Skip to main content

Python client for the Evergreen API

Project description

Evergreen.py

A client library for the Evergreen API written in python. Currently supports the V2 version of the API. For more details, see https://github.com/evergreen-ci/evergreen/wiki/REST-V2-Usage.

PyPI - Python Version PyPI Coverage Status

Table of contents

  1. Description
  2. Getting Help
  3. Dependencies
  4. Installation
  5. Usage
  6. Documentation
  7. Contributor's Guide

Description

This is a Python client library for interacting with Evergreen and Evergreen objects. It currently only supports the V2 version of Evergreen's api. It can be used either by Python code in a separate application or on the command line to get data about Evergreen objects quickly and easily.

Getting Help

What's the right channel to ask my question?

If you have a question about evergreen.py, please mention @dag-on-call in slack channel #evergreen-users, or email us at dev-prod-dag@mongodb.com.

How can I request a change/report a bug in evergreen.py?

Create a DAG ticket.

What should I include in my ticket or #evergreen-users question?

Since #evergreen-users questions are interrupts, please include as much information as possible. This can help avoid long information-gathering threads.

Please include the following:

  • Motivation for Request
    • provide us the motivation for this change.
  • Context
    • provide some background contexts for this issue.
  • Description
    • provide some descriptions on how this issue happened.

Dependencies

  • Python 3.7 or later

Installation

$ pip install evergreen.py

Usage

This client can be used either in code or directly via the command line.

In code:

>> from evergreen.api import EvgAuth, EvergreenApi
>> api = EvergreenApi.get_api(EvgAuth('david.bradford', '***'))
>> project = api.project_by_id('mongodb-mongo-master')
>> project.display_name
'MongoDB (master)'

Cli:

$ evg-api --json list-hosts
{
    "host_id": "host num 0",
    "host_url": "host.num.com",
    "distro": {
        "distro_id": "ubuntu1804-build",
        "provider": "static",
        "image_id": ""
    },
    "provisioned": true,
    "started_by": "mci",
    "host_type": "",
    "user": "mci-exec",
    "status": "running",
    "running_task": {
        "task_id": null,
        "name": null,
        "dispatch_time": null,
        "version_id": null,
        "build_id": null
    },
    "user_host": false
}

Documentation

You can find the documentation here.

Contributor's Guide

Setting up a local development environment

Requirements

  • Poetry 1.1 or later

You will need Evergreen credentials on your local machine to use this library or the attached CLI. You can set up your credentials by following the link here.

Linting/formatting

This project uses black for formatting.

poetry run black src tests

Running tests

poetry run pytest

There are a few tests that are slow running. These tests are not run by default, but can be included by setting the env variable RUN_SLOW_TESTS to any value.

$ RUN_SLOW_TEST=1 poetry run pytest

To get code coverage information:

$ poetry run pytest --cov=src --cov-report=html

Automatically running checks on commit

This project has pre-commit configured. Pre-commit will run configured checks at git commit time. To enable pre-commit on your local repository run:

$ poetry run pre-commit install

Versioning

Before deploying a new version, please update the CHANGELOG.md file with a description of what is being changed.

Deploys to PyPi are done automatically on merges to master. In order to avoid overwriting a previous deploy, the version should be updated on all changes. The semver versioning scheme should be used for determining the version number.

The version is found in the pyproject.toml file.

Code Review

This project uses the Evergreen Commit Queue. Add a PR comment with evergreen merge to trigger a merge.

Deployment

Deployment to production is automatically triggered on merges to master.

Project details


Release history Release notifications | RSS feed

This version

3.5.4

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

evergreen.py-3.5.4.tar.gz (43.2 kB view details)

Uploaded Source

Built Distribution

evergreen.py-3.5.4-py3-none-any.whl (52.7 kB view details)

Uploaded Python 3

File details

Details for the file evergreen.py-3.5.4.tar.gz.

File metadata

  • Download URL: evergreen.py-3.5.4.tar.gz
  • Upload date:
  • Size: 43.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.1.14 CPython/3.9.2 Linux/4.15.0-1044-aws

File hashes

Hashes for evergreen.py-3.5.4.tar.gz
Algorithm Hash digest
SHA256 22fdf290e6f889cad420a27c8ae75ef2f72b3282efdbf549b3b4a2c027a2fa97
MD5 f77eb8318d11c3e9822c016afcb8ecff
BLAKE2b-256 e1b1596aee4b983951bb6caa98f0a084df914b980fcdaec64a9622e03e4ae923

See more details on using hashes here.

File details

Details for the file evergreen.py-3.5.4-py3-none-any.whl.

File metadata

  • Download URL: evergreen.py-3.5.4-py3-none-any.whl
  • Upload date:
  • Size: 52.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.1.14 CPython/3.9.2 Linux/4.15.0-1044-aws

File hashes

Hashes for evergreen.py-3.5.4-py3-none-any.whl
Algorithm Hash digest
SHA256 421a112ed12ad9c7510f9a56d372d436651923ee0d5c862a8b3fc1413e661e5d
MD5 fecdb00ec14feb19e1789effcf558078
BLAKE2b-256 8343b6326e894e53d24ca7acac387439206815ab45da5a67983974523c8938ef

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page