Saving numpy array in mongodb

问题:

I have a couple of MongoDB documents wherein one my the fields is best represented as a matrix (numpy array). I would like to save this document to MongoDB, how do I do this?

{
'name' : 'subject1',
'image_name' : 'blah/foo.png',
'feature1' : np.array(...)
}

回答1:

For a 1D numpy array, you can use lists:

# serialize 1D array x
record['feature1'] = x.tolist()

# deserialize 1D array x
x = np.fromiter( record['feature1'] )

For multidimensional data, I believe you'll need to use pickle and pymongo.binary.Binary:

# serialize 2D array y
record['feature2'] = pymongo.binary.Binary( pickle.dumps( y, protocol=2) ) )

# deserialize 2D array y
y = pickle.loads( record['feature2'] )

回答2:

We've built an open source library for storing numeric data (Pandas, numpy, etc.) in MongoDB:

https://github.com/manahl/arctic

Best of all it's really easy to use, pretty fast and supports data versioning, multiple data libraries and more.

回答3:

The code pymongo.binary.Binary(...) didnt work for me, may be we need to use bson as @tcaswell suggested.

Anyway here is one solution for multi-dimensional numpy array

>>from bson.binary import Binary
>>import pickle
# convert numpy array to Binary, store record in mongodb
>>record['feature2'] = Binary(pickle.dumps(npArray, protocol=2), subtype=128 )
# get record from mongodb, convert Binary to numpy array
>> npArray = pickle.loads(record['feature2'])

Having said that, the credit goes to MongoWrapper used the code written by them.

回答4:

Have you tried Monary?

They have examples on the site

http://djcinnovations.com/index.php/archives/103

回答5:

Have you try MongoWrapper, i think it simple :

Declare connection to mongodb server and collection to save your np.

import monogowrapper as mdb
db = mdb.MongoWrapper(dbName='test',
                      collectionName='test_collection', 
                      hostname="localhost", 
                      port="27017") 
my_dict = {"name": "Important experiment", 
            "data":np.random.random((100,100))}

The dictionary's just as you'd expect it to be:

print my_dict
{'data': array([[ 0.773217,  0.517796,  0.209353, ...,  0.042116,  0.845194,
         0.733732],
       [ 0.281073,  0.182046,  0.453265, ...,  0.873993,  0.361292,
         0.551493],
       [ 0.678787,  0.650591,  0.370826, ...,  0.494303,  0.39029 ,
         0.521739],
       ..., 
       [ 0.854548,  0.075026,  0.498936, ...,  0.043457,  0.282203,
         0.359131],
       [ 0.099201,  0.211464,  0.739155, ...,  0.796278,  0.645168,
         0.975352],
       [ 0.94907 ,  0.363454,  0.912208, ...,  0.480943,  0.810243,
         0.217947]]),
 'name': 'Important experiment'}

Save data to mongo :

db.save(my_dict)

To load back data :

my_loaded_dict = db.load({"name":"Important experiment"})