Optimize the installation speed of Python packages: use pip to speed up commands

How to use the pip acceleration command to increase the installation speed of Python packages

Introduction:
For Python developers, install and manage Python packages through pip It's a basic job. However, the process of installing Python packages may be very slow or fail due to reasons such as network limitations or resource limitations. Fortunately, we can use some tricks and commands to speed up pip installation. This article will introduce how to use the pip acceleration command to improve the installation speed of Python packages and provide specific code examples.

1. Use domestic sources
Since pip downloads Python packages from foreign mirror services by default, the download speed in China will be affected. Therefore, switching the pip source to a domestic mirror source is a common practice to speed up pip installation.

1.1 View the current pip source:
Enter the following command on the command line interface to view the current pip source:

pip config get global.index-url

1.2 Modify the pip source:
For domestic users, commonly used pip sources There are Tsinghua University mirror source and Alibaba Cloud mirror source. Through the following command, we can switch the pip source to the Tsinghua University mirror source:

pip config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple

or switch to the Alibaba Cloud mirror source:

pip config set global.index-url https://mirrors.aliyun.com/pypi/simple/

2. Use the mirror acceleration tool
In addition to switching pip Source, we can also use some third-party image acceleration tools to improve the pip installation speed, such as pipenv, cnpm, pipx, etc.

2.1 Using pipenv
pipenv is a Python project management tool that can effectively isolate the packages and running environment required by the project. By using pipenv, we can switch the pip source to a domestic mirror source and use its quick installation mechanism to speed up the download and installation of packages.

First, install pipenv via the following command:

pip install pipenv

Then, create a virtual environment and download the packages required to install the project by entering the project directory and executing the following command:

pipenv install

2.2 Use cnpm
cnpm is the Chinese image of npm, which can speed up the installation of Node.js packages. When using cnpm, we can run the following command through the terminal to install pipenv to speed up the pip installation:

cnpm install pipenv

Then, switch to cnpm to speed up the pip source through the following command:

pipenv --python <Python版本>
pipenv install

Among them, is the Python version required for the project.

2.3 Using pipx
pipx is a Python package installation tool that can install the package into a separate virtual environment and provide a script to run the package. By using pipx, we can use the following command to speed up pip installation:

pipx install pipenv

3. Use cache
Using cache can greatly improve the speed of pip installation. pip stores downloaded packages and related files in the cache directory. By default, the cache is located at ~/.cache/pip (%APPDATA%pipCache under Windows). If you install the same package again next time, pip will get it directly from the cache without re-downloading.

If you want to use caching to speed up pip installation, you can configure the pip cache directory through the following command:

pip config set global.cache-dir <缓存路径>

Among them, is the cache directory you want to set. . For example, to set the cache directory to /var/my_cache, you can use the following command:

pip config set global.cache-dir /var/my_cache

In this way, the next time you install the same package, pip will get it directly from the cache directory, Improve installation speed.

Conclusion:
By using domestic sources in pip configuration, using image acceleration tools and reasonably setting cache paths, we can effectively speed up the installation speed of pip and improve the installation efficiency of Python packages. Hope the content of this article can help you.

References:

1. pip documentation: https://pip.pypa.io/en/stable/
2. pipenv official documentation: https://pipenv .readthedocs.io/en/latest/
3. cnpm official website: https://cnpmjs.org/
4. pipx official documentation: https://pipxproject.github.io/pipx/

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