navigator.mediaDevices.getUserMedia + MediaRecorder create WEBM files without duration metadata. This library appends missing metadata section right to the file blob.
Utility to fix TypeScript declarations when using default exports in CommonJS.
Implementation of Structured Field Values for HTTP (RFC9651, RFC8941)
Easy autofixable import sorting
Access deep object properties using a path
Fork of eslint rule that sorts keys in objects (https://eslint.org/docs/rules/sort-keys) with autofix enabled
Working around a Safari 14 IndexedDB bug
navigator.mediaDevices.getUserMedia + MediaRecorder create WEBM files without duration metadata. This library appends missing metadata section right to the file blob.
Shareable commitlint config enforcing conventional commits
A memoization function that uses a WeakMap
Utilities for ESLint rule fixers and suggestions. 🧑🔧
navigator.mediaDevices.getUserMedia + MediaRecorder create WEBM files without duration metadata. This library appends missing metadata section right to the file blob.
A react-native module that can listen on orientation changing of device, get current orientation, lock to preferred orientation.
The CLI tool to run `eslint --fix` for each rule
OCSP Stapling implementation
Excel Workbook Manager - Read and Write xlsx and csv Files.
Gain more control over how ESLint fixes are applied.
The missing `yarn audit fix`
Fix broken node modules with no fuss
Fix startTime for webpack watcher
Lint files staged by git
Provide eslint and prettier integration
Fixes multiple Cypress plugins subscribing to "on" events
Composable primitives for dead code elimination in Babel
Provides "let" method for memoized helper definition.
A gem to get your users' backup avatar from public resources
Fixedwidth data parsing.
Rails plugin to manage static data in ActiveRecord models/tables
A currency conversion that fetch from external source and also let's you add a fixed rate for different currencies
middleware to let you know when escaped html tags are being rendered, so you can fix them
Runs a set of "checks" against your objects and lets you know what passes and what fails. Use the report as a basis for proposing fixes to your users.
A tool to clean up your sources.list: * apt-repair-sources -d: let's you examine your current sources * apt-repair-sources -f: attempts to fix them apt-repair-sources checks the following locations: * /etc/apt/sources.list * /etc/apt/sources.list.d/*.list
I know you're always always in the middle of doing something with HTML, js and CSS, but want to use real server-side paths. I know how it bothers you to set up Apache, nginx, IIS, SOMETHING, just to see your pages and apps blossom. volna lets you run a server for a given path on a fixed port, no sweat. You're left with the clackety sound, now.
Create curses applications for the terminal easier than ever. Create panes (with the colors and(or border), manipulate the panes and add content. Dress up text (in panes or anywhere in the terminal) in bold, italic, underline, reverse color, blink and in any 256 terminal colors for foreground and background. Use a simple editor to let users edit text in panes. Left, right or center align text in panes. Cursor movement around the terminal. 6.2.0: Popup widget, emoji picker, pane color cache invalidation, stdin flush, Unicode display_width fixes.
This gem is designed to help you simplify working with views in Rails frameworks — especially for developers who have no background in frontend development but need to build an app. The initial idea was to create something similar to Elementor or WPBakery, but for Rails. I hope it’s useful. If you encounter any issues, please open a commit or let me know — I’ll do my best to fix it.
This is a ruby gem that lets you implement categorization systems with ease. Associative memory neural networks make it easy to identify probable patterns between sets of named data points. It can be cumbersome to interface with the neural network directly, however, as a typical implementation has a fixed size and training period, which limits how useful they can be to an integrated system. associative_memory simplifies these kind of machine learning models by offering dynamic input and output sets. This allows your code to concentrate on extrapolating meaningful patterns rather than juggling bitmasks and transposition matrices.
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