Python控制台提示工具:promptly的样式定制与更新

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资源摘要信息:"promptly:Python 控制台提示工具" 知识点: 1. Python 控制台提示工具:Promptly 是一个设计用来增强Python命令行交互体验的库。它允许开发者创建具有良好用户界面的命令行应用程序。通过使用Promptly,开发者可以构建出包含多种输入类型和样式的命令行界面,并且用户可以通过CSS来定制提示符的外观。 2. 可定制的样式:Promptly 提供的功能之一就是支持CSS样式设置,意味着用户可以对控制台提示进行视觉上的定制,使其更加符合应用程序的风格和用户的个性化需求。这包括改变提示符的颜色、字体、背景等,从而提升用户体验。 3. 支持的Python版本:Promptly 至少从版本0.6.1开始兼容Python 3.4。这意味着它支持现代Python的所有重要特性,并且与较新的Python版本保持兼容。开发者可以放心使用该工具,不必担心版本兼容性问题。 4. Travis测试集成:版本v0.6.1中为Python 3.4加入了travis测试,这表明Promptly的开发团队注重代码质量和稳定性。通过持续集成测试,可以确保提交的代码不会破坏现有的功能,同时能及时发现并修复可能出现的问题。 5. 输入处理:Promptly 提供了对输入的高级处理功能,包括能够处理重复键的输入并返回列表。这意味着当用户在命令行中输入数据时,如果输入了重复的数据项,Promptly可以将这些数据项组织成列表形式返回,从而方便开发者进行后续处理。 6. Form 类的使用:通过Promptly提供的Form类,开发者可以轻松创建表单,并通过add方法添加不同类型的数据字段,如字符串(string)和整数(int)等。这为收集和验证用户输入提供了一种结构化的方式。 7. 数据字段类型:Promptly支持多种类型的数据字段,用户可以添加不同类型的输入字段,如字符串和整数。这种灵活性使得Promptly能够适应各种不同的用户输入场景。 8. 默认值设置:在添加输入字段时,开发者可以为各个字段指定默认值,这样在用户没有输入的情况下,系统会自动采用预设的默认值。这个特性使得表单的数据收集变得更加灵活和健壮。 9. 文件名:该资源文件的压缩包名称为"promptly-master",表明这是一个主要版本的代码仓库的主干,通常包含了最新的开发版本代码。 总结:Promptly是一个非常实用的Python库,它通过增加样式和输入处理的灵活性,大大提升了Python命令行应用程序的开发效率和用户体验。随着Python版本的更新和测试的完善,Promptly正在不断进化,以适应更多样化的开发需求。
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With the rapid development of China's economy, the per capita share of cars has rapidly increased, bringing great convenience to people's lives. However, with it came a huge number of traffic accidents. A statistical data from Europe shows that if a warning can be issued to drivers 0.5 seconds before an accident occurs, 70% of traffic accidents can be avoided. Therefore, it is particularly important to promptly remind drivers of potential dangers to prevent traffic accidents from occurring. The purpose of this question is to construct a machine vision based driving assistance system based on machine vision, providing driving assistance for drivers during daytime driving. The main function of the system is to achieve visual recognition of pedestrians and traffic signs, estimate the distance from the vehicle in front, and issue a warning to the driver when needed. This driving assistance system can effectively reduce the probability of traffic accidents and ensure the safety of drivers' lives and property. The main research content of this article includes the following aspects: 1. Implement object detection based on the YOLOv5 model. Conduct research on convolutional neural networks and YOLOv5 algorithm, and develop an object detection algorithm based on YOLO5. Detect the algorithm through road images, and analyze the target detection algorithm based on the data returned after training. 2. Estimate the distance from the front vehicle based on a monocular camera. Study the principle of estimating distance with a monocular camera, combined with parameters fed back by object detection algorithms, to achieve distance estimation for vehicles ahead. Finally, the distance estimation function was tested and the error in the system's distance estimation was analyzed. 3. Design and implementation of a driving assistance system. Based on the results of two parts: target detection and distance estimation, an intelligent driving assistance system is constructed. The system is tested through actual road images, and the operational effectiveness of the intelligent driving assistance system is analyzed. Finally, the driving assistance system is analyzed and summarized.

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