open-alchemy.package-database 4.0.1

Facade for the OpenAlchemy package database

Database

The database has a facade exposes a series of functions that enable services to personalize responses.

Interface

The interface for the database is defined as the TDatabase class here: open_alchemy/package_database/types.py

It can be retrieved using:

from open_alchemy import package_database

database_instance = package_database.get()

Note that the STAGE environment variable needs to be set. The possible values are:

• TEST: DynamoDB is assumed to be running at http://localhost:8000
• PROD: a connection is established to the AWS hosted DynamoDB

Tables

Specs

Stores information about the specs for a user. The following access patterns are expected:

• count the number of models for a user,
• create or update a spec record for a user,
• get the latest version of a spec for a user,
• list all specs for a user,
• retrieve a particular spec for a user,
• delete a particular spec for a user,
• list all versions of a spec for a user and
• delete all specs for a user.

Count Models for a User

Counts the number of models a user has defined.

Input:

• sub: unique identifier for the user.

Output:

• The sum of the latest model_count for each spec for the user.

Algorithm:

1. filter by the sub and updated_at_id to start with latest# and
2. sum over the model_count of each record.

Create or Update a Spec

Input:

• sub,
• name: the name of the spec,
• version: the version of the spec,
• model_count: the number of models in the spec,
• title (optional): the title of the spec and
• description (optional): the description of the spec.

Output:

Algorithm:

1. calculate the id of the spec using https://packaging.pypa.io/en/latest/utils.html#packaging.utils.canonicalize_name based on the name,
2. calculate updated_at based on he current EPOCH time using https://docs.python.org/3/library/time.html#time.time and convert to an integer represented as a string,
3. calculate the value for updated_at_id by joining a zero padded updated_at to 20 characters and id with a # and for id_updated_at by joining id and updated_at with a #,
4. save the item to the database,
5. create another item but use latest for updated_at when generating updated_at_id and id_updated_at

Get Latest Spec Version

Retrieve the latest version of a spec.

Input:

• sub and
• name.

Output:

• The latest version of the spec.

Algorithm:

1. calculate the id of the spec using https://packaging.pypa.io/en/latest/utils.html#packaging.utils.canonicalize_name based on the name,
2. Retrieve the item using the sub partition key and updated_at_id sort key equal to latest#<id> and
3. return the version of the item.

List Specs

Returns information about all the available specs for a user.

Input:

• sub.

Output:

• A list of dictionaries with the id, name, updated_at, version, model_count and title and description if they are defined.

Algorithm:

1. filter items using the sub partition key and updated_at_id starting with latest# and
2. convert the items to dictionaries.

Get Spec

Retrieve a particular spec for a user.

Input:

• sub and
• name.

Output:

• dictionary with the id, name, updated_at, version, model_count and title and description if they are defined

Algorithm:

1. calculate the id of the spec using https://packaging.pypa.io/en/latest/utils.html#packaging.utils.canonicalize_name based on the name,
2. get the item based on sub and updated_at_id with the value latest#<id>,
3. handle the case where it is not found by returning None and
4. convert the item to a dictionary.

Delete Spec

Delete a particular spec for a user.

Input:

• sub and
• name.

Output:

Algorithm:

1. calculate the id of the spec using https://packaging.pypa.io/en/latest/utils.html#packaging.utils.canonicalize_name based on the name,
2. query the id_updated_at_index local secondary index by filtering for sub and id_updated_at starting with <id># and
3. delete all returned items.

List Spec Versions

Returns information about all the available versions of a spec for a user.

Input:

• sub and
• name.

Output:

• A list of dictionaries with the id, name, updated_at, version, model_count and title and description if they are defined.

Algorithm:

1. calculate the id of the spec using https://packaging.pypa.io/en/latest/utils.html#packaging.utils.canonicalize_name based on the name,
2. query the id_updated_at_index local secondary index by filtering for sub and id_updated_at starting with <id>#,
3. filter out any items where updated_at_id starts with latest# and
4. convert the items to dictionaries.

Delete All Specs for a User

Input:

• sub.

Output:

Algorithm:

1. Delete all entries for sub.

Spec Properties

• sub: A string that is the partition key of the table.
• id: A string.
• name: A string.
• updated_at: A string.
• version: A string.
• title: An optional string.
• description: An optional string.
• model_count A number.
• updated_at_id: A string that is the sort key of the table.
• id_updated_at: A string that is the sort key of the idUpdatedAt local secondary index of the table.

Credentials

Stores credentials for a user. The following access patterns are expected:

• list available credentials for a user,
• create or update credentials for a user,
• retrieve particular credentials for a user,
• check that a public and secret key combination exists and retrieve the sub for it,
• delete particular credentials for a user and
• delete all credentials for a user.

List Credentials

List all available credentials for a user.

Input:

• sub.

Output:

• list of dictionaries with the id, public_key and salt keys.

Algorithm:

1. use the sub partition key to retrieve all credentials for the user and
2. map the items to a dictionary.

Create or Update Credentials

Create or update credentials for a user.

Input:

• sub: unique identifier for the user,
• id: unique identifier for the credentials,
• public_key: public identifier for the credentials,
• secret_key_hash: a hash of the secret key for the credentials that is safe to store,
• salt: a random value used to generate the credentials.

Output:

Algorithm:

1. create and store an item based on the input.

Retrieve Credentials

If the credential with the id exists, return it. Otherwise, return None.

Input:

• sub: unique identifier for the user and
• id: unique identifier for the credential.

Output:

• id,
• public_key,
• salt.

Algorithm:

1. Use the sub partition key and id sort key to check whether an entry exists,
2. if an entry exists, return the public_key and salt and
3. return None.

Retrieve User

Check that the public key exists and retrieve the user and salt for it.

Input:

• public_key.

Output:

• sub,
• salt and
• secret_key_hash.

Algorithm:

1. check whether an entry exists using the public_key partition key for the publicKey global secondary index
2. if it does not exist, return None and
3. retrieve and return the sub, salt and secret_key_hash.

Delete a Credential for a User

Input:

• sub and
• id.

Output:

Algorithm:

1. Delete all entries for sub and id.

Delete All Credentials for a User

Input:

• sub.

Output:

Algorithm:

1. Delete all entries for sub.

Credentials Properties

• sub: A string that is the partition key of the table.
• id: A string that is the sort key of the table.
• public_key: A string that is the partition key of the publicKey global secondary index.
• secret_key_hash: Bytes.
• salt: Bytes.

test

Executes the tests defined at tests.

build

Builds the database package defined at ..

release-required

Has 2 outputs:

• result: whether a release to PyPI is required based on the latest released version and the version configured in the project and
• project-version: the version configured in the code base.

deploy

Deploys the CloudFormation stack for the database defined at ../infrastructure/lib/database-stack.ts.

release

If the result output from release-required is true, the package is deployed to both test and production PyPI.

Irrespective of whether the release was executed, the version of the package defined in the code base is installed from both test and production PyPI and the tests defined at ../test/database/tests are executed against the deployed infrastructure on AWS.

Periodic Production Tests

The workflow is defined here: ../.github/workflows/production-test-database.yaml.

Executes the tests defined at ../test/database/tests against a configured version of the package and against the currently deployed infrastructure on AWS.

Pytest Plugin

A pytest plugin is made available to make testing easier. It is defined at open_alchemy/package_database/pytest_plugin.py.

It requires the dynalite NPM package to be installed in the project using npm install --save-dev dynalite to run a local dynamoDB instance at http://localhost:8000. More information on the package is here: https://www.npmjs.com/package/dynalite.

Fixtures

All fixtures that have an effect but yield None are prefixed with _ so that tools like pylint do not complain about unused arguments for test functions.

_database

Spins up the database at the start of the tests and tars down the database at the end. This fixture is unlikely to be useful as no tables are created. The table specific fixtures depend on the _database fixture so it is not necessary to include this fixture in any tests.

_specs_table

Creates the package.specs table before all the tests and deletes it after all tests complete.

_clean_specs_table

Deletes all items from the package.specs table before and after each test.

_credentials_table

Creates the package.credentials table before all the tests and deletes it after all tests complete.

_clean_credentials_table

Deletes all items from the package.credentials table before and after each test.

Infrastructure

The CloudFormation stack is defined here: ../infrastructure/lib/database-stack.ts.

CI-CD

The workflow is defined here: ../.github/workflows/ci-cd-database.yaml.

There are a few groups of jobs in the CI-CD:

• test: runs the tests for the package in supported python versions,
• build: builds the database package,
• deploy: deploys database infrastructure to AWS,
• release-required: determines whether a release to PyPI is required and
• release: a combination of deploying to test and production PyPI and executing tests on the published packages

Production Tests

The tests against the deployed database facade are defined here: ../test/database/.

The workflow that periodically executes the tests is defined here: ../.github/workflows/production-test-database.yaml.