Let's make a SQL parser so we can provide a familiar interface to non-sql datastores!

Branch	Status
master
dev

SQL is a familiar language used to access databases. Although, each database vendor has its quirky implementation, the average developer does not know enough SQL to be concerned with those quirks. This familiar core SQL (lowest common denominator, if you will) is useful enough to explore data in primitive ways. It is hoped that, once programmers have reviewed a datastore with basic SQL queries, and they see the value of that data, they will be motivated to use the datastore's native query format.

The primary objective of this library is to convert some subset of SQL-92 queries to JSON-izable parse trees. A big enough subset to provide superficial data access via SQL, but not so much as we must deal with the document-relational impedance mismatch.

• No plans to provide update statements, like update or insert
• No plans to expand the language to all of SQL:2011
• No plans to provide data access tools

There are over 400 tests. This parser is good enough for basic usage, including inner queries.

You can see the parser in action at https://sql.telemetry.mozilla.org/ while using the ActiveData datasource

pip install moz-sql-parser

>>> from moz_sql_parser import parse
>>> import json
>>> json.dumps(parse("select count(1) from jobs"))
'{"select": {"value": {"count": 1}}, "from": "jobs"}'

Each SQL query is parsed to an object: Each clause is assigned to an object property of the same name.

>>> json.dumps(parse("select a as hello, b as world from jobs"))
'{"select": [{"value": "a", "name": "hello"}, {"value": "b", "name": "world"}], "from": "jobs"}'

The SELECT clause is an array of objects containing name and value properties.

See the tests directory for instructions running tests, or writing new ones.

SQL queries are translated to JSON objects: Each clause is assigned to an object property of the same name.

# SELECT * FROM dual WHERE a>b ORDER BY a+b
{
    "select": "*", 
    "from": "dual", 
    "where": {"gt": ["a", "b"]}, 
    "orderby": {"value": {"add": ["a", "b"]}}
}

Expressions are also objects, but with only one property: The name of the operation, and the value holding (an array of) parameters for that operation.

{op: parameters}

and you can see this pattern in the previous example:

{"gt": ["a","b"]}

• Uses the glorious pyparsing library (see https://github.com/pyparsing/pyparsing) to define the grammar, and define the shape of the tokens it generates.
• sqlparse does not provide a tree, rather a list of tokens.