tfquery | Run SQL queries on your Terraform infrastructure | Security library

 by   mazen160 Python Version: 0.0.2 License: MIT

kandi X-RAY | tfquery Summary

kandi X-RAY | tfquery Summary

tfquery is a Python library typically used in Security, Terraform applications. tfquery 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 tfquery' or download it from GitHub, PyPI.

tfquery is a framework that allows running SQL queries on Terraform code. It's made to analyze your Terraform infrastructure, locate resources, run security compliance checks, spot misconfigured resources, develop CI benchmarks, and much more. tfquery is made to help in answering questions that are hard to answer about your infrastructure-as-code. It allows querying resources and analyzing its configuration using a SQL-powered framework.
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              tfquery has a low active ecosystem.
              It has 324 star(s) with 17 fork(s). There are 6 watchers for this library.
              OutlinedDot
              It had no major release in the last 12 months.
              There are 0 open issues and 2 have been closed. On average issues are closed in 116 days. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of tfquery is 0.0.2

            kandi-Quality Quality

              tfquery has 0 bugs and 0 code smells.

            kandi-Security Security

              tfquery has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              tfquery code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              tfquery is licensed under the MIT License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              tfquery releases are available to install and integrate.
              Deployable package is available in PyPI.
              Build file is available. You can build the component from source.
              Installation instructions, examples and code snippets are available.
              It has 318 lines of code, 27 functions and 7 files.
              It has high code complexity. Code complexity directly impacts maintainability of the code.

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            tfquery Key Features

            No Key Features are available at this moment for tfquery.

            tfquery Examples and Code Snippets

            No Code Snippets are available at this moment for tfquery.

            Community Discussions

            QUESTION

            Conditional join of query using PostgreSQL
            Asked 2018-Dec-10 at 03:11

            I have a case where I need to run different query in join per function variable

            Currently I have a function as:

            ...

            ANSWER

            Answered 2017-May-15 at 17:24

            You can use logic like this to kill all possible readability to your query and get expected results:

            Source https://stackoverflow.com/questions/43984208

            QUESTION

            OpenGL Transform Feedback with dynamic Geometry
            Asked 2017-Feb-25 at 22:09

            I am currently trying out Transform Feedback with a Geometry Shader. The Geometry Shader takes a Triangle, makes a Prism out of it and also puts a tetraeder on top of it (Think of it like an Obelisk but only with 3 instead of 4 sides).

            I get the right result using Transform Feedback once. However i wanted to create additional Geometry with Transform Feedback. I wanted to do the Geometry Shader Process for each of the Triangles of the Tetraeder.

            Result after first Pass

            Result after second Pass So instead of the black part going to infinity in the second pass, there should have been another of these branches that you can see left and right, but that one towards the camera.

            What am i doing wrong here? I am not sure how to handle the always increasing size of data for the two Vertex Buffer Objects and i am probably doing something wrong there. Help would be appreciated.

            Transform Feedback before the Main window Loop:

            ...

            ANSWER

            Answered 2017-Feb-25 at 18:24

            It's OK to perform a transform feedback operation into the same buffer that you're reading vertex data from. It's not OK to perform a transform feedback operation on top of the vertex data you're reading from.

            And that's essentially what you're doing in the second operation.

            What you need to do is use glBindBufferBase to offset the feedback buffer in the second TF operation, so that it's writing to fresh vertex data.

            The other thing you're doing wrong is that you're passing the wrong triangles to your feedback operation. From your description of what you want, you only want to execute the process on the topmost triangles of the obelisk. But you pass the whole thing in your TF rendering code. You need to isolate the specific triangles you want to expand and only render them.

            Transform feedback will write triangles in the order that you output them. So you need to isolate those specific triangles and only perform feedback operations on them.

            Source https://stackoverflow.com/questions/42458973

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

            Vulnerabilities

            No vulnerabilities reported

            Install tfquery

            You can install using 'pip install tfquery' or download it from GitHub, PyPI.
            You can use tfquery 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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            Install
          • PyPI

            pip install tfquery

          • CLONE
          • HTTPS

            https://github.com/mazen160/tfquery.git

          • CLI

            gh repo clone mazen160/tfquery

          • sshUrl

            git@github.com:mazen160/tfquery.git

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