Consolidated waste pickup calendar
收藏data.public.lu2024-04-02 更新2025-03-26 收录
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This dataset was initiated in 2019 to introduce one of the first apps for Amazon Alexa in Luxembourg. This project aimed to release a real use-case of local services on a voice assistant platform, and we developed a waste pickup calendar. The first challenge was accessing the raw data; at that time, the only choice was to scrap it from official websites. So we developed a nodejs modular scraping tool that connects to multiple sources, which are to this day: HTML from sidec.lu using cheerio library json from valorlux.lu ICS files from vdl.lu using node-ical library When scraping is complete, the tool unifies all results into a single format, normalizes pickup types, matches against the CACLR address database and writes 1 json file per postal code in a simple format : [ { "uid": "5e8a5f0732fc6", "event_date": "1608073200000", "city": "Luxembourg", "location": "Côte d'Eich", "streetNumbers": "1-25, 2-24", "codepostal": 1450, "summary": "BULKY" }, { "uid": "5e8a5f074f2c3", "event_date": "1608505200000", "city": "Luxembourg", "location": "Côte d'Eich", "streetNumbers": "1-25, 2-24", "codepostal": 1450, "summary": "PAPER" } ] Note: The dataset does not cover the entire country (yet). Several other websites/sources should be crawled and consolidated to have a complete picture.
本数据集于2019年启动,旨在为卢森堡的Amazon Alexa引入首款应用程序之一。该项目旨在发布一个在语音助手平台上的真实应用案例,我们开发了一个垃圾回收日历。最初面临的挑战是获取原始数据;当时,唯一的选择是从官方网站上爬取。因此,我们开发了一个基于Node.js的模块化爬取工具,该工具连接到多个数据源,至今仍包括:使用cheerio库从sidec.lu获取的HTML,来自valorlux.lu的JSON数据,以及使用node-ical库从vdl.lu获取的ICS文件。爬取完成后,该工具将所有结果统一成单一格式,标准化回收类型,与CACLR地址数据库进行匹配,并为每个邮编生成一个简单的JSON文件:[ { "uid": "5e8a5f0732fc6", "event_date": "1608073200000", "city": "Luxembourg", "location": "Côte d'Eich", "streetNumbers": "1-25, 2-24", "codepostal": 1450, "summary": "BULKY" }, { "uid": "5e8a5f074f2c3", "event_date": "1608505200000", "city": "Luxembourg", "location": "Côte d'Eich", "streetNumbers": "1-25, 2-24", "codepostal": 1450, "summary": "PAPER" } ] 注:该数据集(目前)尚未覆盖整个国家。应爬取并整合多个其他网站/数据源,以获得完整的视图。
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data.public.lu



