idexample-dbread_data

You should see output similar to:

SingerId:1,AlbumId:1,AlbumTitle:TotalJunkSingerId:1,AlbumId:2,AlbumTitle:Go,Go,GoSingerId:2,AlbumId:1,AlbumTitle:GreenSingerId:2,AlbumId:2,AlbumTitle:ForeverHoldYourPeaceSingerId:2,AlbumId:3,AlbumTitle:Terrified

Update the database schema

Assume you need to add a new column calledMarketingBudget to theAlbumstable. Adding a new column to an existing table requires an update to yourdatabase schema. Spanner supports schema updates to a database while thedatabase continues to serve traffic. Schema updates don't require taking thedatabase offline and they don't lock entire tables or columns; you can continuewriting data to the database during the schema update. Read more about supportedschema updates and schema change performance inMake schema updates.

Add a column

You can add a column on the command line using the Google Cloud CLI orprogrammatically usingthe Spanner client library for Python.

On the command line

Use the followingALTER TABLE command toadd the new column to the table:

GoogleSQL

gcloudspannerdatabasesddlupdateexample-db--instance=test-instance \--ddl='ALTER TABLE Albums ADD COLUMN MarketingBudget INT64'

PostgreSQL

gcloudspannerdatabasesddlupdateexample-db--instance=test-instance \--ddl='ALTER TABLE Albums ADD COLUMN MarketingBudget BIGINT'

You should see:

Schemaupdating...done.

Use the Spanner client library for Python

Use theupdate_ddl()method of theDatabaseclass to modify the schema:

defadd_column(instance_id,database_id):"""Adds a new column to the Albums table in the example database."""fromgoogle.cloud.spanner_admin_database_v1.typesimportspanner_database_adminspanner_client=spanner.Client()database_admin_api=spanner_client.database_admin_apirequest=spanner_database_admin.UpdateDatabaseDdlRequest(database=database_admin_api.database_path(spanner_client.project,instance_id,database_id),statements=["ALTER TABLE Albums ADD COLUMN MarketingBudget INT64",],)operation=database_admin_api.update_database_ddl(request)print("Waiting for operation to complete...")operation.result(OPERATION_TIMEOUT_SECONDS)print("Added the MarketingBudget column.")

Run the sample using theadd_column argument.

pythonsnippets.pytest-instance--database-idexample-dbadd_column

You should see:

AddedtheMarketingBudgetcolumn.

Write data to the new column

The following code writes data to the new column. It setsMarketingBudget to100000 for the row keyed byAlbums(1, 1) and to500000 for the row keyedbyAlbums(2, 2).

defupdate_data(instance_id,database_id):"""Updates sample data in the database.    This updates the `MarketingBudget` column which must be created before    running this sample. You can add the column by running the `add_column`    sample or by running this DDL statement against your database:        ALTER TABLE Albums ADD COLUMN MarketingBudget INT64    """spanner_client=spanner.Client()instance=spanner_client.instance(instance_id)database=instance.database(database_id)withdatabase.batch()asbatch:batch.update(table="Albums",columns=("SingerId","AlbumId","MarketingBudget"),values=[(1,1,100000),(2,2,500000)],)print("Updated data.")

Run the sample using theupdate_data argument.

pythonsnippets.pytest-instance--database-idexample-dbupdate_data

You can also execute a SQL query or a read call to fetch the values that youjust wrote.

Here's the code to execute the query:

defquery_data_with_new_column(instance_id,database_id):"""Queries sample data from the database using SQL.    This sample uses the `MarketingBudget` column. You can add the column    by running the `add_column` sample or by running this DDL statement against    your database:        ALTER TABLE Albums ADD COLUMN MarketingBudget INT64    """spanner_client=spanner.Client()instance=spanner_client.instance(instance_id)database=instance.database(database_id)withdatabase.snapshot()assnapshot:results=snapshot.execute_sql("SELECT SingerId, AlbumId, MarketingBudget FROM Albums")forrowinresults:print("SingerId:{}, AlbumId:{}, MarketingBudget:{}".format(*row))

To execute this query, run the sample using thequery_data_with_new_column argument.

pythonsnippets.pytest-instance--database-idexample-dbquery_data_with_new_column

You should see:

SingerId:2,AlbumId:2,MarketingBudget:500000SingerId:1,AlbumId:2,MarketingBudget:NoneSingerId:2,AlbumId:1,MarketingBudget:NoneSingerId:2,AlbumId:3,MarketingBudget:NoneSingerId:1,AlbumId:1,MarketingBudget:100000

Update data

You can update data using DML in a read-write transaction.

You use theexecute_update() method to execute a DML statement.

# instance_id = "your-spanner-instance"# database_id = "your-spanner-db-id"spanner_client=spanner.Client()instance=spanner_client.instance(instance_id)database=instance.database(database_id)deftransfer_budget(transaction):# Transfer marketing budget from one album to another. Performed in a# single transaction to ensure that the transfer is atomic.second_album_result=transaction.execute_sql("SELECT MarketingBudget from Albums ""WHERE SingerId = 2 and AlbumId = 2")second_album_row=list(second_album_result)[0]second_album_budget=second_album_row[0]transfer_amount=200000# Transaction will only be committed if this condition still holds at# the time of commit. Otherwise it will be aborted and the callable# will be rerun by the client libraryifsecond_album_budget >=transfer_amount:first_album_result=transaction.execute_sql("SELECT MarketingBudget from Albums ""WHERE SingerId = 1 and AlbumId = 1")first_album_row=list(first_album_result)[0]first_album_budget=first_album_row[0]second_album_budget-=transfer_amountfirst_album_budget+=transfer_amount# Update first albumtransaction.execute_update("UPDATE Albums ""SET MarketingBudget = @AlbumBudget ""WHERE SingerId = 1 and AlbumId = 1",params={"AlbumBudget":first_album_budget},param_types={"AlbumBudget":spanner.param_types.INT64},)# Update second albumtransaction.execute_update("UPDATE Albums ""SET MarketingBudget = @AlbumBudget ""WHERE SingerId = 2 and AlbumId = 2",params={"AlbumBudget":second_album_budget},param_types={"AlbumBudget":spanner.param_types.INT64},)print("Transferred{} from Album2's budget to Album1's".format(transfer_amount))database.run_in_transaction(transfer_budget)

Run the sample using thewrite_with_dml_transaction argument.

pythonsnippets.pytest-instance--database-idexample-dbwrite_with_dml_transaction

You should see:

Transferred200000fromAlbum2's budget to Album1's
Note: You can alsoupdate data using mutations.

Use a secondary index

Suppose you wanted to fetch all rows ofAlbums that haveAlbumTitle valuesin a certain range. You could read all values from theAlbumTitle column usinga SQL statement or a read call, and then discard the rows that don't meet thecriteria, but doing this full table scan is expensive, especially for tableswith a lot of rows. Instead you can speed up the retrieval of rows whensearching by non-primary key columns by creating asecondary index on the table.

Adding a secondary index to an existing table requires a schema update. Likeother schema updates, Spanner supports adding an index while thedatabase continues to serve traffic. Spanner automatically backfills theindex with your existing data. Backfills might take a few minutes to complete,but you don't need to take the database offline or avoid writing to the indexedtable during this process. For more details, seeAdd a secondary index.

After you add a secondary index, Spanner automatically uses it forSQL queries that are likely to run faster with the index. If you use the readinterface, you must specify the index that you want to use.

Add a secondary index

You can add an index on the command line using the gcloud CLI orprogrammatically using the Spanner client library for Python.

On the command line

Use the followingCREATE INDEX commandto add an index to the database:

gcloudspannerdatabasesddlupdateexample-db--instance=test-instance\--ddl='CREATE INDEX AlbumsByAlbumTitle ON Albums(AlbumTitle)'

You should see:

Schemaupdating...done.

Using the Spanner client library for Python

Use theupdate_ddl()method of theDatabaseclass to add an index:

defadd_index(instance_id,database_id):"""Adds a simple index to the example database."""fromgoogle.cloud.spanner_admin_database_v1.typesimportspanner_database_adminspanner_client=spanner.Client()database_admin_api=spanner_client.database_admin_apirequest=spanner_database_admin.UpdateDatabaseDdlRequest(database=database_admin_api.database_path(spanner_client.project,instance_id,database_id),statements=["CREATE INDEX AlbumsByAlbumTitle ON Albums(AlbumTitle)"],)operation=database_admin_api.update_database_ddl(request)print("Waiting for operation to complete...")operation.result(OPERATION_TIMEOUT_SECONDS)print("Added the AlbumsByAlbumTitle index.")

Run the sample using theadd_index argument.

pythonsnippets.pytest-instance--database-idexample-dbadd_index

Adding an index can take a few minutes. After the index is added, you shouldsee:

AddedtheAlbumsByAlbumTitleindex.

Read using the index

For SQL queries, Spanner automatically uses an appropriate index. In theread interface, you must specify the index in your request.

To use the index in the read interface, provide anIndex argument to theread() method of aSnapshotobject. To get aSnapshot object, call thesnapshot() method of theDatabase class in awith statement.

defread_data_with_index(instance_id,database_id):"""Reads sample data from the database using an index.    The index must exist before running this sample. You can add the index    by running the `add_index` sample or by running this DDL statement against    your database:        CREATE INDEX AlbumsByAlbumTitle ON Albums(AlbumTitle)    """spanner_client=spanner.Client()instance=spanner_client.instance(instance_id)database=instance.database(database_id)withdatabase.snapshot()assnapshot:keyset=spanner.KeySet(all_=True)results=snapshot.read(table="Albums",columns=("AlbumId","AlbumTitle"),keyset=keyset,index="AlbumsByAlbumTitle",)forrowinresults:print("AlbumId:{}, AlbumTitle:{}".format(*row))

Run the sample using theread_data_with_index argument.

pythonsnippets.pytest-instance--database-idexample-dbread_data_with_index

You should see:

AlbumId:2,AlbumTitle:ForeverHoldYourPeaceAlbumId:2,AlbumTitle:Go,Go,GoAlbumId:1,AlbumTitle:GreenAlbumId:3,AlbumTitle:TerrifiedAlbumId:1,AlbumTitle:TotalJunk

Add an index for index-only reads

You might have noticed that the previous read example doesn't include readingtheMarketingBudget column. This is because Spanner's read interfacedoesn't support the ability to join an index with a data table to look up valuesthat are not stored in the index.

Create an alternate definition ofAlbumsByAlbumTitle that stores a copy ofMarketingBudget in the index.

On the command line

GoogleSQL

gcloudspannerdatabasesddlupdateexample-db--instance=test-instance \--ddl='CREATE INDEX AlbumsByAlbumTitle2 ON Albums(AlbumTitle) STORING (MarketingBudget)

PostgreSQL

gcloudspannerdatabasesddlupdateexample-db--instance=test-instance \--ddl='CREATE INDEX AlbumsByAlbumTitle2 ON Albums(AlbumTitle) INCLUDE (MarketingBudget)

Adding an index can take a few minutes. After the index is added, you shouldsee:

Schemaupdating...done.

Using the Spanner client library for Python

Use theupdate_ddl()method of theDatabaseclass to add an index with aSTORING clause:

defadd_storing_index(instance_id,database_id):"""Adds an storing index to the example database."""fromgoogle.cloud.spanner_admin_database_v1.typesimportspanner_database_adminspanner_client=spanner.Client()database_admin_api=spanner_client.database_admin_apirequest=spanner_database_admin.UpdateDatabaseDdlRequest(database=database_admin_api.database_path(spanner_client.project,instance_id,database_id),statements=["CREATE INDEX AlbumsByAlbumTitle2 ON Albums(AlbumTitle)""STORING (MarketingBudget)"],)operation=database_admin_api.update_database_ddl(request)print("Waiting for operation to complete...")operation.result(OPERATION_TIMEOUT_SECONDS)print("Added the AlbumsByAlbumTitle2 index.")

Run the sample using theadd_storing_index argument.

pythonsnippets.pytest-instance--database-idexample-dbadd_storing_index

You should see:

AddedtheAlbumsByAlbumTitle2index.

Now you can execute a read that fetches allAlbumId,AlbumTitle, andMarketingBudget columns from theAlbumsByAlbumTitle2 index:

defread_data_with_storing_index(instance_id,database_id):"""Reads sample data from the database using an index with a storing    clause.    The index must exist before running this sample. You can add the index    by running the `add_scoring_index` sample or by running this DDL statement    against your database:        CREATE INDEX AlbumsByAlbumTitle2 ON Albums(AlbumTitle)        STORING (MarketingBudget)    """spanner_client=spanner.Client()instance=spanner_client.instance(instance_id)database=instance.database(database_id)withdatabase.snapshot()assnapshot:keyset=spanner.KeySet(all_=True)results=snapshot.read(table="Albums",columns=("AlbumId","AlbumTitle","MarketingBudget"),keyset=keyset,index="AlbumsByAlbumTitle2",)forrowinresults:print("AlbumId:{}, AlbumTitle:{}, ""MarketingBudget:{}".format(*row))

Run the sample using theread_data_with_storing_index argument.

pythonsnippets.pytest-instance--database-idexample-dbread_data_with_storing_index

You should see output similar to:

AlbumId:2,AlbumTitle:ForeverHoldYourPeace,MarketingBudget:300000AlbumId:2,AlbumTitle:Go,Go,Go,MarketingBudget:NoneAlbumId:1,AlbumTitle:Green,MarketingBudget:NoneAlbumId:3,AlbumTitle:Terrified,MarketingBudget:NoneAlbumId:1,AlbumTitle:TotalJunk,MarketingBudget:300000

Retrieve data using read-only transactions

Suppose you want to execute more than one read at the same timestamp.Read-onlytransactions observe a consistentprefix of the transaction commit history, so your application always getsconsistent data.Use aSnapshotobject for executing read-only transactions. To get aSnapshot object, call thesnapshot()method of theDatabaseclass in awith statement.

The following shows how to run a query and perform a read in the same read-onlytransaction:

defread_only_transaction(instance_id,database_id):"""Reads data inside of a read-only transaction.    Within the read-only transaction, or "snapshot", the application sees    consistent view of the database at a particular timestamp.    """spanner_client=spanner.Client()instance=spanner_client.instance(instance_id)database=instance.database(database_id)withdatabase.snapshot(multi_use=True)assnapshot:# Read using SQL.results=snapshot.execute_sql("SELECT SingerId, AlbumId, AlbumTitle FROM Albums")print("Results from first read:")forrowinresults:print("SingerId:{}, AlbumId:{}, AlbumTitle:{}".format(*row))# Perform another read using the `read` method. Even if the data# is updated in-between the reads, the snapshot ensures that both# return the same data.keyset=spanner.KeySet(all_=True)results=snapshot.read(table="Albums",columns=("SingerId","AlbumId","AlbumTitle"),keyset=keyset)print("Results from second read:")forrowinresults:print("SingerId:{}, AlbumId:{}, AlbumTitle:{}".format(*row))

Run the sample using theread_only_transaction argument.

pythonsnippets.pytest-instance--database-idexample-dbread_only_transaction

You should see output similar to:

Resultsfromfirstread:SingerId:2,AlbumId:2,AlbumTitle:ForeverHoldYourPeaceSingerId:1,AlbumId:2,AlbumTitle:Go,Go,GoSingerId:2,AlbumId:1,AlbumTitle:GreenSingerId:2,AlbumId:3,AlbumTitle:TerrifiedSingerId:1,AlbumId:1,AlbumTitle:TotalJunkResultsfromsecondread:SingerId:1,AlbumId:1,AlbumTitle:TotalJunkSingerId:1,AlbumId:2,AlbumTitle:Go,Go,GoSingerId:2,AlbumId:1,AlbumTitle:GreenSingerId:2,AlbumId:2,AlbumTitle:ForeverHoldYourPeaceSingerId:2,AlbumId:3,AlbumTitle:Terrified

Cleanup

To avoid incurring additional charges to your Cloud Billing account for theresources used in this tutorial, drop the database and delete the instance thatyou created.

Delete the database

If you delete an instance, all databases within it are automatically deleted.This step shows how to delete a database without deleting an instance (you wouldstill incur charges for the instance).

On the command line

gcloudspannerdatabasesdeleteexample-db--instance=test-instance

Using the Google Cloud console

  1. Go to theSpanner Instances page in the Google Cloud console.

    Go to the Instances page

  2. Click the instance.

  3. Click the database that you want to delete.

  4. In theDatabase details page, clickDelete.

  5. Confirm that you want to delete the database and clickDelete.

Delete the instance

Deleting an instance automatically drops all databases created in that instance.

On the command line

gcloudspannerinstancesdeletetest-instance

Using the Google Cloud console

  1. Go to theSpanner Instances page in the Google Cloud console.

    Go to the Instances page

  2. Click your instance.

  3. ClickDelete.

  4. Confirm that you want to delete the instance and clickDelete.

What's next

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Last updated 2025-12-17 UTC.