pyright | Static Type Checker for Python | Code Analyzer library

 by   microsoft Python Version: 1.1.314 License: Non-SPDX

kandi X-RAY | pyright Summary

kandi X-RAY | pyright Summary

pyright is a Python library typically used in Code Quality, Code Analyzer applications. pyright has no bugs, it has no vulnerabilities and it has medium support. However pyright build file is not available and it has a Non-SPDX License. You can download it from GitHub.

Static Type Checker for Python

            kandi-support Support

              pyright has a medium active ecosystem.
              It has 10485 star(s) with 1055 fork(s). There are 104 watchers for this library.
              It had no major release in the last 12 months.
              There are 5 open issues and 4123 have been closed. On average issues are closed in 10 days. There are 1 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of pyright is 1.1.314

            kandi-Quality Quality

              pyright has 0 bugs and 0 code smells.

            kandi-Security Security

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

            kandi-License License

              pyright 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

              pyright releases are available to install and integrate.
              pyright has no build file. You will be need to create the build yourself to build the component from source.
              It has 15793 lines of code, 2546 functions and 1168 files.
              It has low code complexity. Code complexity directly impacts maintainability of the code.

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            pyright Key Features

            No Key Features are available at this moment for pyright.

            pyright Examples and Code Snippets

            pandas-stubs: Public type stubs for pandas,Usage
            Pythondot img1Lines of Code : 16dot img1License : Permissive (BSD-3-Clause)
            copy iconCopy
            import pandas as pd
            decimals = pd.DataFrame({'TSLA': 2, 'AMZN': 1})
            prices = pd.DataFrame(data={'date': ['2021-08-13', '2021-08-07', '2021-08-21'],
                                        'TSLA': [720.13, 716.22, 731.22], 'AMZN': [3316.50, 3200.50, 3100.23]})
            Extending-Wrapping the Decorator-Pyright
            Pythondot img2Lines of Code : 12dot img2License : Permissive (MIT)
            copy iconCopy
            def custom_define(f):
                return attr.define(f)
            def __dataclass_transform__(
                eq_default: bool = True,
                order_default: bool = False,
                kw_only_default: bool = False,
                field_descriptors: Tuple[Union[type, Callable[..., Any]], ...] =  
            Type Annotations
            Pythondot img3Lines of Code : 10dot img3License : Permissive (MIT)
            copy iconCopy
            >>> from attrs import define, field
            >>> @define
            ... class SomeClass:
            ...     a_number = field(default=42)
            ...     list_of_numbers = field(factory=list)
            >>> sc = SomeClass(1, [1, 2, 3])
            >>> sc

            Community Discussions


            apply transformation on a ParamSpec variable?
            Asked 2022-Mar-12 at 05:24

            Is there any way for me to apply a transformation on a ParamSpec? I can illustrate the problem with an example:



            Answered 2022-Mar-12 at 05:24

            This decorator cannot be properly typed with currently available tools (Python 3.10).

            Two main problems here:

            • ParamSpec and Concatenate for now only allow us to modify a fixed number of parameters.
            • We cannot concatenate keyword-only arguments (which makes transforming **kwargs: P.kwargs impossible)

            However, under these constraints, we can achieve a less elegant solution if the positional parameters are known, taking advantage of currying:



            Why are Python classes with identical attributes considered "incompatible" by type checkers?
            Asked 2022-Feb-28 at 18:07

            If two classes have the same set of attributes, why do Python type checkers warn that they aren't compatible?

            In the example below I could, in reality, pass a T to wants_s and all would be fine. So why don't type checkers "allow" this?



            Answered 2022-Feb-28 at 17:53

            The issue you are talking about is called "Duck Typing". You can find more information about it by Googling the term.

            Python explicitly allows duck typing. If an object has a swim method, then you can call swim() and hope that it does the right thing.

            One of the jobs of a linter is to protect you against duck typing. If you're saying that a method accepts a Duck, then the type checker's job is make sure that you only pass it an instance of a Duck. Sure, you can pass it an instance of a Whale, and that whale also has a swim method. But what happens when you later decide you want your duck to fly()?

            The solution to your problem is Protocols. You might have a protocol Swimmable indicating that the object has a swim() method. Then your method makes it argument type be Swimmable.

            In short, the linter is doing its job.



            How can I use TypeGuards to narrow types for multiple object fields in Python?
            Asked 2022-Feb-20 at 16:15

            Say I've got a Foo object which has multiple fields which can either be None or some other type. Whether or not the field is None relates to whether other fields are None or not, so by checking one field, I can instantly know if the other fields are None.

            I understand this is terrible class design, but I'm not able to modify it as it is other people's code that I am annotating.

            It looks like TypeGuards introduced in PEP 647 are my best bet for adding this functionality, but I can't figure out how I could specifically apply them to this situation. I've attached an attempt I made with subclasses, but it fails both in MyPy and in Pyright.



            Answered 2022-Feb-20 at 16:15

            What if you're explicit about the types in SingularFoo? This seems to make mypy happy:



            Python type-checking: Literal[False], overload, and NoReturn
            Asked 2021-Dec-13 at 01:48

            I have the following (typed) Python function:



            Answered 2021-Dec-13 at 01:48

            I posted this to the Pyright issue tracker and was informed that I had to add a Union[NoReturn, None] annotation to the check implementation to resolve the error:

            [This] falls out of pyright's rules for return type inference. Pyright will infer a NoReturn type only in the case that all code paths raise an exception. It's quite common for some code paths raise an exception, and it would produce many false positives if pyright were to include NoReturn in the union in that case, so NoReturn is always elided from a union in an inferred return type.

            Mypy doesn't have any support for return type inference, so that explains why this doesn't occur for mypy.

            The correct way to annotate this is to include an explicit None | NoReturn return type for the implementation.

            Unfortunately, this defeats the purpose of the overloads in the first place, which is to allow PyRight to infer from the arguments when NoReturn is the return type. I asked whether it is possible to use overloads to conditionally express NoReturn to the type checker. Apparently it is not:

            Unfortunately, pyright cannot make this determination because of its core architecture. The "reachability" of nodes within a code flow graph cannot rely on type evaluations because type evaluations depend on reachability of code flow nodes. To work around this chicken-and-egg problem, the logic that determines reachability does some basic checks to determine if the called function is potentially a "NoReturn" function, but these basic checks are not sophisticated enough to handle overload evaluation. Evaluating overloads requires the full type evaluator, and that depends on reachability.



            Is it possible to maintain type information when unpacking object attributes?
            Asked 2021-Nov-10 at 05:43

            Imagine I have an object which is an instance of a class such as the following:



            Answered 2021-Nov-10 at 05:43

            As juanpa.arrivillaga has pointed out, the assignment statements docs indicate that, in the case that the left hand side of an assignment statement is a comma separated list of one or more targets,

            The object must be an iterable with the same number of items as there are targets in the target list, and the items are assigned, from left to right, to the corresponding targets.

            Therefore, if one wants to unpack a bare object, one must necessarily implement __iter__, which will always have a return type of Iterator[Union[...]] or Iterator[SufficientlyGenericSubsumingType] when it includes multiple attribute types. A static type checker, therefore, cannot effectively reason about the specific types of unpacked variables.

            Presumably, when a tuple is on the right hand side of an assignment, even though the language specification indicates that it will be treated as an iterable, a static type checker can still reason effectively about the types of its constituents.

            As such, as juanpa.arrivillaga has also pointed out, a bespoke astuple method which emits a tuple[...] type is probably the best approach if one must unpack attributes, even though it does not avoid the pitfall of multi-level list comprehensions mentioned in the question. In terms of the question, we could now have:



            Make a Union of strings to be used as possible dictionary keys
            Asked 2021-Oct-29 at 11:05

            I have some Python 3.7 code and I am trying to add types to it. One of the types I want to add is actually an Union of several possible strings:



            Answered 2021-Oct-29 at 11:05

            "fruits" is not a type (hint), but Literal["fruits"] is.



            Sorting imports fails on Python VSCode extension
            Asked 2021-Oct-27 at 09:34

            I have an anaconda environment that has Python 3.7 installed. I have a file with some imports out of order which I want VScode to order when pressing CRTL+s.

            However, instead or ordering the imports, there is a crash and nothing happens.


            When I press CRTL+s on my VScode, I get a pop up saying the Python extension crashes. After some investigation, this is the stack-trace I found:



            Answered 2021-Oct-27 at 09:34

            The problem here is that I had broken dependencies which would not allow me to do any updates nor new installs.

            This had to do with having packages from both conda and pip. Some of them play nice together, some don't.


            My solution, was unfortunately, rather atomic. I deleted the environment and created a new one with Python 3.7. Upon doing that, I also added an extra conda channel conda-forge which I recommend instead of pip.

            Once I did that I installed all the dependencies and packages using conda and it worked.


            Here are the command I used:



            How to convert between 2 type aliases in python?
            Asked 2021-Oct-17 at 18:55

            I am trying to do the following in python:



            Answered 2021-Oct-17 at 18:54

            You can always use the typing.cast function to say "trust me, I know what I'm doing."



            If there are multiple possible return values, should pyright automatically infer the right one, based on the passed arguments?
            Asked 2021-Oct-11 at 12:33

            I have the following function:



            Answered 2021-Aug-12 at 09:43

            This is not how type hinting works. To know that an input of etree._Element always results in a return of etree._Element and an input of None always results in None the IDE would need to parse the function, analyse all paths and get to that result.

            I highly doubt that it is build to do that. Instead the IDE simply parses for annotations in the signatures and returns them as hint - type hints are just that - they are not enforced on code execution.

            You may want to check with a simpler function:



            How do I annotate a function whose return type depends on its argument?
            Asked 2021-Oct-10 at 10:19

            In Python, I often write functions that filter a collection to find instances of specific subtypes. For example I might look for a specific kind of nodes in a DOM or a specific kind of events in a log:



            Answered 2021-Oct-10 at 10:19

            Okay, here we go. It passes MyPy --strict, but it isn't pretty.

            What's going on here

            For a given class A, we know that the type of an instance of A will be A (obviously). But what is the type of A itself? Technically, the type of A is type, as all python classes that don't use metaclassses are instances of type. However, annotating an argument with type doesn't tell the type-checker much. The syntax used for python type-checking to go "one step up" in the type hierarchy is, instead, Type[A]. So if we have a function myfunc that returns an instance of a class inputted as a parameter, we can fairly simply annotate that as follows:


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


            No vulnerabilities reported

            Install pyright

            You can download it from GitHub.
            You can use pyright 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.


            For additional information about Python static typing, refer to this community-maintained Python Type School.
            Find more information at:

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