Python MongoDB Find

Retrieving data is one of the core operations when working with databases. MongoDB, with its flexible query system, allows developers to fetch data effortlessly. Using Python’s pymongo library, you can perform powerful queries to extract the information you need. At The Coding College, we help simplify such operations for you!

Prerequisites

Before diving into the examples, ensure you have the following:

  1. Python Installed: Download it from python.org.
  2. MongoDB Installed: Install it from mongodb.com.
  3. pymongo Installed: Install the driver using: 
pip install pymongo

The find() Method

In MongoDB, the find() method retrieves documents from a collection. By default, it fetches all documents unless specific conditions (queries) are applied.

Syntax

collection.find(query, projection)
  • query: Filters documents based on specified conditions (default is {} to fetch all documents).
  • projection: Specifies which fields to include or exclude in the result.

Example 1: Fetch All Documents

Use find() without arguments to retrieve all documents:

import pymongo

# Connect to MongoDB
client = pymongo.MongoClient("mongodb://localhost:27017/")
db = client["mydatabase"]
collection = db["customers"]

# Fetch all documents
for document in collection.find():
    print(document)

Example 2: Fetch Documents with a Query

To filter documents, pass a query object:

# Fetch documents where "city" is "New York"
query = {"city": "New York"}
for document in collection.find(query):
    print(document)

Example 3: Include/Exclude Fields

Use the projection parameter to limit the fields in the result:

# Fetch documents with "name" and exclude "_id"
query = {"city": "New York"}
projection = {"_id": 0, "name": 1, "city": 1}
for document in collection.find(query, projection):
    print(document)

Example 4: Fetch with Comparison Operators

MongoDB supports operators like $gt, $lt, $eq, etc.:

# Fetch documents where "age" is greater than 25
query = {"age": {"$gt": 25}}
for document in collection.find(query):
    print(document)

Example 5: Fetch Documents with Logical Operators

Combine conditions using $and, $or, $not, and more:

# Fetch documents where "age" is greater than 25 OR "city" is "Chicago"
query = {"$or": [{"age": {"$gt": 25}}, {"city": "Chicago"}]}
for document in collection.find(query):
    print(document)

Example 6: Sort the Results

Sort documents using sort() method:

# Sort by "name" in ascending order
for document in collection.find().sort("name", 1):
    print(document)

Example 7: Limit the Number of Results

Use limit() to restrict the number of documents returned:

# Fetch only 3 documents
for document in collection.find().limit(3):
    print(document)

Complete Example

Here’s a complete script combining multiple features:

import pymongo

# Connect to MongoDB
client = pymongo.MongoClient("mongodb://localhost:27017/")
db = client["company"]
collection = db["employees"]

# Fetch documents based on query, projection, and sort
query = {"salary": {"$gte": 50000}}
projection = {"_id": 0, "name": 1, "salary": 1}
for document in collection.find(query, projection).sort("salary", -1).limit(5):
    print(document)

Exercises

  1. Basic Query: Write a script to fetch all documents from a products collection.
  2. Field Projection: Fetch documents from a users collection, displaying only name and email.
  3. Filter and Sort: Query documents where age is less than 30, sorted by name in descending order.

Common Errors

  1. Empty Result:
    • If your query doesn’t match any document, find() returns an empty cursor. Double-check your query.
  2. Projection Errors:
    • Mixing inclusion and exclusion in projection (except _id) will raise an error.

Why Use MongoDB’s find()?

The find() method is powerful and flexible, allowing developers to extract data efficiently. Combined with Python, it provides a robust tool for handling and analyzing data.

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