Table of Contents
Visual Studio Code plug -in: Prospector code quality check tool
Provector is a powerful Python code static analysis tool collection. It improves the quality of code by running multiple code checkers and static analysis tools at one time. It integrates many commonly used tools and can easily configure and customize the needs of different projects. You can view the complete list of supporting tools.
Home Backend Development Python Tutorial Prospector on Visual Studio Code

Prospector on Visual Studio Code

Jan 30, 2025 am 02:26 AM

Visual Studio Code plug -in: Prospector code quality check tool

In order to improve the integration of Prospector and mainstream IDE, I developed a Visual Studio Code plug -in based on the VS Code Linter plug -in. Although the plug -in is not currently maintained, it provides valuable experience for the rapid construction of a new Prospector VS Code integrated plug -in.

This plug -in allows users to run the Prospector directly in VS Code, and check the code check results in the editor to use the experience smooth and seamless.

Results display:

Prospector on Visual Studio Code Plug -in has been published in the Visual Studio Code market.

Provector Introduction

Provector is a powerful Python code static analysis tool collection. It improves the quality of code by running multiple code checkers and static analysis tools at one time. It integrates many commonly used tools and can easily configure and customize the needs of different projects. You can view the complete list of supporting tools.

In the years of working in CAMPTOCAMP, we have made many improvements to the Prospector, including:

Python 3.12 Compatibility
    : Make sure that the Prospector is perfectly compatible with the latest version of Python.
  • Integrate RUFF : Integrate RUFF, a fast Python code checker to improve the inspection performance.
  • Improve BANDIT and Mypy Integration : Enhanced the integration of Bandit (safety -related static analysis tools) and Mypy (static type checking tool).
  • Support the configuration file in the pypi package

  • : Allows users to publish the Prospector configuration file as a PYPI package. Fixed
  • : Fix a variety of problems so that the tool is more reliable.
  • The latest Prospector version
  • In the latest version of Prospector, I focus on improving the integration of and IDE, especially the JSON output generated by the Prospector. These improvements enable Prospector to better interact with code editor and IDE (such as Visual Studio Code):
  • The end of the line number and characters
: This change allows the IDE to highlight the code element (such as, function or variables) that have problems with the entire problem, not just the first character. This provides a more intuitive user experience when checking the code check errors.

Document URL

: New features, provide direct links to related documents for each code checking rule. This allows developers to quickly understand and solve problems without the need to search for documents manually.

  • Other useful related packages I maintain
  • Basic Prospector configuration file
  • : A set of basic configuration files to help you configure the Prospector for the project. The PROSPECTOR configuration file used to avoid repeated messages
  • : A set of configuration files designed to prevent duplicate code checking messages, making the output more concise and easy to understand.

The above is the detailed content of Prospector on Visual Studio Code. For more information, please follow other related articles on the PHP Chinese website!

Statement of this Website
The content of this article is voluntarily contributed by netizens, and the copyright belongs to the original author. This site does not assume corresponding legal responsibility. If you find any content suspected of plagiarism or infringement, please contact admin@php.cn

Hot AI Tools

Undresser.AI Undress

Undresser.AI Undress

AI-powered app for creating realistic nude photos

AI Clothes Remover

AI Clothes Remover

Online AI tool for removing clothes from photos.

Undress AI Tool

Undress AI Tool

Undress images for free

Clothoff.io

Clothoff.io

AI clothes remover

Video Face Swap

Video Face Swap

Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Tools

Notepad++7.3.1

Notepad++7.3.1

Easy-to-use and free code editor

SublimeText3 Chinese version

SublimeText3 Chinese version

Chinese version, very easy to use

Zend Studio 13.0.1

Zend Studio 13.0.1

Powerful PHP integrated development environment

Dreamweaver CS6

Dreamweaver CS6

Visual web development tools

SublimeText3 Mac version

SublimeText3 Mac version

God-level code editing software (SublimeText3)

Hot Topics

Java Tutorial
1655
14
PHP Tutorial
1253
29
C# Tutorial
1227
24
Python vs. C  : Applications and Use Cases Compared Python vs. C : Applications and Use Cases Compared Apr 12, 2025 am 12:01 AM

Python is suitable for data science, web development and automation tasks, while C is suitable for system programming, game development and embedded systems. Python is known for its simplicity and powerful ecosystem, while C is known for its high performance and underlying control capabilities.

How Much Python Can You Learn in 2 Hours? How Much Python Can You Learn in 2 Hours? Apr 09, 2025 pm 04:33 PM

You can learn the basics of Python within two hours. 1. Learn variables and data types, 2. Master control structures such as if statements and loops, 3. Understand the definition and use of functions. These will help you start writing simple Python programs.

Python: Games, GUIs, and More Python: Games, GUIs, and More Apr 13, 2025 am 12:14 AM

Python excels in gaming and GUI development. 1) Game development uses Pygame, providing drawing, audio and other functions, which are suitable for creating 2D games. 2) GUI development can choose Tkinter or PyQt. Tkinter is simple and easy to use, PyQt has rich functions and is suitable for professional development.

The 2-Hour Python Plan: A Realistic Approach The 2-Hour Python Plan: A Realistic Approach Apr 11, 2025 am 12:04 AM

You can learn basic programming concepts and skills of Python within 2 hours. 1. Learn variables and data types, 2. Master control flow (conditional statements and loops), 3. Understand the definition and use of functions, 4. Quickly get started with Python programming through simple examples and code snippets.

Python vs. C  : Learning Curves and Ease of Use Python vs. C : Learning Curves and Ease of Use Apr 19, 2025 am 12:20 AM

Python is easier to learn and use, while C is more powerful but complex. 1. Python syntax is concise and suitable for beginners. Dynamic typing and automatic memory management make it easy to use, but may cause runtime errors. 2.C provides low-level control and advanced features, suitable for high-performance applications, but has a high learning threshold and requires manual memory and type safety management.

Python and Time: Making the Most of Your Study Time Python and Time: Making the Most of Your Study Time Apr 14, 2025 am 12:02 AM

To maximize the efficiency of learning Python in a limited time, you can use Python's datetime, time, and schedule modules. 1. The datetime module is used to record and plan learning time. 2. The time module helps to set study and rest time. 3. The schedule module automatically arranges weekly learning tasks.

Python: Exploring Its Primary Applications Python: Exploring Its Primary Applications Apr 10, 2025 am 09:41 AM

Python is widely used in the fields of web development, data science, machine learning, automation and scripting. 1) In web development, Django and Flask frameworks simplify the development process. 2) In the fields of data science and machine learning, NumPy, Pandas, Scikit-learn and TensorFlow libraries provide strong support. 3) In terms of automation and scripting, Python is suitable for tasks such as automated testing and system management.

Python: Automation, Scripting, and Task Management Python: Automation, Scripting, and Task Management Apr 16, 2025 am 12:14 AM

Python excels in automation, scripting, and task management. 1) Automation: File backup is realized through standard libraries such as os and shutil. 2) Script writing: Use the psutil library to monitor system resources. 3) Task management: Use the schedule library to schedule tasks. Python's ease of use and rich library support makes it the preferred tool in these areas.

See all articles