BlingFire VS Nightmare

Compare BlingFire vs Nightmare and see what are their differences.

BlingFire

A lightning fast Finite State machine and REgular expression manipulation library. (by microsoft)
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BlingFire Nightmare
2 8
1,781 19,511
0.3% 0.1%
3.6 1.5
6 months ago 12 days ago
C++ JavaScript
MIT License MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

BlingFire

Posts with mentions or reviews of BlingFire. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-12-27.

Nightmare

Posts with mentions or reviews of Nightmare. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-09-24.

What are some alternatives?

When comparing BlingFire and Nightmare you can also consider the following projects:

tokenizers - 💥 Fast State-of-the-Art Tokenizers optimized for Research and Production

puppeteer - Node.js API for Chrome

Mattermost - Mattermost is an open source platform for secure collaboration across the entire software development lifecycle..

nightwatch - Integrated end-to-end testing framework written in Node.js and using W3C Webdriver API. Developed at @browserstack

OpenKP - Automatically extracting keyphrases that are salient to the document meanings is an essential step to semantic document understanding. An effective keyphrase extraction (KPE) system can benefit a wide range of natural language processing and information retrieval tasks. Recent neural methods formulate the task as a document-to-keyphrase sequence-to-sequence task. These seq2seq learning models have shown promising results compared to previous KPE systems The recent progress in neural KPE is mostly observed in documents originating from the scientific domain. In real-world scenarios, most potential applications of KPE deal with diverse documents originating from sparse sources. These documents are unlikely to include the structure, prose and be as well written as scientific papers. They often include a much diverse document structure and reside in various domains whose contents target much wider audiences than scientists. To encourage the research community to develop a powerful neural m

Cypress - Fast, easy and reliable testing for anything that runs in a browser.

sgr - sgr (command line client for Splitgraph) and the splitgraph Python library

phantomjs - Scriptable Headless Browser

python-fake-data-producer-for-apache-kafka - The Python fake data producer for Apache Kafka® is a complete demo app allowing you to quickly produce JSON fake streaming datasets and push it to an Apache Kafka topic.

Playwright - Playwright is a framework for Web Testing and Automation. It allows testing Chromium, Firefox and WebKit with a single API.

fargate-game-servers - This repository contains an example solution on how to scale a fleet of game servers on AWS Fargate on Elastic Container Service and route players to game sessions using a Serverless backend. Game Server data is stored in ElastiCache Redis. All resources are deployed with Infrastructure as Code using CloudFormation, Serverless Application Model, Docker and bash/powershell scripts. By leveraging AWS Fargate for your game servers you don't need to manage the underlying virtual machines.

WebdriverIO - Next-gen browser and mobile automation test framework for Node.js