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Rails6和deliver_later不会影响ActionMailer::Base.deliveries

Rails6是一个流行的Ruby on Rails框架的版本,而deliver_later是Rails框架中的一个方法,用于异步发送电子邮件。它不会影响ActionMailer::Base.deliveries,因为它只是将邮件发送任务放入后台队列中,而不是立即发送邮件。

具体来说,Rails6引入了Active Job框架,它提供了一种统一的方式来处理后台任务,包括异步发送电子邮件。deliver_later方法是Active Job框架提供的一个方法,它将邮件发送任务添加到后台队列中,然后由后台任务处理器异步执行。

使用deliver_later方法发送电子邮件有以下优势:

  1. 异步发送:邮件发送任务被放入后台队列中,不会阻塞当前请求的处理过程,提高了应用的响应速度。
  2. 可靠性:即使后台任务处理器出现故障或重启,邮件发送任务也不会丢失,因为它们已经被持久化到队列中。
  3. 扩展性:通过使用后台任务处理器,可以轻松地扩展邮件发送能力,处理大量的邮件发送请求。

适用场景:

  1. 需要异步发送电子邮件的应用场景,例如发送大量邮件或需要发送邮件的操作不需要立即完成的情况。
  2. 提高应用的响应速度,避免长时间等待邮件发送完成导致用户体验下降的情况。

推荐的腾讯云相关产品和产品介绍链接地址: 腾讯云提供了一系列云计算相关的产品和服务,包括云服务器、云数据库、云存储等。具体针对邮件发送的场景,可以使用腾讯云的云函数(Serverless)服务来处理后台任务,实现异步发送电子邮件的功能。

腾讯云云函数产品介绍链接地址:https://cloud.tencent.com/product/scf

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无人机应用参考文献_无人机应用论文3000字

Abstract:Energy consumption has become a crucial problem in the design of vehicle routing problems, hence the need to use another delivery method powered by batteries. Unmanned aerial vehicles have become fundamental tools in tasks for which man has limited skills that prevent a superlative optimization of time. The increasing use of drones by commercial companies such as Amazon, Google, and DHL has given birth to a new variant of vehicle routing problem (VRP) called VRP with drones (VRPD) which has a positive influence on the environment. Where vehicles and drones are used to deliver packages or goods to customers. In VRPD, vehicles and drones make dependent or independent deliveries. In the case of a dependent delivery, at a given point (customer or depot) the drone takes off from a vehicle to serve a customer and then return to travel with the same vehicle, as long as the capacity and endurance constraints for a drone are satisfied. In the other case, each type of vehicle travels independently to others. A MILP model is presented to describe the problem, and then we confirm the formulation via a CPLEX software with small instances. We propose a hybrid genetic algorithm to solve the VRPD. Experiments are carried out on the instances taken from the literature in different settings. The results show the performance of the proposed algorithm to solve this variant.

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