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What is a PyMongo Cursor?

Last Updated : 25 Jul, 2025

When working with MongoDB in Python using PyMongo, you typically retrieve data from a collection using the find() method. But instead of getting all the matching documents at once, PyMongo returns something called a cursor.

A PyMongo cursor is a special iterable object that acts like a pointer to the result set of a MongoDB query. It allows you to fetch and process query results one document at a time rather than loading everything into memory at once.

Using a cursor provides several important advantages, especially when dealing with large datasets:

• Memory-efficient: Documents are retrieved in small batches instead of all at once, preventing memory overload.
• Lazy loading: Results are fetched as you iterate, which avoids blocking your application.
• Incremental processing: You can handle one document at a time in a loop, which is great for streaming, filtering or transforming data.
• Improved performance: Reduces pressure on both the client and the MongoDB server.

You can fine-tune the data returned by the cursor using:

• projection : to select specific fields from documents
• sort() : to order results based on one or more fields
• limit() : to restrict the number of documents returned
• skip() : to skip a specified number of documents

Sample database is as follows:  

Example: Using Cursor in PyMongo

from pymongo import MongoClient
    
# Connecting to mongodb    
client = MongoClient('mongodb://localhost:27017/')

with client:
    
    db = client.GFG
    lectures = db.lecture.find()

    print(lectures.next())
    print(lectures.next())
    print(lectures.next())    
    
    print("\nRemaining Lectures\n")
    print(list(lectures))

Explanation:

• find() method returns the cursor object.
• next() method we get the next document in the collection.
• list() method, we can transform the cursor to a Python list.

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