Use the pip command to quickly manage dependent libraries of Python projects

Quick Start: Use the pip command to manage Python project dependent libraries

Introduction:
When developing Python projects, we often use various third-party libraries to Assist with code development. To manage these dependent libraries, pip is a very convenient and commonly used tool. This article will introduce how to use the pip command to manage the dependent libraries of Python projects and provide specific code examples.

1. Introduction to pip
Pip is a third-party package management system for Python, which provides operations such as installation, uninstallation, and update of Python packages. It comes with Python version 2.7.9 and later, so in most cases we do not need to perform additional installation.

2. Install dependency packages
In Python projects, we usually use some third-party libraries to provide additional functions. It is very simple to install these dependent libraries using pip. You only need to run the following instructions on the command line:

pip install package_name

where package_name is the name of the third-party library to be installed.

For example, assuming we want to install pandas, a library used for data analysis, we only need to run the following command:

pip install pandas

3. Upgrade dependency packages
Sometimes, we need to update Existing dependency package versions to obtain the latest features or fix bugs. Upgrading dependent packages using pip is also very simple. You only need to run the following command:

pip install --upgrade package_name

Among them, package_name is the name of the dependent library to be upgraded.

For example, we want to upgrade the previously installed pandas library to the latest version:

pip install --upgrade pandas

4. View the installed dependency packages
If you want to view the installed dependency packages in the current environment and its version, you can use the following command:

pip list

This command will list the names and version numbers of all installed dependent packages in the current environment.

5. Uninstall dependency packages
In some cases, we may need to uninstall an installed dependency package. You can use the following command to uninstall:

pip uninstall package_name

where package_name is the name of the dependent library to be uninstalled.

For example, we want to uninstall the previously installed pandas library:

pip uninstall pandas

6. Use the requirements.txt file to manage dependency packages
In actual project development, we usually put all Dependent libraries and their version numbers are recorded in a file named requirements.txt to facilitate management. Use pip to install dependent libraries in batches based on this file.

First, we need to create a requirements.txt file to record the project's dependent libraries and their versions. The format is as follows:

package_name==version

For example, create a requirements.txt file with the following content:

pandas==1.2.3
numpy==1.21.0
matplotlib==3.4.3

Then, run the following command in the command line to batch install the dependent libraries listed in the requirements.txt file:

pip install -r requirements.txt

7. Use the virtual environment
The virtual environment is A tool created to resolve dependency conflicts between Python projects. You can use virtualenv or venv to create a virtual environment and independently manage the project's dependency libraries in the virtual environment.

First, use the following instructions to create a virtual environment:

python -m venv myenv

Among them, myenv is the name of the virtual environment, which can be defined according to the actual situation.

Next, activate the virtual environment and use the following command:

source myenv/bin/activate    # Linux/MacOS
myenvScriptsctivate    # Windows

After activating the virtual environment, all pip commands will run in the virtual environment.

The instructions for using pip to install, upgrade, and uninstall dependent packages are the same as those introduced previously, and you can just run them in a virtual environment.

8. Summary
This article introduces how to use pip instructions to manage dependency libraries of Python projects, including installing dependency packages, upgrading dependency packages, viewing installed dependency packages, uninstalling dependency packages, and using requirements. txt file to manage dependency packages and use virtual environments to manage dependency libraries of projects. By mastering these basic operations, you can better manage and maintain the dependencies of Python projects and improve development efficiency.

Reference materials:

1. pip documentation: https://pip.pypa.io/en/stable/
2. virtualenv documentation: https://virtualenv. pypa.io/en/stable/
3. venv documentation: https://docs.python.org/3/library/venv.html

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