Home Development Tools VSCode A brief analysis of how to use anaconda to import python library in vscode

A brief analysis of how to use anaconda to import python library in vscode

Dec 13, 2022 pm 08:23 PM
python vscode

How to import python library in vscode? The following article will show you how to use anaconda to import the python library in vscode. I hope it will be helpful to you!

A brief analysis of how to use anaconda to import python library in vscode

#When I first started learning to write python using vscode, I encountered many problems.

This time the code needs to import numpy, pandas and other libraries. After browsing many methods on the Internet, I found what I thought was the easiest method: Use anaconda to import the library.
It also facilitates the import of other libraries in the future. [Recommended learning: vscode tutorial, Programming teaching]

Existing environment: vs code has been installed and the plug-in used to run python

Install anaconda


##Introduction to Anacond

Anaconda refers to an open source Python distribution, which includes more than 180 scientific packages such as conda and Python and their Dependencies. Because it contains a large number of scientific packages, the download file of Anaconda is relatively large (400 MB). If you only need certain packages, or need to save bandwidth or storage space, you can also use Miniconda, a smaller distribution (containing only conda and Python ).

Conda is an open source package and environment manager that can be used to install different versions of software packages and their dependencies on the same machine, and can switch between different environments

Anaconda includes Conda, Python and a lot of installed tool packages, such as: numpy, pandas, etc.

Miniconda includes Conda, Python

Anacond download and installation

Official website download address:

link

You can refer to this article to download and install. There are several points to note:

link

Test


Reference article:

link 1. Open cmd [WIN R /cmd]
Enter -conda list.
As shown in the figure below, Anaconda is installed successfully.

A brief analysis of how to use anaconda to import python library in vscode 2. Create an environment

Enter -conda create -n test python=3.8.3 pip

#Modify the Python version according to the version number, such as your python If the version is 3.7, change it to -conda create -n test python=3.7 pip

A brief analysis of how to use anaconda to import python library in vscode #You can see the Python version in the lower left corner of the vs code page

A brief analysis of how to use anaconda to import python library in vscode Proceed (y/[n])? will appear, enter y
The rest of the steps are explained clearly in the article linked above

vscode configuration environment


Problems encountered: The current code needs to import the numpy library


Solution:

1. Still click on the version number in the lower left corner of vs code , the options in the figure below will appear, select the interpreter as test: conda version

A brief analysis of how to use anaconda to import python library in vscode 2. At this time, the error is still reported when running, saying that there is no numpy library, we need to install this library
3. Open cmd, enter -conda install numpy, run it again after successfully installing the numpy library, and solve the problem
Reference article for the process of installing the library:
link

Conclusion


#1. You can use the above method to install various libraries, which is simple and convenient.

2. By learning other people’s methods and then summarizing records, I hope to be able to help others

For more relevant knowledge about VSCode, please visit:

vscode Basic Tutorial!

The above is the detailed content of A brief analysis of how to use anaconda to import python library in vscode. 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)

PHP and Python: Different Paradigms Explained PHP and Python: Different Paradigms Explained Apr 18, 2025 am 12:26 AM

PHP is mainly procedural programming, but also supports object-oriented programming (OOP); Python supports a variety of paradigms, including OOP, functional and procedural programming. PHP is suitable for web development, and Python is suitable for a variety of applications such as data analysis and machine learning.

Choosing Between PHP and Python: A Guide Choosing Between PHP and Python: A Guide Apr 18, 2025 am 12:24 AM

PHP is suitable for web development and rapid prototyping, and Python is suitable for data science and machine learning. 1.PHP is used for dynamic web development, with simple syntax and suitable for rapid development. 2. Python has concise syntax, is suitable for multiple fields, and has a strong library ecosystem.

Python vs. JavaScript: The Learning Curve and Ease of Use Python vs. JavaScript: The Learning Curve and Ease of Use Apr 16, 2025 am 12:12 AM

Python is more suitable for beginners, with a smooth learning curve and concise syntax; JavaScript is suitable for front-end development, with a steep learning curve and flexible syntax. 1. Python syntax is intuitive and suitable for data science and back-end development. 2. JavaScript is flexible and widely used in front-end and server-side programming.

PHP and Python: A Deep Dive into Their History PHP and Python: A Deep Dive into Their History Apr 18, 2025 am 12:25 AM

PHP originated in 1994 and was developed by RasmusLerdorf. It was originally used to track website visitors and gradually evolved into a server-side scripting language and was widely used in web development. Python was developed by Guidovan Rossum in the late 1980s and was first released in 1991. It emphasizes code readability and simplicity, and is suitable for scientific computing, data analysis and other fields.

How to run python with notepad How to run python with notepad Apr 16, 2025 pm 07:33 PM

Running Python code in Notepad requires the Python executable and NppExec plug-in to be installed. After installing Python and adding PATH to it, configure the command "python" and the parameter "{CURRENT_DIRECTORY}{FILE_NAME}" in the NppExec plug-in to run Python code in Notepad through the shortcut key "F6".

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.

Golang vs. Python: Performance and Scalability Golang vs. Python: Performance and Scalability Apr 19, 2025 am 12:18 AM

Golang is better than Python in terms of performance and scalability. 1) Golang's compilation-type characteristics and efficient concurrency model make it perform well in high concurrency scenarios. 2) Python, as an interpreted language, executes slowly, but can optimize performance through tools such as Cython.

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