allure-framework / allure-framework/allure-python

[allure-behave] Support @flaky tag for scenarios (to mark them as flaky in the allure report)

未关闭
#305 2 条评论 0 个 reaction 已指派 0 人 在 GitHub 查看
task:new feature theme:behave
主要语言
Python
星标
814
派生
260
PR 合并指标
30 天内没有已合并 PR

描述

#### I'm submitting a ...
- [ ] bug report
- [x] feature request
- [ ] support request => Please do not submit support request here, see note at the top of this template.

#### What is the current behavior?
In an allure report based on the output of the `allure-behave` formatter, a `@flaky` tag is simply shown in the list of all scenario tags.
But the scenario is not marked as flaky or special in any way.

#### If the current behavior is a bug, please provide the steps to reproduce and if possible a minimal demo of the problem
Use the allure-behave formatter for testruns with scenarios containing a `@flaky` tag and view the corresponding allure test report.

#### What is the expected behavior?
It would be nice if a scenario tagged as flaky was marked as flaky in the json file produced by the `allure-behave` formatter (allure's flaky attribute set to `True`) - and thus shown as flaky test in a resulting allure test report.

#### What is the motivation / use case for changing the behavior?
Scenarios tagged as flaky could be more easily spotted in the overall allure test report.

Allure does support marking tests as flaky:
https://docs.qameta.io/allure/#_flaky_tests

Tagging a scenario or feature as flaky is apparently already supported by `allure-cucumber-jvm`:
https://docs.qameta.io/allure/#_test_markers

#### Please tell us about your environment:

- allure-behave 2.5.1
- allure-python-commons 2.5.1
- allure 2.3-SNAPSHOT

#### Other information

[//]: # (
. e.g. detailed explanation, stacktraces, related issues, suggestions
. how to fix, links for us to have more context, eg. Stackoverflow, Gitter etc
)

贡献指南

打开贡献指南

调研方向

从 allure-behave formatter 开始,跟踪 scenario 标签如何转换为 JSON 结果。对带有 @flaky 的 scenario 运行 formatter 输出,然后验证生成的 JSON 设置了 Allure 的 flaky 属性,并且生成的报告将该 scenario 标记为 flaky。

由索引模型根据 Issue 内容生成。

评估

技术栈
python
领域
testing
Issue 类型
功能
难度
3/5
预计耗时
1-2 天
活跃度
停滞
描述清晰度
基本清楚
新手友好度
45/100

把新 issue 发到你的邮箱

精选适合新手参与的 GitHub issue 摘要。