Software Alternatives, Accelerators & Startups

Pyright VS Landscape (Python)

Compare Pyright VS Landscape (Python) and see what are their differences

Pyright logo Pyright

Static type checker for Python. Contribute to microsoft/pyright development by creating an account on GitHub.

Landscape (Python) logo Landscape (Python)

Hosted continuous Python code metrics
  • Pyright Landing page
    Landing page //
    2023-08-01
  • Landscape (Python) Landing page
    Landing page //
    2020-04-08

Pyright videos

Vim setup for Python programmers: conquer of completion (coc) and pyright

Landscape (Python) videos

No Landscape (Python) videos yet. You could help us improve this page by suggesting one.

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Category Popularity

0-100% (relative to Pyright and Landscape (Python))
Code Coverage
74 74%
26% 26
Code Analysis
72 72%
28% 28
Code Quality
64 64%
36% 36
Code Review
52 52%
48% 48

User comments

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Social recommendations and mentions

Based on our record, Pyright seems to be more popular. It has been mentiond 13 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Pyright mentions (13)

  • Introducing Tapyr: Create and Deploy Enterprise-Ready PyShiny Dashboards with Ease
    Static Type Checking with PyRight: Improve code quality and reduce bugs with PyRight, a static type checking feature not available in R. This proactive error detection ensures your applications are reliable, before you even start them. - Source: dev.to / about 2 months ago
  • Enhance Your Project Quality with These Top Python Libraries
    Pyright is a fast type checker meant for large Python source bases. It can run in a “watch” mode and performs fast incremental updates when files are modified. - Source: dev.to / 3 months ago
  • VSCodium – Libre Open Source Software Binaries of VS Code
    You can use pyright instead[0]. It is the FOSS version of pyright, but having some features missing. [0]: https://github.com/microsoft/pyright. - Source: Hacker News / 10 months ago
  • PSA: Configuring LSP w/o nvim-lspconfig is Simple!
    This is not the case! After reading the LSP help pages (:help lsp), I installed and configured two language servers: Typescript Language Server for JavaScript and Pyright for Python. Neovim has fantastic defaults, so things like tags, omnicompletion, and semantic highlighting (New in 0.9) are enabled and configured by default as long as your language server supports them. You can see my configuration below. Source: about 1 year ago
  • Python is two languages now, and that's great
    I've had lots of success using pyright [1] for Python projects, it has sensible defaults and can be configured with a pyproject.toml file so everyone's using the same settings. I use the Pylance VSCode extension to catch errors earlier, but I also put it in pre-commit and as a CI check, so all contributors are committing the same quality of typed code. With more complex types, I've found it isn't necessary to do... - Source: Hacker News / over 1 year ago
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Landscape (Python) mentions (0)

We have not tracked any mentions of Landscape (Python) yet. Tracking of Landscape (Python) recommendations started around Mar 2021.

What are some alternatives?

When comparing Pyright and Landscape (Python), you can also consider the following products

PyLint - Pylint is a Python source code analyzer which looks for programming errors.

Codacy - Automatically reviews code style, security, duplication, complexity, and coverage on every change while tracking code quality throughout your sprints.

flake8 - A wrapper around Python tools to check the style and quality of Python code.

SonarQube - SonarQube, a core component of the Sonar solution, is an open source, self-managed tool that systematically helps developers and organizations deliver Clean Code.

PyFlakes - A simple program which checks Python source files for errors.

CodeClimate - Code Climate provides automated code review for your apps, letting you fix quality and security issues before they hit production. We check every commit, branch and pull request for changes in quality and potential vulnerabilities.