Hay más ejemplos de AWS SDK disponibles en el GitHub repositorio de [ejemplos de AWS Doc SDK](https://github.com/awsdocs/aws-doc-sdk-examples).
Las traducciones son generadas a través de traducción automática. En caso de conflicto entre la traducción y la version original de inglés, prevalecerá la version en inglés.
# Ejemplos de Aurora usando SDK para Python (Boto3)
Los siguientes ejemplos de código muestran cómo realizar acciones e implementar escenarios comunes mediante el uso AWS SDK para Python (Boto3) de Aurora.
Los *conceptos básicos* son ejemplos de código que muestran cómo realizar las operaciones esenciales dentro de un servicio.
Las *acciones* son extractos de código de programas más grandes y deben ejecutarse en contexto. Mientras las acciones muestran cómo llamar a las distintas funciones de servicio, es posible ver las acciones en contexto en los escenarios relacionados.
Los *escenarios* son ejemplos de código que muestran cómo llevar a cabo una tarea específica a través de llamadas a varias funciones dentro del servicio o combinado con otros Servicios de AWS.
En cada ejemplo se incluye un enlace al código de origen completo, con instrucciones de configuración y ejecución del código en el contexto.
**Topics**
+ [Introducción](#get_started)
+ [Conceptos básicos](#basics)
+ [Acciones](#actions)
+ [Escenarios](#scenarios)
## Introducción
### Introducción a Aurora
En el siguiente ejemplo de código, se muestra cómo empezar a utilizar Aurora.
**SDK para Python (Boto3)**
Hay más información al respecto GitHub. Busque el ejemplo completo y aprenda a configurar y ejecutar en el [Repositorio de ejemplos de código de AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/aurora#code-examples).
```
import boto3
# Create an RDS client
rds = boto3.client("rds")
# Create a paginator for the describe_db_clusters operation
paginator = rds.get_paginator("describe_db_clusters")
# Use the paginator to get a list of DB clusters
response_iterator = paginator.paginate(
PaginationConfig={
"PageSize": 50, # Adjust PageSize as needed
"StartingToken": None,
}
)
# Iterate through the pages of the response
clusters_found = False
for page in response_iterator:
if "DBClusters" in page and page["DBClusters"]:
clusters_found = True
print("Here are your RDS Aurora clusters:")
for cluster in page["DBClusters"]:
print(
f"Cluster ID: {cluster['DBClusterIdentifier']}, Engine: {cluster['Engine']}"
)
if not clusters_found:
print("No clusters found!")
```
+ Para obtener más información sobre la API, consulta la [sección Describe DBClusters](https://docs.aws.amazon.com/goto/boto3/rds-2014-10-31/DescribeDBClusters) en la referencia de la API de *AWS SDK for Python (Boto3*).
## Conceptos básicos
### Conceptos básicos
En el siguiente ejemplo de código, se muestra cómo:
+ Cree un grupo de parámetros de clúster de base de datos de Aurora y defina los valores de los parámetros.
+ Cree un clúster de base de datos que utilice el grupo de parámetros.
+ Cree una instancia de base de datos que contenga una base de datos.
+ Realice una instantánea del clúster de base de datos y luego limpie los recursos.
**SDK para Python (Boto3)**
Hay más información al respecto. GitHub Busque el ejemplo completo y aprenda a configurar y ejecutar en el [Repositorio de ejemplos de código de AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/aurora#code-examples).
Ejecutar un escenario interactivo en un símbolo del sistema.
```
class AuroraClusterScenario:
"""Runs a scenario that shows how to get started using Aurora DB clusters."""
def __init__(self, aurora_wrapper):
"""
:param aurora_wrapper: An object that wraps Aurora DB cluster actions.
"""
self.aurora_wrapper = aurora_wrapper
def create_parameter_group(self, db_engine, parameter_group_name):
"""
Shows how to get available engine versions for a specified database engine and
create a DB cluster parameter group that is compatible with a selected engine family.
:param db_engine: The database engine to use as a basis.
:param parameter_group_name: The name given to the newly created parameter group.
:return: The newly created parameter group.
"""
print(
f"Checking for an existing DB cluster parameter group named {parameter_group_name}."
)
parameter_group = self.aurora_wrapper.get_parameter_group(parameter_group_name)
if parameter_group is None:
print(f"Getting available database engine versions for {db_engine}.")
engine_versions = self.aurora_wrapper.get_engine_versions(db_engine)
families = list({ver["DBParameterGroupFamily"] for ver in engine_versions})
family_index = q.choose("Which family do you want to use? ", families)
print(f"Creating a DB cluster parameter group.")
self.aurora_wrapper.create_parameter_group(
parameter_group_name, families[family_index], "Example parameter group."
)
parameter_group = self.aurora_wrapper.get_parameter_group(
parameter_group_name
)
print(f"Parameter group {parameter_group['DBClusterParameterGroupName']}:")
pp(parameter_group)
print("-" * 88)
return parameter_group
def set_user_parameters(self, parameter_group_name):
"""
Shows how to get the parameters contained in a custom parameter group and
update some of the parameter values in the group.
:param parameter_group_name: The name of the parameter group to query and modify.
"""
print("Let's set some parameter values in your parameter group.")
auto_inc_parameters = self.aurora_wrapper.get_parameters(
parameter_group_name, name_prefix="auto_increment"
)
update_params = []
for auto_inc in auto_inc_parameters:
if auto_inc["IsModifiable"] and auto_inc["DataType"] == "integer":
print(f"The {auto_inc['ParameterName']} parameter is described as:")
print(f"\t{auto_inc['Description']}")
param_range = auto_inc["AllowedValues"].split("-")
auto_inc["ParameterValue"] = str(
q.ask(
f"Enter a value between {param_range[0]} and {param_range[1]}: ",
q.is_int,
q.in_range(int(param_range[0]), int(param_range[1])),
)
)
update_params.append(auto_inc)
self.aurora_wrapper.update_parameters(parameter_group_name, update_params)
print(
"You can get a list of parameters you've set by specifying a source of 'user'."
)
user_parameters = self.aurora_wrapper.get_parameters(
parameter_group_name, source="user"
)
pp(user_parameters)
print("-" * 88)
def create_cluster(self, cluster_name, db_engine, db_name, parameter_group):
"""
Shows how to create an Aurora DB cluster that contains a database of a specified
type. The database is also configured to use a custom DB cluster parameter group.
:param cluster_name: The name given to the newly created DB cluster.
:param db_engine: The engine of the created database.
:param db_name: The name given to the created database.
:param parameter_group: The parameter group that is associated with the DB cluster.
:return: The newly created DB cluster.
"""
print("Checking for an existing DB cluster.")
cluster = self.aurora_wrapper.get_db_cluster(cluster_name)
if cluster is None:
admin_username = q.ask(
"Enter an administrator user name for the database: ", q.non_empty
)
admin_password = q.ask(
"Enter a password for the administrator (at least 8 characters): ",
q.non_empty,
)
engine_versions = self.aurora_wrapper.get_engine_versions(
db_engine, parameter_group["DBParameterGroupFamily"]
)
engine_choices = [
ver["EngineVersionDescription"] for ver in engine_versions
]
print("The available engines for your parameter group are:")
engine_index = q.choose("Which engine do you want to use? ", engine_choices)
print(
f"Creating DB cluster {cluster_name} and database {db_name}.\n"
f"The DB cluster is configured to use\n"
f"your custom parameter group {parameter_group['DBClusterParameterGroupName']}\n"
f"and selected engine {engine_choices[engine_index]}.\n"
f"This typically takes several minutes."
)
cluster = self.aurora_wrapper.create_db_cluster(
cluster_name,
parameter_group["DBClusterParameterGroupName"],
db_name,
db_engine,
engine_versions[engine_index]["EngineVersion"],
admin_username,
admin_password,
)
while cluster.get("Status") != "available":
wait(30)
cluster = self.aurora_wrapper.get_db_cluster(cluster_name)
print("Cluster created and available.\n")
print("Cluster data:")
pp(cluster)
print("-" * 88)
return cluster
def create_instance(self, cluster):
"""
Shows how to create a DB instance in an existing Aurora DB cluster. A new DB cluster
contains no DB instances, so you must add one. The first DB instance that is added
to a DB cluster defaults to a read-write DB instance.
:param cluster: The DB cluster where the DB instance is added.
:return: The newly created DB instance.
"""
print("Checking for an existing database instance.")
cluster_name = cluster["DBClusterIdentifier"]
db_inst = self.aurora_wrapper.get_db_instance(cluster_name)
if db_inst is None:
print("Let's create a database instance in your DB cluster.")
print("First, choose a DB instance type:")
inst_opts = self.aurora_wrapper.get_orderable_instances(
cluster["Engine"], cluster["EngineVersion"]
)
inst_choices = list(
{
opt["DBInstanceClass"] + ", storage type: " + opt["StorageType"]
for opt in inst_opts
}
)
inst_index = q.choose(
"Which DB instance class do you want to use? ", inst_choices
)
print(
f"Creating a database instance. This typically takes several minutes."
)
db_inst = self.aurora_wrapper.create_instance_in_cluster(
cluster_name,
cluster_name,
cluster["Engine"],
inst_opts[inst_index]["DBInstanceClass"],
)
while db_inst.get("DBInstanceStatus") != "available":
wait(30)
db_inst = self.aurora_wrapper.get_db_instance(cluster_name)
print("Instance data:")
pp(db_inst)
print("-" * 88)
return db_inst
@staticmethod
def display_connection(cluster):
"""
Displays connection information about an Aurora DB cluster and tips on how to
connect to it.
:param cluster: The DB cluster to display.
"""
print(
"You can now connect to your database using your favorite MySql client.\n"
"One way to connect is by using the 'mysql' shell on an Amazon EC2 instance\n"
"that is running in the same VPC as your database cluster. Pass the endpoint,\n"
"port, and administrator user name to 'mysql' and enter your password\n"
"when prompted:\n"
)
print(
f"\n\tmysql -h {cluster['Endpoint']} -P {cluster['Port']} -u {cluster['MasterUsername']} -p\n"
)
print(
"For more information, see the User Guide for Aurora:\n"
"\thttps://docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/CHAP_GettingStartedAurora.CreatingConnecting.Aurora.html#CHAP_GettingStartedAurora.Aurora.Connect"
)
print("-" * 88)
def create_snapshot(self, cluster_name):
"""
Shows how to create a DB cluster snapshot and wait until it's available.
:param cluster_name: The name of a DB cluster to snapshot.
"""
if q.ask(
"Do you want to create a snapshot of your DB cluster (y/n)? ", q.is_yesno
):
snapshot_id = f"{cluster_name}-{uuid.uuid4()}"
print(
f"Creating a snapshot named {snapshot_id}. This typically takes a few minutes."
)
snapshot = self.aurora_wrapper.create_cluster_snapshot(
snapshot_id, cluster_name
)
while snapshot.get("Status") != "available":
wait(30)
snapshot = self.aurora_wrapper.get_cluster_snapshot(snapshot_id)
pp(snapshot)
print("-" * 88)
def cleanup(self, db_inst, cluster, parameter_group):
"""
Shows how to clean up a DB instance, DB cluster, and DB cluster parameter group.
Before the DB cluster parameter group can be deleted, all associated DB instances and
DB clusters must first be deleted.
:param db_inst: The DB instance to delete.
:param cluster: The DB cluster to delete.
:param parameter_group: The DB cluster parameter group to delete.
"""
cluster_name = cluster["DBClusterIdentifier"]
parameter_group_name = parameter_group["DBClusterParameterGroupName"]
if q.ask(
"\nDo you want to delete the database instance, DB cluster, and parameter "
"group (y/n)? ",
q.is_yesno,
):
print(f"Deleting database instance {db_inst['DBInstanceIdentifier']}.")
self.aurora_wrapper.delete_db_instance(db_inst["DBInstanceIdentifier"])
print(f"Deleting database cluster {cluster_name}.")
self.aurora_wrapper.delete_db_cluster(cluster_name)
print(
"Waiting for the DB instance and DB cluster to delete.\n"
"This typically takes several minutes."
)
while db_inst is not None or cluster is not None:
wait(30)
if db_inst is not None:
db_inst = self.aurora_wrapper.get_db_instance(
db_inst["DBInstanceIdentifier"]
)
if cluster is not None:
cluster = self.aurora_wrapper.get_db_cluster(
cluster["DBClusterIdentifier"]
)
print(f"Deleting parameter group {parameter_group_name}.")
self.aurora_wrapper.delete_parameter_group(parameter_group_name)
def run_scenario(self, db_engine, parameter_group_name, cluster_name, db_name):
print("-" * 88)
print(
"Welcome to the Amazon Relational Database Service (Amazon RDS) get started\n"
"with Aurora DB clusters demo."
)
print("-" * 88)
parameter_group = self.create_parameter_group(db_engine, parameter_group_name)
self.set_user_parameters(parameter_group_name)
cluster = self.create_cluster(cluster_name, db_engine, db_name, parameter_group)
wait(5)
db_inst = self.create_instance(cluster)
self.display_connection(cluster)
self.create_snapshot(cluster_name)
self.cleanup(db_inst, cluster, parameter_group)
print("\nThanks for watching!")
print("-" * 88)
if __name__ == "__main__":
logging.basicConfig(level=logging.INFO, format="%(levelname)s: %(message)s")
try:
scenario = AuroraClusterScenario(AuroraWrapper.from_client())
scenario.run_scenario(
"aurora-mysql",
"doc-example-cluster-parameter-group",
"doc-example-aurora",
"docexampledb",
)
except Exception:
logging.exception("Something went wrong with the demo.")
```
Defina las funciones a las que llama el escenario para administrar las acciones de Aurora.
```
class AuroraWrapper:
"""Encapsulates Aurora DB cluster actions."""
def __init__(self, rds_client):
"""
:param rds_client: A Boto3 Amazon Relational Database Service (Amazon RDS) client.
"""
self.rds_client = rds_client
@classmethod
def from_client(cls):
"""
Instantiates this class from a Boto3 client.
"""
rds_client = boto3.client("rds")
return cls(rds_client)
def get_parameter_group(self, parameter_group_name):
"""
Gets a DB cluster parameter group.
:param parameter_group_name: The name of the parameter group to retrieve.
:return: The requested parameter group.
"""
try:
response = self.rds_client.describe_db_cluster_parameter_groups(
DBClusterParameterGroupName=parameter_group_name
)
parameter_group = response["DBClusterParameterGroups"][0]
except ClientError as err:
if err.response["Error"]["Code"] == "DBParameterGroupNotFound":
logger.info("Parameter group %s does not exist.", parameter_group_name)
else:
logger.error(
"Couldn't get parameter group %s. Here's why: %s: %s",
parameter_group_name,
err.response["Error"]["Code"],
err.response["Error"]["Message"],
)
raise
else:
return parameter_group
def create_parameter_group(
self, parameter_group_name, parameter_group_family, description
):
"""
Creates a DB cluster parameter group that is based on the specified parameter group
family.
:param parameter_group_name: The name of the newly created parameter group.
:param parameter_group_family: The family that is used as the basis of the new
parameter group.
:param description: A description given to the parameter group.
:return: Data about the newly created parameter group.
"""
try:
response = self.rds_client.create_db_cluster_parameter_group(
DBClusterParameterGroupName=parameter_group_name,
DBParameterGroupFamily=parameter_group_family,
Description=description,
)
except ClientError as err:
logger.error(
"Couldn't create parameter group %s. Here's why: %s: %s",
parameter_group_name,
err.response["Error"]["Code"],
err.response["Error"]["Message"],
)
raise
else:
return response
def delete_parameter_group(self, parameter_group_name):
"""
Deletes a DB cluster parameter group.
:param parameter_group_name: The name of the parameter group to delete.
:return: Data about the parameter group.
"""
try:
response = self.rds_client.delete_db_cluster_parameter_group(
DBClusterParameterGroupName=parameter_group_name
)
except ClientError as err:
logger.error(
"Couldn't delete parameter group %s. Here's why: %s: %s",
parameter_group_name,
err.response["Error"]["Code"],
err.response["Error"]["Message"],
)
raise
else:
return response
def get_parameters(self, parameter_group_name, name_prefix="", source=None):
"""
Gets the parameters that are contained in a DB cluster parameter group.
:param parameter_group_name: The name of the parameter group to query.
:param name_prefix: When specified, the retrieved list of parameters is filtered
to contain only parameters that start with this prefix.
:param source: When specified, only parameters from this source are retrieved.
For example, a source of 'user' retrieves only parameters that
were set by a user.
:return: The list of requested parameters.
"""
try:
kwargs = {"DBClusterParameterGroupName": parameter_group_name}
if source is not None:
kwargs["Source"] = source
parameters = []
paginator = self.rds_client.get_paginator("describe_db_cluster_parameters")
for page in paginator.paginate(**kwargs):
parameters += [
p
for p in page["Parameters"]
if p["ParameterName"].startswith(name_prefix)
]
except ClientError as err:
logger.error(
"Couldn't get parameters for %s. Here's why: %s: %s",
parameter_group_name,
err.response["Error"]["Code"],
err.response["Error"]["Message"],
)
raise
else:
return parameters
def update_parameters(self, parameter_group_name, update_parameters):
"""
Updates parameters in a custom DB cluster parameter group.
:param parameter_group_name: The name of the parameter group to update.
:param update_parameters: The parameters to update in the group.
:return: Data about the modified parameter group.
"""
try:
response = self.rds_client.modify_db_cluster_parameter_group(
DBClusterParameterGroupName=parameter_group_name,
Parameters=update_parameters,
)
except ClientError as err:
logger.error(
"Couldn't update parameters in %s. Here's why: %s: %s",
parameter_group_name,
err.response["Error"]["Code"],
err.response["Error"]["Message"],
)
raise
else:
return response
def get_db_cluster(self, cluster_name):
"""
Gets data about an Aurora DB cluster.
:param cluster_name: The name of the DB cluster to retrieve.
:return: The retrieved DB cluster.
"""
try:
response = self.rds_client.describe_db_clusters(
DBClusterIdentifier=cluster_name
)
cluster = response["DBClusters"][0]
except ClientError as err:
if err.response["Error"]["Code"] == "DBClusterNotFoundFault":
logger.info("Cluster %s does not exist.", cluster_name)
else:
logger.error(
"Couldn't verify the existence of DB cluster %s. Here's why: %s: %s",
cluster_name,
err.response["Error"]["Code"],
err.response["Error"]["Message"],
)
raise
else:
return cluster
def create_db_cluster(
self,
cluster_name,
parameter_group_name,
db_name,
db_engine,
db_engine_version,
admin_name,
admin_password,
):
"""
Creates a DB cluster that is configured to use the specified parameter group.
The newly created DB cluster contains a database that uses the specified engine and
engine version.
:param cluster_name: The name of the DB cluster to create.
:param parameter_group_name: The name of the parameter group to associate with
the DB cluster.
:param db_name: The name of the database to create.
:param db_engine: The database engine of the database that is created, such as MySql.
:param db_engine_version: The version of the database engine.
:param admin_name: The user name of the database administrator.
:param admin_password: The password of the database administrator.
:return: The newly created DB cluster.
"""
try:
response = self.rds_client.create_db_cluster(
DatabaseName=db_name,
DBClusterIdentifier=cluster_name,
DBClusterParameterGroupName=parameter_group_name,
Engine=db_engine,
EngineVersion=db_engine_version,
MasterUsername=admin_name,
MasterUserPassword=admin_password,
)
cluster = response["DBCluster"]
except ClientError as err:
logger.error(
"Couldn't create database %s. Here's why: %s: %s",
db_name,
err.response["Error"]["Code"],
err.response["Error"]["Message"],
)
raise
else:
return cluster
def delete_db_cluster(self, cluster_name):
"""
Deletes a DB cluster.
:param cluster_name: The name of the DB cluster to delete.
"""
try:
self.rds_client.delete_db_cluster(
DBClusterIdentifier=cluster_name, SkipFinalSnapshot=True
)
logger.info("Deleted DB cluster %s.", cluster_name)
except ClientError:
logger.exception("Couldn't delete DB cluster %s.", cluster_name)
raise
def create_cluster_snapshot(self, snapshot_id, cluster_id):
"""
Creates a snapshot of a DB cluster.
:param snapshot_id: The ID to give the created snapshot.
:param cluster_id: The DB cluster to snapshot.
:return: Data about the newly created snapshot.
"""
try:
response = self.rds_client.create_db_cluster_snapshot(
DBClusterSnapshotIdentifier=snapshot_id, DBClusterIdentifier=cluster_id
)
snapshot = response["DBClusterSnapshot"]
except ClientError as err:
logger.error(
"Couldn't create snapshot of %s. Here's why: %s: %s",
cluster_id,
err.response["Error"]["Code"],
err.response["Error"]["Message"],
)
raise
else:
return snapshot
def get_cluster_snapshot(self, snapshot_id):
"""
Gets a DB cluster snapshot.
:param snapshot_id: The ID of the snapshot to retrieve.
:return: The retrieved snapshot.
"""
try:
response = self.rds_client.describe_db_cluster_snapshots(
DBClusterSnapshotIdentifier=snapshot_id
)
snapshot = response["DBClusterSnapshots"][0]
except ClientError as err:
logger.error(
"Couldn't get DB cluster snapshot %s. Here's why: %s: %s",
snapshot_id,
err.response["Error"]["Code"],
err.response["Error"]["Message"],
)
raise
else:
return snapshot
def create_instance_in_cluster(
self, instance_id, cluster_id, db_engine, instance_class
):
"""
Creates a database instance in an existing DB cluster. The first database that is
created defaults to a read-write DB instance.
:param instance_id: The ID to give the newly created DB instance.
:param cluster_id: The ID of the DB cluster where the DB instance is created.
:param db_engine: The database engine of a database to create in the DB instance.
This must be compatible with the configured parameter group
of the DB cluster.
:param instance_class: The DB instance class for the newly created DB instance.
:return: Data about the newly created DB instance.
"""
try:
response = self.rds_client.create_db_instance(
DBInstanceIdentifier=instance_id,
DBClusterIdentifier=cluster_id,
Engine=db_engine,
DBInstanceClass=instance_class,
)
db_inst = response["DBInstance"]
except ClientError as err:
logger.error(
"Couldn't create DB instance %s. Here's why: %s: %s",
instance_id,
err.response["Error"]["Code"],
err.response["Error"]["Message"],
)
raise
else:
return db_inst
def get_engine_versions(self, engine, parameter_group_family=None):
"""
Gets database engine versions that are available for the specified engine
and parameter group family.
:param engine: The database engine to look up.
:param parameter_group_family: When specified, restricts the returned list of
engine versions to those that are compatible with
this parameter group family.
:return: The list of database engine versions.
"""
try:
kwargs = {"Engine": engine}
if parameter_group_family is not None:
kwargs["DBParameterGroupFamily"] = parameter_group_family
response = self.rds_client.describe_db_engine_versions(**kwargs)
versions = response["DBEngineVersions"]
except ClientError as err:
logger.error(
"Couldn't get engine versions for %s. Here's why: %s: %s",
engine,
err.response["Error"]["Code"],
err.response["Error"]["Message"],
)
raise
else:
return versions
def get_orderable_instances(self, db_engine, db_engine_version):
"""
Gets DB instance options that can be used to create DB instances that are
compatible with a set of specifications.
:param db_engine: The database engine that must be supported by the DB instance.
:param db_engine_version: The engine version that must be supported by the DB instance.
:return: The list of DB instance options that can be used to create a compatible DB instance.
"""
try:
inst_opts = []
paginator = self.rds_client.get_paginator(
"describe_orderable_db_instance_options"
)
for page in paginator.paginate(
Engine=db_engine, EngineVersion=db_engine_version
):
inst_opts += page["OrderableDBInstanceOptions"]
except ClientError as err:
logger.error(
"Couldn't get orderable DB instances. Here's why: %s: %s",
err.response["Error"]["Code"],
err.response["Error"]["Message"],
)
raise
else:
return inst_opts
def get_db_instance(self, instance_id):
"""
Gets data about a DB instance.
:param instance_id: The ID of the DB instance to retrieve.
:return: The retrieved DB instance.
"""
try:
response = self.rds_client.describe_db_instances(
DBInstanceIdentifier=instance_id
)
db_inst = response["DBInstances"][0]
except ClientError as err:
if err.response["Error"]["Code"] == "DBInstanceNotFound":
logger.info("Instance %s does not exist.", instance_id)
else:
logger.error(
"Couldn't get DB instance %s. Here's why: %s: %s",
instance_id,
err.response["Error"]["Code"],
err.response["Error"]["Message"],
)
raise
else:
return db_inst
def delete_db_instance(self, instance_id):
"""
Deletes a DB instance.
:param instance_id: The ID of the DB instance to delete.
:return: Data about the deleted DB instance.
"""
try:
response = self.rds_client.delete_db_instance(
DBInstanceIdentifier=instance_id,
SkipFinalSnapshot=True,
DeleteAutomatedBackups=True,
)
db_inst = response["DBInstance"]
except ClientError as err:
logger.error(
"Couldn't delete DB instance %s. Here's why: %s: %s",
instance_id,
err.response["Error"]["Code"],
err.response["Error"]["Message"],
)
raise
else:
return db_inst
```
+ Para obtener información sobre la API, consulte los siguientes temas en la *Referencia de la API de AWS SDK para Python (Boto3)*.
+ [CrearDBCluster](https://docs.aws.amazon.com/goto/boto3/rds-2014-10-31/CreateDBCluster)
+ [CrearDBClusterParameterGroup](https://docs.aws.amazon.com/goto/boto3/rds-2014-10-31/CreateDBClusterParameterGroup)
+ [Crear DBCluster instantánea](https://docs.aws.amazon.com/goto/boto3/rds-2014-10-31/CreateDBClusterSnapshot)
+ [CrearDBInstance](https://docs.aws.amazon.com/goto/boto3/rds-2014-10-31/CreateDBInstance)
+ [DeleteDBCluster](https://docs.aws.amazon.com/goto/boto3/rds-2014-10-31/DeleteDBCluster)
+ [DeleteDBClusterParameterGroup](https://docs.aws.amazon.com/goto/boto3/rds-2014-10-31/DeleteDBClusterParameterGroup)
+ [DeleteDBInstance](https://docs.aws.amazon.com/goto/boto3/rds-2014-10-31/DeleteDBInstance)
+ [DescribirDBClusterParameterGroups](https://docs.aws.amazon.com/goto/boto3/rds-2014-10-31/DescribeDBClusterParameterGroups)
+ [Describa DBCluster los parámetros](https://docs.aws.amazon.com/goto/boto3/rds-2014-10-31/DescribeDBClusterParameters)
+ [Describa las DBCluster instantáneas](https://docs.aws.amazon.com/goto/boto3/rds-2014-10-31/DescribeDBClusterSnapshots)
+ [DescribirDBClusters](https://docs.aws.amazon.com/goto/boto3/rds-2014-10-31/DescribeDBClusters)
+ [Describa las versiones DBEngine](https://docs.aws.amazon.com/goto/boto3/rds-2014-10-31/DescribeDBEngineVersions)
+ [DescribirDBInstances](https://docs.aws.amazon.com/goto/boto3/rds-2014-10-31/DescribeDBInstances)
+ [DescribeOrderableDBInstanceOpciones](https://docs.aws.amazon.com/goto/boto3/rds-2014-10-31/DescribeOrderableDBInstanceOptions)
+ [ModifyDBClusterParameterGroup](https://docs.aws.amazon.com/goto/boto3/rds-2014-10-31/ModifyDBClusterParameterGroup)
## Acciones
### `CreateDBCluster`
En el siguiente ejemplo de código, se muestra cómo utilizar `CreateDBCluster`.
**SDK para Python (Boto3)**
Hay más información GitHub. Busque el ejemplo completo y aprenda a configurar y ejecutar en el [Repositorio de ejemplos de código de AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/aurora#code-examples).
```
class AuroraWrapper:
"""Encapsulates Aurora DB cluster actions."""
def __init__(self, rds_client):
"""
:param rds_client: A Boto3 Amazon Relational Database Service (Amazon RDS) client.
"""
self.rds_client = rds_client
@classmethod
def from_client(cls):
"""
Instantiates this class from a Boto3 client.
"""
rds_client = boto3.client("rds")
return cls(rds_client)
def create_db_cluster(
self,
cluster_name,
parameter_group_name,
db_name,
db_engine,
db_engine_version,
admin_name,
admin_password,
):
"""
Creates a DB cluster that is configured to use the specified parameter group.
The newly created DB cluster contains a database that uses the specified engine and
engine version.
:param cluster_name: The name of the DB cluster to create.
:param parameter_group_name: The name of the parameter group to associate with
the DB cluster.
:param db_name: The name of the database to create.
:param db_engine: The database engine of the database that is created, such as MySql.
:param db_engine_version: The version of the database engine.
:param admin_name: The user name of the database administrator.
:param admin_password: The password of the database administrator.
:return: The newly created DB cluster.
"""
try:
response = self.rds_client.create_db_cluster(
DatabaseName=db_name,
DBClusterIdentifier=cluster_name,
DBClusterParameterGroupName=parameter_group_name,
Engine=db_engine,
EngineVersion=db_engine_version,
MasterUsername=admin_name,
MasterUserPassword=admin_password,
)
cluster = response["DBCluster"]
except ClientError as err:
logger.error(
"Couldn't create database %s. Here's why: %s: %s",
db_name,
err.response["Error"]["Code"],
err.response["Error"]["Message"],
)
raise
else:
return cluster
```
+ Para obtener más información sobre la API, consulta la referencia de la API [Create DBCluster](https://docs.aws.amazon.com/goto/boto3/rds-2014-10-31/CreateDBCluster) in *AWS SDK for Python (Boto3*).
### `CreateDBClusterParameterGroup`
En el siguiente ejemplo de código, se muestra cómo utilizar `CreateDBClusterParameterGroup`.
**SDK para Python (Boto3)**
Hay más información al respecto. GitHub Busque el ejemplo completo y aprenda a configurar y ejecutar en el [Repositorio de ejemplos de código de AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/aurora#code-examples).
```
class AuroraWrapper:
"""Encapsulates Aurora DB cluster actions."""
def __init__(self, rds_client):
"""
:param rds_client: A Boto3 Amazon Relational Database Service (Amazon RDS) client.
"""
self.rds_client = rds_client
@classmethod
def from_client(cls):
"""
Instantiates this class from a Boto3 client.
"""
rds_client = boto3.client("rds")
return cls(rds_client)
def create_parameter_group(
self, parameter_group_name, parameter_group_family, description
):
"""
Creates a DB cluster parameter group that is based on the specified parameter group
family.
:param parameter_group_name: The name of the newly created parameter group.
:param parameter_group_family: The family that is used as the basis of the new
parameter group.
:param description: A description given to the parameter group.
:return: Data about the newly created parameter group.
"""
try:
response = self.rds_client.create_db_cluster_parameter_group(
DBClusterParameterGroupName=parameter_group_name,
DBParameterGroupFamily=parameter_group_family,
Description=description,
)
except ClientError as err:
logger.error(
"Couldn't create parameter group %s. Here's why: %s: %s",
parameter_group_name,
err.response["Error"]["Code"],
err.response["Error"]["Message"],
)
raise
else:
return response
```
+ Para obtener más información sobre la API, consulta la referencia de la API [Create DBCluster ParameterGroup](https://docs.aws.amazon.com/goto/boto3/rds-2014-10-31/CreateDBClusterParameterGroup) in *AWS SDK for Python (Boto3*).
### `CreateDBClusterSnapshot`
En el siguiente ejemplo de código, se muestra cómo utilizar `CreateDBClusterSnapshot`.
**SDK para Python (Boto3)**
Hay más información al respecto. GitHub Busque el ejemplo completo y aprenda a configurar y ejecutar en el [Repositorio de ejemplos de código de AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/aurora#code-examples).
```
class AuroraWrapper:
"""Encapsulates Aurora DB cluster actions."""
def __init__(self, rds_client):
"""
:param rds_client: A Boto3 Amazon Relational Database Service (Amazon RDS) client.
"""
self.rds_client = rds_client
@classmethod
def from_client(cls):
"""
Instantiates this class from a Boto3 client.
"""
rds_client = boto3.client("rds")
return cls(rds_client)
def create_cluster_snapshot(self, snapshot_id, cluster_id):
"""
Creates a snapshot of a DB cluster.
:param snapshot_id: The ID to give the created snapshot.
:param cluster_id: The DB cluster to snapshot.
:return: Data about the newly created snapshot.
"""
try:
response = self.rds_client.create_db_cluster_snapshot(
DBClusterSnapshotIdentifier=snapshot_id, DBClusterIdentifier=cluster_id
)
snapshot = response["DBClusterSnapshot"]
except ClientError as err:
logger.error(
"Couldn't create snapshot of %s. Here's why: %s: %s",
cluster_id,
err.response["Error"]["Code"],
err.response["Error"]["Message"],
)
raise
else:
return snapshot
```
+ Para obtener más información sobre la API, consulta [Crear DBCluster una instantánea](https://docs.aws.amazon.com/goto/boto3/rds-2014-10-31/CreateDBClusterSnapshot) en la referencia de la API del *AWS SDK for Python (Boto3*).
### `CreateDBInstance`
En el siguiente ejemplo de código, se muestra cómo utilizar `CreateDBInstance`.
**SDK para Python (Boto3)**
Hay más información al respecto. GitHub Busque el ejemplo completo y aprenda a configurar y ejecutar en el [Repositorio de ejemplos de código de AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/aurora#code-examples).
```
class AuroraWrapper:
"""Encapsulates Aurora DB cluster actions."""
def __init__(self, rds_client):
"""
:param rds_client: A Boto3 Amazon Relational Database Service (Amazon RDS) client.
"""
self.rds_client = rds_client
@classmethod
def from_client(cls):
"""
Instantiates this class from a Boto3 client.
"""
rds_client = boto3.client("rds")
return cls(rds_client)
def create_instance_in_cluster(
self, instance_id, cluster_id, db_engine, instance_class
):
"""
Creates a database instance in an existing DB cluster. The first database that is
created defaults to a read-write DB instance.
:param instance_id: The ID to give the newly created DB instance.
:param cluster_id: The ID of the DB cluster where the DB instance is created.
:param db_engine: The database engine of a database to create in the DB instance.
This must be compatible with the configured parameter group
of the DB cluster.
:param instance_class: The DB instance class for the newly created DB instance.
:return: Data about the newly created DB instance.
"""
try:
response = self.rds_client.create_db_instance(
DBInstanceIdentifier=instance_id,
DBClusterIdentifier=cluster_id,
Engine=db_engine,
DBInstanceClass=instance_class,
)
db_inst = response["DBInstance"]
except ClientError as err:
logger.error(
"Couldn't create DB instance %s. Here's why: %s: %s",
instance_id,
err.response["Error"]["Code"],
err.response["Error"]["Message"],
)
raise
else:
return db_inst
```
+ Para obtener más información sobre la API, consulta la referencia de la API [Create DBInstance](https://docs.aws.amazon.com/goto/boto3/rds-2014-10-31/CreateDBInstance) in *AWS SDK for Python (Boto3*).
### `DeleteDBCluster`
En el siguiente ejemplo de código, se muestra cómo utilizar `DeleteDBCluster`.
**SDK para Python (Boto3)**
Hay más información al respecto. GitHub Busque el ejemplo completo y aprenda a configurar y ejecutar en el [Repositorio de ejemplos de código de AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/aurora#code-examples).
```
class AuroraWrapper:
"""Encapsulates Aurora DB cluster actions."""
def __init__(self, rds_client):
"""
:param rds_client: A Boto3 Amazon Relational Database Service (Amazon RDS) client.
"""
self.rds_client = rds_client
@classmethod
def from_client(cls):
"""
Instantiates this class from a Boto3 client.
"""
rds_client = boto3.client("rds")
return cls(rds_client)
def delete_db_cluster(self, cluster_name):
"""
Deletes a DB cluster.
:param cluster_name: The name of the DB cluster to delete.
"""
try:
self.rds_client.delete_db_cluster(
DBClusterIdentifier=cluster_name, SkipFinalSnapshot=True
)
logger.info("Deleted DB cluster %s.", cluster_name)
except ClientError:
logger.exception("Couldn't delete DB cluster %s.", cluster_name)
raise
```
+ Para obtener más información sobre la API, consulta [Eliminar DBCluster](https://docs.aws.amazon.com/goto/boto3/rds-2014-10-31/DeleteDBCluster) en la referencia de la API del *AWS SDK for Python (Boto3*).
### `DeleteDBClusterParameterGroup`
En el siguiente ejemplo de código, se muestra cómo utilizar `DeleteDBClusterParameterGroup`.
**SDK para Python (Boto3)**
Hay más información al respecto. GitHub Busque el ejemplo completo y aprenda a configurar y ejecutar en el [Repositorio de ejemplos de código de AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/aurora#code-examples).
```
class AuroraWrapper:
"""Encapsulates Aurora DB cluster actions."""
def __init__(self, rds_client):
"""
:param rds_client: A Boto3 Amazon Relational Database Service (Amazon RDS) client.
"""
self.rds_client = rds_client
@classmethod
def from_client(cls):
"""
Instantiates this class from a Boto3 client.
"""
rds_client = boto3.client("rds")
return cls(rds_client)
def delete_parameter_group(self, parameter_group_name):
"""
Deletes a DB cluster parameter group.
:param parameter_group_name: The name of the parameter group to delete.
:return: Data about the parameter group.
"""
try:
response = self.rds_client.delete_db_cluster_parameter_group(
DBClusterParameterGroupName=parameter_group_name
)
except ClientError as err:
logger.error(
"Couldn't delete parameter group %s. Here's why: %s: %s",
parameter_group_name,
err.response["Error"]["Code"],
err.response["Error"]["Message"],
)
raise
else:
return response
```
+ Para obtener más información sobre la API, consulta [Eliminar DBCluster ParameterGroup](https://docs.aws.amazon.com/goto/boto3/rds-2014-10-31/DeleteDBClusterParameterGroup) en la referencia de la API del *AWS SDK for Python (Boto3*).
### `DeleteDBInstance`
En el siguiente ejemplo de código, se muestra cómo utilizar `DeleteDBInstance`.
**SDK para Python (Boto3)**
Hay más información al respecto. GitHub Busque el ejemplo completo y aprenda a configurar y ejecutar en el [Repositorio de ejemplos de código de AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/aurora#code-examples).
```
class AuroraWrapper:
"""Encapsulates Aurora DB cluster actions."""
def __init__(self, rds_client):
"""
:param rds_client: A Boto3 Amazon Relational Database Service (Amazon RDS) client.
"""
self.rds_client = rds_client
@classmethod
def from_client(cls):
"""
Instantiates this class from a Boto3 client.
"""
rds_client = boto3.client("rds")
return cls(rds_client)
def delete_db_instance(self, instance_id):
"""
Deletes a DB instance.
:param instance_id: The ID of the DB instance to delete.
:return: Data about the deleted DB instance.
"""
try:
response = self.rds_client.delete_db_instance(
DBInstanceIdentifier=instance_id,
SkipFinalSnapshot=True,
DeleteAutomatedBackups=True,
)
db_inst = response["DBInstance"]
except ClientError as err:
logger.error(
"Couldn't delete DB instance %s. Here's why: %s: %s",
instance_id,
err.response["Error"]["Code"],
err.response["Error"]["Message"],
)
raise
else:
return db_inst
```
+ Para obtener más información sobre la API, consulta [Eliminar DBInstance](https://docs.aws.amazon.com/goto/boto3/rds-2014-10-31/DeleteDBInstance) en la referencia de la API del *AWS SDK for Python (Boto3*).
### `DescribeDBClusterParameterGroups`
En el siguiente ejemplo de código, se muestra cómo utilizar `DescribeDBClusterParameterGroups`.
**SDK para Python (Boto3)**
Hay más información al respecto. GitHub Busque el ejemplo completo y aprenda a configurar y ejecutar en el [Repositorio de ejemplos de código de AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/aurora#code-examples).
```
class AuroraWrapper:
"""Encapsulates Aurora DB cluster actions."""
def __init__(self, rds_client):
"""
:param rds_client: A Boto3 Amazon Relational Database Service (Amazon RDS) client.
"""
self.rds_client = rds_client
@classmethod
def from_client(cls):
"""
Instantiates this class from a Boto3 client.
"""
rds_client = boto3.client("rds")
return cls(rds_client)
def get_parameter_group(self, parameter_group_name):
"""
Gets a DB cluster parameter group.
:param parameter_group_name: The name of the parameter group to retrieve.
:return: The requested parameter group.
"""
try:
response = self.rds_client.describe_db_cluster_parameter_groups(
DBClusterParameterGroupName=parameter_group_name
)
parameter_group = response["DBClusterParameterGroups"][0]
except ClientError as err:
if err.response["Error"]["Code"] == "DBParameterGroupNotFound":
logger.info("Parameter group %s does not exist.", parameter_group_name)
else:
logger.error(
"Couldn't get parameter group %s. Here's why: %s: %s",
parameter_group_name,
err.response["Error"]["Code"],
err.response["Error"]["Message"],
)
raise
else:
return parameter_group
```
+ Para obtener más información sobre la API, consulta la [descripción DBCluster ParameterGroups](https://docs.aws.amazon.com/goto/boto3/rds-2014-10-31/DescribeDBClusterParameterGroups) en la referencia de la API del *AWS SDK for Python (Boto3*).
### `DescribeDBClusterParameters`
En el siguiente ejemplo de código, se muestra cómo utilizar `DescribeDBClusterParameters`.
**SDK para Python (Boto3)**
Hay más información al respecto. GitHub Busque el ejemplo completo y aprenda a configurar y ejecutar en el [Repositorio de ejemplos de código de AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/aurora#code-examples).
```
class AuroraWrapper:
"""Encapsulates Aurora DB cluster actions."""
def __init__(self, rds_client):
"""
:param rds_client: A Boto3 Amazon Relational Database Service (Amazon RDS) client.
"""
self.rds_client = rds_client
@classmethod
def from_client(cls):
"""
Instantiates this class from a Boto3 client.
"""
rds_client = boto3.client("rds")
return cls(rds_client)
def get_parameters(self, parameter_group_name, name_prefix="", source=None):
"""
Gets the parameters that are contained in a DB cluster parameter group.
:param parameter_group_name: The name of the parameter group to query.
:param name_prefix: When specified, the retrieved list of parameters is filtered
to contain only parameters that start with this prefix.
:param source: When specified, only parameters from this source are retrieved.
For example, a source of 'user' retrieves only parameters that
were set by a user.
:return: The list of requested parameters.
"""
try:
kwargs = {"DBClusterParameterGroupName": parameter_group_name}
if source is not None:
kwargs["Source"] = source
parameters = []
paginator = self.rds_client.get_paginator("describe_db_cluster_parameters")
for page in paginator.paginate(**kwargs):
parameters += [
p
for p in page["Parameters"]
if p["ParameterName"].startswith(name_prefix)
]
except ClientError as err:
logger.error(
"Couldn't get parameters for %s. Here's why: %s: %s",
parameter_group_name,
err.response["Error"]["Code"],
err.response["Error"]["Message"],
)
raise
else:
return parameters
```
+ Para obtener más información sobre la API, consulta [Describe DBCluster los parámetros](https://docs.aws.amazon.com/goto/boto3/rds-2014-10-31/DescribeDBClusterParameters) en la referencia de la API del *AWS SDK for Python (Boto3*).
### `DescribeDBClusterSnapshots`
En el siguiente ejemplo de código, se muestra cómo utilizar `DescribeDBClusterSnapshots`.
**SDK para Python (Boto3)**
Hay más información al respecto. GitHub Busque el ejemplo completo y aprenda a configurar y ejecutar en el [Repositorio de ejemplos de código de AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/aurora#code-examples).
```
class AuroraWrapper:
"""Encapsulates Aurora DB cluster actions."""
def __init__(self, rds_client):
"""
:param rds_client: A Boto3 Amazon Relational Database Service (Amazon RDS) client.
"""
self.rds_client = rds_client
@classmethod
def from_client(cls):
"""
Instantiates this class from a Boto3 client.
"""
rds_client = boto3.client("rds")
return cls(rds_client)
def get_cluster_snapshot(self, snapshot_id):
"""
Gets a DB cluster snapshot.
:param snapshot_id: The ID of the snapshot to retrieve.
:return: The retrieved snapshot.
"""
try:
response = self.rds_client.describe_db_cluster_snapshots(
DBClusterSnapshotIdentifier=snapshot_id
)
snapshot = response["DBClusterSnapshots"][0]
except ClientError as err:
logger.error(
"Couldn't get DB cluster snapshot %s. Here's why: %s: %s",
snapshot_id,
err.response["Error"]["Code"],
err.response["Error"]["Message"],
)
raise
else:
return snapshot
```
+ Para obtener más información sobre la API, consulta [Describe DBCluster las instantáneas](https://docs.aws.amazon.com/goto/boto3/rds-2014-10-31/DescribeDBClusterSnapshots) en la referencia de la API *AWS del SDK for Python (Boto3).*
### `DescribeDBClusters`
En el siguiente ejemplo de código, se muestra cómo utilizar `DescribeDBClusters`.
**SDK para Python (Boto3)**
Hay más información al respecto. GitHub Busque el ejemplo completo y aprenda a configurar y ejecutar en el [Repositorio de ejemplos de código de AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/aurora#code-examples).
```
class AuroraWrapper:
"""Encapsulates Aurora DB cluster actions."""
def __init__(self, rds_client):
"""
:param rds_client: A Boto3 Amazon Relational Database Service (Amazon RDS) client.
"""
self.rds_client = rds_client
@classmethod
def from_client(cls):
"""
Instantiates this class from a Boto3 client.
"""
rds_client = boto3.client("rds")
return cls(rds_client)
def get_db_cluster(self, cluster_name):
"""
Gets data about an Aurora DB cluster.
:param cluster_name: The name of the DB cluster to retrieve.
:return: The retrieved DB cluster.
"""
try:
response = self.rds_client.describe_db_clusters(
DBClusterIdentifier=cluster_name
)
cluster = response["DBClusters"][0]
except ClientError as err:
if err.response["Error"]["Code"] == "DBClusterNotFoundFault":
logger.info("Cluster %s does not exist.", cluster_name)
else:
logger.error(
"Couldn't verify the existence of DB cluster %s. Here's why: %s: %s",
cluster_name,
err.response["Error"]["Code"],
err.response["Error"]["Message"],
)
raise
else:
return cluster
```
+ Para obtener más información sobre la API, consulta la [sección Describe DBClusters](https://docs.aws.amazon.com/goto/boto3/rds-2014-10-31/DescribeDBClusters) en la referencia de la API de *AWS SDK for Python (Boto3*).
### `DescribeDBEngineVersions`
En el siguiente ejemplo de código, se muestra cómo utilizar `DescribeDBEngineVersions`.
**SDK para Python (Boto3)**
Hay más información al respecto. GitHub Busque el ejemplo completo y aprenda a configurar y ejecutar en el [Repositorio de ejemplos de código de AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/aurora#code-examples).
```
class AuroraWrapper:
"""Encapsulates Aurora DB cluster actions."""
def __init__(self, rds_client):
"""
:param rds_client: A Boto3 Amazon Relational Database Service (Amazon RDS) client.
"""
self.rds_client = rds_client
@classmethod
def from_client(cls):
"""
Instantiates this class from a Boto3 client.
"""
rds_client = boto3.client("rds")
return cls(rds_client)
def get_engine_versions(self, engine, parameter_group_family=None):
"""
Gets database engine versions that are available for the specified engine
and parameter group family.
:param engine: The database engine to look up.
:param parameter_group_family: When specified, restricts the returned list of
engine versions to those that are compatible with
this parameter group family.
:return: The list of database engine versions.
"""
try:
kwargs = {"Engine": engine}
if parameter_group_family is not None:
kwargs["DBParameterGroupFamily"] = parameter_group_family
response = self.rds_client.describe_db_engine_versions(**kwargs)
versions = response["DBEngineVersions"]
except ClientError as err:
logger.error(
"Couldn't get engine versions for %s. Here's why: %s: %s",
engine,
err.response["Error"]["Code"],
err.response["Error"]["Message"],
)
raise
else:
return versions
```
+ Para obtener más información sobre la API, consulta [Describir DBEngine las versiones](https://docs.aws.amazon.com/goto/boto3/rds-2014-10-31/DescribeDBEngineVersions) en la referencia de la API de *AWS SDK for Python (Boto3*).
### `DescribeDBInstances`
En el siguiente ejemplo de código, se muestra cómo utilizar `DescribeDBInstances`.
**SDK para Python (Boto3)**
Hay más información al respecto. GitHub Busque el ejemplo completo y aprenda a configurar y ejecutar en el [Repositorio de ejemplos de código de AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/aurora#code-examples).
```
class AuroraWrapper:
"""Encapsulates Aurora DB cluster actions."""
def __init__(self, rds_client):
"""
:param rds_client: A Boto3 Amazon Relational Database Service (Amazon RDS) client.
"""
self.rds_client = rds_client
@classmethod
def from_client(cls):
"""
Instantiates this class from a Boto3 client.
"""
rds_client = boto3.client("rds")
return cls(rds_client)
def get_db_instance(self, instance_id):
"""
Gets data about a DB instance.
:param instance_id: The ID of the DB instance to retrieve.
:return: The retrieved DB instance.
"""
try:
response = self.rds_client.describe_db_instances(
DBInstanceIdentifier=instance_id
)
db_inst = response["DBInstances"][0]
except ClientError as err:
if err.response["Error"]["Code"] == "DBInstanceNotFound":
logger.info("Instance %s does not exist.", instance_id)
else:
logger.error(
"Couldn't get DB instance %s. Here's why: %s: %s",
instance_id,
err.response["Error"]["Code"],
err.response["Error"]["Message"],
)
raise
else:
return db_inst
```
+ Para obtener más información sobre la API, consulta la [sección Describe DBInstances](https://docs.aws.amazon.com/goto/boto3/rds-2014-10-31/DescribeDBInstances) en la referencia de la API de *AWS SDK for Python (Boto3*).
### `DescribeOrderableDBInstanceOptions`
En el siguiente ejemplo de código, se muestra cómo utilizar `DescribeOrderableDBInstanceOptions`.
**SDK para Python (Boto3)**
Hay más información al respecto. GitHub Busque el ejemplo completo y aprenda a configurar y ejecutar en el [Repositorio de ejemplos de código de AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/aurora#code-examples).
```
class AuroraWrapper:
"""Encapsulates Aurora DB cluster actions."""
def __init__(self, rds_client):
"""
:param rds_client: A Boto3 Amazon Relational Database Service (Amazon RDS) client.
"""
self.rds_client = rds_client
@classmethod
def from_client(cls):
"""
Instantiates this class from a Boto3 client.
"""
rds_client = boto3.client("rds")
return cls(rds_client)
def get_orderable_instances(self, db_engine, db_engine_version):
"""
Gets DB instance options that can be used to create DB instances that are
compatible with a set of specifications.
:param db_engine: The database engine that must be supported by the DB instance.
:param db_engine_version: The engine version that must be supported by the DB instance.
:return: The list of DB instance options that can be used to create a compatible DB instance.
"""
try:
inst_opts = []
paginator = self.rds_client.get_paginator(
"describe_orderable_db_instance_options"
)
for page in paginator.paginate(
Engine=db_engine, EngineVersion=db_engine_version
):
inst_opts += page["OrderableDBInstanceOptions"]
except ClientError as err:
logger.error(
"Couldn't get orderable DB instances. Here's why: %s: %s",
err.response["Error"]["Code"],
err.response["Error"]["Message"],
)
raise
else:
return inst_opts
```
+ Para obtener más información sobre la API, consulta [DescribeOrderableDBInstanceOpciones](https://docs.aws.amazon.com/goto/boto3/rds-2014-10-31/DescribeOrderableDBInstanceOptions) en la referencia de la API del *AWS SDK for Python (Boto3*).
### `ModifyDBClusterParameterGroup`
En el siguiente ejemplo de código, se muestra cómo utilizar `ModifyDBClusterParameterGroup`.
**SDK para Python (Boto3)**
Hay más información al respecto. GitHub Busque el ejemplo completo y aprenda a configurar y ejecutar en el [Repositorio de ejemplos de código de AWS](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/example_code/aurora#code-examples).
```
class AuroraWrapper:
"""Encapsulates Aurora DB cluster actions."""
def __init__(self, rds_client):
"""
:param rds_client: A Boto3 Amazon Relational Database Service (Amazon RDS) client.
"""
self.rds_client = rds_client
@classmethod
def from_client(cls):
"""
Instantiates this class from a Boto3 client.
"""
rds_client = boto3.client("rds")
return cls(rds_client)
def update_parameters(self, parameter_group_name, update_parameters):
"""
Updates parameters in a custom DB cluster parameter group.
:param parameter_group_name: The name of the parameter group to update.
:param update_parameters: The parameters to update in the group.
:return: Data about the modified parameter group.
"""
try:
response = self.rds_client.modify_db_cluster_parameter_group(
DBClusterParameterGroupName=parameter_group_name,
Parameters=update_parameters,
)
except ClientError as err:
logger.error(
"Couldn't update parameters in %s. Here's why: %s: %s",
parameter_group_name,
err.response["Error"]["Code"],
err.response["Error"]["Message"],
)
raise
else:
return response
```
+ Para obtener más información sobre la API, consulta [Modificar DBCluster ParameterGroup](https://docs.aws.amazon.com/goto/boto3/rds-2014-10-31/ModifyDBClusterParameterGroup) en la referencia de la API del *AWS SDK for Python (Boto3*).
## Escenarios
### Creación de una API de REST de biblioteca de préstamos
En el siguiente ejemplo de código se muestra cómo crear una biblioteca de préstamos en la que los usuarios puedan pedir prestados y devolver libros mediante una API de REST respaldada por una base de datos de Amazon Aurora.
**SDK para Python (Boto3)**
Muestra cómo utilizarla AWS SDK para Python (Boto3) con la API de Amazon Relational Database Service (Amazon RDS) y AWS Chalice para crear una API REST respaldada por una base de datos de Amazon Aurora. El servicio web es totalmente sin servidor y representa una biblioteca de préstamos sencilla en la que los usuarios pueden pedir prestados libros y devolverlos. Aprenda cómo:
+ Crear y administrar un clúster de base de datos Aurora sin servidor.
+ Se utiliza para administrar AWS Secrets Manager las credenciales de la base de datos.
+ Implementar una capa de almacenamiento de datos que utilice Amazon RDS para mover datos dentro y fuera de la base de datos.
+ Use AWS Chalice para implementar una API REST sin servidor en Amazon API Gateway y. AWS Lambda
+ Utilice el paquete Requests para enviar solicitudes al servicio web.
Para obtener el código fuente completo y las instrucciones sobre cómo configurarla y ejecutarla, consulte el ejemplo completo en. [GitHub](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/cross_service/aurora_rest_lending_library)
**Servicios utilizados en este ejemplo**
+ API Gateway
+ Aurora
+ Lambda
+ Secrets Manager
### Crear un rastreador de elementos de trabajo de Aurora Serverless
El siguiente ejemplo de código muestra cómo crear una aplicación web que realice un seguimiento de los elementos de trabajo de una base de datos de Amazon Aurora sin servidor y use Amazon Simple Email Service (Amazon SES) para enviar informes.
**SDK para Python (Boto3)**
Muestra cómo usarlo AWS SDK para Python (Boto3) para crear un servicio REST que rastrea los elementos de trabajo en una base de datos Amazon Aurora Serverless y envía informes por correo electrónico mediante Amazon Simple Email Service (Amazon SES). En este ejemplo se utiliza el marco web de Flask para gestionar el enrutamiento HTTP y se integra con una página web de React para presentar una aplicación web completamente funcional.
+ Cree un servicio REST de Flask que se integre con. Servicios de AWS
+ Lea, escriba y actualice los elementos de trabajo almacenados en una base de datos de Aurora Serverless.
+ Cree un AWS Secrets Manager secreto que contenga las credenciales de la base de datos y utilícelo para autenticar las llamadas a la base de datos.
+ Utilice Amazon SES para enviar informes de elementos de trabajo por correo electrónico.
Para obtener el código fuente completo y las instrucciones sobre cómo configurarlo y ejecutarlo, consulte el ejemplo completo en [GitHub](https://github.com/awsdocs/aws-doc-sdk-examples/tree/main/python/cross_service/aurora_item_tracker).
**Servicios utilizados en este ejemplo**
+ Aurora
+ Amazon RDS
+ Servicio de datos de Amazon RDS
+ Amazon SES