Recommendations for seven Python code review tools

Directory 1. DeepSource
2. Codacy3. SonarQube
4. Veracode
5. Checkmarx
6. Coverity
7. CodeScene
Summary

Although Python is one of the most flexible development languages at present, developers often abuse its flexibility and even violate relevant standards. Therefore, the following common quality problems often occur in Python code:

Imported 1 unused modules Function missing arguments in various calls Missing proper format indentation Missing appropriate space before and after parentheses, square brackets or curly braces

Obviously, the above problems will not only affect the readability of the code, but also make the review of the code more complicated. To do this, we need to use PyLint or Flake8

Such static analysis tools to solve this problem and reduce various possible false positives.

At the same time, with the expansion of software development teams, many developers often need to use static code analysis tools (Static Code Analysis Tool) to help the team identify errors at various code levels and vulnerabilities on anti-patterns (anti-patterns) as early as possible in the early stage of development.

Generally speaking, static code analysis tools will analyze the target program code every time a request is submitted or extracted, and find various problems such as quality, security and style of the program code before the actual deployment and release of software products. In this article, I'll introduce you to the seven best Python code review tools for developers to make choices based on actual development projects.

1. DeepSource

DeepSource provides static code analysis for a variety of general-purpose programming languages, such as Python, Javascript, Golang, and so on. In actual use, DeepSource generates a configuration file that can be embedded in the repository for continuous analysis of the code. Because of the custom functionality provided, we can use DeepSource to easily carry out static analysis of Python code.

The main features of the DeepSource include:

Persistent analysis can be configured through a single file Support for style code typesetting tools such as Black and AutoPep8 Ability to perform quality checks on each pull request Provides automatic fixes for common problems Can be embedded in CI/CD pipes such as Travis CI to improve test coverage

Compared with various static code analysis tools, DeepSource provides a lower false alarm rate and resolution time. Because it provides access to the corresponding framework, maintainers can easily use DeepSource for application review.

In addition, in order to facilitate various operations on private repositories, DeepSource can use a dedicated token to obtain code for each pull request or commit and analyze it in an isolated environment. After the analysis is completed, it will actively clear the code base to reduce the exposure of security risks.

2. Codacy

Codacy provides code reviews for various general-purpose programming languages, such as Python, submitting reports on code coverage, repetition, and complexity. At the same time, it can help developers to carry out "pure" code review on the basis of maintaining code integrity.

The main features of the Codacy include:

Provide automation of code review Can continuously analyze the quality of code Remind developers by providing various automated resource suggestions Users can focus on emerging problems by shielding "noise" Ability to analyze individual pull requests and submissions separately

The main disadvantages are:

Unable to let developers prioritize problems found Missing the ability to export code patterns Setup and configuration pages are complicated The false alarm rate is high

3. SonarQube

SonarQube provides continuous analysis of code quality by performing automated checks. As a static code analysis tool, it can find code errors, anti-patterns, and security vulnerabilities in Python. Of course, SonarQube can easily be matched with CI/CD pipeline for effective code quality management.

SonarQube comes with two sub-tools, among which Sonar Scanner is responsible for performing analysis, and SonarQube Server is responsible for managing and saving results.

The main features of the SonarQube include:

Can identify thorny problems such as security vulnerabilities and execution path errors Automate the code review process by providing access to Webhooks (a paradigm used by microservice API) and API Quality control can be strengthened according to different requirements and practices (quality gate) By providing various plug-ins for popular IDE, the need for the overall software package is reduced

The main disadvantages are:

Lack of ability to set automatic analysis and alarm Lack of selective neglect or non-repair function for some problems Setting up SonarQube for the Python project is complicated because you need to install packages and plug-ins to set up client-side analysis and server-side storage. You can check its official documentation for more information on how to configure SonarQube for the Python project

4. Veracode

Veracode is another popular Python code review tool. It not only provides scanning for common vulnerabilities and security exposures, but also can identify and report anti-patterns and other problems through static analysis. In addition, Veracode can also provide other enterprise-class products including interactive analysis and dynamic analysis.

The main functions of Veracode include:

Simplify code quality checking by providing integration of developer tools, API and workflow Seamless integration with DevOps pipeline Its scanning based on SCA agent can be used to find various problems and vulnerabilities Its code base and license can be synchronized with PyPi (Python Package Index) After each scan, the risk rating can be forwarded

The main disadvantages are:

Lack of continuous integration setting of 1 Labor Yongyi Lack of intuitive user experience

In general, installing and setting up a scanning agent based on the Veracode agent is relatively easy. You can use Python's standard package manager, pip, to install the tool and perform code analysis. However, Veracode lacks both the ability to optimize scanning and language-specific recommendations.

5. Checkmarx

Checkmarx is a tool for applying security testing and static code analysis. It provides static application testing, runtime (runtime), interactive testing, dependency scanning and other functions, which can easily eliminate various vulnerabilities by scanning source code.

The main features of Checkmarx include:

Users can use Checkmarx SAST to conduct static analysis and find various security vulnerabilities Provides integration with the CI/CD pipeline Have an intuitive and easy-to-use user interface Provide various popular IDE plug-ins

The main disadvantages are:

The false alarm rate is high In the process of continuous integration, it takes a lot of time to scan

Objectively speaking, the advantage of Checkmarx is that it can provide native support for most general-purpose programming languages without configuration. Its disadvantages are high false alarm rate and lack of support for large code base.

6. Coverity

As a static analysis tool, Coverity aims to find and fix defects in various general programming languages (such as Python, Javascript, Ruby, Java, etc.). Star companies such as Boeing and Lockheed Martin will use Coverity to test and scan software code.

The main features of the Coverity include:

Reduce the false alarm rate by testing various possible paths to Easy to set up and customize, and can flexibly meet development requirements Provides a setup wizard to facilitate specifying the path of Python Easy integration with GitHub, Jenkins and Travis CI workflow

The main disadvantages are:

The degree of permission depends on the number of lines of code that need to be analyzed Compared with similar products on the market, its price is too high When the code base under test is huge and complex, it runs for a long time in order to meet the coverage.

7. CodeScene

CodeScene is not only a static code analysis tool, but also provides behavioral analysis to facilitate developers to identify different patterns according to the evolution of code base. Users can either invoke CodeScene through an Git service provider (such as Github or Bitbucket) or use it directly locally.

The main features of CodeScene include:

You can analyze the history of version control and produce visual effects It is convenient for developers to find various errors and problems You can use machine learning algorithms to find different patterns Code quality can be adjusted according to business requirements Not only can it ensure that the team is far away from technical risks, but it can also help identify various bottlenecks in the production environment

The main disadvantages are:

Lack of intuitive user interface It is difficult for users to follow up errors and improve code

Summary

To sum up, code review tools can help developers identify the complexity of existing code, find various problems such as anti-patterns, and security flaws, and make the process of code review and repair more efficient. Therefore, you can choose and try out according to the characteristics of the project at hand.

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