Seven Python code review tools recommended

Time:2021-10-22

althoughPythonLanguage is one of the most flexible development languages at present, but developers often abuse its flexibility and even violate relevant standards. So PythoncodeThe following common quality problems often occur:

  • Some unused modules have been imported
  • Function is missing arguments in various calls
  • The appropriate format indentation is missing
  • Missing appropriate spaces before and after parentheses, square brackets, or braces

Obviously, the above problems will not only affect the readability of the code, but also make the code more readableexaminationThe work becomes more complex. To do this, we need to pass such as 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 the software development team, many developers often need to use the static code analysis tool to help the team identify various code level errors and anti patterns as soon as possible in the early stage of development.

Generally speaking, the static code analysis tool will analyze the target program code every time a request is submitted or extracted, and find various problems in the quality, security, style and other aspects of the program code before the actual deployment and release of the software product. In this article, I will introduce you to the seven best Python code review tools for developers, so that you can make a choice according to the actual development project.

1. DeepSource

Deepsource provides static code analysis for various general-purpose programming languages (such as python, JavaScript, golang, etc.). In practical use, deepsource will generate a configuration file that can be embedded in the repository for continuous analysis of the code. Due to the custom function, we can use deepsource to easily carry out static analysis of Python code.

The main functions of deepsource include:

  • Continuous analysis can be performed through a single file configuration
  • Support style code typesetting tools such as black and autopep8
  • Ability to perform quality checks on each pull request
  • Provides automatic repair of common problems
  • It can be embedded in CI / CD pipes such as Travis Ci to improve test coverage

Compared with other static code analysis tools, deepsource provides lower false positive rate and solution time. Since access to the corresponding framework is provided, maintenance personnel can easily use deepsource for application review.

In addition, in order to facilitate various operations on the private repository, deepsource can use a special token to obtain the code for each pull request or submission, 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 can provide code review for various general-purpose programming languages (such as Python) and submit reports on code coverage, repetition rate and complexity. At the same time, it can help developers carry out “pure” code review on the basis of maintaining code integrity.

The main functions of codacy include:

  • Provide automation of code review
  • You can continuously analyze the quality of your code
  • Remind developers by providing various automated resource suggestions
  • By shielding “noise”, users can focus on emerging problems
  • Each pull request and submission can be analyzed separately

The main disadvantages are:

  • It is not possible for developers to prioritize the problems found
  • Lack of functionality to export code patterns
  • The setup and configuration pages are complex
  • High false positive rate

3. SonarQube

Sonarqube provides continuous analysis of code quality by performing automatic checks. As a static code analysis tool, it can find code errors, anti patterns, and security vulnerabilities in Python. Of course, sonarqube is also easy to match with CI / CD pipeline for effective code quality management.

Sonarqube comes with two sub tools, in which sonar scanner is responsible for performing analysis and sonarqube server is responsible for managing and saving the results.

The main functions of sonarqube include:

  • It 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 APIs) and APIs
  • The quality gate can be strengthened according to different requirements and practices
  • By providing various popular ide plug-ins, the demand for the overall software package is reduced

The main disadvantages are:

  • Lack of ability to set up automatic analysis and alerts
  • Lack of selective ignore or no repair function for some problems
  • Since it is necessary to install software packages and plug-ins to set up client-side analysis and server-side storage, it is complex to set up sonarqube for Python projects. You can check its official documentation to learn more about how to configure sonarqube for Python projects

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 through static analysis. In addition, veracode can provide other enterprise products including interactive analysis and dynamic analysis.

The main functions of veracode include:

  • By providing the integration of developer tools, APIs and workflows, it can simplify the inspection of code quality
  • Seamless integration with Devops pipes
  • Its scan 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)
  • The risk rating can be forwarded after each scan

The main disadvantages are:

  • Lack of continuous integration settings once and for all
  • Lack of intuitive user experience

In general, it is relatively easy to install and set up a veracode agent-based scanning agent. 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, interactive testing, dependency scanning and other functions, which can easily eliminate various vulnerabilities by scanning the source code.

The main functions of checkmarx include:

  • Users can use checkmarx SAST to conduct static analysis and find various security vulnerabilities
  • Provides integration with CI / CD pipes
  • Intuitive and easy-to-use user interface
  • Provide various popular ide plug-ins

The main disadvantages are:

  • High false positive rate
  • 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 positive 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-purpose 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 functions of coverage include:

  • The false positive rate is reduced by testing various possible paths
  • It is easy to set and customize, and can flexibly meet the development needs
  • Provides a setup wizard to facilitate specifying Python paths
  • Easily integrate with workflow such as GitHub, Jenkins and Travis Ci

The main disadvantages are:

  • The degree of license depends on the number of lines of code that need to be analyzed
  • Compared with similar products in the market, its price is too high
  • When the tested code base is large and complex, its running time is long in order to meet the coverage.

7. CodeScene

Codescene is not only a static code analysis tool, but also can provide behavior analysis to facilitate developers to identify different patterns according to the evolution of the code base. Users can call codescene through git service providers (such as GitHub or bitbucket) or directly use it locally.

The main functions of codescene include:

  • It can analyze the history of version control and produce visual effects
  • It can facilitate developers to find various errors and problems
  • Machine learning algorithms can be used to find different patterns
  • Code quality can be adjusted according to business requirements
  • It not only ensures that the team is away from technical risks, but also helps identify 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 codes

Summary

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

The above is the details of the recommendations of the seven Python code review tools. For more information about the recommendations of Python code review tools, please pay attention to other relevant articles of developeppaper!