pyanalyze | A Python type checker | Code Analyzer library

 by   quora Python Version: 0.12.0 License: Apache-2.0

kandi X-RAY | pyanalyze Summary

kandi X-RAY | pyanalyze Summary

pyanalyze is a Python library typically used in Code Quality, Code Analyzer applications. pyanalyze 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 pyanalyze' or download it from GitHub, PyPI.

Pyanalyze is a tool for programmatically detecting common mistakes in Python code, such as references to undefined variables and type errors. It can be extended to add additional rules and perform checks specific to particular functions.
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            kandi-support Support

              pyanalyze has a low active ecosystem.
              It has 251 star(s) with 26 fork(s). There are 7 watchers for this library.
              There were 1 major release(s) in the last 12 months.
              There are 29 open issues and 57 have been closed. On average issues are closed in 123 days. There are 10 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of pyanalyze is 0.12.0

            kandi-Quality Quality

              pyanalyze has 0 bugs and 0 code smells.

            kandi-Security Security

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

            kandi-License License

              pyanalyze 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.

            kandi-Reuse Reuse

              pyanalyze 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 are not available. Examples and code snippets are available.
              pyanalyze saves you 7088 person hours of effort in developing the same functionality from scratch.
              It has 30533 lines of code, 3130 functions and 63 files.
              It has medium code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed pyanalyze and discovered the below as its top functions. This is intended to give you an instant insight into pyanalyze implemented functionality, and help decide if they suit your requirements.
            • Returns the default argspec for the given object .
            • Convert a value into a Value .
            • Return the argument signature for obj .
            • Show an error .
            • Visit function definition .
            • Convert a Value into a Value instance .
            • Check whether an attribute is read .
            • Implement setdefault .
            • Parse a replacement field .
            • Return the value of the given arguments .
            Get all kandi verified functions for this library.

            pyanalyze Key Features

            No Key Features are available at this moment for pyanalyze.

            pyanalyze Examples and Code Snippets

            How to convert Python object to a std::vector of Cython extension type and back?
            Pythondot img1Lines of Code : 22dot img1License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
             def PyAnalyze(classesIn):
                 # classesIn is a list of PyClassIn objects and needs to be converted to a PyClassInVector
                 cdef vector[ClassIn] vecIn
                 cdef vector[ClassOut] vecOut
                 cdef PyClassIn a
                 for a in classesIn:
                
            Returning a complex object containing PyObject from c++ function Cython
            Pythondot img2Lines of Code : 39dot img2License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            # unchanged [...]
            from cpython.ref cimport PyObject, Py_DECREF
            from cython.operator cimport dereference as deref, preincrement
            # unchanged [...]
            
            ctypedef PyObject* PyObjectPtr # I run into a bug templaing vector otherwise
            
            cdef extern fro

            Community Discussions

            QUESTION

            How to convert Python object to a std::vector of Cython extension type and back?
            Asked 2019-Oct-07 at 13:18

            I use Cython to wrap C++ code. The code contains a function defined as:

            ...

            ANSWER

            Answered 2019-Oct-07 at 13:18

            In the comments I tried to recommend a solution involving wrapping C++ vectors. I prefer this approach because it avoids copying memory multiple times, but I think it's causing more confusion and you'd rather just use Python lists. Sorry.

            To use Python lists you just have to copy the input and output within PyAnalyze. You have to do it manually - no automatic conversions exists. You also have to be aware of the difference between your wrapped classes and the underlying C++ classes. You can only send the C++ classes to C++, not the wrapped ones.

            Dealing with the input is easy:

            Source https://stackoverflow.com/questions/58171611

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

            Vulnerabilities

            No vulnerabilities reported

            Install pyanalyze

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

            Pyanalyze supports Python 3.6 through 3.10. Because it imports the code it checks, you have to run it using the same version of Python you use to run your code.
            Find more information at:

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            Install
          • PyPI

            pip install pyanalyze

          • CLONE
          • HTTPS

            https://github.com/quora/pyanalyze.git

          • CLI

            gh repo clone quora/pyanalyze

          • sshUrl

            git@github.com:quora/pyanalyze.git

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