Python MongoDB Query

Last modified on: October 20, 2024

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<h3><strong>Querying Documents in MongoDB Using Python</strong></h3>
<p>MongoDB allows for flexible querying of documents within collections. This guide will show you how to use various query techniques with the <code>pymongo</code> library in Python.</p>
<hr />
<h3><strong>1. Prerequisites</strong></h3>
<p>Ensure you have:</p>
<ul>
<li>MongoDB installed and running locally or access to a cloud MongoDB service (e.g., MongoDB Atlas).</li>
<li>The <code>pymongo</code> library installed. If you haven&rsquo;t done this yet, run:</li>
</ul>
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<pre class="language-python"><code>pip install pymongo
</code></pre>
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<h3><strong>2. Import Required Libraries</strong></h3>
<p>Start by importing <code>pymongo</code>:</p>
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<pre class="language-python"><code>import pymongo
from pymongo import MongoClient
</code></pre>
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<h3><strong>3. Connecting to MongoDB</strong></h3>
<p>Connect to your MongoDB instance. For a local database, use:</p>
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<pre class="language-python"><code>client = MongoClient("mongodb://localhost:27017/")
</code></pre>
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<p>For a cloud-based MongoDB instance (like MongoDB Atlas), use your MongoDB URI:</p>
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<pre class="language-python"><code>client = MongoClient("your_mongodb_atlas_uri")
</code></pre>
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<h3><strong>4. Creating or Accessing a Database and Collection</strong></h3>
<p>Create or access a database and a collection:</p>
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<pre class="language-python"><code>db = client["mydatabase"]
collection = db["mycollection"]
</code></pre>
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<h3><strong>5. Querying Documents</strong></h3>
<h4><strong>a. Basic Queries</strong></h4>
<p>To find documents that match a specific condition, you can pass a query dictionary to the <code>find()</code> method.</p>
<ul>
<li><strong>Find Documents by a Single Field</strong></li>
</ul>
<p>For example, to find documents where the name is "Alice":</p>
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<pre class="language-python"><code>query = { "name": "Alice" }
result = collection.find(query)

for doc in result:
    print(doc)
</code></pre>
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<ul>
<li><strong>Find Documents by Multiple Fields</strong></li>
</ul>
<p>To find documents where the name is "Alice" and the age is 30:</p>
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<pre class="language-python"><code>query = { "name": "Alice", "age": 30 }
result = collection.find(query)

for doc in result:
    print(doc)
</code></pre>
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<h4><strong>b. Using Comparison Operators</strong></h4>
<p>MongoDB supports several comparison operators that you can use in your queries:</p>
<ul>
<li><strong>Greater Than (<code>$gt</code>)</strong></li>
<li><strong>Less Than (<code>$lt</code>)</strong></li>
<li><strong>Greater Than or Equal To (<code>$gte</code>)</strong></li>
<li><strong>Less Than or Equal To (<code>$lte</code>)</strong></li>
<li><strong>Not Equal To (<code>$ne</code>)</strong></li>
</ul>
<p>Example: Find documents where age is greater than 25:</p>
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<pre class="language-python"><code>query = { "age": { "$gt": 25 } }
result = collection.find(query)

for doc in result:
    print(doc)
</code></pre>
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<h4><strong>c. Using Logical Operators</strong></h4>
<p>You can combine queries using logical operators:</p>
<ul>
<li><strong>AND (<code>$and</code>)</strong></li>
<li><strong>OR (<code>$or</code>)</strong></li>
<li><strong>NOR (<code>$nor</code>)</strong></li>
<li><strong>NOT (<code>$not</code>)</strong></li>
</ul>
<p>Example: Find documents where the age is less than 30 <strong>or</strong> the city is "Chicago":</p>
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<pre class="language-python"><code>query = { "$or": [{ "age": { "$lt": 30 } }, { "city": "Chicago" }] }
result = collection.find(query)

for doc in result:
    print(doc)
</code></pre>
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<h4><strong>d. Regular Expressions</strong></h4>
<p>You can use regular expressions to query string fields. For example, to find names that start with "A":</p>
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<pre class="language-python"><code>query = { "name": { "$regex": "^A" } }
result = collection.find(query)

for doc in result:
    print(doc)
</code></pre>
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<h3><strong>6. Closing the Connection</strong></h3>
<p>After performing your operations, close the connection:</p>
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<pre class="language-python"><code>client.close()
</code></pre>
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<h3><strong>Complete Example</strong></h3>
<p>Here&rsquo;s a complete script demonstrating various query techniques:</p>
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<pre class="language-python"><code>import pymongo
from pymongo import MongoClient

# Connect to MongoDB
client = MongoClient("mongodb://localhost:27017/")

# Create or access a database
db = client["mydatabase"]

# Create or access a collection
collection = db["mycollection"]

# Insert sample documents (if collection is empty)
if collection.count_documents({}) == 0:
    documents = [
        { "name": "Alice", "age": 30, "city": "New York" },
        { "name": "Bob", "age": 25, "city": "Los Angeles" },
        { "name": "Charlie", "age": 35, "city": "Chicago" },
        { "name": "Diana", "age": 28, "city": "New York" },
    ]
    collection.insert_many(documents)

# Find documents by a single field
print("Documents where name is 'Alice':")
query = { "name": "Alice" }
for doc in collection.find(query):
    print(doc)

# Find documents by multiple fields
print("\nDocuments where name is 'Alice' and age is 30:")
query = { "name": "Alice", "age": 30 }
for doc in collection.find(query):
    print(doc)

# Using comparison operators
print("\nDocuments where age is greater than 25:")
query = { "age": { "$gt": 25 } }
for doc in collection.find(query):
    print(doc)

# Using logical operators
print("\nDocuments where age is less than 30 or city is 'Chicago':")
query = { "$or": [{ "age": { "$lt": 30 } }, { "city": "Chicago" }] }
for doc in collection.find(query):
    print(doc)

# Using regular expressions
print("\nDocuments where name starts with 'A':")
query = { "name": { "$regex": "^A" } }
for doc in collection.find(query):
    print(doc)

# Close the connection
client.close()
</code></pre>
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<h3><strong>Conclusion</strong></h3>
<p>In this guide, you learned how to:</p>
<ol>
<li>Connect to MongoDB using Python.</li>
<li>Query documents using various conditions and operators.</li>
<li>Use regular expressions for pattern matching.</li>
</ol>
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