nimoy | A testing and specification framework for Python | Unit Testing library

by browncoat-ninjas Python Version: 1.1.1 License: Apache-2.0

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | nimoy Summary

nimoy is a Python library typically used in Testing, Unit Testing applications. nimoy has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can install using 'pip install nimoy' or download it from GitHub, PyPI.

A testing and specification framework for Python 3, heavily inspired by the amazing Spock Framework.

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Quality

Security

License

Reuse

Support

nimoy has a low active ecosystem.

It has 103 star(s) with 14 fork(s). There are 9 watchers for this library.

It had no major release in the last 6 months.

There are 4 open issues and 8 have been closed. On average issues are closed in 158 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of nimoy is 1.1.1

Quality

nimoy has 0 bugs and 0 code smells.

Security

nimoy has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

nimoy code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

nimoy is licensed under the Apache-2.0 License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

nimoy releases are not available. You will need to build from source code and install.

Deployable package is available in PyPI.

Build file is available. You can build the component from source.

Installation instructions are not available. Examples and code snippets are available.

It has 3830 lines of code, 268 functions and 60 files.

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

Top functions reviewed by kandi - BETA

kandi has reviewed nimoy and discovered the below as its top functions. This is intended to give you an instant insight into nimoy implemented functionality, and help decide if they suit your requirements.

Convert an Assertion to a nimoy expression
Convert an expression node to a Nimoy expression AST
Transform an expression AST to a Nimoy expression AST
Append an expression as expression values
Test if feature was added
Return a SpecMetadata object
Add a feature
Takes a feature block as a feature block
Add a variable to the model
This function runs a single variable with the specified parameters
Creates a single variable with the given parameters
Test for stringy_matrix
Test the matrix form
Runs a single variable with a static function
Creates a static function for a single variable
Generate a single variable using the given generator function
Test if a feature is added
Visit a class node
Visit a function node
Generate a static variable with a static source
Transform an attribute AST node to a nimoy expression
Transform a function call node from a function call node
Visit an expression node
Test if a feature block is added
Visit with block
Transform a function call node to a nimoy expression

Get all kandi verified functions for this library.

nimoy Key Features

No Key Features are available at this moment for nimoy.

nimoy Examples and Code Snippets

No Code Snippets are available at this moment for nimoy.

Community Discussions

Trending Discussions on nimoy

Combine results of multiple aggregations

QUESTION

Combine results of multiple aggregations

Asked 2020-May-06 at 09:01

I have movies index in which each document has this structure :

Document : ...

ANSWER

Answered 2020-May-06 at 09:01

This is not going to work w/ terms. Gotta resort to scripted_metric, I think:

Source https://stackoverflow.com/questions/61614748

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

Vulnerabilities

No vulnerabilities reported

Install nimoy

You can install using 'pip install nimoy' or download it from GitHub, PyPI.
You can use nimoy 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 .

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