Comprehend / Client / start_topics_detection_job
start_topics_detection_job#
- Comprehend.Client.start_topics_detection_job(**kwargs)#
Starts an asynchronous topic detection job. Use the
DescribeTopicDetectionJob
operation to track the status of a job.See also: AWS API Documentation
Request Syntax
response = client.start_topics_detection_job( InputDataConfig={ 'S3Uri': 'string', 'InputFormat': 'ONE_DOC_PER_FILE'|'ONE_DOC_PER_LINE', 'DocumentReaderConfig': { 'DocumentReadAction': 'TEXTRACT_DETECT_DOCUMENT_TEXT'|'TEXTRACT_ANALYZE_DOCUMENT', 'DocumentReadMode': 'SERVICE_DEFAULT'|'FORCE_DOCUMENT_READ_ACTION', 'FeatureTypes': [ 'TABLES'|'FORMS', ] } }, OutputDataConfig={ 'S3Uri': 'string', 'KmsKeyId': 'string' }, DataAccessRoleArn='string', JobName='string', NumberOfTopics=123, ClientRequestToken='string', VolumeKmsKeyId='string', VpcConfig={ 'SecurityGroupIds': [ 'string', ], 'Subnets': [ 'string', ] }, Tags=[ { 'Key': 'string', 'Value': 'string' }, ] )
- Parameters:
InputDataConfig (dict) –
[REQUIRED]
Specifies the format and location of the input data for the job.
S3Uri (string) – [REQUIRED]
The Amazon S3 URI for the input data. The URI must be in same region as the API endpoint that you are calling. The URI can point to a single input file or it can provide the prefix for a collection of data files.
For example, if you use the URI
S3://bucketName/prefix
, if the prefix is a single file, Amazon Comprehend uses that file as input. If more than one file begins with the prefix, Amazon Comprehend uses all of them as input.InputFormat (string) –
Specifies how the text in an input file should be processed:
ONE_DOC_PER_FILE
- Each file is considered a separate document. Use this option when you are processing large documents, such as newspaper articles or scientific papers.ONE_DOC_PER_LINE
- Each line in a file is considered a separate document. Use this option when you are processing many short documents, such as text messages.
DocumentReaderConfig (dict) –
Provides configuration parameters to override the default actions for extracting text from PDF documents and image files.
DocumentReadAction (string) – [REQUIRED]
This field defines the Amazon Textract API operation that Amazon Comprehend uses to extract text from PDF files and image files. Enter one of the following values:
TEXTRACT_DETECT_DOCUMENT_TEXT
- The Amazon Comprehend service uses theDetectDocumentText
API operation.TEXTRACT_ANALYZE_DOCUMENT
- The Amazon Comprehend service uses theAnalyzeDocument
API operation.
DocumentReadMode (string) –
Determines the text extraction actions for PDF files. Enter one of the following values:
SERVICE_DEFAULT
- use the Amazon Comprehend service defaults for PDF files.FORCE_DOCUMENT_READ_ACTION
- Amazon Comprehend uses the Textract API specified by DocumentReadAction for all PDF files, including digital PDF files.
FeatureTypes (list) –
Specifies the type of Amazon Textract features to apply. If you chose
TEXTRACT_ANALYZE_DOCUMENT
as the read action, you must specify one or both of the following values:TABLES
- Returns information about any tables that are detected in the input document.FORMS
- Returns information and the data from any forms that are detected in the input document.
(string) –
Specifies the type of Amazon Textract features to apply. If you chose
TEXTRACT_ANALYZE_DOCUMENT
as the read action, you must specify one or both of the following values:TABLES
- Returns additional information about any tables that are detected in the input document.FORMS
- Returns additional information about any forms that are detected in the input document.
OutputDataConfig (dict) –
[REQUIRED]
Specifies where to send the output files. The output is a compressed archive with two files,
topic-terms.csv
that lists the terms associated with each topic, anddoc-topics.csv
that lists the documents associated with each topicS3Uri (string) – [REQUIRED]
When you use the
OutputDataConfig
object with asynchronous operations, you specify the Amazon S3 location where you want to write the output data. The URI must be in the same region as the API endpoint that you are calling. The location is used as the prefix for the actual location of the output file.When the topic detection job is finished, the service creates an output file in a directory specific to the job. The
S3Uri
field contains the location of the output file, calledoutput.tar.gz
. It is a compressed archive that contains the ouput of the operation.For a PII entity detection job, the output file is plain text, not a compressed archive. The output file name is the same as the input file, with
.out
appended at the end.KmsKeyId (string) –
ID for the AWS Key Management Service (KMS) key that Amazon Comprehend uses to encrypt the output results from an analysis job. The KmsKeyId can be one of the following formats:
KMS Key ID:
"1234abcd-12ab-34cd-56ef-1234567890ab"
Amazon Resource Name (ARN) of a KMS Key:
"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"
KMS Key Alias:
"alias/ExampleAlias"
ARN of a KMS Key Alias:
"arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias"
DataAccessRoleArn (string) –
[REQUIRED]
The Amazon Resource Name (ARN) of the AWS Identity and Access Management (IAM) role that grants Amazon Comprehend read access to your input data. For more information, see https://docs.aws.amazon.com/comprehend/latest/dg/access-control-managing-permissions.html#auth-role-permissions.
JobName (string) – The identifier of the job.
NumberOfTopics (integer) – The number of topics to detect.
ClientRequestToken (string) –
A unique identifier for the request. If you do not set the client request token, Amazon Comprehend generates one.
This field is autopopulated if not provided.
VolumeKmsKeyId (string) –
ID for the AWS Key Management Service (KMS) key that Amazon Comprehend uses to encrypt data on the storage volume attached to the ML compute instance(s) that process the analysis job. The VolumeKmsKeyId can be either of the following formats:
KMS Key ID:
"1234abcd-12ab-34cd-56ef-1234567890ab"
Amazon Resource Name (ARN) of a KMS Key:
"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"
VpcConfig (dict) –
Configuration parameters for an optional private Virtual Private Cloud (VPC) containing the resources you are using for your topic detection job. For more information, see Amazon VPC.
SecurityGroupIds (list) – [REQUIRED]
The ID number for a security group on an instance of your private VPC. Security groups on your VPC function serve as a virtual firewall to control inbound and outbound traffic and provides security for the resources that you’ll be accessing on the VPC. This ID number is preceded by “sg-”, for instance: “sg-03b388029b0a285ea”. For more information, see Security Groups for your VPC.
(string) –
Subnets (list) – [REQUIRED]
The ID for each subnet being used in your private VPC. This subnet is a subset of the a range of IPv4 addresses used by the VPC and is specific to a given availability zone in the VPC’s region. This ID number is preceded by “subnet-”, for instance: “subnet-04ccf456919e69055”. For more information, see VPCs and Subnets.
(string) –
Tags (list) –
Tags to associate with the topics detection job. A tag is a key-value pair that adds metadata to a resource used by Amazon Comprehend. For example, a tag with “Sales” as the key might be added to a resource to indicate its use by the sales department.
(dict) –
A key-value pair that adds as a metadata to a resource used by Amazon Comprehend. For example, a tag with the key-value pair ‘Department’:’Sales’ might be added to a resource to indicate its use by a particular department.
Key (string) – [REQUIRED]
The initial part of a key-value pair that forms a tag associated with a given resource. For instance, if you want to show which resources are used by which departments, you might use “Department” as the key portion of the pair, with multiple possible values such as “sales,” “legal,” and “administration.”
Value (string) –
The second part of a key-value pair that forms a tag associated with a given resource. For instance, if you want to show which resources are used by which departments, you might use “Department” as the initial (key) portion of the pair, with a value of “sales” to indicate the sales department.
- Return type:
dict
- Returns:
Response Syntax
{ 'JobId': 'string', 'JobArn': 'string', 'JobStatus': 'SUBMITTED'|'IN_PROGRESS'|'COMPLETED'|'FAILED'|'STOP_REQUESTED'|'STOPPED' }
Response Structure
(dict) –
JobId (string) –
The identifier generated for the job. To get the status of the job, use this identifier with the
DescribeTopicDetectionJob
operation.JobArn (string) –
The Amazon Resource Name (ARN) of the topics detection job. It is a unique, fully qualified identifier for the job. It includes the AWS account, Region, and the job ID. The format of the ARN is as follows:
arn:<partition>:comprehend:<region>:<account-id>:topics-detection-job/<job-id>
The following is an example job ARN:
arn:aws:comprehend:us-west-2:111122223333:document-classification-job/1234abcd12ab34cd56ef1234567890ab
JobStatus (string) –
The status of the job:
SUBMITTED - The job has been received and is queued for processing.
IN_PROGRESS - Amazon Comprehend is processing the job.
COMPLETED - The job was successfully completed and the output is available.
FAILED - The job did not complete. To get details, use the
DescribeTopicDetectionJob
operation.
Exceptions
Comprehend.Client.exceptions.InvalidRequestException
Comprehend.Client.exceptions.TooManyRequestsException
Comprehend.Client.exceptions.KmsKeyValidationException
Comprehend.Client.exceptions.TooManyTagsException
Comprehend.Client.exceptions.InternalServerException