[HN Gopher] DocArray: a data structure for unstructured data
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       DocArray: a data structure for unstructured data
        
       Author : jonbaer
       Score  : 74 points
       Date   : 2022-10-02 17:19 UTC (3 days ago)
        
 (HTM) web link (docarray.jina.ai)
 (TXT) w3m dump (docarray.jina.ai)
        
       | fhaltmayer wrote:
       | The description of this is kind of confusing but I think the
       | easiest way to understand it is that it is a data processing
       | pipeline of sorts. Take unstructured data and apply
       | transformation and computation. A similar project to this is
       | Towhee (https://github.com/towhee-io/towhee). This project tries
       | to simplify unstructured data processing and provides pretrained
       | models and pipelines from their hub.
        
       | jbverschoor wrote:
       | > What is DocArray?
       | 
       | Still don't know what it is.
        
         | nsxwolf wrote:
         | It's a data structure for unstructured data.
        
           | BiteCode_dev wrote:
           | And it gots electrolites.
        
           | [deleted]
        
           | jbverschoor wrote:
           | But it's also like a library and like protobufs, but it's
           | named after arrays. I don't see how the format works, etc.
           | 
           | In other words, it's everything, which usually means it's
           | really bad at everything, and in reality it's nothing.
           | 
           | So again, what is it? The first screenshot is some python
           | code, and then it's talking about hugging face.
           | 
           | It'd call it 0clarityArray
        
             | nsxwolf wrote:
             | I have the same impression.
             | 
             | "If you are a deep learning engineer who works on scalable
             | deep learning services, you should use DocArray: it can be
             | the basic building block of your system."
             | 
             | I mean, wow. The basic building block of your system. The
             | very nucleus of any scalable deep learning service! But,
             | what is it?
        
       | Q6T46nT668w6i3m wrote:
       | I'm excited to look at this but the comparisons are misleading!
       | E.g., NPY has existed since 2007 (I believe it was the first
       | NumPy RFC) and is exceedingly popular; JSON can, of course,
       | represent multi-dimensional arrays (you can't get much simpler or
       | readable than [[1, 2], [3, 4]]); I also don't understand
       | "Pythonic experience" for JSON since dictionaries are so
       | ubiquitous; I could go on ...
        
       | mdaniel wrote:
       | That linked document must be written for a very specific target
       | audience because it seems to use a lot of words without providing
       | context of the problem it's solving. The example in their GH repo
       | is a little more "this does _what_? ": https://github.com/jina-
       | ai/docarray#example-1-represent-mult... although even that is a
       | little "don't worry where there seemingly random methods on
       | Document came from" which
       | https://docarray.jina.ai/api/docarray.document/#docarray.doc...
       | seems to fill in a little more
       | 
       | Then again, I guess folks were similarly confused in the past:
       | 
       | https://news.ycombinator.com/from?site=jina.ai
       | 
       | https://news.ycombinator.com/from?site=github.com/jina-ai
        
         | danbrooks wrote:
         | Thanks, the GitHub readme is much clearer.
        
         | jonbaer wrote:
         | Thanks for pointing that out, I came across it via @
         | https://qdrant.tech/documentation/install/#docarray so I was
         | not sure what other libs were integrating it
        
         | scott_s wrote:
         | I felt the same. The most important thing for a new library or
         | language to do in its introduction is to _show meaningful
         | examples_ that solve a problem in the target domain in the
         | canonical way.
        
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       (page generated 2022-10-05 23:01 UTC)