MongoDB with Python Workshop

Hosted by Amin M. Boulouma, contact and questions: amine.boulouma.com

• Learn MongoDB with Python
• Source code

Prerequisites

PyMongo: https://pymongo.readthedocs.io/en/stable/installation.html

pip install pymongo

MongoDB: https://docs.mongodb.com/manual/installation/

brew tap mongodb/brew

brew install mongodb-community@4.4

Start MongoDB

$ mongod

Making a Connection with MongoClient

The first step when working with PyMongo is to create a MongoClient to the running mongod instance. Doing so is easy:

from pymongo import MongoClient

client = MongoClient()

Creating the client with port specification

client = MongoClient('localhost', 27017)

Getting a Database

db = client.test_database

Getting a Collection

collection = db.test_collection

Documents

Data in MongoDB is represented (and stored) using JSON-style documents. In PyMongo we use dictionaries to represent documents. As an example, the following dictionary might be used to represent a blog post:

import datetime

post = {"author": "Amin",
        "text": "MongoDB with Python",
        "tags": ["mongodb", "python", "pymongo"],
        "date": datetime.datetime.utcnow()
       }

Inserting a Document

posts = db.posts
post_id = posts.insert_one(post).inserted_id
post_id

ObjectId('60b7100120bfc60abf20bcbd')

db.list_collection_names()

['posts']

Getting a Single Document With find_one()

import pprint

pprint.pprint(posts.find_one())

{'_id': ObjectId('60b70b1a44ca0fefd174f09b'),
 'author': 'Amin',
 'date': datetime.datetime(2021, 6, 2, 4, 37, 46, 983000),
 'tags': ['mongodb', 'python', 'pymongo'],
 'text': 'MongoDB with Python'}

pprint.pprint(posts.find_one({"text": "MongoDB with Python"}))

{'_id': ObjectId('60b70b1a44ca0fefd174f09b'),
 'author': 'Amin',
 'date': datetime.datetime(2021, 6, 2, 4, 37, 46, 983000),
 'tags': ['mongodb', 'python', 'pymongo'],
 'text': 'MongoDB with Python'}

posts.find_one({"author": "Somebody"})

Querying By ObjectId

post_id

ObjectId('60b7100120bfc60abf20bcbd')

pprint.pprint(posts.find_one({"_id": post_id}))

{'_id': ObjectId('60b7100120bfc60abf20bcbd'),
 'author': 'Amin',
 'date': datetime.datetime(2021, 6, 2, 4, 58, 27, 840000),
 'tags': ['mongodb', 'python', 'pymongo'],
 'text': 'MongoDB with Python'}

Note that an ObjectId is not the same as its string representation:

post_id == str(post_id)

False

str(post_id)

'60b7100120bfc60abf20bcbd'

posts.find_one({"_id": str(post_id)})

A common task in web applications is to get an ObjectId from the request URL and find the matching document. It’s necessary in this case to convert the ObjectId from a string before passing it to find_one:

from bson.objectid import ObjectId

def get(post_id):
    document = client.db.collection.find_one({'_id': ObjectId(post_id)})

Bulk Inserts

new_posts = [{"author": "Amin",
              "text": "ElasticSearch With Python",
              "tags": ["elasticsearch", "python"],
              "date": datetime.datetime(2009, 11, 12, 11, 14)},
             {"author": "Amin",
              "title": "Flask with python",
              "text": "That is amazing!",
              "date": datetime.datetime(2009, 11, 10, 10, 45)}]

result = posts.insert_many(new_posts)
result.inserted_ids

[ObjectId('60b7109120bfc60abf20bcbe'), ObjectId('60b7109120bfc60abf20bcbf')]

Querying for More Than One Document

for post in posts.find():
    pprint.pprint(post)

{'_id': ObjectId('60b70b1a44ca0fefd174f09b'),
 'author': 'Amin',
 'date': datetime.datetime(2021, 6, 2, 4, 37, 46, 983000),
 'tags': ['mongodb', 'python', 'pymongo'],
 'text': 'MongoDB with Python'}
{'_id': ObjectId('60b70c9c44ca0fefd174f09c'),
 'author': 'Amin',
 'date': datetime.datetime(2009, 11, 12, 11, 14),
 'tags': ['elasticsearch', 'python'],
 'text': 'ElasticSearch With Python'}
{'_id': ObjectId('60b70c9c44ca0fefd174f09d'),
 'author': 'Amin',
 'date': datetime.datetime(2009, 11, 10, 10, 45),
 'text': 'That is amazing!',
 'title': 'Flask with python'}
{'_id': ObjectId('60b7100120bfc60abf20bcbd'),
 'author': 'Amin',
 'date': datetime.datetime(2021, 6, 2, 4, 58, 27, 840000),
 'tags': ['mongodb', 'python', 'pymongo'],
 'text': 'MongoDB with Python'}
{'_id': ObjectId('60b7109120bfc60abf20bcbe'),
 'author': 'Amin',
 'date': datetime.datetime(2009, 11, 12, 11, 14),
 'tags': ['elasticsearch', 'python'],
 'text': 'ElasticSearch With Python'}
{'_id': ObjectId('60b7109120bfc60abf20bcbf'),
 'author': 'Amin',
 'date': datetime.datetime(2009, 11, 10, 10, 45),
 'text': 'That is amazing!',
 'title': 'Flask with python'}

for post in posts.find({"text": "That is amazing!"}):
    pprint.pprint(post)

{'_id': ObjectId('60b70c9c44ca0fefd174f09d'),
 'author': 'Amin',
 'date': datetime.datetime(2009, 11, 10, 10, 45),
 'text': 'That is amazing!',
 'title': 'Flask with python'}
{'_id': ObjectId('60b7109120bfc60abf20bcbf'),
 'author': 'Amin',
 'date': datetime.datetime(2009, 11, 10, 10, 45),
 'text': 'That is amazing!',
 'title': 'Flask with python'}

Counting

posts.count_documents({})

6

posts.count_documents({"text": "ElasticSearch With Python"})

2