​
Add credentials

  1. Create a new pipeline or open an existing pipeline.
  2. Expand the left side of your screen to view the file browser.
  3. Scroll down and click on a file named io_config.yaml.
  4. Enter the following keys and values under the key named default (you can have multiple profiles, add it under whichever is relevant to you)
version: 0.1.1
default:
  # Specify either the connection string or the (host, password, user, port) to connect to MongoDB.
  MONGODB_CONNECTION_STRING: "mongodb://{username}:{password}@{host}:{port}/"
  MONGODB_HOST: host
  MONGODB_PORT: 27017
  MONGODB_USER: user
  MONGODB_PASSWORD: password
  MONGODB_DATABASE: database
  MONGODB_COLLECTION: collection

​
Using Python block

  1. Create a new pipeline or open an existing pipeline.
  2. Add a data loader, transformer, or data exporter block (the code snippet below is for a data loader).
  3. Select Generic (no template).
  4. Enter this code snippet (note: change the config_profile from default if you have a different profile):
from mage_ai.settings.repo import get_repo_path
from mage_ai.io.config import ConfigFileLoader
from mage_ai.io.mongodb import MongoDB
from os import path
if 'data_loader' not in globals():
    from mage_ai.data_preparation.decorators import data_loader
if 'test' not in globals():
    from mage_ai.data_preparation.decorators import test


@data_loader
def load_from_mongodb(*args, **kwargs):
    config_path = path.join(get_repo_path(), 'io_config.yaml')
    config_profile = 'default'

    query = {}

    return MongoDB.with_config(ConfigFileLoader(config_path, config_profile)).load(
        query=query,
        collection='collection_name',
    )
  1. Run the block.

​
Export a dataframe

Here is an example code snippet to export a dataframe to MongoDB:

from os import path

from pandas import DataFrame

from mage_ai.settings.repo import get_repo_path
from mage_ai.io.config import ConfigFileLoader
from mage_ai.io.mongodb import MongoDB

if 'data_exporter' not in globals():
    from mage_ai.data_preparation.decorators import data_exporter


@data_exporter
def export_data_to_mongodb(df: DataFrame, **kwargs) -> None:
    config_path = path.join(get_repo_path(), 'io_config.yaml')
    config_profile = 'default'

    MongoDB.with_config(ConfigFileLoader(config_path, config_profile)).export(
        df,
        collection='collection_name',
    )

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