CODEWITHSUNDEEP
pythonamazon-web-servicesboto3
Kyle Krull
Kyle Krull

Reputation: 1708

Where is the API documentation for boto3?

The user guide for boto3 refers high-level Resources and low-level clients. They are accessed by passing the name of the service to boto3.resource and boto3.client, respectively.

This might seem kind of pedantic - I could probably make reasonable guesses as to the names of each resource or client - but where do I find a list of available resources? Unless I missed something, it doesn't appear to be in the User Guide. And I'm not finding a more detailed API reference anywhere.

Once I do have a resource (like EC2) - where do I find documentation on what I can do with it? There are some examples here in the user guide, but they appear to be a subset.

This leaves me feeling like my only option is to inspect objects on the REPL for plausible looking method names.

Am I missing something here? How do people actually use this library?

Upvotes: 3

Views: 3291

Answers (1)

wim
wim

Reputation: 362836

The API documentation is here:

https://boto3.readthedocs.io/en/stable/index.html

Available resources are generated dynamically. If you just try to create a bogus one, you should be able to see which top-level resources are currently available in the error message:

>>> boto3.resource('potato')
ResourceNotExistsError: The 'potato' resource does not exist.
The available resources are:
   - cloudformation
   - cloudwatch
   - dynamodb
   - ec2
   - glacier
   - iam
   - opsworks
   - s3
   - sns
   - sqs

>>> boto3.client('bogus')
UnknownServiceError: Unknown service: 'bogus'. Valid service names are: acm, apigateway, application-autoscaling, appstream, autoscaling, batch, budgets, clouddirectory, cloudformation, cloudfront, cloudhsm, cloudsearch, cloudsearchdomain, cloudtrail, cloudwatch, codebuild, codecommit, codedeploy, codepipeline, codestar, cognito-identity, cognito-idp, cognito-sync, config, cur, datapipeline, devicefarm, directconnect, discovery, dms, ds, dynamodb, dynamodbstreams, ec2, ecr, ecs, efs, elasticache, elasticbeanstalk, elastictranscoder, elb, elbv2, emr, es, events, firehose, gamelift, glacier, health, iam, importexport, inspector, iot, iot-data, kinesis, kinesisanalytics, kms, lambda, lex-models, lex-runtime, lightsail, logs, machinelearning, marketplacecommerceanalytics, meteringmarketplace, mturk, opsworks, opsworkscm, organizations, pinpoint, polly, rds, redshift, rekognition, resourcegroupstaggingapi, route53, route53domains, s3, sdb, servicecatalog, ses, shield, sms, snowball, sns, sqs, ssm, stepfunctions, storagegateway, sts, support, swf, waf, waf-regional, workdocs, workspaces, xray

What you can actually do with a client is also generated dynamically, from json files. For example here is the service description for Amazon Glacier.

A client can also tell you the available subresources, using this method:

>>> glacier = boto3.resource('glacier')
>>> glacier.get_available_subresources()
['Account', 'Archive', 'Job', 'MultipartUpload', 'Notification', 'Vault']

The parameters necessary to instantiate a glacier.Archive(), for example, are clearly documented. The docs are quite good, but it is also pretty easy to discern the same information from reading the service description files directly.

Upvotes: 2

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