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TFMongoDB is a C++ implemented dataset op for google’s tensorflow that allows you to connect to your MongoDatabase natively. Hence you can access your mongodb stored documents more efficiently.

Currently only MacOS X is supported while Tensorflow >= 1.5 is required.


Installation

In order to use the dataset you need to install it with pip:

pip install tfmongodb

Usage

TFMongoDB can be accessed through the MongoDBDataset:

dataset = MongoDBDataset(<database_name>, <collection_name>)

example:

from tfmongodb import MongoDBDataset
from tensorflow.python.framework import ops
from tensorflow.python.data.ops import iterator_ops
import tensorflow as tf

CSV_TYPES = [[""], [""], [0]]

def _parse_line(line):
    fields = tf.decode_csv(line, record_defaults=CSV_TYPES)
    return fields

dataset = MongoDBDataset("eccounting", "creditors")
dataset = dataset.map(_parse_line)
repeat_dataset2 = dataset.repeat()
batch_dataset = repeat_dataset2.batch(20)

iterator = iterator_ops.Iterator.from_structure(batch_dataset.output_types)
#init_op = iterator.make_initializer(dataset)
init_batch_op = iterator.make_initializer(batch_dataset)
get_next = iterator.get_next()


with tf.Session() as sess:
    # Basic test: read from topic 0.
    sess.run(init_batch_op, feed_dict={})

    for i in range(5):
        print(sess.run(get_next))

Release files for TFMongoDB 0.1.3

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Built distribution (wheel)

Table of built distributions (wheels) for TFMongoDB 0.1.3
File Interpreter ABI Platform
TFMongoDB-0.1.3-cp37-cp37m-macosx_10_14_x86_64.whl CPython 3.7 CPython 3.7 pymalloc macOS 10.14+ x86-64 Details

Release files / TFMongoDB-0.1.3-cp37-cp37m-macosx_10_14_x86_64.whl

Download URL TFMongoDB-0.1.3-cp37-cp37m-macosx_10_14_x86_64.whl
Size 73.5 kB
Tags CPython 3.7 CPython 3.7 pymalloc macOS 10.14+ x86-64
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