Python is one of the most popular programming languages in the world and its popularity is only growing. As a result, more and more companies are looking to hire dedicated Python developers to help them build their applications. But what tools should these developers know in order to be successful? In this article, we will discuss 10 must-know tools for Python developers in 2023. We will cover everything from web frameworks like Django and Flask, to automation tools like Ansible and Fabric, as well as other essential tools such as virtualenv and pip. With these 10 tools at your disposal, you'll be well on your way to becoming a successful Python developer.
Here are 10 popular coding tools that can be useful for Python developers:
PyCharm: PyCharm is a powerful integrated development environment (IDE) designed specifically for Python. It offers a wide range of features, such as intelligent code completion, debugging, testing, and integration with version control systems.
Jupyter Notebook: Jupyter Notebook is an open-source web application that allows users to create and share documents that contain live code, equations, visualizations, and narrative text.
Sublime Text: Sublime Text is a lightweight text editor that offers a clean and customizable interface. It is particularly popular among Python developers due to its powerful code editing features.
VS Code: Visual Studio Code (VS Code) is a popular open-source code editor that offers a wide range of features for Python development, including intelligent code completion, debugging, and Git integration.
Spyder: Spyder is another popular IDE for Python that offers a wide range of features, including a multi-language editor, an interactive console, and a variable explorer.
Pytest: Pytest is a popular testing framework for Python that makes it easy to write and run tests for your code.
Flake8: Flake8 is a Python code linter that checks your code for syntax errors, coding standards, and other issues.
Black: Black is a Python code formatter that automatically formats your code according to a set of predefined rules.
Git: Git is a powerful version control system that allows you to track changes to your code, collaborate with others, and revert to previous versions of your code if needed.
Docker: Docker is a containerization platform that allows you to package your Python code and dependencies into a single container, making it easy to deploy your code to different environments.
