pytest-metadata | Plugin for accessing test session metadata | Plugin library

by pytest-dev Python Version: 3.1.1 License: Non-SPDX

X-Ray Key Features Code Snippets Community Discussions(2)Vulnerabilities Install Support

kandi X-RAY | pytest-metadata Summary

pytest-metadata is a Python library typically used in Plugin applications. pytest-metadata has no bugs, it has no vulnerabilities and it has low support. However pytest-metadata build file is not available and it has a Non-SPDX License. You can install using 'pip install pytest-metadata' or download it from GitHub, PyPI.

Plugin for accessing test session metadata

Support

Quality

Security

License

Reuse

Support

pytest-metadata has a low active ecosystem.

It has 53 star(s) with 23 fork(s). There are 6 watchers for this library.

There were 2 major release(s) in the last 12 months.

There are 2 open issues and 17 have been closed. On average issues are closed in 135 days. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of pytest-metadata is 3.1.1

Quality

pytest-metadata has 0 bugs and 0 code smells.

Security

pytest-metadata has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

pytest-metadata code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

pytest-metadata has a Non-SPDX License.

Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

Reuse

pytest-metadata releases are not available. You will need to build from source code and install.

Deployable package is available in PyPI.

pytest-metadata has no build file. You will be need to create the build yourself to build the component from source.

pytest-metadata saves you 152 person hours of effort in developing the same functionality from scratch.

It has 374 lines of code, 17 functions and 13 files.

It has low code complexity. Code complexity directly impacts maintainability of the code.

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pytest-metadata Key Features

No Key Features are available at this moment for pytest-metadata.

pytest-metadata Examples and Code Snippets

No Code Snippets are available at this moment for pytest-metadata.

Community Discussions

Trending Discussions on pytest-metadata

Adding [aliases] fails with error: invalid command 'xyz'

Import Error while running pytest in virtualenv

QUESTION

Adding [aliases] fails with error: invalid command 'xyz'

Asked 2020-Aug-31 at 14:30

Attempting to add shortcuts such as cov = coverage report --show-missing to the [aliases] section of setup.cfg causes python setup.py cov to fail with error: invalid command 'coverage'. What additional options are needed to support this?

Version info:

...

ANSWER

Answered 2020-Aug-31 at 14:30

setup.cfg aliases creates aliases for setup.py, not general commands. In your case python setup.py cov is equivalent to

Source https://stackoverflow.com/questions/63672256

QUESTION

Import Error while running pytest in virtualenv

Asked 2020-Jul-28 at 11:02

I am trying to run my pytest (bdd) test cases in virtualenv. I have created a requirements.txt (using pip freeze) file in the root folder as below.

...

ANSWER

Answered 2020-Jul-28 at 11:02

There's an open issue with pytest-yield that prevents it to work with latest pytest version (5.1 and up): #6. This means that you have either to downgrade to an older version of pytest:

Source https://stackoverflow.com/questions/63128862

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install pytest-metadata

You can install using 'pip install pytest-metadata' or download it from GitHub, PyPI.
You can use pytest-metadata like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

Find more information at: