Because json-based queries are not for humans.

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• A parse(query) function that can be used to parse SQL queries and return objects that can then be used to perform actual queries.

  For complete SQL commands, a DatabaseOperation object will be returned. This object has an apply(db) name to apply the query on a database object (MongoClient instance).

  For SELECTs, a .query attribute is available, containing the query that would be executed on MongoDB (try parse('SELECT * FROM mytable WHERE one == "foo" and two == "bar"').query.to_mongo())

• A MongoSqlClient, that can be used as a normal MongoClient (from which inherits), the only difference being returned databases has a .sql(query) method, allowing to run SQL queries directly.

First, prepare a database with some data:

from mongosql import MongoSqlClient

conn = MongoSqlClient('mongodb://localhost:27017')
db = conn.testdb

for item in 'World Spam Eggs Bacon Spam Spam Spam'.split():
	db.mycollection.save({'hello': 'Hello, {0}'.format(item)})

Then, we'll create a query:

>>> list(db.sql('SELECT * FROM mycollection'))

[{u'_id': ObjectId('00112233445566778899AA00'), u'hello': u'Hello, World'},
{u'_id': ObjectId('00112233445566778899AA01'), u'hello': u'Hello, Spam'},
{u'_id': ObjectId('00112233445566778899AA02'), u'hello': u'Hello, Eggs'},
{u'_id': ObjectId('00112233445566778899AA03'), u'hello': u'Hello, Bacon'},
{u'_id': ObjectId('00112233445566778899AA04'), u'hello': u'Hello, Spam'},
{u'_id': ObjectId('00112233445566778899AA05'), u'hello': u'Hello, Spam'},
{u'_id': ObjectId('00112233445566778899AA06'), u'hello': u'Hello, Spam'}]

..yay! It worked!

Let's try with something more complex:

>>> list(db.sql('SELECT * FROM mycollection WHERE hello == "Hello, World"'))

[{u'_id': ObjectId('00112233445566778899AA00'), u'hello': u'Hello, World'}]

SELECT field, field1, field2
FROM mycollection
WHERE field == 'value'
LIMIT 100 SKIP 20
SORT field1 ASC, field2 DESC

Becomes:

db['mycollection'].find(
	{'field': 'value'},
	fields=['field', 'field1', 'field2'],
	limit=100,
	skip=20,
	sort={'field1': 1, 'field2': -1})

(Only projections supported at the moment, more coming soon)

AGGREGATE article
PROJECT title = 1,
        stats = {
            pv = '$pageViews',
            foo = '$other.foo',
            dpv = '$pageViews' + 10,
        }

Becomes:

db.article.aggregate([
    {'$project': {
        'title': 1,
        'stats': {
            'pv': "$pageViews",
            'foo': "$other.foo",
            'dpv': {'$add': ["$pageViews", 10]}
        },
    }}
])

The reasons behind this project are:

• Many times I need to run test queries on a MongoDB server, eg. to see the status of the stored data, often with some aggregations / "GROUP BY". And I hate having to write JSON inline in the CLI, with all the (un)readability problems..

• In any case, I find that JSON queries tend to become unreadable quite soon, even in program code.

  And I hate writing things like: {'$and': [cond1, cond2, ...]}.

  And I think that polish notation tends to become hard to follow quickly: compare, for example, (5 - 6) * 7 with * - 5 6 7 (polish notation), (* (- 5 6) 7) (lisp) or, worse of them all, the mongodb way: {'$multiply': [{'$subtract': [5, 6]}, 7]}...

The goal of this project is not to use MongoDB as a drop-in, web-scale replacement for MySQL, to make your cats blog run the speed of light!