How to Fix the \'certificate verify failed\' Error in Python?-Python Tutorial-php.cn

Home

Backend Development

Python Tutorial

How to Fix the \'certificate verify failed\' Error in Python?

Mary-Kate Olsen

Nov 01, 2024 am 11:56 AM

How to Fix the

Fixing the "certificate verify failed" Error

When attempting to access HTTPS websites using Python, users may encounter the error "certificate verify failed: unable to get local issuer certificate." This issue arises due to the inability to verify the SSL certificate of the website.

To resolve this, users have two options:

Option 1: Install System Certificates

Running the "Install Certificates.command" command, located within the Python installation directory, installs the system's SSL certificates into the Python environment. This allows Python to access the HTTPS website by trusting the certificates provided by the system.

Option 2: Install "certifi" Package

Alternatively, users can install the "certifi" package using the following command:

pip install --upgrade certifi

This package contains a collection of SSL certificates trusted by most operating systems. By installing "certifi," Python can verify SSL certificates without relying on the system-installed certificates.

Understanding SSL and Certificates

SSL (Secure Sockets Layer) is a protocol that provides secure communication between a web browser and a website. It uses encryption to protect data during transmission over the internet.

SSL certificates are used to verify the identity of websites. They are issued by trusted certificate authorities (CAs) and contain details such as the website's domain name, organization name, and expiration date. Browsers and operating systems maintain a list of trusted CAs.

When a browser accesses a website using HTTPS, it checks the website's SSL certificate to ensure that it is valid and comes from a trusted source. If the certificate cannot be verified, the browser will display an error message and prevent access to the website.

By installing SSL certificates or using the "certifi" package, users can resolve the "certificate verify failed" error and establish a secure connection to HTTPS websites.

Resources for Learning about Security and Certificates

[Mozilla Developer Network: SSL Certificates](https://developer.mozilla.org/en-US/docs/Glossary/Certificate)
[Let's Encrypt: Certificate Transparency](https://letsencrypt.org/certificates/)
[Coursera: Cybersecurity Fundamentals](https://www.coursera.org/specializations/cybersecurity-fundamentals)

The above is the detailed content of How to Fix the \'certificate verify failed\' Error in Python?. For more information, please follow other related articles on the PHP Chinese website!

Statement

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

How to Use Python to Find the Zipf Distribution of a Text FileMar 05, 2025 am 09:58 AM

This tutorial demonstrates how to use Python to process the statistical concept of Zipf's law and demonstrates the efficiency of Python's reading and sorting large text files when processing the law. You may be wondering what the term Zipf distribution means. To understand this term, we first need to define Zipf's law. Don't worry, I'll try to simplify the instructions. Zipf's Law Zipf's law simply means: in a large natural language corpus, the most frequently occurring words appear about twice as frequently as the second frequent words, three times as the third frequent words, four times as the fourth frequent words, and so on. Let's look at an example. If you look at the Brown corpus in American English, you will notice that the most frequent word is "th

Image Filtering in PythonMar 03, 2025 am 09:44 AM

Dealing with noisy images is a common problem, especially with mobile phone or low-resolution camera photos. This tutorial explores image filtering techniques in Python using OpenCV to tackle this issue. Image Filtering: A Powerful Tool Image filter

How Do I Use Beautiful Soup to Parse HTML?Mar 10, 2025 pm 06:54 PM

This article explains how to use Beautiful Soup, a Python library, to parse HTML. It details common methods like find(), find_all(), select(), and get_text() for data extraction, handling of diverse HTML structures and errors, and alternatives (Sel

Introduction to Parallel and Concurrent Programming in PythonMar 03, 2025 am 10:32 AM

Python, a favorite for data science and processing, offers a rich ecosystem for high-performance computing. However, parallel programming in Python presents unique challenges. This tutorial explores these challenges, focusing on the Global Interprete

How to Perform Deep Learning with TensorFlow or PyTorch?Mar 10, 2025 pm 06:52 PM

This article compares TensorFlow and PyTorch for deep learning. It details the steps involved: data preparation, model building, training, evaluation, and deployment. Key differences between the frameworks, particularly regarding computational grap

How to Implement Your Own Data Structure in PythonMar 03, 2025 am 09:28 AM

This tutorial demonstrates creating a custom pipeline data structure in Python 3, leveraging classes and operator overloading for enhanced functionality. The pipeline's flexibility lies in its ability to apply a series of functions to a data set, ge

Serialization and Deserialization of Python Objects: Part 1Mar 08, 2025 am 09:39 AM

Serialization and deserialization of Python objects are key aspects of any non-trivial program. If you save something to a Python file, you do object serialization and deserialization if you read the configuration file, or if you respond to an HTTP request. In a sense, serialization and deserialization are the most boring things in the world. Who cares about all these formats and protocols? You want to persist or stream some Python objects and retrieve them in full at a later time. This is a great way to see the world on a conceptual level. However, on a practical level, the serialization scheme, format or protocol you choose may determine the speed, security, freedom of maintenance status, and other aspects of the program

Mathematical Modules in Python: StatisticsMar 09, 2025 am 11:40 AM

Python's statistics module provides powerful data statistical analysis capabilities to help us quickly understand the overall characteristics of data, such as biostatistics and business analysis. Instead of looking at data points one by one, just look at statistics such as mean or variance to discover trends and features in the original data that may be ignored, and compare large datasets more easily and effectively. This tutorial will explain how to calculate the mean and measure the degree of dispersion of the dataset. Unless otherwise stated, all functions in this module support the calculation of the mean() function instead of simply summing the average. Floating point numbers can also be used. import random import statistics from fracti

See all articles