CloudSchedulerAsyncClient(*, credentials: Optional[google.auth.credentials.Credentials] = None, transport: Union[str, google.cloud.scheduler_v1.services.cloud_scheduler.transports.base.CloudSchedulerTransport] = 'grpc_asyncio', client_options: Optional[google.api_core.client_options.ClientOptions] = None, client_info: google.api_core.gapic_v1.client_info.ClientInfo = <google.api_core.gapic_v1.client_info.ClientInfo object>)
The Cloud Scheduler API allows external entities to reliably schedule asynchronous jobs.
Inheritance
builtins.object > CloudSchedulerAsyncClientProperties
transport
Returns the transport used by the client instance.
Type | Description |
CloudSchedulerTransport | The transport used by the client instance. |
Methods
CloudSchedulerAsyncClient
CloudSchedulerAsyncClient(*, credentials: Optional[google.auth.credentials.Credentials] = None, transport: Union[str, google.cloud.scheduler_v1.services.cloud_scheduler.transports.base.CloudSchedulerTransport] = 'grpc_asyncio', client_options: Optional[google.api_core.client_options.ClientOptions] = None, client_info: google.api_core.gapic_v1.client_info.ClientInfo = <google.api_core.gapic_v1.client_info.ClientInfo object>)
Instantiates the cloud scheduler client.
Name | Description |
credentials |
Optional[google.auth.credentials.Credentials]
The authorization credentials to attach to requests. These credentials identify the application to the service; if none are specified, the client will attempt to ascertain the credentials from the environment. |
transport |
Union[str, `.CloudSchedulerTransport`]
The transport to use. If set to None, a transport is chosen automatically. |
client_options |
ClientOptions
Custom options for the client. It won't take effect if a |
Type | Description |
google.auth.exceptions.MutualTlsChannelError | If mutual TLS transport creation failed for any reason. |
common_billing_account_path
common_billing_account_path(billing_account: str)
Returns a fully-qualified billing_account string.
common_folder_path
common_folder_path(folder: str)
Returns a fully-qualified folder string.
common_location_path
common_location_path(project: str, location: str)
Returns a fully-qualified location string.
common_organization_path
common_organization_path(organization: str)
Returns a fully-qualified organization string.
common_project_path
common_project_path(project: str)
Returns a fully-qualified project string.
create_job
create_job(request: Optional[Union[google.cloud.scheduler_v1.types.cloudscheduler.CreateJobRequest, dict]] = None, *, parent: Optional[str] = None, job: Optional[google.cloud.scheduler_v1.types.job.Job] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Creates a job.
from google.cloud import scheduler_v1
async def sample_create_job():
# Create a client
client = scheduler_v1.CloudSchedulerAsyncClient()
# Initialize request argument(s)
request = scheduler_v1.CreateJobRequest(
parent="parent_value",
)
# Make the request
response = await client.create_job(request=request)
# Handle the response
print(response)
Name | Description |
request |
Union[google.cloud.scheduler_v1.types.CreateJobRequest, dict]
The request object. Request message for CreateJob. |
parent |
`str`
Required. The location name. For example: |
job |
Job
Required. The job to add. The user can optionally specify a name for the job in name. name cannot be the same as an existing job. If a name is not specified then the system will generate a random unique name that will be returned (name) in the response. This corresponds to the |
retry |
google.api_core.retry.Retry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Type | Description |
google.cloud.scheduler_v1.types.Job | Configuration for a job. The maximum allowed size for a job is 100KB. |
delete_job
delete_job(request: Optional[Union[google.cloud.scheduler_v1.types.cloudscheduler.DeleteJobRequest, dict]] = None, *, name: Optional[str] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Deletes a job.
from google.cloud import scheduler_v1
async def sample_delete_job():
# Create a client
client = scheduler_v1.CloudSchedulerAsyncClient()
# Initialize request argument(s)
request = scheduler_v1.DeleteJobRequest(
name="name_value",
)
# Make the request
await client.delete_job(request=request)
Name | Description |
request |
Union[google.cloud.scheduler_v1.types.DeleteJobRequest, dict]
The request object. Request message for deleting a job using DeleteJob. |
name |
`str`
Required. The job name. For example: |
retry |
google.api_core.retry.Retry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
from_service_account_file
from_service_account_file(filename: str, *args, **kwargs)
Creates an instance of this client using the provided credentials file.
Name | Description |
filename |
str
The path to the service account private key json file. |
Type | Description |
CloudSchedulerAsyncClient | The constructed client. |
from_service_account_info
from_service_account_info(info: dict, *args, **kwargs)
Creates an instance of this client using the provided credentials info.
Name | Description |
info |
dict
The service account private key info. |
Type | Description |
CloudSchedulerAsyncClient | The constructed client. |
from_service_account_json
from_service_account_json(filename: str, *args, **kwargs)
Creates an instance of this client using the provided credentials file.
Name | Description |
filename |
str
The path to the service account private key json file. |
Type | Description |
CloudSchedulerAsyncClient | The constructed client. |
get_job
get_job(request: Optional[Union[google.cloud.scheduler_v1.types.cloudscheduler.GetJobRequest, dict]] = None, *, name: Optional[str] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Gets a job.
from google.cloud import scheduler_v1
async def sample_get_job():
# Create a client
client = scheduler_v1.CloudSchedulerAsyncClient()
# Initialize request argument(s)
request = scheduler_v1.GetJobRequest(
name="name_value",
)
# Make the request
response = await client.get_job(request=request)
# Handle the response
print(response)
Name | Description |
request |
Union[google.cloud.scheduler_v1.types.GetJobRequest, dict]
The request object. Request message for GetJob. |
name |
`str`
Required. The job name. For example: |
retry |
google.api_core.retry.Retry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Type | Description |
google.cloud.scheduler_v1.types.Job | Configuration for a job. The maximum allowed size for a job is 100KB. |
get_mtls_endpoint_and_cert_source
get_mtls_endpoint_and_cert_source(
client_options: Optional[google.api_core.client_options.ClientOptions] = None,
)
Return the API endpoint and client cert source for mutual TLS.
The client cert source is determined in the following order:
(1) if GOOGLE_API_USE_CLIENT_CERTIFICATE
environment variable is not "true", the
client cert source is None.
(2) if client_options.client_cert_source
is provided, use the provided one; if the
default client cert source exists, use the default one; otherwise the client cert
source is None.
The API endpoint is determined in the following order:
(1) if client_options.api_endpoint
if provided, use the provided one.
(2) if GOOGLE_API_USE_CLIENT_CERTIFICATE
environment variable is "always", use the
default mTLS endpoint; if the environment variabel is "never", use the default API
endpoint; otherwise if client cert source exists, use the default mTLS endpoint, otherwise
use the default API endpoint.
More details can be found at https://google.aip.dev/auth/4114.
Name | Description |
client_options |
google.api_core.client_options.ClientOptions
Custom options for the client. Only the |
Type | Description |
google.auth.exceptions.MutualTLSChannelError | If any errors happen. |
Type | Description |
Tuple[str, Callable[[], Tuple[bytes, bytes]]] | returns the API endpoint and the client cert source to use. |
get_transport_class
get_transport_class()
Returns an appropriate transport class.
job_path
job_path(project: str, location: str, job: str)
Returns a fully-qualified job string.
list_jobs
list_jobs(request: Optional[Union[google.cloud.scheduler_v1.types.cloudscheduler.ListJobsRequest, dict]] = None, *, parent: Optional[str] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Lists jobs.
from google.cloud import scheduler_v1
async def sample_list_jobs():
# Create a client
client = scheduler_v1.CloudSchedulerAsyncClient()
# Initialize request argument(s)
request = scheduler_v1.ListJobsRequest(
parent="parent_value",
)
# Make the request
page_result = client.list_jobs(request=request)
# Handle the response
async for response in page_result:
print(response)
Name | Description |
request |
Union[google.cloud.scheduler_v1.types.ListJobsRequest, dict]
The request object. Request message for listing jobs using ListJobs. |
parent |
`str`
Required. The location name. For example: |
retry |
google.api_core.retry.Retry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Type | Description |
google.cloud.scheduler_v1.services.cloud_scheduler.pagers.ListJobsAsyncPager | Response message for listing jobs using ListJobs. Iterating over this object will yield results and resolve additional pages automatically. |
parse_common_billing_account_path
parse_common_billing_account_path(path: str)
Parse a billing_account path into its component segments.
parse_common_folder_path
parse_common_folder_path(path: str)
Parse a folder path into its component segments.
parse_common_location_path
parse_common_location_path(path: str)
Parse a location path into its component segments.
parse_common_organization_path
parse_common_organization_path(path: str)
Parse a organization path into its component segments.
parse_common_project_path
parse_common_project_path(path: str)
Parse a project path into its component segments.
parse_job_path
parse_job_path(path: str)
Parses a job path into its component segments.
parse_topic_path
parse_topic_path(path: str)
Parses a topic path into its component segments.
pause_job
pause_job(request: Optional[Union[google.cloud.scheduler_v1.types.cloudscheduler.PauseJobRequest, dict]] = None, *, name: Optional[str] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Pauses a job.
If a job is paused then the system will stop executing the job until it is re-enabled via xref_ResumeJob. The state of the job is stored in xref_state; if paused it will be set to xref_Job.State.PAUSED. A job must be in xref_Job.State.ENABLED to be paused.
from google.cloud import scheduler_v1
async def sample_pause_job():
# Create a client
client = scheduler_v1.CloudSchedulerAsyncClient()
# Initialize request argument(s)
request = scheduler_v1.PauseJobRequest(
name="name_value",
)
# Make the request
response = await client.pause_job(request=request)
# Handle the response
print(response)
Name | Description |
request |
Union[google.cloud.scheduler_v1.types.PauseJobRequest, dict]
The request object. Request message for PauseJob. |
name |
`str`
Required. The job name. For example: |
retry |
google.api_core.retry.Retry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Type | Description |
google.cloud.scheduler_v1.types.Job | Configuration for a job. The maximum allowed size for a job is 100KB. |
resume_job
resume_job(request: Optional[Union[google.cloud.scheduler_v1.types.cloudscheduler.ResumeJobRequest, dict]] = None, *, name: Optional[str] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Resume a job.
This method reenables a job after it has been xref_Job.State.PAUSED. The state of a job is stored in xref_Job.state; after calling this method it will be set to xref_Job.State.ENABLED. A job must be in xref_Job.State.PAUSED to be resumed.
from google.cloud import scheduler_v1
async def sample_resume_job():
# Create a client
client = scheduler_v1.CloudSchedulerAsyncClient()
# Initialize request argument(s)
request = scheduler_v1.ResumeJobRequest(
name="name_value",
)
# Make the request
response = await client.resume_job(request=request)
# Handle the response
print(response)
Name | Description |
request |
Union[google.cloud.scheduler_v1.types.ResumeJobRequest, dict]
The request object. Request message for ResumeJob. |
name |
`str`
Required. The job name. For example: |
retry |
google.api_core.retry.Retry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Type | Description |
google.cloud.scheduler_v1.types.Job | Configuration for a job. The maximum allowed size for a job is 100KB. |
run_job
run_job(request: Optional[Union[google.cloud.scheduler_v1.types.cloudscheduler.RunJobRequest, dict]] = None, *, name: Optional[str] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Forces a job to run now. When this method is called, Cloud Scheduler will dispatch the job, even if the job is already running.
from google.cloud import scheduler_v1
async def sample_run_job():
# Create a client
client = scheduler_v1.CloudSchedulerAsyncClient()
# Initialize request argument(s)
request = scheduler_v1.RunJobRequest(
name="name_value",
)
# Make the request
response = await client.run_job(request=request)
# Handle the response
print(response)
Name | Description |
request |
Union[google.cloud.scheduler_v1.types.RunJobRequest, dict]
The request object. Request message for forcing a job to run now using RunJob. |
name |
`str`
Required. The job name. For example: |
retry |
google.api_core.retry.Retry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Type | Description |
google.cloud.scheduler_v1.types.Job | Configuration for a job. The maximum allowed size for a job is 100KB. |
topic_path
topic_path(project: str, topic: str)
Returns a fully-qualified topic string.
update_job
update_job(request: Optional[Union[google.cloud.scheduler_v1.types.cloudscheduler.UpdateJobRequest, dict]] = None, *, job: Optional[google.cloud.scheduler_v1.types.job.Job] = None, update_mask: Optional[google.protobuf.field_mask_pb2.FieldMask] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Updates a job.
If successful, the updated xref_Job
is returned. If the job does not exist, NOT_FOUND
is
returned.
If UpdateJob does not successfully return, it is possible for the job to be in an xref_Job.State.UPDATE_FAILED state. A job in this state may not be executed. If this happens, retry the UpdateJob request until a successful response is received.
from google.cloud import scheduler_v1
async def sample_update_job():
# Create a client
client = scheduler_v1.CloudSchedulerAsyncClient()
# Initialize request argument(s)
request = scheduler_v1.UpdateJobRequest(
)
# Make the request
response = await client.update_job(request=request)
# Handle the response
print(response)
Name | Description |
request |
Union[google.cloud.scheduler_v1.types.UpdateJobRequest, dict]
The request object. Request message for UpdateJob. |
job |
Job
Required. The new job properties. name must be specified. Output only fields cannot be modified using UpdateJob. Any value specified for an output only field will be ignored. This corresponds to the |
update_mask |
`google.protobuf.field_mask_pb2.FieldMask`
A mask used to specify which fields of the job are being updated. This corresponds to the |
retry |
google.api_core.retry.Retry
Designation of what errors, if any, should be retried. |
timeout |
float
The timeout for this request. |
metadata |
Sequence[Tuple[str, str]]
Strings which should be sent along with the request as metadata. |
Type | Description |
google.cloud.scheduler_v1.types.Job | Configuration for a job. The maximum allowed size for a job is 100KB. |