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Designing a Pythonic search DSL for SQL and NoSQL databases

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I am analysing designing an abstraction layer over a select few NoSQL and SQL databases.

Specifically:

  • Redis, Neo4j, MongoDB, CouchDB
  • PostgreSQL

Being inexperienced; it is hard to know a nice way of abstracting search. For conciseness in my explanation, think of Table as being table, object, entity or key; and name as being name or type.

Maybe res = Table.name.search()

Or on multiple Table:
`res = AbstractDB().AbstractSearch(

)`

Then: res.paginate(limit=25, offset=5)

Or if you want all: res.all()

And additionally borrow/alias from a relevant subset of PEP249, e.g.: fetchone and fetchmany

Will open-source this once it's of sufficient functionality. Any suggestion

posted Jul 19, 2013 by anonymous

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1 Answer

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Before you even begin to think about "how to do this in Python", you need to think about "how to do this at all". You've got a huge range of storage paradigms there. Redis is basically a key-value store. Mongo does documents. Postgres does relations. I'm not familiar with Neo and Couch, but I assume they also have their own interesting ways of storing things.

You need to figure out what it means to abstract search over such a diverse range of technologies. I honestly don't think it's possible, but maybe you've got some good ideas. In any case, you need to figure that part out before you even begin to think about how to implement it in any particular language.

answer Jul 19, 2013 by anonymous
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