MongoAdapter — Anaconda Enterprise 4.4 documentation

Anaconda Enterprise: Documentation

# MongoAdapter

Contents

- MongoAdapter
  - Methods
  - Basic Usage

The MongoAdapter module reads data from a Mongo database collection and produces a NumPy array containing the loaded. The following features are currently implemented:

- The MongoAdapter engine is written in C to ensure data is loaded fast with minimal memory usage.
- Python slicing notation can be used to specify the subset of records to be read from the data source.
- The MongoAdapter engine has automatic type inference so the user does not have to specify dtypes of the output array.

## Methods

The MongoAdapter module contains the follwowing constructor for creating MongoAdapter objects:

MongoAdapter (host, port, database, collection)
  MongoAdapter contructor
  host - Host name where Mongo database is running.
  port - Port number where Mongo database is running.
  database - Mongo database to connect to
  collection - Mongo database collection
set_field_names (names)
  Set field names to read when creating output NumPy array.
get_field_names ()
  Returns names of fields that will be read when reading data from Mongo database.
set_field_types (types=None)
  Set NumPy dtypes for each field, specified as a dict of field names/indices and associated dtype. (Example: {0:’u4’, 1:’f8’, 2:’S10’})
get_field_types ()
  Returns dict of field names/indices and associated NumPy dtype.

The MongoAdapter object contains the following properties:

size (readonly)
  Number of documents in the Mongo database + collection specified in constructor.

## Basic Usage

1. Create MongoAdapter object for data source

       >>> import iopro
       >>> adapter = iopro.MongoAdapter('localhost', 27017, 'database_name', 'collection_name')

2. Load Mongo collection documents into NumPy array using slicing notation

       >>> # read all records for 'field0' field
       >>> array = adapter['field0'][:]

       >>> # read first ten records for 'field0' and 'field1' fields
       >>> array = adapter[['field0', 'field1']][0:10]

       >>> # read last record
       >>> array = adapter['field0'][-1]

       >>> # read every other record
       >>> array = adapter['field0'][::2]