Gblock VS cppq

• Spy Pixel protection
  Spy pixel tracking is a sneaky technique based on adding an invisible 1x1 image, known as a "tracking pixel," to an email. When you open the email, this pixel sends information back to the sender, revealing details like when you opened it, where you were, and what device you used. All of this is done without your knowledge or consent, making it a serious privacy concern. Gblock detects and blocks tracking pixels, providing complete protection against spy pixel tracking.
• Tracking links protection
  Link tracking involves adding custom tracking parameters to URLs, such as "?utm_source=newsletter", or embedding unique tracking codes. Some email marketing tools take this a step further by using URL shorteners to obscure the final destination, making it impossible to remove tracking parameters. Similar to spy pixels, tracking links can expose your location, device details, and other personal information. Gblock protects you from tracking links in two ways: Stripping all known tracking parameters from URLs, and using our proxy server to follow email links, masking your IP address and fully anonymizing your activity. Our proxy also caches responses, so if a tracking link is shared among multiple users, we already know the final destination and can serve it directly without accessing the tracking link. We are confident this would cover you for 99% of the cases.
• Automated tracker detection
  Other Browser extensions rely on static lists that require frequent manual updates. But as trackers constantly evolve, this outdated approach becomes less effective. Only Gblock offers a truly intelligent solution with automated tracker detection. Instead of fixed lists, our advanced system dynamically identifies and flags new trackers in real-time. The moment Gblock encounters a new tracker, it analyzes its behavior and reports it to our server—ensuring that future emails containing the same tracker are automatically blocked.

• Lightweight C++ implementation
  cppq is written in modern C++ and designed to be a minimal, efficient task queue library, making it a good fit for performance-sensitive applications where the overhead of scripting language runtimes is undesirable.
• Redis-backed reliability
  Built on top of Redis as the message broker, cppq benefits from Redis's persistence, atomic operations, and wide adoption, giving the queue system durability and the ability to survive process restarts.
• Inspired by proven design (asynq)
  The library's architecture mirrors the popular Go asynq task queue, so it inherits a well-thought-out API design for task enqueueing, retries, and worker processing patterns that have already been validated in production systems.
• Native integration for C++ projects
  For teams already working in a C++ codebase, cppq allows adding background job processing without needing to introduce a separate service written in another language (like Go or Python), simplifying the technology stack.
• Open source and inspectable
  Being open source on GitHub, developers can review the source code, modify it for custom needs, and contribute improvements, which offers transparency not available with closed-source queueing solutions.

Possible disadvantages

• Limited maturity and battle-testing
  Compared to established task queue libraries like Sidekiq, Celery, or asynq itself, cppq is a newer and smaller project with less real-world production usage, which may translate into undiscovered bugs or edge cases.
• Smaller community and ecosystem
  Because it has far fewer users and contributors than mainstream task queue systems, finding community support, third-party tutorials, or pre-built integrations is more difficult.
• Documentation gaps
  As a smaller project, cppq may have less comprehensive documentation compared to major task queue frameworks, requiring developers to read source code directly to understand advanced features or edge-case behaviors.
• C++ build and dependency complexity
  Using cppq requires managing C++ build toolchains and dependencies (such as a Redis client library), which can be more cumbersome than installing a package via pip or npm in other ecosystems.
• Fewer built-in features and tooling
  cppq likely lacks the extensive ecosystem tooling of more mature queues, such as web-based monitoring dashboards, extensive metrics/observability integrations, or advanced scheduling features found in more established solutions.

Using gBlocks® Gene Fragments as Synthetic Templates for qPCR

More videos

No cppq videos yet. You could help us improve this page by suggesting one.

• Stopping email trackers in Gmail: What Works?

  - Doesn’t leak any data to third parties I’ve been experimenting with this problem myself and I built a small extension called gblock (https://gblock.app. - Source: Hacker News / about 1 year ago

Tracking cppq since Nov 2022.