Codacy
blog.codacy.com › python-static-analysis-tools
Which Python static analysis tools should I use? - Codacy | Blog
April 1, 2026 - The above output indicates that there are issues with the code: E703: PEP 8 does not recommend using semicolons to terminate statements in Python. A newline typically terminates statements. The error suggests that the statement ends with a semicolon./li> E225: PEP 8 recommends adding whitespace around binary operators to improve readability. The error suggests that there is missing whitespace around the + operator. Bandit is a security-focused static analysis tool that detects security vulnerabilities like hard-coded passwords, shell injections, SQL injections, and invalid pickle serialization/deserialization.
G2
g2.com › categories › static-code-analysis › f › python
Best Static Code Analysis Tools with Python Capabilities | G2
Embold supports developers and development teams by finding critical code issues before they become roadblocks. It is the perfect tool to analyze, diagnose, transform, and sustain your software effici · Industries: Computer Software · Market Segment: 56% Small-Business, 28% Mid-Market ... Pylint is a tool that checks for errors in Python code, tries to enforce a coding standard and looks for bad code smells.
Python static code analysis stack?
We use mypy for type checking (worth making your mypy stricter than the default settings and enforcing type hints for every function), pylint for linting (and ruff but pylint still has more rules), black for code formatting, pytest for testing (you can check coverage with pytest-cov). This is set up with a VSCode devcontainer to give people a reproducible environment to work in and all the tests and checks are part of the CI so team members know that they need them to pass before opening a pull request. I think it works quite well and it’s fairly standard stuff for Python development. More on reddit.com
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January 17, 2024What Python code analysis tools are you using?
Pylance on vscode. I just turned on strict mode and now everything Ive ever written is apparently wrong and bad and terrible and an error. More on reddit.com
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September 14, 2022Dead code detection tool?
Use coverage.py and just see which lines never run during normal operation. More on reddit.com
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June 26, 2013Facebook releases pysa, a python static analysis tool for security issues, with built in Django support
I haven't tried it myself yet, but it looks really interesting and I will try to test it out tomorrow.
More on reddit.com 7
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August 8, 2020What is Sonar’s Python static code analysis and how does it help improve quality code?
Sonar’s Python static code analysis is an automated process that examines your Python source code to detect bugs, vulnerabilities, code smells, and maintainability issues before the code is executed. By analyzing code statically, Sonar tools provide actionable feedback directly in your workflow, helping developers identify and resolve issues early in the development lifecycle. This proactive approach ensures that potential problems are caught before they reach production, reducing technical debt and improving overall software reliability.
Using Sonar’s static analysis for Python supports the c
sonarsource.com
sonarsource.com › knowledge › languages › python
Python Static Code Analysis & Quality Code | Sonar
What are the benefits of using Sonar for Python static code analysis compared to other tools?
Sonar stands out for its deep integration with development workflows, comprehensive rule sets, and support for both on-premises and cloud deployments. Its focus on quality code, new code quality, and quality at the source ensures that teams can maintain high standards without slowing down development.
Unlike many other tools, Sonar provides actionable feedback directly in the developer’s environment and supports a wide range of frameworks and libraries. This holistic approach not only improves code quality but also fosters a culture of continuous improvement and collaboration across teams.
sonarsource.com
sonarsource.com › knowledge › languages › python
Python Static Code Analysis & Quality Code | Sonar
What types of issues does Sonar’s Python static code analysis detect?
Sonar’s Python static code analysis detects a wide range of issues, including bugs, security vulnerabilities, code smells, and maintainability concerns. The analysis engine checks for common programming errors, such as null dereferences, resource leaks, and incorrect API usage. It also identifies security risks like SQL injection, command injection, and improper input validation.
In addition to these critical issues, Sonar highlights code smells—patterns that may indicate deeper problems or make the code harder to maintain. By surfacing these issues early, Sonar empowers developers to write qu
sonarsource.com
sonarsource.com › knowledge › languages › python
Python Static Code Analysis & Quality Code | Sonar
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Luminous Men
luminousmen.com › post › python-static-analysis-tools
Python Static Analysis Tools
November 21, 2023 - Improve code quality with Python static analysis tools like Mypy, Pylint, Pyflakes, and more. Detect bugs and security issues efficiently. Optimize your code now!
Cygnostic
cygnostic.io › 10-essential-python-static-analysis-tools-for-code-quality
10 Essential Python Static Analysis Tools for Code Quality – Cygnostic
March 21, 2026 - Pylint is a static analysis tool that checks for errors in Python scripts, enforces coding standards, and provides comprehensive reports on software quality with actionable recommendations for enhancements.
Sonar
sonarsource.com › knowledge › languages › python
Python Static Code Analysis & Quality Code | Sonar
Sonar’s Python static code analysis is an automated process that examines your Python source code to detect bugs, vulnerabilities, code smells, and maintainability issues before the code is executed. By analyzing code statically, Sonar tools ...
Wikipedia
en.wikipedia.org › wiki › List_of_tools_for_static_code_analysis
List of tools for static code analysis - Wikipedia
February 28, 2026 - PyCharm – Cross-platform Python IDE with code inspections available for analyzing code on-the-fly in the editor and bulk analysis of the whole project. PyDev – Eclipse-based Python IDE with code analysis available on-the-fly in the editor or at save time. Pylint – Static code analyzer.
DEV Community
dev.to › camelcaseguy › python-static-analysis-tools-275b
Python Static Analysis tools - DEV Community
June 25, 2021 - From Python... def fib(n): a, b = 0, 1 while a < n: yield a a, b = b, a+b ... Type declarations act as machine-tested documentation, and static typing makes your code clear and easy to modify without making errors. ... Prospector is a powerful ...
IN-COM DATA SYSTEMS
in-com.com › blog › top-20-python-static-analysis-tools-in-2025-improve-code-quality-and-performance
Top 20 Python Static Analysis Tools: Improve Code Quality and Performance - IN-COM DATA SYSTEMS
February 18, 2025 - In this guide, we’ll explore how Python developers can leverage these tools to improve performance, security, and code quality. ... Smart TS XL is a high-performance, AI-driven static code analysis and impact assessment tool designed for modern ...
GitHub
github.com › analysis-tools-dev › static-analysis
GitHub - analysis-tools-dev/static-analysis: ⚙️ A curated list of static analysis (SAST) tools and linters for all programming languages, config files, build tools, and more. The focus is on tools which improve code quality.
Svace ©️ — Static code analysis tool for Java,C,C++,C#,Go. Synopsys ©️ — A commercial static analysis platform that allows for scanning of multiple languages (C/C++, Android, C#, Java, JS, PHP, Python, Node.JS, Ruby, Fortran, and Swift).
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Forked by 1.5K users
Languages Rust 97.0% | Makefile 3.0%
Analysis-tools
analysis-tools.dev › tag › python
135 Python Static Analysis Tools, Linters, And Code Formatters | Analysis Tools
Autocompletion/static analysis library for Python. ... The strictest and most opinionated python linter ever. ... Check compliance with Python docstring conventions. ... A linter, formatter for finding and removing unused import statements. ... Check Python source files for errors. ... Find unused classes, functions and variables in Python code.
Spectral
spectralops.io › home › static code analysis for python: 7 features to look out for
Static Code Analysis for Python: 7 features to look out for - Spectral
October 12, 2024 - You can unlock a new level of code excellence by leveraging the power of SCA tools like Spectral. Spectral goes beyond traditional linting and static analysis, providing a comprehensive platform for code quality management. With its deep understanding of Python’s intricacies, Spectral identifies potential issues and offers intelligent suggestions and even automated fixes, streamlining the remediation process.
Pawamoy
pawamoy.github.io › posts › python-static-code-analysis-tools
Python static code analysis tools - pawamoy's website
May 31, 2017 - Prospector also helped me discover tools I never heard of before, like Dodgy, Vulture, Pyroma and Frosted. I would like to see integrations for Radon (used by Pylama) as it offers the same thing as McCabe plus other stuff, as well as for Bandit which is a Python code security checker.
HackerNoon
hackernoon.com › python-static-analysis-tools-clean-your-code-before-running
Python Static Analysis Tools: Clean Your Code Before Running | HackerNoon
April 25, 2023 - Review of essential modern Python code static analysis tools.
FB
engineering.fb.com › home › pysa: an open source static analysis tool to detect and prevent security issues in python code
Pysa: An open source static analysis tool to detect and prevent security issues in Python code
October 19, 2020 - Pysa is an open source static analysis tool we’ve built to detect and prevent security and privacy issues in Python code.
Medium
camelcaseguy.medium.com › python-static-analysis-tools-fe5960d8035
Python Static Analysis tools. In a survey by stack-overflow in 2020… | by Shubhendra Singh Chauhan | Medium
June 25, 2021 - It requires your code to be annotated using Python 3 function annotation syntax (PEP484) in order to type-check the code and detect common bugs. The purpose of mypy is to combine the advantages of dynamic and static typing (using a typing module). ... Type declarations act as machine-tested documentation, and static typing makes your code clear and easy to modify without making errors. ... Prospector is a powerful static analysis tool for Python code.
Reddit
reddit.com › r/experienceddevs › python static code analysis stack?
r/ExperiencedDevs on Reddit: Python static code analysis stack?
January 17, 2024 -
I am researching standard static code analysis tooling in Python.
In the company, we mostly work in the Java ecosystem and we have a stable set of tooling that helps us meet and measure our code quality requirements: jacoco for code coverage (automated tests) measure, PMD/Spotbug/Checkstyle for code analysis, and OWASP dependency-check to check dependencies against known vulnerabilities.
We are going to work on some external code made in Python and we need to recreate a similar tool stack for it.
What would be your suggestions? Thanks in advance.
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We use mypy for type checking (worth making your mypy stricter than the default settings and enforcing type hints for every function), pylint for linting (and ruff but pylint still has more rules), black for code formatting, pytest for testing (you can check coverage with pytest-cov). This is set up with a VSCode devcontainer to give people a reproducible environment to work in and all the tests and checks are part of the CI so team members know that they need them to pass before opening a pull request. I think it works quite well and it’s fairly standard stuff for Python development.
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I work at a place with 500+ engineers working across distributed services built primary in Python. Some of the tools we use: MyPy for static typing Ruff for code formatting, standards Codecov for test coverage reports Keep in mind however that Python is an inherently dynamic language, statis analysis will only be effective if you put principles in place that 1) encourage type annotations 2) discourage usage of dynamic language features that can easily be refactored in a type-friendly manner. E.g. you'll get very little value out of static analysis when you encourage use of language features like dunder methods: class DomainAggregate: def __init__(self, data): self.data = data def __getattr__(self, field): return self.data[field] agg = DomainAggregate({name: 'John', email: 'jd@gmail.com', age: 15}) But promoting a more explicit implementation, sometimes at the cost of more boilerplate, gives you a much safer codebase in the long-run: @dataclass class DomainAggregate: name: str email: str age: int agg = DomainAggregate(name='John', email='jd@gmail.com', age=15)
Keploy
keploy.io › home › community › top tools for static analysis help in your python projects
Top Tools for Static Analysis Help in Your Python Projects | Keploy Blog
March 19, 2025 - We’ll dive into how it helps identify potential issues in your code without execution, differentiate static analysis from linters and then guide you through setting up popular Python static analysis tools like Flake8, Mypy, and Pyright within ...
Jit
jit.io › resources › appsec-tools › top-python-code-analysis-tools-to-improve-code-quality
Top 10 Python Code Analysis Tools in 2026 to Improve Code Quality
May 21, 2025 - Pyright performs static type checking by analyzing code and type annotations, providing immediate feedback on type errors. Developers benefit from improved code reliability and faster development cycles due to early error detection.
DeepSource
deepsource.com › blog › introduction-static-code-analysis
A hands-on introduction to static code analysis • DeepSource
We learn where to tap points in this pipeline to plug in our analyzers and extract meaningful information. In the latter half, we get our feet wet, and write four such static analyzers, completely from scratch, in Python.
Reddit
reddit.com › r/python › what python code analysis tools are you using?
r/Python on Reddit: What Python code analysis tools are you using?
September 14, 2022 -
I am writing a new tool to do code analysis for Python. I know about pylint, bandit and like these tools but I have been frustrated by the fact that it's hard to extend and they do not provide fixes.
I was curious to learn from the community what tool they use: what rules are the most relevant/valuable to you and what feature/rule would are useful to you.
Thanks for any idea!