Un-accents and un-umlauts characters in a string. Also preliminary converts the string to lower case. We use it for autocomplete: both for the matched strings -- on the server side, when indexing; and for the strings the user types into a text input in th
TypeScript definitions for normalize-for-search
Utility for normalizing a numeric range, with a wrapping function useful for polar coordinates
Normalize slashes in a file path to be posix/unix-like forward slashes. Also condenses repeat slashes to a single slash and removes and trailing slashes, unless disabled.
Safe defaults for cssnano which require minimal configuration.
Normalizes data that can be found in package.json files.
Normalize a URL
Normalize URLs with PostCSS
TypeScript definitions for normalize-package-data
Normalize keyword values for position into length values.
Normalize unicode-range descriptors, and can convert to wildcard ranges.
Normalize multiple value display syntaxes into single values.
Convert two value syntax for repeat-style into one value.
micromark utility normalize identifiers (as found in references, definitions)
Turn any flavor of allowable package.json bin into a normalized object
modernize node.js to current ECMAScript standards
Use two values display syntax for inner and outer display types.
Trim whitespace inside and around CSS rules & declarations.
Normalize CSS animation/transition timing functions.
Normalize wrapping quotes for CSS string literals.
Color normalization for React Native.
Read a package.json file
String case utils
Return a normal number `y` and exponent `exp` satisfying `x = y * 2^exp`.
Normalized searching and browsing of public resources
An abstraction/normalization layer for querying and displaying results for external search engines, in Ruby on Rails.
Sort-order-normalize Library of Congress call numbers and determine search ranges for left-anchor search
Get normalized date values for searching, faceting and display (e.g. in Solr search engine)
A rails engine with questioning authority gem installed to serve as an authority search server with normalized results.
Encrypting a field makes it very difficult to perform a case insensitive search for the columns data. This gem normalizes the text before encrypted it and storing it in a search column. The current normalization method is to convert the text to all lowercase.
In order to have a quick access to your .log files this gem provides *nix `tail` command functionality to your Rails application. If something goes wrong you don't have to ssh to your server anymore. Now you have normal scroll and search in browser instead of `nano`, `eamacs`, `vim`, `mcedit` - name it.
Toolkit for security research manipulating Unicode: confusables, homoglyphs, hexdump, code point, UTF-8, UTF-16, UTF-32, properties, regexp search, size, grapheme, surrogates, version, ICU, CLDR, UCD, BiDi, normalization
Keep track of your devices. Features: - User registration/login/validation - User levels (normal/admin) - Checkout devices - Return devices - Assign devices to someone (Admin only) - Validate a user (Admin only) - Search devices - Keep track of number of times devices used - Manage OS versions - Send reminders when devices have been out for period of time - Password reset
Keep track of your devices. Features: - User registration/login/validation - User levels (normal/admin) - Checkout devices - Return devices - Assign devices to someone (Admin only) - Validate a user (Admin only) - Search devices - Keep track of number of times devices used - Manage OS versions - Send reminders to someone who has had a device checked out for a long time - Password reset
Our product is a full text processing pipeline from data preparation to extracting the most relevant information andanalysis utilizing precise, focused AI that has built-in human understanding. Text Analytics provides foundationallinguistic analysis for identifying languages and relating words. The result is enriched and normalized text forhigh-speed search and processing without translation.Text Analytics extracts events and entities — people, organizations, and places — from unstructured text and adds thestructure of associating those entities into events that deliver only the necessary information for near real-timedecision making. Accompanying tools shorten the process of training AI models to recognize domain-specific events.The product delivers a multitude of ways to sharpen and expand search results. Semantic similarity expands searchbeyond keywords to words with the same meaning, even in other languages. Sentiment analysis and topic extraction helpfilter results to what’s relevant.
CafePress Wrapper was built to create a portal for multiple CafePress basic stores. The intent is to create a fully fledged site where all product browsing and searching is done on the wrapper site, while shopping cart functionality and checkout is all done normally on cafepress.com The use case for which this is best used, is to combine several different basic CafePress stores. Each cafepress store containing many products, but only a single design. For example, http://rockclimbingshirts.com/ combines the following CafePress basic stores: http://www.cafepress.com/carabinerpirate http://www.cafepress.com/humancrashpad http://www.cafepress.com/midnight_lightning http://www.cafepress.com/be_safe_use_pro and http://www.cafepress.com/tightharness CafePress Wrapper is a Rails plugin distributed as a gem. Runs great on Heroku.