easygen VS go-baseutils

there are lots of other transformation support function already builtin inside easygen, check out the full list with sample usage and results here.

The problem of both jq or jp is that although they can do data projection in any direction (doing data filtering in any way), their purpose are still focusing on data transformation, but when talking about rendering json data into a format more presentable to human beings, then there is no better tools than easygen. In fact, the easygen is a universal code/text generator that not only works on json data but it can take in data defined in YAML format as well. It can be used as any text (or html, or any other forms) generator for arbitrary purposes with arbitrary data and templates. It is built on top of the powerful Go template engine.

In this article, we'll first look at those few more boilerplates that enable you to only write the above few lines and everything will work out magically. Then we'll move on to how to make things even simpler, with the help of easygen.

There are a few more boilerplates that need to be in place so that you can only write the above few lines and everything will work out magically, which will be covered in next article, with the help of easygen.

Best practices for channel in concurrency, including fan_in,fan_out,map_reduce,or_done,orderly,pipeline,stream,generic version can be found at https://github.com/songzhibin97/go-baseutils/tree/main/app/bconcurrent

Cache-related components > buffer & mbuffer provide similar functionality, buffer has more encapsulation and implements some of the io interfaces, while mbuffer is just a memory cache. > local_cache provides a local data cache, and also has some expiry mechanisms, you can set the expiry time, and regularly clean up the expired data, but he is now older, if needed there is a generic version https://github.com/songzhibin97/go-baseutils/blob/main/ app/bcache > singleflight wraps golang.org/x/sync/singleflight to prevent the impact of changes