Software Alternatives, Accelerators & Startups

Landscape (Python) VS PyLint

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

Landscape (Python) logo Landscape (Python)

Hosted continuous Python code metrics

PyLint logo PyLint

Pylint is a Python source code analyzer which looks for programming errors.
  • Landscape (Python) Landing page
    Landing page //
    2020-04-08
  • PyLint Landing page
    Landing page //
    2023-09-22

Landscape (Python) features and specs

  • Code Quality Improvement
    Landscape helps enhance code quality by analyzing Python code to identify possible issues, ensuring compliance with coding standards.
  • Continuous Integration
    The tool integrates seamlessly with continuous integration systems to automate code analysis with every code change, helping catch issues early.
  • User-Friendly Reports
    Generates detailed reports with easy-to-understand visualizations, making it simpler for developers to pinpoint and address code issues.
  • Support for Pyflakes and pep8
    Landscape supports existing Python tools like Pyflakes and pep8 for comprehensive code analysis and style checking.
  • Badges for Code Health
    Provides embeddable badges that reflect the current health of the codebase, fostering a culture of code quality in teams.

Possible disadvantages of Landscape (Python)

  • Limited Language Support
    Being focused on Python, Landscape does not support other programming languages, which limits its utility in multi-language projects.
  • Resource Intensity
    The analysis process can be resource-intensive, potentially slowing down CI/CD pipelines, especially for larger codebases.
  • Potential Learning Curve
    Developers new to static code analysis might experience a learning curve in understanding and correctly addressing reported issues.
  • Dependency on External Service
    Relying on an external service for code quality analysis may pose risks related to service availability and data privacy concerns.

PyLint features and specs

  • Extensive Error Checking
    PyLint provides comprehensive checks for errors in Python code, including syntax errors, structural problems, and more complex issues like unused variables and undefined names.
  • Customizability
    PyLint allows users to configure which types of errors and warnings they want to check for through configuration files, making it adaptable to different coding standards and preferences.
  • Integration with Development Tools
    PyLint can be integrated with various IDEs and editors such as Visual Studio Code, PyCharm, and more, enhancing the development workflow by providing real-time feedback.
  • Code Quality Metrics
    It offers additional metrics and ratings for code quality, helping developers understand the complexity and maintainability of their code.
  • Code Refactoring Support
    PyLint suggests specific code improvements and refactorings, which can enhance the readability and performance of the code.

Possible disadvantages of PyLint

  • Performance Overhead
    Analyzing large codebases can be slow with PyLint, impacting performance and increasing the time taken for continuous integration pipelines to run.
  • False Positives
    PyLint can generate false positive warnings, particularly in complex or dynamically-typed code, which might lead to developers spending time investigating non-issues.
  • Steep Learning Curve
    The initial setup and configuration of PyLint can be challenging for new users who are not familiar with its extensive customization options.
  • Strictness
    PyLint is very strict by default, which might overwhelm developers, especially those working in less formal or rapid development environments, with a high volume of warnings and errors.
  • Compatibility Issues
    There might be compatibility issues with certain Python versions or specific coding patterns, leading to inaccurate linting results or the need for frequent adjustments to configurations.

Analysis of PyLint

Overall verdict

  • PyLint is generally considered a good tool for Python developers, especially those who want to maintain high code quality. While some users may find it overly strict at times, its comprehensive analysis is beneficial for identifying both significant errors and minor code improvements. Its configurability allows users to tailor its checks according to their project's specific needs.

Why this product is good

  • PyLint is a widely used static code analysis tool for Python that helps ensure code quality and adherence to coding standards. It analyzes Python source code to look for programming errors, enforce a coding standard, and suggest code improvements. It provides detailed insights into potential issues and helps maintain consistency and readability in Python projects.

Recommended for

  • Python developers who care about code quality and adherence to PEP 8 standards.
  • Teams working on collaborative projects where maintaining a consistent coding style is important.
  • Projects that require thorough documentation and linting for all code artifacts.
  • Developers who want to catch errors and potential bugs early in the development process.

Landscape (Python) videos

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PyLint videos

Pylint Tutorial โ€“ How to Write Clean Python

More videos:

  • Tutorial - How to write pylint plugins

Category Popularity

0-100% (relative to Landscape (Python) and PyLint)
Code Analysis
12 12%
88% 88
Code Coverage
14 14%
86% 86
Code Quality
39 39%
61% 61
Code Review
13 13%
87% 87

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Landscape (Python) and PyLint

Landscape (Python) Reviews

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PyLint Reviews

7 best recommended IntelliJ IDEA Python plugins - Programmer Sought
As the name suggests, this plugin is a Python linter. It provides real-time and on-demand scanning of Python files with Pylint ideas from your Intellij. Pylint is an open source project, so it can be fully customized according to your needs. In addition, Pylint has a lot of documentation on the plugin website.

Social recommendations and mentions

Based on our record, PyLint 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.

Landscape (Python) mentions (0)

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

PyLint mentions (13)

  • Nix-Powered Python Development
    These requirements are not too uncommon. I have seen many projects with similar setup, with alternatives such as tox instead of nox, or black and pylint instead of ruff, etc. - Source: dev.to / about 1 year ago
  • Nix Flake Templates
    Use pylint and flake8 for linting and static analysis. - Source: dev.to / about 1 year ago
  • The Cloud Resume Challenge - GCP :)
    I used Pylint to perform basic test on the code and for the security bit I used snyk SCM to check for vulnerabilities within my code and it's dependencies. - Source: dev.to / almost 4 years ago
  • I'm being told that one of my projects on GitHub is poorly coded. Can anyone tell me why? The only thing I see ugly, not necessary wrong or poorly coded, is the two variables with the list of iPhone models, and the incredibly long if, elif, and else statements.
    Pylint - https://pylint.pycqa.org/en/latest/ Black - https://black.readthedocs.io/en/stable/. Source: almost 4 years ago
  • API pull into pandas with formatting.
    Your code isn't PEP-8 compliant. Use black or autopep8 on your code to auto-format your code, or at least use pylint to check for issues, before asking anyone else to read your code. Source: about 4 years ago
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What are some alternatives?

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

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

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.

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.

PyCharm - Python & Django IDE with intelligent code completion, on-the-fly error checking, quick-fixes, and much more...

Source Insight - Source Insight is a programming editor & code browser with built-in live analysis for C/C++, C#, Java, and more; helping you understand large projects.

Coverity Scan - Find and fix defects in your Java, C/C++ or C# open source project for free