| Name | mongoquery JSON |
| Version |
1.4.2
JSON |
| download |
| home_page | http://github.com/kapouille/mongoquery |
| Summary | A utility library that provides a MongoDB-like query language for querying python collections. It's mainly intended to parse objects structured as fundamental types in a similar fashion to what is produced by JSON or YAML parsers. |
| upload_time | 2022-05-24 12:39:12 |
| maintainer | |
| docs_url | None |
| author | Olivier Carrere |
| requires_python | |
| license | |
| keywords |
mongodb
query
match
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
|
| coveralls test coverage |
No coveralls.
|
==========
mongoquery
==========
.. image:: https://travis-ci.org/kapouille/mongoquery.svg?branch=master
:target: https://travis-ci.org/kapouille/mongoquery
A utility library that provides a `MongoDB <http://www.mongodb.org>`_-like query
language for querying python collections. It's mainly intended to parse objects
structured as fundamental types in a similar fashion to what is produced by `JSON`
or `YAML` parsers. It follows the specification of queries for MongoDB version 3.4.
-----
Usage
-----
Example:
.. code-block:: python
from mongoquery import Query, QueryError
records = [
{"a": 5, "b": 5, "c": None},
{"a": 3, "b": None, "c": 8},
{"a": None, "b": 3, "c": 9},
{"a": 1, "b": 2, "c": 3},
{"a": 2, "c": 5},
{"a": 3, "b": 2},
{"a": 4},
{"b": 2, "c": 4},
{"b": 2},
{"c": 6}
]
a_is_3 = Query({"a": 3})
# match a single object
matched = a_is_3.match(records[1])
assert matched
matched = a_is_3.match(records[0])
assert not matched
# filter elements
filtered = filter(
a_is_3.match,
records
)
assert filtered == [records[1], records[5]]
# incorrect filters raise QueryError
try:
matched = query({"$foo": 2}).match(records[1])
except QueryError:
pass # => "$foo" operator isn't supported
------------
Query syntax
------------
The syntax of queries matches closely the one of
`MongoDB queries <http://docs.mongodb.org/manual/tutorial/query-documents/>`_,
and translates it to python using the following rules:
- operators and field identifiers are expressed as strings. For instance,
the following MongoDB query:
.. code-block:: javascript
{
memos: {
$elemMatch: {
memo: 'on time',
by: 'billing'
}
}
}
Translates straightforwardly to the following Python dict:
.. code-block:: python
{
"memos": {
"$elemMatch": {
"memo": 'on time',
"by": 'billing'
}
}
}
- regular expressions are expected to be expressed as string containing
the MongoDB regular expression syntax. For instance:
.. code-block:: javascript
{description: {$regex: /^S/m}}
Translates to the following Python dict:
.. code-block:: python
{"description": {"$regex": "/^S/m"}}
- the boolean, null syntax used in MongoDB follows the JavaScript syntax.
It is expected the python equivalents are used. For instance:
.. code-block:: javascript
{a: {$exists: true}, b: null}
Translates to the following Python dict:
.. code-block:: python
{"a": {"$exists": True}, "b": None}
---------------------------------------------
Functional differences with MongoDB's queries
---------------------------------------------
There are a few features that are not supported by ``mongoquery``:
- Only the ``"/pattern/<options>"`` syntax is supported for ``$regex``. As
a consequence, ``$options`` isn't supported. Alternatively you can
compile a regex using ``re.compile`` and supply options as parameters, and pass
the ``re.Pattern`` object as the value of ``$regex``.
- ``$text`` hasn't been implemented.
- Due to the pure python nature of this library, ``$where`` isn't supported.
- The `Geospatial` operators ``$geoIntersects``, ``$geoWithin``,
``$nearSphere``, and ``$near`` are not implemented.
- Projection operators `$``, ``$elemMatch``, ``$meta``, and ``$slice`` are
not implemented (only querying is implemented)
- ``$type`` is limited to recognising generic python types, it won't look
into recognising the format of the data (for instance, it doesn't check
Object ID's format, only that they are strings)
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