Use Docker and Python for a MongoDB Application

Written by Data Pilot

December 12, 2019

Docker
MongoDB
Python

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Introduction

Docker is an open source platform designed principally for Windows and Linux systems. A Docker image file is used to execute code in a Docker container created from the executable version of an application. The image becomes one, or multiple, instances of that container when a user runs an image. This tutorial will cover how to use Docker and Python for a MongoDB containerized web application, specifically how to create a simple Docker container able to run a MongoDB, Python and PyMongo driver web application.

Prerequisites

Docker and Docker Compose must be installed on the machine or server with elevated admin privileges in order to use Docker and Python for a MongoDB containerized web application.

Installing Docker

Both MacOS and Windows should have interactive installers from Docker’s downloads page. Confirm whether the OS has a 32-bit or 64-bit architecture and make sure to download the correct version for the corresponding system.

Use the APT-GET repository to install Docker on Debian Linux

The following commands will install the Docker engine on a Debian-based distro of Linux that uses the APT-GET repository:

1 2	sudo apt-get update sudo apt-get install docker-engine

Execute the following service docker start command to initialize the Docker engine:

1	sudo service docker start

Verify that Docker is installed

Use the docker version and docker-compose version commands to confirm Docker was correctly installed.

Docker Compose File

A Docker Compose YAML file must be created to handle the services running on the Docker container. To make this as simple as possible, the example will use just one container, called py-mongo. This container will use Dockerfile commands to install Python, the PIP package manager for Python modules and the PyMongo client library for MongoDB.

Name the file docker-compose.yml or docker-compose.yaml and place it somewhere inside the project directory.

Set the version number for Docker Compose

Depending on the version of the Docker engine being used, downgrading the version string to 2.x may be required. The most stable and currently recommended version is 3.x, however, some older versions of Docker may not be compatible.

Execute the following code to place the Docker Compose version at the top of the YAML file:

1	version: "3.2"

Create a container for Python and MongoDB

The services key is a top-level key used in the construction of the Docker containers. When executing this command, make certain to indent the name of the container one level below services, as shown here:

1 2	services: py-mongo:

The build and context keys are required for the Dockerfile that will now be created.

Make sure to pass the relative path for the Dockerfile location. Alternatively, the . or ${PWD} (present working directory path name) commands can be used provided it is in the same directory as the following docker-compose file:

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# build the image from Dockerfile
build:
context: ${PWD}

Mount volumes for the MongoDB database data

A volume can be mounted into multiple containers. For the volumes used in this tutorial, have Docker create and bind mount the mongo-app and mongo-data folders on the local machine for the respective Python app and MongoDB database directories as follows:

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# bind mount volume for MongoDB documents
volumes:
- $PWD/mongo-data:/data/db
- $PWD/mongo-app:/var/www/html

Open a port for MongoDB

The following key and indentation will bind mount and open MongoDB’s default port of 27017 to the host machine:

1 2	ports: - "27017:27017"

MongoDB environmental variables

Execute the following commands to pass the username and password to the Docker Compose file’s environment key:

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# configure the Docker entrypoint for MongoDB
environment:
- MONGO_INITDB_ROOT_USERNAME=root
- MONGO_INITDB_ROOT_PASSWORD=1234

These files will be used later in the Python script when connecting to MongoDB. Make certain to save the file and then create another file called Dockerfile, without a file extension, and then edit the new file.

MongoDB Dockerfile

Put the following commands in the Dockerfile, making sure to save the file in the relative path specified in the above docker-compose file:

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FROM mongo:latest

# install Python 3
RUN apt-get update && apt-get install -y python3 python3-pip
RUN apt-get -y install python3.7-dev
RUN pip3 install pymongo

EXPOSE 27017

Note that the above Dockerfile commands should pull the latest MongoDB image and install Python and its PyMongo library for MongoDB.

Build the Docker container

Save the Dockerfile changes. Next, navigate to the terminal and execute the following command in the same directory where the docker-compose file is located:

1	docker-compose up --build

Note that the above command will spin up the Docker container after it is created.

Python script for MongoDB

Typing ls in the project directory should now bring up the mongo-app/ folder for the Python application. Navigate into that directory and create a Python script for the PyMongo application.

Get the container’s IP address

Use docker ps to get the ID of the running container and then use the docker inspect {CONTAINER_ID} command to obtain the IP address the container is using. This is displayed in the folloing screenshot:

Screenshot of MongoDB Python script and Docker container IP address

Connect Docker and Python to MongoDB

Put the following code into the Python file and make certain to change the IP address and MongoDB user credentials before running the script:

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#!/usr/bin/env python3
#-*- coding: utf-8 -*-

# import the MongoClient class
from pymongo import MongoClient, errors

# global variables for MongoDB host (default port is 27017)
DOMAIN = '{IP_ADDRESS_HERE}'
PORT = 27017

# use a try-except indentation to catch MongoClient() errors
try:
# try to instantiate a client instance
client = MongoClient(
host = [ str(DOMAIN) + ":" + str(PORT) ],
serverSelectionTimeoutMS = 3000, # 3 second timeout
username = "objectrocket",
password = "1234",
)

# print the version of MongoDB server if connection successful
print ("server version:", client.server_info()["version"])

# get the database_names from the MongoClient()
database_names = client.list_database_names()

except errors.ServerSelectionTimeoutError as err:
# set the client and DB name list to 'None' and `[]` if exception
client = None
database_names = []

# catch pymongo.errors.ServerSelectionTimeoutError
print ("pymongo ERROR:", err)

print ("\ndatabases:", database_names)

The above code should return all of the database names for the MongoDB server.

NOTE: Make absolutely certain to change the "objectrocket" username and password so it matches the container’s MONGO_INITDB_ROOT environment as specified in the docker-compose.yml file.

Docker container’s interactive shell

The docker exec command allows for executing terminal commands inside of the container and the -it options allows for interaction with the container itself.

The following example shows how to interactively connect to a Docker container with an ID of 0950bf7d5036:

1	docker exec -it 095 /bin/bash

Screenshot of Docker container exec interactive terminal MongoDB Python

Execute the Python script inside of the Docker container

Use cd /var/www/html to navigate to the directory storing the Python script once inside of the Docker container. Because this directory was bind mounted to the mongo-app directory, the Python script should be stored in that directory as persistent data.

Use the python3 command followed by the script name to execute the script and have MongoDB return the names of the database. Since the 27017 port was opened on the host machine, the script should be able to be executed from outside of the container. This action just requires replacing the Docker container’s IP address with localhost for the MongoClient’s host parameter. This is shown in the following screenshot:

Screenshot of interactive Docker container with exec running Python PyMongo app

Make sure to type exit to leave the container’s interactive terminal. Use the docker-compose down command in the project directory to have Docker Compose delete the container.

Conclusion

This tutorial explained how to use Docker and Python for a MongoDB containerized web application. The article specifically covered how to use Docker to create and pull MongoDB and Python images for use with the PyMongo driver using Python programming language. The tutorial also explained how to install Docker and verify the installation was successful, how to create a container for Python and MongoDB and mount volumes for the MongoDB database. The MongoDB environmental variables, the Docker container’s interactive shell and how to execute the Python script inside of the Docker container were also covered. Remember to use the docker-compose down command in the project directory to remover the container.

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