Skip to content
Permalink
Browse files
docs: update samples from python-docs-samples (#146)
NUMERIC samples were recently added and need to be copied over to here.
  • Loading branch information
larkee committed Sep 25, 2020
1 parent 0fba41a commit 754938386c96814a3546d30d38d874734d1c201c
@@ -1,4 +1,3 @@

.. This file is automatically generated. Do not edit this file directly.
Google Cloud Spanner Python Samples
@@ -15,12 +14,10 @@ This directory contains samples for Google Cloud Spanner. `Google Cloud Spanner`

.. _Google Cloud Spanner: https://cloud.google.com/spanner/docs


Setup
-------------------------------------------------------------------------------



Authentication
++++++++++++++

@@ -31,9 +28,6 @@ credentials for applications.
.. _Authentication Getting Started Guide:
https://cloud.google.com/docs/authentication/getting-started




Install Dependencies
++++++++++++++++++++

@@ -48,7 +42,7 @@ Install Dependencies
.. _Python Development Environment Setup Guide:
https://cloud.google.com/python/setup
#. Create a virtualenv. Samples are compatible with Python 3.6+.
#. Create a virtualenv. Samples are compatible with Python 2.7 and 3.4+.

.. code-block:: bash
@@ -64,15 +58,9 @@ Install Dependencies
.. _pip: https://pip.pypa.io/
.. _virtualenv: https://virtualenv.pypa.io/






Samples
-------------------------------------------------------------------------------


Snippets
+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++

@@ -88,10 +76,32 @@ To run this sample:
$ python snippets.py
usage: snippets.py [-h] [--database-id DATABASE_ID]
instance_id
{create_instance,create_database,insert_data,delete_data,query_data,read_data,read_stale_data,add_column,update_data,query_data_with_new_column,read_write_transaction,read_only_transaction,add_index,query_data_with_index,read_data_with_index,add_storing_index,read_data_with_storing_index,create_table_with_timestamp,insert_data_with_timestamp,add_timestamp_column,update_data_with_timestamp,query_data_with_timestamp,write_struct_data,query_with_struct,query_with_array_of_struct,query_struct_field,query_nested_struct_field,insert_data_with_dml,update_data_with_dml,delete_data_with_dml,update_data_with_dml_timestamp,dml_write_read_transaction,update_data_with_dml_struct,insert_with_dml,query_data_with_parameter,write_with_dml_transaction,update_data_with_partitioned_dml,delete_data_with_partitioned_dml,update_with_batch_dml,create_table_with_datatypes,insert_datatypes_data,query_data_with_array,query_data_with_bool,query_data_with_bytes,query_data_with_date,query_data_with_float,query_data_with_int,query_data_with_string,query_data_with_timestamp_parameter,query_data_with_query_options,create_client_with_query_options}
{create_database,insert_data,query_data,read_data,
read_stale_data,add_column,update_data,
query_data_with_new_column,read_write_transaction,
read_only_transaction,add_index,query_data_with_index,
read_data_with_index,add_storing_index,
read_data_with_storing_index,
create_table_with_timestamp,insert_data_with_timestamp,
add_timestamp_column,update_data_with_timestamp,
query_data_with_timestamp,write_struct_data,
query_with_struct,query_with_array_of_struct,
query_struct_field,query_nested_struct_field,
insert_data_with_dml,update_data_with_dml,
delete_data_with_dml,update_data_with_dml_timestamp,
dml_write_read_transaction,update_data_with_dml_struct,
insert_with_dml,query_data_with_parameter,
write_with_dml_transaction,
update_data_with_partitioned_dml,
delete_data_with_partitioned_dml,update_with_batch_dml,
create_table_with_datatypes,insert_datatypes_data,
query_data_with_array,query_data_with_bool,
query_data_with_bytes,query_data_with_date,
query_data_with_float,query_data_with_int,
query_data_with_string,
query_data_with_timestamp_parameter}
...
This application demonstrates how to do basic operations using Cloud
@@ -101,15 +111,32 @@ To run this sample:
positional arguments:
instance_id Your Cloud Spanner instance ID.
{create_instance,create_database,insert_data,delete_data,query_data,read_data,read_stale_data,add_column,update_data,query_data_with_new_column,read_write_transaction,read_only_transaction,add_index,query_data_with_index,read_data_with_index,add_storing_index,read_data_with_storing_index,create_table_with_timestamp,insert_data_with_timestamp,add_timestamp_column,update_data_with_timestamp,query_data_with_timestamp,write_struct_data,query_with_struct,query_with_array_of_struct,query_struct_field,query_nested_struct_field,insert_data_with_dml,update_data_with_dml,delete_data_with_dml,update_data_with_dml_timestamp,dml_write_read_transaction,update_data_with_dml_struct,insert_with_dml,query_data_with_parameter,write_with_dml_transaction,update_data_with_partitioned_dml,delete_data_with_partitioned_dml,update_with_batch_dml,create_table_with_datatypes,insert_datatypes_data,query_data_with_array,query_data_with_bool,query_data_with_bytes,query_data_with_date,query_data_with_float,query_data_with_int,query_data_with_string,query_data_with_timestamp_parameter,query_data_with_query_options,create_client_with_query_options}
create_instance Creates an instance.
{create_database, insert_data, delete_data, query_data, read_data,
read_stale_data, add_column, update_data, query_data_with_new_column,
read_write_transaction, read_only_transaction, add_index,
query_data_with_index, read_data_with_index, add_storing_index,
read_data_with_storing_index, create_table_with_timestamp,
insert_data_with_timestamp, add_timestamp_column,
update_data_with_timestamp, query_data_with_timestamp,
write_struct_data, query_with_struct, query_with_array_of_struct,
query_struct_field, query_nested_struct_field, insert_data_with_dml,
update_data_with_dml, delete_data_with_dml,
update_data_with_dml_timestamp, dml_write_read_transaction,
update_data_with_dml_struct, insert_with_dml, query_data_with_parameter,
write_with_dml_transaction, update_data_with_partitioned_dml,
delete_data_with_partitioned_dml, update_with_batch_dml,
create_table_with_datatypes, insert_datatypes_data,
query_data_with_array, query_data_with_bool, query_data_with_bytes,
query_data_with_date, query_data_with_float, query_data_with_int,
query_data_with_string, query_data_with_timestamp_parameter}
create_database Creates a database and tables for sample data.
insert_data Inserts sample data into the given database. The
database and table must already exist and can be
created using `create_database`.
delete_data Deletes sample data from the given database. The
database, table, and data must already exist and can
be created using `create_database` and `insert_data`.
database, table, and data must already exist and
can be created using `create_database` and
`insert_data`.
query_data Queries sample data from the database using SQL.
read_data Reads sample data from the database.
read_stale_data Reads sample data from the database. The data is
@@ -210,53 +237,59 @@ To run this sample:
Deletes sample data from the database using a DML
statement.
update_data_with_dml_timestamp
Updates data with Timestamp from the database using a
DML statement.
Updates data with Timestamp from the database using
a DML statement.
dml_write_read_transaction
First inserts data then reads it from within a
transaction using DML.
update_data_with_dml_struct
Updates data with a DML statement and STRUCT
parameters.
insert_with_dml Inserts data with a DML statement into the database.
insert_with_dml Inserts data with a DML statement into the
database.
query_data_with_parameter
Queries sample data from the database using SQL with a
parameter.
Queries sample data from the database using SQL
with a parameter.
write_with_dml_transaction
Transfers part of a marketing budget from one album to
another.
Transfers part of a marketing budget from one
album to another.
update_data_with_partitioned_dml
Update sample data with a partitioned DML statement.
Update sample data with a partitioned DML
statement.
delete_data_with_partitioned_dml
Delete sample data with a partitioned DML statement.
Delete sample data with a partitioned DML
statement.
update_with_batch_dml
Updates sample data in the database using Batch DML.
Updates sample data in the database using Batch
DML.
create_table_with_datatypes
Creates a table with supported dataypes.
insert_datatypes_data
Inserts data with supported datatypes into a table.
query_data_with_array
Queries sample data using SQL with an ARRAY parameter.
Queries sample data using SQL with an ARRAY
parameter.
query_data_with_bool
Queries sample data using SQL with a BOOL parameter.
Queries sample data using SQL with a BOOL
parameter.
query_data_with_bytes
Queries sample data using SQL with a BYTES parameter.
Queries sample data using SQL with a BYTES
parameter.
query_data_with_date
Queries sample data using SQL with a DATE parameter.
Queries sample data using SQL with a DATE
parameter.
query_data_with_float
Queries sample data using SQL with a FLOAT64
parameter.
query_data_with_int
Queries sample data using SQL with a INT64 parameter.
Queries sample data using SQL with a INT64
parameter.
query_data_with_string
Queries sample data using SQL with a STRING parameter.
Queries sample data using SQL with a STRING
parameter.
query_data_with_timestamp_parameter
Queries sample data using SQL with a TIMESTAMP
parameter.
query_data_with_query_options
Queries sample data using SQL with query options.
create_client_with_query_options
Create a client with query options.
optional arguments:
-h, --help show this help message and exit
@@ -267,10 +300,6 @@ To run this sample:
The client library
-------------------------------------------------------------------------------

@@ -286,5 +315,4 @@ to `browse the source`_ and `report issues`_.
https://github.com/GoogleCloudPlatform/google-cloud-python/issues



.. _Google Cloud SDK: https://cloud.google.com/sdk/
.. _Google Cloud SDK: https://cloud.google.com/sdk/
@@ -69,7 +69,7 @@ def restore_database(instance_id, new_database_id, backup_id):
operation = new_database.restore(backup)

# Wait for restore operation to complete.
operation.result(1200)
operation.result(1600)

# Newly created database has restore information.
new_database.reload()
@@ -13,8 +13,10 @@
# limitations under the License.
import uuid

from google.api_core.exceptions import DeadlineExceeded
from google.cloud import spanner
import pytest
from test_utils.retry import RetryErrors

import backup_sample

@@ -68,6 +70,7 @@ def test_create_backup(capsys, database):
assert BACKUP_ID in out


@RetryErrors(exception=DeadlineExceeded, max_tries=2)
def test_restore_database(capsys):
backup_sample.restore_database(INSTANCE_ID, RESTORE_DB_ID, BACKUP_ID)
out, _ = capsys.readouterr()
@@ -1,2 +1,3 @@
pytest==5.4.3
pytest==6.0.1
mock==4.0.2
google-cloud-testutils==0.1.0
@@ -23,6 +23,7 @@
import argparse
import base64
import datetime
import decimal

from google.cloud import spanner
from google.cloud.spanner_v1 import param_types
@@ -723,6 +724,64 @@ def query_data_with_timestamp(instance_id, database_id):
# [END spanner_query_data_with_timestamp_column]


# [START spanner_add_numeric_column]
def add_numeric_column(instance_id, database_id):
""" Adds a new NUMERIC column to the Venues table in the example database.
"""
spanner_client = spanner.Client()
instance = spanner_client.instance(instance_id)

database = instance.database(database_id)

operation = database.update_ddl(["ALTER TABLE Venues ADD COLUMN Revenue NUMERIC"])

print("Waiting for operation to complete...")
operation.result(120)

print(
'Altered table "Venues" on database {} on instance {}.'.format(
database_id, instance_id
)
)


# [END spanner_add_numeric_column]


# [START spanner_update_data_with_numeric_column]
def update_data_with_numeric(instance_id, database_id):
"""Updates Venues tables in the database with the NUMERIC
column.
This updates the `Revenue` column which must be created before
running this sample. You can add the column by running the
`add_numeric_column` sample or by running this DDL statement
against your database:
ALTER TABLE Venues ADD COLUMN Revenue NUMERIC
"""
spanner_client = spanner.Client()
instance = spanner_client.instance(instance_id)

database = instance.database(database_id)

with database.batch() as batch:
batch.update(
table="Venues",
columns=("VenueId", "Revenue"),
values=[
(4, decimal.Decimal("35000")),
(19, decimal.Decimal("104500")),
(42, decimal.Decimal("99999999999999999999999999999.99")),
],
)

print("Updated data.")


# [END spanner_update_data_with_numeric_column]


# [START spanner_write_data_for_struct_queries]
def write_struct_data(instance_id, database_id):
"""Inserts sample data that can be used to test STRUCT parameters
@@ -843,7 +902,7 @@ def query_struct_field(instance_id, database_id):
print(u"SingerId: {}".format(*row))


# [START spanner_field_access_on_struct_parameters]
# [END spanner_field_access_on_struct_parameters]


# [START spanner_field_access_on_nested_struct_parameters]
@@ -1500,6 +1559,31 @@ def query_data_with_string(instance_id, database_id):
# [END spanner_query_with_string_parameter]


def query_data_with_numeric_parameter(instance_id, database_id):
"""Queries sample data using SQL with a NUMERIC parameter. """
# [START spanner_query_with_numeric_parameter]
# 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)

example_numeric = decimal.Decimal("100000")
param = {"revenue": example_numeric}
param_type = {"revenue": param_types.NUMERIC}

with database.snapshot() as snapshot:
results = snapshot.execute_sql(
"SELECT VenueId, Revenue FROM Venues " "WHERE Revenue < @revenue",
params=param,
param_types=param_type,
)

for row in results:
print(u"VenueId: {}, Revenue: {}".format(*row))
# [END spanner_query_with_numeric_parameter]


def query_data_with_timestamp_parameter(instance_id, database_id):
"""Queries sample data using SQL with a TIMESTAMP parameter. """
# [START spanner_query_with_timestamp_parameter]
@@ -1510,6 +1594,13 @@ def query_data_with_timestamp_parameter(instance_id, database_id):
database = instance.database(database_id)

example_timestamp = datetime.datetime.utcnow().isoformat() + "Z"
# [END spanner_query_with_timestamp_parameter]
# Avoid time drift on the local machine.
# https://github.com/GoogleCloudPlatform/python-docs-samples/issues/4197.
example_timestamp = (
datetime.datetime.utcnow() + datetime.timedelta(days=1)
).isoformat() + "Z"
# [START spanner_query_with_timestamp_parameter]
param = {"last_update_time": example_timestamp}
param_type = {"last_update_time": param_types.TIMESTAMP}

0 comments on commit 7549383

Please sign in to comment.