Indexing in MongoDB using Python Last Updated : 04 Jul, 2025 Summarize Comments Improve Suggest changes Share Like Article Like Report In PyMongo, indexing is used to improve the performance of queries by allowing MongoDB to quickly locate and access the requested data without scanning every document in a collection. create_index() defines indexes to optimize queries and enforce constraints. MongoDB auto-indexes _id, but custom indexes can be added on fields using various directions and options.Syntaxcollection.create_index([(field, direction)], **options)Parameters:field: Field to index (e.g., "name")direction: pymongo.ASCENDING or pymongo.DESCENDINGoptions: Additional index options like unique=True, name="customIndex" etc.Here is our sample data. Python from pymongo import MongoClient, ASCENDING c = MongoClient("mongodb://localhost:27017/") db = c["indexDB"] col = db["users"] data = [ {"name": "Alice", "email": "[email protected]"}, {"name": "Bob", "email": "[email protected]"}, {"name": "Charlie", "email": "[email protected]"} ] col.delete_many({}) col.insert_many(data) print("Sample data inserted.") OutputSample data insertedSample data Explanation:Connects to the local MongoDB server and selects the indexDB database and users collection.Clears existing documents in the collection using delete_many({}).Inserts three sample user records into the collection using insert_many().ExamplesExample 1: Create index on a field Python from pymongo import MongoClient, ASCENDING c = MongoClient("mongodb://localhost:27017/") db = c["indexDB"] col = db["users"] idx_name = col.create_index([("name", ASCENDING)]) print(idx_name) Output Explanation: Creates an ascending index on the name field to speed up queries using name.Example 2: List all index Python from pymongo import MongoClient, ASCENDING c = MongoClient("mongodb://localhost:27017/") db = c["indexDB"] col = db["users"] for idx in col.list_indexes(): print(idx) OutputSnapshot of the OutputExplanation: Displays all indexes on the users collection. The default _id_ index and the created name_1 index will be shown.Example 3: Drop an index Python from pymongo import MongoClient, ASCENDING c = MongoClient("mongodb://localhost:27017/") db = c["indexDB"] col = db["users"] col.drop_index("name_1") OutputIndex droppedExplanation: Drops the index named "name_1". You must pass the exact index name created earlier.Example 4: Create index on a new field (default ascending) Python from pymongo import MongoClient, ASCENDING c = MongoClient("mongodb://localhost:27017/") db = c["indexDB"] col = db["users"] res = col.create_index("index_created") print(res) Outputindex_created_1Explanation: Creates an ascending index (default) on a new field index_created.Example 5: Create compound index Python from pymongo import MongoClient, ASCENDING c = MongoClient("mongodb://localhost:27017/") db = c["indexDB"] col = db["users"] res = col.create_index([ ("ascending_index", 1), ("second_descending_index", DESCENDING) ]) print(res) OutputOutputExplanation: ascending_index is indexed in ascending order, second_descending_index in descending order. This index improves performance for queries and sorts using both fields together.Related articlesPython MongoDBInsert and Update Operations in MongoDBMongoDB Aggregation Pipeline using PythonHow to Setup MongoDB with Python on Localhost Comment More infoAdvertise with us Next Article Python MongoDB - create_index Query GeeksforGeeks Improve Article Tags : Python Python-mongoDB Practice Tags : python Similar Reads Python MongoDB Tutorial MongoDB is a popular NoSQL database designed to store and manage data flexibly and at scale. Unlike traditional relational databases that use tables and rows, MongoDB stores data as JSON-like documents using a format called BSON (Binary JSON). This document-oriented model makes it easy to handle com 2 min read Python MongoDB - IntroductionMongoDB: An introductionMongoDB is a powerful, open-source NoSQL database that offers a document-oriented data model, providing a flexible alternative to traditional relational databases. 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The data that is exchanged between the Python applicatio 3 min read Working with Collections and documents in MongoDBHow to access a collection in MongoDB using Python?MongoDB is a cross-platform, document-oriented database that works on the concept of collections and documents. MongoDB offers high speed, high availability, and high scalability. Accessing a Collection 1) Getting a list of collection: For getting a list of a MongoDB database's collections list_coll 2 min read Get the Names of all Collections using PyMongoPyMongo is the module used for establishing a connection to the MongoDB using Python and perform all the operations like insertion, deletion, updating, etc. PyMongo is the recommended way to work with MongoDB and Python. Note: For detailed information about Python and MongoDB visit MongoDB and Pyth 2 min read Drop Collection if already exists in MongoDB using PythonUsing drop() method we can drop collection if collection exists. If collection is not found then it returns False otherwise it returns True if collection is dropped. Syntax: drop() Example 1: The sample database is as follows:  Python3 import pymongo client = pymongo.MongoClient("mongodb://local 1 min read How to update data in a Collection using Python?MongoDB is a cross-platform, document-oriented database that works on the concept of collections and documents. MongoDB offers high speed, high availability, and high scalability. Updating Data in MongoDB We can update data in a collection using update_one() method and update_many() method.  update 2 min read Get all the Documents of the Collection using PyMongoTo get all the Documents of the Collection use find() method. The find() method takes a query object as a parameter if we want to find all documents then pass none in the find() method. 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It stores the value of a specific field or set of fields whic 2 min read How to create index for MongoDB Collection using Python?Creating indexes in MongoDB improves query performance, especially on large datasets. PyMongo, the official MongoDB driver for Python, provides the create_index() method to define indexes on specific fields. By default, MongoDB indexes the _id field, but adding custom indexes is important for optimi 2 min read Get all the information of a Collection's indexes using PyMongoIn PyMongo, retrieving index information is useful for understanding how queries are optimized and what constraints are applied to a collection. The index_information() method provides metadata about all indexes in a collection, including index names, fields, sort order and options such as uniquenes 2 min read Python MongoDB - drop_index QueryThe drop_index() library function in PyMongo is used to drop the index from a collection in the database, as the name suggests. In this article, we are going to discuss how to remove an index from a collection using our python application with PyMongo. Syntax: drop_index(index_or_name, session=None 3 min read How to Drop all the indexes in a Collection using PyMongo?In PyMongo, the drop_indexes() method is used to remove all non-default indexes from a collection. It helps developers clean up or reset indexing strategies, especially during optimization or testing. The method retains the default _id index, which cannot be dropped.Syntaxcollection.drop_indexes()No 2 min read How to rebuild all the indexes of a collection using PyMongo?According to MongoDB documentation, normally, MongoDB compacts indexes during routine updates. For most users, the reIndex command is unnecessary. 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It means that MongoDB isn’t based on the table-like relational database structure but provides an altogether different mechanism for storage and retrieval of data. This fo 3 min read Like