validictory | deprecated general purpose python data validator | Validation library

 by   jamesturk Python Version: 1.1.3 License: Non-SPDX

kandi X-RAY | validictory Summary

kandi X-RAY | validictory Summary

validictory is a Python library typically used in Utilities, Validation applications. validictory has no bugs, it has no vulnerabilities, it has build file available and it has low support. However validictory has a Non-SPDX License. You can install using 'pip install validictory' or download it from GitHub, PyPI.

🎓 deprecated general purpose python data validator
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            kandi-support Support

              validictory has a low active ecosystem.
              It has 242 star(s) with 57 fork(s). There are 18 watchers for this library.
              There were 1 major release(s) in the last 12 months.
              There are 1 open issues and 63 have been closed. On average issues are closed in 216 days. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of validictory is 1.1.3

            kandi-Quality Quality

              validictory has 0 bugs and 0 code smells.

            kandi-Security Security

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

            kandi-License License

              validictory 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.

            kandi-Reuse Reuse

              validictory 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.

            Top functions reviewed by kandi - BETA

            kandi has reviewed validictory and discovered the below as its top functions. This is intended to give you an instant insight into validictory implemented functionality, and help decide if they suit your requirements.
            • Validate additional properties
            • Validate field
            • Return the default value
            • Validates the type of the field
            • Validate field values
            • Validate unknown properties
            • Validates that value is divisibleBy value
            • Validate that the field is present in x
            • Validates that field value is greater than or equal to length
            • Validates that the value is greater than or equal to length
            • Validates that the value in x is greater than or equal to number of properties
            • Validate that the value is less than or equal to number of properties
            • Validate that field is disallowed
            • Validate that value matches a regular expression
            • Validate pattern properties
            • Validate that value is a valid enum value
            • Validates that the value is less than the specified value
            • Validate additional items in field list
            • Validate that the value is greater than the specified value
            • Validate properties of a field
            • Generate a datetime validation function
            • Validates that the given field contains all dependencies
            • Validate that the value is unique
            • Validate data against a schema
            Get all kandi verified functions for this library.

            validictory Key Features

            No Key Features are available at this moment for validictory.

            validictory Examples and Code Snippets

            No Code Snippets are available at this moment for validictory.

            Community Discussions

            Trending Discussions on validictory

            QUESTION

            validictory is not able to validate properly
            Asked 2021-Mar-22 at 06:02

            I'm trying to validate the headers of a flask request and its failing. I'm trying to use the below code to simulate the same and can see that its failing to validate the headers properly even if I miss some of the mandatory headers.

            The below code is expected to fail but its passing.

            ...

            ANSWER

            Answered 2021-Mar-22 at 06:02

            I was able to find out the reason for this issue by going through the source code of validictory.

            It was passing the type validation since EnvironHeaders has both the attributes 'keys' and 'values'.

            Source https://stackoverflow.com/questions/66686455

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

            Vulnerabilities

            No vulnerabilities reported

            Install validictory

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

          • CLONE
          • HTTPS

            https://github.com/jamesturk/validictory.git

          • CLI

            gh repo clone jamesturk/validictory

          • sshUrl

            git@github.com:jamesturk/validictory.git

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