PyMongo: How to list all collections in a database

Introduction

In this tutorial, we’ll dive deep into how you can use PyMongo, the popular Python distribution containing tools for working with MongoDB, to list all collections in a database. We will start with basic examples and progressively move to more advanced techniques. Whether you’re just starting with MongoDB and PyMongo or looking for more in-depth knowledge, this guide has got you covered.

Getting Started with PyMongo

First, ensure that you have MongoDB and PyMongo installed. You can install PyMongo using pip:

pip install pymongo

Once installed, you’ll need to establish a connection to your MongoDB server. If you’re working with a local development environment, your connection string might look like this:

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

Now, let’s select the database:

db = client['your_database_name']

Basic: Listing Collections

To list all collections in a database, use the list_collection_names method:

collections = db.list_collection_names()
print(collections)

This will output a list of collection names:

['collection_name1', 'collection_name2', ...]

Filtering Collections

If you have a large number of collections and are only interested in those that match certain patterns, you can use Python’s list comprehension along with conditionals:

filtered_collections = [col for col in db.list_collection_names() if 'pattern' in col]
print(filtered_collections)

This filters out collections that do not contain a specified pattern in their name.

Advanced: Using System Commands for Listing Collections

For a more advanced approach, you can list collections by using the MongoDB command listCollections directly:

collections = db.command('listCollections')
for collection in collections['cursor']['firstBatch']:
    print(collection['name'])

This method provides more detailed information about each collection, such as its options and index information.

Working with Large Databases

In cases where you’re dealing with a very large database, performance can become an issue when listing all collections. Utilizing cursors and batching can help manage resources more efficiently:

collections_cursor = db.collection_names(batch_size=10)
while collections_cursor.alive:
    print(collections_cursor.next())

This example demonstrates how to process the results in chunks rather than loading all names into memory at once.

Security and Accessibility

When accessing MongoDB, always consider the security of your database. Ensure you are authorized to list the collections and that your MongoDB instance is secure, especially if accessible over the internet.

Conclusion

Listing collections in a MongoDB database using PyMongo is straightforward and can be achieved in various ways depending on your specific requirements and the size of your database. This tutorial covered essential methods to list collections, from basic to more detailed and advanced techniques, enhancing your capability to interact with MongoDB using Python. Armed with this knowledge, navigating and managing MongoDB collections becomes a smoother experience.