node-command-line-training
node-command-line-training
node-command-line-training
Salesforce Command Line Training Workshop at Forcelandia
node-command-line-training-add
Get the command from a shebang
Filter Cypress tests using title or tags
JavaScript parser, mangler/compressor and beautifier toolkit
Generates command-line usage information
A mature, feature-complete library to parse command-line options.
An object-oriented command-line parser for TypeScript
JavaScript parser, mangler/compressor and beautifier toolkit for ES6+
Ship compositional knowledge for AI coding agents alongside your npm packages
SVGO is a Node.js library and command-line application for optimizing vector images.
TensorFlow layers API in JavaScript
TypeScript definitions for command-line-args
UiAutomator2 integration for Appium
TypeScript definitions for command-line-usage
A global executable to run applications with the ENV variables loaded by dotenv
Cypress command for flexible test data setup
Portable Unix shell commands for Node.js
Like ruby's abbrev module, but in js
A Typescript wrapper around command-line-args with additional support for markdown usage guide generation
Node.js native addon build tool
A command line tool to check the status of a merge train in gitlab
This is a command line tool for talking to the Bolt Train JMRI JSON Server. It includes a method for installing it as a service, working in concert with the Bolt Train API server.
This gem provides a command line tool to create \*.scad and \*.stl files of Brick Train Wheels.
Simple training command line application. Increasing your arithmetical ability. If you need a feature added, send me a message on Github!
Arachni is a feature-full, modular, high-performance Ruby framework aimed towards helping penetration testers and administrators evaluate the security of web applications. It is smart, it trains itself by monitoring and learning from the web application's behavior during the scan process and is able to perform meta-analysis using a number of factors in order to correctly assess the trustworthiness of results and intelligently identify (or avoid) false-positives. Unlike other scanners, it takes into account the dynamic nature of web applications, can detect changes caused while travelling through the paths of a web application’s cyclomatic complexity and is able to adjust itself accordingly. This way, attack/input vectors that would otherwise be undetectable by non-humans can be handled seamlessly. Moreover, due to its integrated browser environment, it can also audit and inspect client-side code, as well as support highly complicated web applications which make heavy use of technologies such as JavaScript, HTML5, DOM manipulation and AJAX. Finally, it is versatile enough to cover a great deal of use cases, ranging from a simple command line scanner utility, to a global high performance grid of scanners, to a Ruby library allowing for scripted audits, to a multi-user multi-scan web collaboration platform.
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