Pip
In Python, pip is the default package manager for managing third-party packages, similar to npm in JavaScript projects.
Package Installation
When installing the Python environment, the pip tool is automatically installed in the operating system. You can use the pip install command to install the required third-party packages.
pip install package_name1 package_name2
It is similar to npm install package1 package2 in JavaScript projects.
If you want to install a specific version of a third-party package, you can specify it using ==, for example:
pip install requests==2.20.0
It is similar to npm install axios@0.21.1 in JavaScript projects.
The official software repository for Python is https://pypi.org.
Package Uninstallation
pip uninstall package_name
It is similar to npm uninstall package1 package2 in JavaScript projects.
Python adopts a centralized dependency management strategy by default, which means that the installed third-party packages are stored in the Python interpreter directory instead of the current project directory. Therefore, installing and uninstalling packages does not leave any traces in the project directory.
Third-party packages installed through pip install are essentially installed globally, which is quite different from JavaScript projects that store third-party packages in the node_modules directory by default.
Listing Project Dependencies
In JavaScript, the dependencies and devDependencies in package.json list the names and version numbers of third-party packages used in the project. In Python, this process does not happen automatically. We need to use the pip freeze > requirements.txt command to persist project dependencies to a file called requirements.txt, and others can automatically install all project dependencies by running pip install -r requirements.txt.
We often find many third-party packages listed in requirements.txt that are not directly used in the project. This is because it lists all the third-party packages installed under the current Python interpreter. This happens because there is only one Python environment in the system. If we want to see a clearer list of project dependencies, we need to use a virtual environment for isolation.