Cypress.io
Selenium
TestMu AI (Formerly LambdaTest)
TestRail
Katalon
Playwright
Sauce Labs
BrowserStack
Matplotlib
Pandas
NumPy
Seaborn
D3.js
Plotly
GnuPlot
Jupyter
Cypress.io
MatplotlibBased on our record, Matplotlib should be more popular than Cypress.io. It has been mentiond 114 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
This is pretty cool - the Jira/Linear integration could save a ton of manual work. How do you handle test data setup and teardown? That's usually where these workflows get messy. For alternatives in this space, there's qawolf (https://qawolf.com) for similar automated testing workflows, or I'm actually building bug0 (https://bug0.com) which also does AI-powered test automation, still in beta. For the more... - Source: Hacker News / about 1 year ago
Feature: Web Accessibility Tests Feature: Web Accessibility Tests Scenario Outline: Verify all WCAG Violations Given I am on the "" page And Verify all Accessibility Violations Scenario Outline: Verify P1,P2 WCAG Violations Given I am on the "" page And Verify only P1, P2 issues Examples: | url | | https://google.com | | https://amazon.in | | https://agoda.com | |... - Source: dev.to / almost 2 years ago
In this blog post, we'll explore a Cypress test that replicates this scenario, utilizing the powerful intercept command to manipulate network requests and responses. - Source: dev.to / over 2 years ago
Maybe something like Cypress is what you're looking for? Cypress.io. Source: about 3 years ago
You won't be able to test the javascript function itself from within python, but you can exercise the front-end code using something like cypress (https://cypress.io) or the older but still respectable selenium (https://selenium.dev). Source: over 3 years ago
In February, an AI agent named MJ Rathbun submitted a pull request to matplotlib โ the Python plotting library used by half the scientific computing world. Scott Shambaugh, a volunteer maintainer, rejected it. Standard code review. Nothing unusual. - Source: dev.to / 4 months ago
Numbers are useful, but sometimes itโs easier to spot patterns when you can actually see your data. Pandas works seamlessly with Matplotlib, a popular Python library for creating visualizations. Together, they make it easy to turn raw numbers into clear charts. - Source: dev.to / 7 months ago
We are storing the results in JSON files, which we combine, analyze and visualize using matplotlib in Python. Here's the structure of a benchmark result file:. - Source: dev.to / 8 months ago
NetworkX and Matplotlib were used to visualize the graph structure of the agent. - Source: dev.to / 9 months ago
The book introduces the core libraries essential for working with data in Python: particularly IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and related packages Familiarity with Python as a language is assumed; if you need a quick introduction to the language itself, see the free companion project, Aโฆ. - Source: dev.to / 10 months ago
Selenium - Selenium automates browsers. That's it! What you do with that power is entirely up to you. Primarily, it is for automating web applications for testing purposes, but is certainly not limited to just that.
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
TestMu AI (Formerly LambdaTest) - Worldโs first full-stack Agentic AI Quality Engineering platform.
NumPy - NumPy is the fundamental package for scientific computing with Python
TestRail - TestRail provides comprehensive test case management for software testing. Organize your testing, boost productivity, get real-time insights, and track progress toward milestones. Integrates with leading issue tracking and test automation tools.
Seaborn - Seaborn is a Python data visualization library that uses Matplotlib to make statistical graphics.