Blockly For Arduino 我也来整一个图形化编程软件-Arduino中文社区 - Powered by Discuz! Archiver

奈何col 发表于 2022-5-8 03:43

Blockly For Arduino 我也来整一个图形化编程软件


虽然市面上有Kittenblock、mind+、mixly等blockly编程软件,想自己改改,但也看不懂他们写的,所以最后还是自己写了个。
算是ardublockly的精神续作,参考了其的一些写法,基于最新的blockly 8(最终基于8,现在还是7),重点优化库的编写和添加,目前还在开发中,预计3个月完成,也可能烂尾。
到时候提供一套详尽的库添加说明,方便用户自己添加库。

github地址: coloz/b4a: blockly for arduino (github.com)

目前就一个人开发,这玩意儿虽然不难,但体力活多,还是要耗几个月时间的,寻赞助商ing,赞助形式可议,除logo露出外,还提供版本定制等服务。




todo list:
UI优化
傻瓜化生成库
库的编写和添加教程
常用库补充
。。。
有兴趣的可以一起来开发


Highnose 发表于 2022-5-8 09:22

我一直想知道楼主这个大神是如何修炼的:Q    给100个赞

imhm 发表于 2022-5-8 10:17

启明云端有个 8ms 平台。。应该就是基于 blockly 做的吧 。。控件很像 。。8ms试了下,貌似bug不少,还没人维护。。。

hjq9999 发表于 2022-5-8 13:13

膜拜 期待中

seesea 发表于 2022-5-8 16:51

保护头发!

tv998 发表于 2022-5-8 19:25

有个开源用易语言写的 Arduino--> AvajIDE , 你可以试试搞来修改,这玩意关键是类库例子的翻译工作量太大了。

奈何col 发表于 2022-5-8 20:32

tv998 发表于 2022-5-8 19:25
有个开源用易语言写的 Arduino--> AvajIDE , 你可以试试搞来修改,这玩意关键是类库例子的翻译工作量太大了 ...

对易语言不了解;
类库创建是我这个软件要解决的重点问题,设计了一套方案,还有待试验。

topdog 发表于 2022-5-8 23:11

支持奈何col老师的辛苦劳动,期待能够完工。

flowcode 发表于 2022-5-9 17:30

根据国内现有的基于Blockly制作的软件使用体验给你说说希望对你有所帮助.
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
1.这么大的距离稍微几个积木块就填满窗口了太占空间了.
2不要把arduino的编译器做在软件里. 维护很麻烦用户做库也不好整理.
你做的软件只做转换代码, 编译就是把内容粘贴到arduino的ide编译就行了.
3. Blockly用于设计图形库的方式一定要设计好.
4.不要改原版的Blockly重要参数, 后期Blockly官方升级插件的话直接就能用了.
5.积木块提示信息一定要充足不然不会用,最好能连接到网页. 例程一定要做到直接打开放在显眼的位置
6.uno 2560 已经用不起了.
7一定要做到专精, esp32系列个人强烈推荐
8, mixly也是做Blockly的内部的arduino做的挺好,现在很少更新arduino平台的图形库了原因主要发展MicroPython了, 所以你可以放心的发展基于arduino的esp32图形化




奈何col 发表于 2022-5-9 19:13

flowcode 发表于 2022-5-9 17:30
根据国内现有的基于Blockly制作的软件使用体验给你说说希望对你有所帮助.

1.这么大的距离稍微几个积木块 ...
1. 用的blockly自带zelos主题,makecode也是这个主题,觉得大了可以自己缩放,默认的太丑了,我个人是接受不了,可以提供一个设置项,修改成默认的;
2. 集成了arduino cli,cli会调用arduino15里的编译器,肯定不会让用户自己粘贴的,当然代码也在哪里,要自己复制下,也行;
3. 添加库是重点,主要工作是提供一套库添加方法,让用户和厂家自己添加库和例程。
4. 目前没有用到blockly的插件,这几天才开始学blockly,对插件还不了解;
5. 我只是业余做做,没有时间完善提示信息,这个等用户和厂家自己添加;
6. uno 2560用不起是啥意思,没懂;
7. 第一版支持UNO\MEGA\8266\32,如果要添加其他arduino开发板,多写个开发板引脚配置json即可,编译器是通过arduino cli调用;
8. 咨询了相关从业人员(2名培训机构的老师、5位公立学校老师 和 2个硬件厂家),得到的反馈总结如下:
(1). mind+是他们觉得做的最好的,mixly能用,但主要使用mixly主要原因是,mind+商业性太强(因为是硬件厂家出的,但他们并没有用DF硬件);
(2). mixly团队的教育背景是大多数老师选择mixly的重要原因,相比硬件厂家的软件,教师更愿意选择无商业属性的开源的软件;
(3). DF虽然贵,但硬件和软件都有品质感,有助于培训收费,反之mixly和其他硬件可能还会拉低品质感,让培训显得廉价。


另外,没做MicroPython的原因:因为makecode做的太好了,直接用makecode就行了。

没像mind+一样基于Scratch做,是因为我看不懂Scratch代码,且厂家会基于Scratch做的主要原因,是因为Scratch被禁,需要规避“Scratch”。


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查看完整版本: Blockly For Arduino 我也来整一个图形化编程软件