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Designing a Pythonic search DSL for SQL and NoSQL databases

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Dear Python community,

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(<attr_list with conditions>)`

Or on multiple `Table`:
`res = AbstractDB().AbstractSearch(<Table.attr_list with conditions>
<conditions> <Table.attr_list with conditions>)`

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.

What do you think?

Advice on better design; or just feedback on what I've mentioned?

Thanks,

Alec Taylor

PS: I am using Bottle. You'll note that some of the syntax I've
references is inspired from web2py's DAL and ODMG.

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Designing a Pythonic search DSL for SQL and NoSQL databases Alec Taylor <alec.taylor6@gmail.com> - 2013-07-19 22:25 +1000
  Re: Designing a Pythonic search DSL for SQL and NoSQL databases Roy Smith <roy@panix.com> - 2013-07-19 08:49 -0400
    Re: Designing a Pythonic search DSL for SQL and NoSQL databases Alec Taylor <alec.taylor6@gmail.com> - 2013-07-20 00:55 +1000

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