MongoDB Data Object Layer.

Tools to create data abstractions over mongoDB data.

To install: pip install mongodol

And of course, you need to install MongoDB

from mongodol import MongoClientReader, MongoDbReader, MongoCollectionReaderBase, MongoCollectionReader, MongoCollectionPersister

MongoClientReader gives you access to the databases for a mongoDB host (default is localhost). The keys are database names...

client = MongoClientReader()
list(client)

['admin', 'config', 'local', 'py2store', 'py2store_tests', 'yf']

... and the values are db objects. The keys of db objects are collection names...

db = client['py2store']
list(db)

['tmp', 'test', 'annots_example']

... and the values are collection objects.

mgc = db['test']
len(mgc)

0

The collection is empty. Let's get a collection object that we can actually write with.

Here, we show how you can write by appending data:

writable_mgc = MongoCollectionPersister(mgc)
writable_mgc.append({'mongo': 'uses', 'json': 'data'})

<pymongo.results.InsertOneResult at 0x1203f9940>

See that we have data in the collection now:

keys = list(mgc)
keys

[{'_id': ObjectId('60359a2993b7670664918663')}]

But that's just showing the key, let's see the value under that key:

k = keys[0]
mgc[k]

<pymongo.cursor.Cursor at 0x120fc1be0>

Oh... you get a cursor back. It's okay, a cursor is the object that will provide you with the data you requested if and when you want it.

Let's say you want it now. Just "consume" the cursor. If you're expecting just one item under that key, do this:

v = next(mgc[k], None)  # the None is there as a sentinel -- it will be used to indicate if mgc[k] has no data for you.
v

{'mongo': 'uses', 'json': 'data'}

So indeed it worked.

You can also use extend to write in bulk.

writable_mgc.extend([{'kind': 'example', 'data': 2}, 
                     {'kind': 'example', 'data': [1, 2, 3]},
                     {'kind': 'example', 'data': {'nested': 'dict'}}
                    ])

<pymongo.results.InsertManyResult at 0x11e520200>

list(mgc)

[{'_id': ObjectId('60359a2993b7670664918663')},
 {'_id': ObjectId('60359ac193b7670664918664')},
 {'_id': ObjectId('60359ac193b7670664918665')},
 {'_id': ObjectId('60359ac193b7670664918666')}]

So far, MongoDB gave us an id. MongoDB will make it's own id if we don't ask for a particular one.

But you can also write data to a key of your choice. With the base persister which we're demoing now, with it's base defaults, you need to specify your key as a {'_id': YOUR_CHOICE_OF_ID}.

writable_mgc[{'_id': 'my_id'}] = {'my': 'data'}
list(mgc)

[{'_id': ObjectId('60359a2993b7670664918663')},
 {'_id': ObjectId('60359ac193b7670664918664')},
 {'_id': ObjectId('60359ac193b7670664918665')},
 {'_id': ObjectId('60359ac193b7670664918666')},
 {'_id': 'my_id'}]

mgc[{'_id': 'my_id'}]

{'my': 'data'}

You can delete data given a key:

del writable_mgc[{'_id': 'my_id'}]

list(mgc)

[{'_id': ObjectId('60359a2993b7670664918663')},
 {'_id': ObjectId('60359ac193b7670664918664')},
 {'_id': ObjectId('60359ac193b7670664918665')},
 {'_id': ObjectId('60359ac193b7670664918666')}]

So far, we've seen the base classes.

So far, you have no reason what-so-ever to use mongodol. Might as well use pymongo (which it wraps) directly.

The real reason for using mongodol is that it is a gateway to enabling all the py2store goodies to create the key-value perspectives that make sense to you, without all the backend-dependent boilerplate over the business logic.

So let's show one example of how to do that.

Let's say we have the collection we just made above, but

• We want to access data by doing s['60359a2993b7670664918663'] instead of the (annoying) s[{'_id': ObjectId('60359a2993b7670664918663')}]
• We'd like our values to to come in the form of actual ready to use data. Namely, we want to automatically ask the cursor for it's first element (assuming it's unique for that key), and we'd like to extract the 'data' field from that result.
• We'd like to peruse only part of the mongo collection; only if there's a 'kind' field and it's equal to 'example'.

Here's how it can be done:

from bson import ObjectId
from py2store import wrap_kvs
from mongodol import MongoCollectionReaderBase

@wrap_kvs(id_of_key=lambda x: {'_id': ObjectId(x)}, 
          key_of_id=lambda x: str(x['_id']), 
          obj_of_data=lambda doc: next(doc, None)['data'])
class MyStore(MongoCollectionReaderBase):
    """my special store"""

s = MyStore(mgc=mgc, 
            key_fields=('_id',), 
            data_fields=('data',), 
            filt={'kind': 'example'})

list(s)

['60359ac193b7670664918664',
 '60359ac193b7670664918665',
 '60359ac193b7670664918666']

s['60359ac193b7670664918664']

2

list(s.values())

[2, [1, 2, 3], {'nested': 'dict'}]