On 3/25/2017 11:40 AM, Kyle Lahnakoski wrote:
Pavel,
I like PythonQL. I perform a lot of data transformation, and often find
Python's list comprehensions too limiting; leaving me wishing for
LINQ-like language features.
As an alternative to extending Python with PythonQL, Terry Reedy
suggested interpreting a DSL string, and Pavel Velikhov alluded to using
magic method tricks found in ORM libraries. I can see how both these are
not satisfactory.
A third alternative could be to encode the query clauses as JSON
objects. For example:
PythonQL version
result = [ select (x, sum_y)
for x in range(1,8),
y in range(1,7)
where x % 2 == 0 and y % 2 != 0 and x > y
group by x
let sum_y = sum(y)
where sum_y % 2 != 0
]
Someone mentioned the problem of adding multiple new keywords. Even 1
requires a proposal to meet a high bar; I think we average less than 1
new keyword per release in the last 20 years.
Searching '\bgroup\b' just in /lib (the 3.6 stdlib on Windows) gets over
300 code hits in about 30 files. I think this makes in ineligible to
bere's match.group() accounts for many. 'select' has fair number of
code uses also. I also see 'where', 'let', and 'by' in the above.
result = pq([
{"select":["x", "sum_y"]},
{"for":{"x": range(1,8), "y": range(1,7)}},
{"where": lambda x,y: x % 2 == 0 and y % 2 != 0 and x > y},
{"groupby": "x"},
{"with":{"sum_y":{"SUM":"y"}},
{"where": {"neq":[{"mod":["sum_y", 2]}, 0]}}
])
This representation does look a little lispy, and it may resemble
PythonQL's parse tree. I think the benefits are:
1) no python language change
2) easier to parse
3) better than string-based DSL for catching syntax errors
4) {"clause": parameters} format is flexible for handling common query
patterns **
5) works in javascript too
6) easy to compose with automation (my favorite)
It is probably easy for you to see the drawbacks.
--
Terry Jan Reedy
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