MongoDB is one of the most popular NoSQL databases used in modern applications. Unlike traditional relational databases, MongoDB stores data in flexible, JSON-like documents. In this tutorial, we’ll walk you through how to use MongoDB with Python, from setup to CRUD operations.

Table of Contents

1. What is MongoDB?

2. Why Use MongoDB with Python?

3. Prerequisites

4. Installing PyMongo

5. Connecting to MongoDB

6. Creating a Database and Collection

7. CRUD Operations

   • Create (Insert)

   • Read (Find)

   • Update

   • Delete

8. Complete Working Example

9. Tips and Common Pitfalls

1. What is MongoDB?

MongoDB is a NoSQL, document-oriented database that stores data in BSON (Binary JSON). It's ideal for applications requiring scalability, flexibility, and real-time performance.

2. Why Use MongoDB with Python?

• Python's dynamic typing and dictionaries align naturally with MongoDB's flexible schema

• Great for data-driven applications, REST APIs, and rapid development

• Supports horizontal scaling and real-time analytics

⚙️ 3. Prerequisites

• Python installed (3.6+)

• MongoDB Server installed and running (locally or remotely)

• Basic knowledge of Python and JSON

4. Installing PyMongo

The official MongoDB driver for Python is PyMongo.

Install it using pip:

pip install pymongo

5. Connecting to MongoDB

import pymongo

client = pymongo.MongoClient("mongodb://localhost:27017/")

Connect to a Remote MongoDB Atlas Cluster:

client = pymongo.MongoClient("mongodb+srv://username:[email protected]/mydatabase")

6. Creating a Database and Collection

Create or Access a Database:

db = client["mydatabase"]

Create or Access a Collection (like a table in SQL):

collection = db["users"]

✅ MongoDB will create the database or collection only when you insert data.

✍️ 7. CRUD Operations in MongoDB

Create (Insert)

Insert one document:

user = {"name": "Alice", "age": 25}
collection.insert_one(user)

Insert multiple documents:

users = [
    {"name": "Bob", "age": 30},
    {"name": "Charlie", "age": 28}
]
collection.insert_many(users)

Read (Find)

Find one document:

user = collection.find_one()
print(user)

Find all documents:

for user in collection.find():
    print(user)

With a filter:

for user in collection.find({"age": {"$gt": 25}}):
    print(user)

✏️ Update

Update one document:

collection.update_one({"name": "Alice"}, {"$set": {"age": 26}})

Update many documents:

collection.update_many({}, {"$set": {"verified": True}})

❌ Delete

Delete one:

collection.delete_one({"name": "Bob"})

Delete many:

collection.delete_many({"verified": False})

8. Complete Working Example

import pymongo

# Connect to MongoDB
client = pymongo.MongoClient("mongodb://localhost:27017/")
db = client["company"]
employees = db["employees"]

# Insert documents
employees.insert_many([
    {"name": "Alice", "role": "Engineer", "salary": 75000},
    {"name": "Bob", "role": "Manager", "salary": 90000}
])

# Read documents
print("All Employees:")
for emp in employees.find():
    print(emp)

# Update a document
employees.update_one({"name": "Alice"}, {"$set": {"salary": 80000}})

# Delete a document
employees.delete_one({"name": "Bob"})

9. Tips and Common Pitfalls

Summary Table

Final Thoughts

Python and MongoDB make a powerful pair for developers who need flexibility and performance. With PyMongo, working with MongoDB is simple and intuitive, especially if you're used to Python dictionaries and JSON structures.

Whether you're building a small project or a large-scale system, MongoDB's document model and Python's flexibility can help you move fast and build efficiently.