You can get started with MongoDB and your favorite programming language by leveraging one of its drivers, many of which are maintained by MongoDB engineers, and others which are maintained by members of the community. MongoDB has a native Python driver, PyMongo, and a team of Driver engineers dedicated to making the driver fit to the Python community’s needs.
In this article, which is aimed at Python developers who are new to MongoDB, you will do the following:
- Install PyMongo, the Python Driver
- Connect to MongoDB
- Explore MongoDB Collections and Documents
- Perform basic Create, Retrieve, Update and Delete (CRUD) operations using PyMongo
Install the Python Driver
For this article we will install the Python driver called, pymongo.
Although there are other drivers written by the community, pymongo is the official Python driver for MongoDB.
The easiest way to install the driver is through the pip package management system. Execute the following on a command line:
python -m pip install pymongo
from pymongo import MongoClient
# pprint library is used to make the output look more pretty
from pprint import pprint
connect to MongoDB, change the << MONGODB URL >> to reflect your own connection string
client = MongoClient(<<MONGODB URL>>)
db=client.admin
# Issue the serverStatus command and print the results
serverStatusResult=db.command("serverStatus")
pprint(serverStatusResult)
Now run this file from the command line with:
python mongodbtest.py
Note that the u character comes from the Python output and it means that the strings are stored in unicode. This example also uses the pprint library which is not related to MongoDB but is used here only to make the output structured and visually appealing from a console. Learn more skills from MongoDB Training
In this example we are connecting to our MongoDB instance and issuing the “db.serverStatus()” command. This command returns information about our MongoDB instance and is used in this example as a way to execute a command against MongoDB.
If your application runs successfully, you are ready to continue.
Exploring Collections and Documents
MongoDB stores data in documents. Documents are not like Microsoft Word or Adode PDF documents but rather JSON documents based on the JSON specification.
Notice that documents are not just key/value pairs but can include arrays and subdocuments. The data itself can be different data types like geospatial, decimal, and ISODate to name a few. Internally MongoDB stores a binary representation of JSON known as BSON. This allows MongoDB to provide data types like decimal that are not defined in the JSON specification
A collection in MongoDB is a container for documents. A database is the container for collections. This grouping is similar to relational databases.
Performing CRUD Operations Using PyMongo
To establish a connection to MongoDB with PyMongo you use the MongoClient class.
frompymongoimportMongoClient
client = MongoClient('<<MongoDB URL>>')
The <<MongoDB URL>> is a placeholder for the connection string to MongoDB. See the connection string documentation for detailed information on how to create your MongoDB connection string. If you are using Atlas for your MongoDB database, refer to the “testing your connection” section for more information on obtaining the connection string for MongoDB Atlas. For more info MongoDB Online Training
We can now create a database object referencing a new database, called “business”, as follows:
db = client.business
Once we create this object we can perform our CRUD operations. Since we want something useful to query let’s start by building a sample data generator application.
Generating a Sample Data Code Example
Create a new file called createsamples.py using your development tool or command line text editor and copy the following code:
from pymongo import MongoClient
from random import randint
#Step 1: Connect to MongoDB - Note: Change connection string as needed
client = MongoClient(port=27017)
db=client.business
#Step 2: Create sample data
names = ['Kitchen','Animal','State', 'Tastey', 'Big','City','Fish', 'Pizza','Goat', 'Salty','Sandwich','Lazy', 'Fun']
company_type = ['LLC','Inc','Company','Corporation']
company_cuisine = ['Pizza', 'Bar Food', 'Fast Food', 'Italian', 'Mexican', 'American', 'Sushi Bar', 'Vegetarian']
for x in xrange(1, 501):
business = {
'name' : names[randint(0, (len(names)-1))] + ' ' + names[randint(0, (len(names)-1))] + ' ' + company_type[randint(0, (len(company_type)-1))],
'rating' : randint(1, 5),
'cuisine' : company_cuisine[randint(0, (len(company_cuisine)-1))]
}
#Step 3: Insert business object directly into MongoDB via isnert_one
result=db.reviews.insert_one(business)
#Step 4: Print to the console the ObjectID of the new document
print('Created {0} of 100 as {1}'.format(x,result.inserted_id))
#Step 5: Tell us that you are done
print('finished creating 100 business reviews')
Be sure to change the MongoDB client connection URL to one that points to your MongoDB database instance. Once you run this application, 500 randomly named businesses with their corresponding ratings will be created in the MongoDB database called, “business”. All of these businesses are created in a single collection called, “reviews”. Notice that we do not have to explicitly create a database beforehand in order to use it. This is different from other databases that requires statements like, “CREATE DATABASE” to be performed first.
The command that inserts data into MongoDB in this example is the insert_one() function, which will insert one document into MongoDB. The result set will return the single ObjectID that was created. This is one of a few methods that insert data. If you wanted to insert multiple documents in one call you can use the insert_many function. In addition to an acknowledgement of the insertion, the result set for insert_many will include a list of the ObjectIDs that were created.
We are now ready to explore querying and managing data in MongoDB using Python. To guide this exploration we will create another application that will manage our business reviews.
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