How to Quickly Load MongoDB Data into a Python List?

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To quickly load MongoDB data into a Python list, you can use the PyMongo library, which provides a Python interface for interacting with MongoDB. Here’s an example of how you can accomplish this:

from pymongo import MongoClient

# Connect to MongoDB
client = MongoClient('<mongodb_connection_string>')
db = client['<database_name>']
collection = db['<collection_name>']

# Load data into a Python list
data_list = list(collection.find())

# Print the loaded data
for document in data_list:

In this example, you need to replace <mongodb_connection_string> with the appropriate connection string for your MongoDB instance. You also need to provide the <database_name> and <collection_name> that correspond to the specific database and collection from which you want to load the data.

The collection.find() method retrieves all documents from the collection. By converting the returned cursor to a list using the list() function, you can quickly load all the data into a Python list.

You can then iterate over the data_list to access each document in the collection.

Make sure to install the PyMongo library using pip install pymongo before running the code.

Note: Loading all data into a Python list might not be efficient or practical for large datasets as it requires sufficient memory to store the entire data. If working with large datasets, consider using pagination or processing the data in smaller batches to minimize memory usage.

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