sqlstring -- a library to build a SELECT statement
fumanchu at amor.org
Thu Oct 20 09:10:49 CEST 2005
grunar at gmail.com wrote:
> These objects (such as sqlstring.Select), represent
> complex SQL Statements, but as Python objects. The benefit is that you
> can, at run-time, "build" the statement pythonically, without
> getting bogged down in String Manipulation. The theory is that once in
> use, things that were complex (string magic) become simpler, and allow
> the program to worry about higher-level issues.
> Some of this stuff has been around for a while (using "magic" objects
> to build where clauses, etc.). But I'm trying to take it all the
> way--to a legit Select statement.
> While still in the early stages, it does work with a great many sql
> statements, as seen in the test suite. Currently supported are CASE
> statements, Nested conditional clauses, nested queries and most join
> types. At this point, I'm interested in getting feedback from the
> community on several fronts:
> 1. The Operator Overload model. I've chosen to overload Python's
> operators to give a short-hand syntax to most of the things you'd
> want to do with a select statement. The rest are accessable via
> methods. Currently ** is the "where" operator, // is the "in"
> operator, % the "like" operator and ^ aliases columns. Other
> overloads are as you'd expect- + / - * == all result in Expression
> Objects that dish out the right SQL string. The question is, is the
> "leap" in syntax to confusing? Is there a cleaner way to do this?
> (Functions for example)
The big operator question will be: how will "and" and "or" be
implemented? This is always a sticking point because of Python's
short-circuiting behaviors regarding them (the resultant bytecode will
include a JUMP).
An alternative is to stuff the representation into a string, which can
then be parsed however one likes.
For Dejavu (http://projects.amor.org/dejavu), I didn't do either
one--instead I used lambdas to express the where clause, so that:
f = logic.Expression(lambda x: ('Rick' in x.Name) or
(x.Birthdate == datetime.date(1970, 1, 1)))
units = sandbox.recall(Person, f)
might produce, in the bowels of the ORM:
"SELECT * FROM [Person] WHERE [Person].[Name] Like '%Rick%' or
[Person].[Birthdate] = #1/1/1970#"
Note that the tablename is provided in a separate step. The translation
is based on the codewalk.py and logic.py modules, which are in the
public domain if you want to use any part of them. See
> 2. How to best add further sql function support? Adding magic
> callable objects to columns came to mind, but this has it's own set
> of issues. I'm leaning towards a magic object in the sqlstring
> module. For example:
> sqlstring.F.substring(0, 4, person.first_name)
> would result in: substring(0, 4, person.first_name). the F object
> could be put in the local scope for short-hand.
This is a hard problem, since your sqlstring module doesn't control the
result sets, and so can't provide fallback mechanisms if a given
database does not support a given function (or operator, or minute
detail of how a function or operator works; for example, LIKE is
case-insensitive in MS SQL Server but case-sensitive in PostgreSQL). If
you're going to use subclasses to handle "database-specific overwrites"
(below), then you'll probably want to stick such functions in that base
class (and override them in subclasses), as well.
> 3. I'm undecided on how best to handle database specific
> overwrites. I want this to be as easy as possible. I'm thinking about
> subclassing Expressions with a naming scheme on the Sub-Class (such as
> CaseExpression_oracle). Then the __init__ factory could dish out the
> right version of the object based on the requestor. This brings up
> lots of questions, such as how to support multiple types of databases
> at the same time.
See the Adapter and SQLDecompiler classes in
http://projects.amor.org/dejavu/svn/trunk/storage/db.py (and the
store*.py modules) for some examples of using subclassing to produce
database-specific syntax. There, it's one Adapter class per supported
DB-type; you might consider keeping the Expression objects themselves
free from SQL, and transform the Expressions to SQL in a separate
class, which you could then subclass.
Just a couple of thoughts from someone who's done the
string-manipulation dance once before. ;) I must admit I've always
punted when it came time to produce complex joins or CASE
statements--Dejavu simply doesn't provide that level of expressivity,
preferring instead to hide it behind the object layer.
fumanchu at amor.org
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