xoto3 2.0.1
High level utilities for a subset of boto3 operations common for AWS serverless development in Python.
Requires Python: <4.0,>=3.9

# xoto3

`xoto3` (pronounced zoto-three) is a layer of useful micro-utilities
for `boto3` (the AWS Python library) particularly suitable for
serverless development.

These come from years of experience developing a serverless platform
at XOi Technologies, and represent real production code.

## Installing

Get started quickly by installing the package with `pip install xoto3`

## Features

Some of the features included:

- A more general purpose `boto3` client API paginator.

- Higher-level abstractions for DynamoDB, including:

  - pure data transformation safeguards against various sorts of data
    that DynamoDB won't accept.
  - an multi-item, multi-table composable, retrying, transaction
    wrapper for TransactWriteItems, allowing arbitrary writes (up to
    the built in API limitations) to multiple databases to be
    expressed as pure Python.
  - a transactional single-item update that allows you to express your
    single-item update transformation in pure Python.
  - transparent BatchGet and BatchWrite utilities that work around the
    many annoyances of `boto3` and DynamoDB itself.
  - composable query interfaces that make writing basic queries against DynamoDB fun.

  [see readme for examples](xoto3/dynamodb/README.md)

- Cloudwatch Insights and Log Groups Query URL formatters.

- General-purpose AWS Lambda finalization code, to make sure buffered
  IO gets a chance to flush before your Lambda gets paused.

- Wrapper for SSM parameter puts and gets, including built-in support
  for parameter values larger than what SSM will accept by
  automatically splitting your values and reconstructing them on gets.

Various other utilities are included as well - feel free to poke through the source code.

None of these features "rely" on any of the others, so all of the
power is left in your hands. This is not a framework; just a set of
mostly pure-functional utilities, with a couple of handy wrappers for
`boto3` functions that perform IO.

## Other Utilities

Some fairly general-purpose utilities are also included. See [the readme](xoto3/utils/README.md) for more details.

Some highlights:

- `tree_map` - recursively map through a tree of Python builtins
- `lazy` - general purpose lazy-loading container
- Various serialization utilities (datetimes, decimals, JSON helpers)
- `pipe_multiprocessing` - a Process Pool for places like AWS Lambda
  where Python's built-in shared memory-dependent Pool does not work.

## Development

### Getting set up

This repository leverages Poetry >= 2.0. Install it with `pip install poetry~=2.0`
Then simply run `poetry install`. You'll want to periodically run `poetry update` as well.

**The poetry.lock file** is not version-controlled, and shouldn't be (there's an argument to be made about pinning dev dependencies)

### Versioning

The version is kept in both `pyproject.toml` and `xoto3/__about__.py` for runtime use.
We use [poetry-bumpversion](https://pypi.org/project/poetry-bumpversion/) to keep them in sync.

Therefore, it's important for you to either change the version using the `poetry version (major|minor|patch|<x.y.z>` command, or edit both files manually.

## Testing

You can run all unit tests with `poetry run pytest tests`.

You can additionally include all the DynamoDB integration tests by
setting some environment variables:

`XOTO3_INTEGRATION_TEST_DYNAMODB_ID_TABLE_NAME`: the name of a
DynamoDB table with a primary key that is a partition key of `id`
and no range key.
`XOTO3_INTEGRATION_TEST_NO_RANGE_KEY_INDEX_HASH_KEY`: the name of an
attribute which is the partition key of a GSI with no range key.

If you don't currently have a table viable for testing, you can use the following script to easily create one:
`poetry run python ./scripts/create_integration_test_table.py`

## Development

### Writing tests

Any new changes should be accompanied by unit tests. Integration tests
should also be included where they are helpful.

Integration tests should make use of environment variables and pytest's
ability to skip a test in the event that an environment variable is not set.

Additionally, pytest is configured to run all tests in parallel, so any
integration test you write must be independent of any other test, and must not
leave behind test data.

Your integration tests should be written alongside the unit tests. We do not keep
them in a separate folder.