aws-data-tools 0.1.1

Description:

awsdatatools 0.1.1

AWS Data Tools





A set of opinioned (but flexible) Python libraries for querying and transforming data
from various AWS APIs, as well as a CLI interface.
This is in early development.
Installation
Using pip should work on any system with at least Python 3.9:
$ pip install aws-data-tools

By default, the CLI is not installed. To include it, you can specify it as an extra:
$ pip install aws-data-tools[cli]

Quickstart
The quickest entrypoints are using the data builders and the CLI.
To dump a data representation of an AWS Organization, you can do the following using
the builder:
from aws_data_tools.models.organizations import OrganizationDataBuilder

odb = OrganizationDataBuilder(init_all=True)
organization = odb.as_json()

Here is how to do the same thing with the CLI:
$ awsdata organization dump-all

Usage
There are currently 4 main components of the package: helpers for working with AWS
session and APIs, data models for API data types, builders to query AWS APIs and
perform deserialization and ETL operations of raw data, and a CLI tool to further
abstract some of these operations.
Builders
While it is possible to directly utilize and interact with the data models, probably
the largest benefit are the builders. They abstract any API operations and data
transformations required to build data models. The models can then be serialized to
dicts, as well as DOT, JSON, or YAML strings.
A full model of an AWS Organization can be constructed using the
OrganizationDataBuilder class. It handles recursing the organizational tree and
populating any relational data between the various nodes, e.g., parent-child
relationships between an OU and an account.
The simplest example pulls all supported organizational data and creates the related
data models:
from aws_data_tools.models.organizations import OrganizationDataBuilder

odb = OrganizationDataBuilder(init_all=True)

Note that this makes many API calls to get this data. For example, every OU, policy,
and account requires an API call to pull any associated tags, so every node requires at
least n+3 API calls. Parallel operations are not supported, so everything runs
serially.
To get a sense of the number of API calls required to populate organization data, an
organization with 50 OUs, 5 policies, 200 accounts, and with all policy types activated
requires 316 API calls! That's why this library was created.
For more control over the process, you can init each set of components as desired:
from aws_data_tools.models.organizations import OrganizationDataBuilder

org = OrganizationDataBuilder()
org.init_connection()
org.init_organization()
org.init_root()
org.init_policies()
org.init_policy_tags()
org.init_ous()
org.init_ou_tags()
org.init_accounts()
org.init_account_tags()
org.init_policy_targets()
org.init_effective_policies()

CLI
As noted above, the CLI is an optional component that can be installed using pip's
bracket notation for extras:
$ pip install aws-data-tools[cli]

With no arguments or flags, help content is displayed by default. You can also pass the
--help flag for the help content of any commands or subcommands.
$ awsdata
Usage: awsdata [OPTIONS] COMMAND [ARGS]...

A command-line tool to interact with data from AWS APIs

Options:
--version Show the version and exit.
-d, --debug Enable debug mode
-h, --help Show this message and exit.

Commands:
organization Interact with data from AWS Organizations APIs

Here is how to dump a JSON representation of an AWS Organization to stdout:
The organization subcommand allows dumping organization data to a file or to stdout:
$ awsdata organization dump-json --format json
Usage: awsdata organization dump-json [OPTIONS]

Dump a JSON representation of the organization

Options:
--no-accounts Exclude account data from the model
--no-policies Exclude policy data from the model
-f, --format [JSON|YAML] The output format for the data
-o, --out-file TEXT File path to write data instead of stdout
-h, --help Show this message and exit.

It also supports looking up details about individual accounts:
$ awsdata organization lookup-accounts --help
Usage: awsdata organization lookup-accounts [OPTIONS]

Query for account details using a list of account IDs

Options:
-a, --accounts TEXT A space-delimited list of account IDs
[required]
--include-effective-policies Include effective policies for the accounts
--include-parents Include parent data for the accounts
--include-tags Include tags applied to the accounts
--include-policies Include policies attached to the accounts
-h, --help Show this message and exit.

API Client
The APIClient class wraps the initialization of a boto3
session and a low-level client for a named service. It contains a single api()
function that takes the name of an API operation and any necessary request data as
kwargs.
It supports automatic pagination of any API operations that support it. The pagination
config is set to {'MaxItems': 500} by default, but a pagination_config dict can be
passed for any desired customizations.
When initializing the class, it will create a session and a client.
from aws_data_tools.client import APIClient

client = APIClient("organizations")
org = client.api("describe_organization").get("organization")
roots = client.api("list_roots")
ous = client.api("list_organizational_units_for_parent", parent_id="r-abcd").get(
"organizational_units"
)

Note that, generally, any list operations will return a list with no further filtering
required, while describe calls will have the data keyed under the name of the object
being described. For example, describing an organization returns the relavant data
under an organization key.
Furthermore, you may notice above that API operations and their corresponding arguments
support snake_case format. Arguments can also be passed in the standard PascalCase
format that the APIs utilize. Any returned data has any keys converted to snake_case.
The raw boto3 session is available as the session field, and the raw, low-level
client is available as the client field.
Data Models
The models package contains a collection of opinionated models
implemented as data classes. There is a package for each available service. Each one is
named after the service that would be passed when creating a boto3 client using
boto3.client('service_name').
Most data types used with the Organizations APIs are supported. The top-level
Organization class is the most useful, as it also acts as a container for all other
related data in the organization.
The following data types and operations are currently not supported:

Viewing organization handshakes (for creating and accepting account invitations)
Viewing the status of accounts creations
Viewing organization integrations with AWS services (for org-wide implementations of
things like CloudTrail, Config, etc.)
Viewing delegated accounts and services
Any operations that are not read-only

All other data types are supported.
from aws_data_tools.client import APIClient
from aws_data_tools.models.organizations import Organization

client = APIClient("organizations")
data = client.api("describe_organization").get("organization")
org = Organization(**data)
org.as_json()

View the package for the full list of
models.
Roadmap
The goal of this package is to provide consistent, enriched schemas for data from both
raw API calls and data from logged events. We should also be able to unwrap and parse
data from messaging and streaming services like SNS, Kinesis, and EventBridge.
Here are some examples:

Query Organizations APIs to build consistent, denormalized models of organizations
Validate and enrich data from CloudTrail log events
Parse S3 and ELB access logs into JSON

This initial release only contains support for managing data from AWS Organizations
APIs.
The following table shows what kinds of things may be supported in the future:



Library Name
Description
Data Type
Data Sources
Supported




organizations
Organization and OU hierarchy, policies, and accounts
API
Organizations APIs
☑


cloudtrail
Service API calls recorded by CloudTrail
Log
S3 / SNS / SQS / CloudWatch Logs / Kinesis / Kinesis Firehose
☐


s3
Access logs for S3 buckets
Log
S3 / SNS / SQS
☐


elb
Access logs from Classic, Application, and Network Load Balancers
Log
S3 / SNS / SQS
☐


vpc_flow
Traffic logs from VPCs
Log
S3 / CloudWatch Logs / Kinesis / Kinesis Firehose
☐


config
Resource state change events from AWS Config
Log
S3 / SNS / SQS
☐


firehose
Audit logs for Firehose delivery streams
Log
CloudWatch Logs / Kinesis / Kinesis Firehose
☐


ecs
Container state change events
Log
CloudWatch Events / EventBridge
☐


ecr
Repository events for stored images
Log
CloudWatch Events / EventBridge
☐



References:

CloudWatch Logs: https://docs.aws.amazon.com/AmazonCloudWatch/latest/logs/aws-services-sending-logs.html
CloudWatch Events: https://docs.aws.amazon.com/AmazonCloudWatch/latest/events/EventTypes.html

Contributing
View the Contributing Guide to learn about giving back.