Retrieve Data
On this page
Overview
In this guide, you can learn how to use PyMongo, the MongoDB synchronous Python driver, to retrieve
data from a MongoDB collection by using read operations. You can call the
find() or find_one() method to retrieve documents that match a set of criteria.
Sample Data
The examples in this guide use the sample_restaurants.restaurants collection
from the Atlas sample datasets. To learn how to create a
free MongoDB Atlas cluster and load the sample datasets, see the Get Started with PyMongo.
Find Documents
PyMongo includes two methods for retrieving documents from a collection:
find_one() and find().
These methods take a query filter and return one or more matching documents.
A query filter is an object that specifies the documents you want to retrieve in
your query.
To learn more about query filters, see Specify a Query.
Find One Document
To find a single document in a collection, call the find_one() method and pass a query
filter that specifies the criteria of the document you want to find.
If more than one document matches the query
filter, this method returns the first matching document from the retrieved
results as a Python dictionary. If no documents match the query filter, the method returns
None.
Tip
The find_one() method is useful when you know there's only one matching document,
or you're only interested in the first match.
The following example uses the find_one() method to find the first document where
the "cuisine" field has the value "Bakery":
restaurant = sample_restaurants.restaurants.find_one({"cuisine": "Bakery"})
Tip
Sort Order
The find_one() method returns the first document in
natural order
on disk if no sort criteria is specified.
To learn more about sorting, see the sort guide.
Find Multiple Documents
To find multiple documents in a collection, pass a query filter to the find()
method that specifies the criteria of the documents you want to retrieve.
The following example uses the find() method to find all documents where
the "cuisine" field has the value "Spanish":
cursor = sample_restaurants.restaurants.find({"cuisine": "Spanish"})
You can use a cursor to iterate over the documents returned by the find()
method. A cursor is a mechanism that allows an application to iterate over database
results while holding only a subset of them in memory at a given time. Cursors
are useful when your find() method returns a large amount of documents.
You can iterate over the documents in a cursor by using a for-in loop, as shown in
the following example:
cursor = sample_restaurants.restaurants.find({"cuisine": "Spanish"}) for restaurant in cursor: ...
Note
Find All Documents
To find all documents in a collection, pass an empty filter
to the find() method:
all_restaurants = sample_restaurants.restaurants.find({})
Modify Find Behavior
You can modify the behavior of the find() and find_one() methods by passing
named arguments to them. The following table describes the commonly used arguments:
Argument | Description |
|---|---|
| Limits the number of documents to hold in a cursor at a given time. |
| An instance of the Collation class that sets the collation options. |
| A string to attach to the query. This can help you trace and interpret the
operation in the server logs and in profile data. To learn more about query comments,
see the $comment page. |
| The index to use for the query. |
| The maximum execution time on the server for this operation. If this time is
exceeded, PyMongo aborts the operation and raises an ExecutionTimeout. |
The following example uses the find() method to find all documents where
the "cuisine" field has the value "Italian" and sets a maximum execution
time of 10 seconds (10,000 milliseconds):
cursor = sample_restaurants.restaurants.find({"cuisine": "Italian"}, max_time_ms=10000)
For a full list of available arguments, see the
API documentation
for the find() method.
Additional Information
To learn more about query filters, see Specify a Query.
For runnable code examples of retrieving documents with PyMongo, see Read Data from MongoDB.
API Documentation
To learn more about any of the methods or types discussed in this guide, see the following API documentation: