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a service for managing laboratory credentials

Project description

HEA Keychain

Research Informatics Shared Resource, Huntsman Cancer Institute, Salt Lake City, UT

The HEA server Keychain is a service for managing laboratory and user credentials.

Version 1.4.2

  • Display the role and shares properties again.

Version 1.4.1

  • Use the /credentials endpoint to delete the managed credential not /awscredentials.

Version 1.4.0

  • Fixed issue where credentials were inadvertently deleted.
  • Made DELETE call for deleting managed AWS credentials more like other HEA microservices.

Version 1.3.4

  • Changes in naming of menu items for credentials and updated associated icons
  • Generated Managed Credential's now outputs the expiration for users to copy to clipboard.

Version 1.3.3

  • Making AWS Credential Username unique per account.

Version 1.3.2

  • Upgrading dependencies to get bug fixes affecting creating and deleting Managed Credentials.
  • Increased delay of background task that checks to see if credentials are expired.

Version 1.3.1

  • Introduces Managed Credentials with ability create and specify life span of credential

Version 1.3.0

  • Now all Credentials objects have a role attribute, replacing the old AWSCredentials role_arn attribute.

Version 1.2.0

  • Display type display name in properties card.

Version 1.1.0

  • Pass desktop object permissions back to clients.
  • Return type_display_name attribute from GET calls.

Version 1.0.3

  • Improved performance.

Version 1.0.2

  • Added endpoint and links for generating an AWS CLI .aws/credentials file.

Version 1.0.1

  • Improved performance.

Version 1

Initial release.

Runtime requirements

  • Python 3.10 or 3.11

Development environment

Build requirements

  • Any development environment is fine.
  • On Windows, you also will need:
  • On Mac, Xcode or the command line developer tools is required, found in the Apple Store app.
  • Python 3.10 or 3.11: Download and install Python 3.10 from https://www.python.org, and select the options to install for all users and add Python to your environment variables. The install for all users option will help keep you from accidentally installing packages into your Python installation's site-packages directory instead of to your virtualenv environment, described below.
  • Create a virtualenv environment using the python -m venv <venv_directory> command, substituting <venv_directory> with the directory name of your virtual environment. Run source <venv_directory>/bin/activate (or <venv_directory>/Scripts/activate on Windows) to activate the virtual environment. You will need to activate the virtualenv every time before starting work, or your IDE may be able to do this for you automatically. Note that PyCharm will do this for you, but you have to create a new Terminal panel after you newly configure a project with your virtualenv.
  • From the project's root directory, and using the activated virtualenv, run pip install wheel followed by pip install -r requirements_dev.txt. Do NOT run python setup.py develop. It will break your environment.

Running tests

Run tests with the pytest command from the project root directory. To improve performance, run tests in multiple processes with pytest -n auto.

Versioning

Use semantic versioning as described in https://packaging.python.org/guides/distributing-packages-using-setuptools/#choosing-a-versioning-scheme. In addition, while development is underway, the version should be the next version number suffixed by .dev.

Version tags in git

Version tags should follow the format heaserver-keychains-<version>, for example, heaserver-keychains-1.0.0.

Uploading to an index server

The following instructions assume separate stable and staging indexes. Numbered releases, including alphas and betas, go into the stable index. Snapshots of works in progress go into the staging index. Thus, use staging to upload numbered releases, verify the uploaded packages, and then upload to stable.

From the project's root directory:

  1. For numbered releases, remove .dev from the version number in setup.py, tag it in git to indicate a release, and commit to version control. Skip this step for developer snapshot releases.
  2. Run python setup.py clean --all sdist bdist_wheel to create the artifacts.
  3. Run twine upload -r <repository> dist/<wheel-filename> dist/<tarball-filename> to upload to the repository. The repository name has to be defined in a twine configuration file such as $HOME/.pypirc.
  4. For numbered releases, increment the version number in setup.py, append .dev to it, and commit to version control with a commit message like, "Prepare for next development iteration."

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