Python MongoDB

Introduction

MongoDB is a popular NoSQL database known for its flexibility and scalability. Unlike traditional relational databases, MongoDB stores data in JSON-like documents, making it easier to work with hierarchical data structures. Python, with its extensive library support, makes it easy to interact with MongoDB. In this guide, we will use the pymongo library to perform various operations on a MongoDB database.

Setting Up

Install PyMongo

First, you need to install the PyMongo library. You can install it using pip:

pip install pymongo

Connecting to MongoDB

To connect to a MongoDB server, you need to specify the hostname and port number. The default hostname is localhost, and the default port is 27017.

Example: Connecting to MongoDB

from pymongo import MongoClient

# Connect to the MongoDB server
client = MongoClient('localhost', 27017)

# Access a database
db = client['mydatabase']

print("Connected to MongoDB database")

Creating a Collection

In MongoDB, databases hold collections, and collections hold documents. Collections are equivalent to tables in relational databases.

Example: Creating a Collection

# Access a collection
collection = db['employees']

print("Collection created")

Inserting Documents

You can insert documents into a collection using the insert_one() and insert_many() methods.

Example: Inserting a Single Document

# Insert a single document
employee = {
    "name": "John Doe",
    "age": 28,
    "position": "Software Engineer"
}
collection.insert_one(employee)

print("Document inserted")

Example: Inserting Multiple Documents

# Insert multiple documents
employees = [
    {"name": "Jane Smith", "age": 32, "position": "Project Manager"},
    {"name": "Mike Johnson", "age": 45, "position": "CTO"},
    {"name": "Emma Davis", "age": 29, "position": "Data Scientist"}
]
collection.insert_many(employees)

print("Multiple documents inserted")

Querying Documents

You can query documents in a collection using the find() method. The find_one() method returns a single document, while the find() method returns all documents that match the query.

Example: Querying a Single Document

# Query a single document
employee = collection.find_one({"name": "John Doe"})
print(employee)

Example: Querying Multiple Documents

# Query multiple documents
employees = collection.find({"age": {"$gt": 30}})
for emp in employees:
    print(emp)

Updating Documents

You can update documents in a collection using the update_one() and update_many() methods.

Example: Updating a Single Document

# Update a single document
collection.update_one(
    {"name": "John Doe"},
    {"$set": {"age": 29}}
)

print("Document updated")

Example: Updating Multiple Documents

# Update multiple documents
collection.update_many(
    {"age": {"$gt": 30}},
    {"$set": {"position": "Experienced Employee"}}
)

print("Multiple documents updated")

Deleting Documents

You can delete documents in a collection using the delete_one() and delete_many() methods.

Example: Deleting a Single Document

# Delete a single document
collection.delete_one({"name": "John Doe"})

print("Document deleted")

Example: Deleting Multiple Documents

# Delete multiple documents
collection.delete_many({"age": {"$gt": 30}})

print("Multiple documents deleted")

Using Indexes

Indexes can improve the performance of your queries. You can create indexes on one or more fields in a collection.

Example: Creating an Index

# Create an index on the "name" field
collection.create_index("name")

print("Index created")

Complete Example

Here is a complete example that includes connecting to MongoDB, creating a collection, inserting documents, querying documents, updating documents, deleting documents, and creating indexes.

from pymongo import MongoClient

# Connect to the MongoDB server
client = MongoClient('localhost', 27017)

# Access a database
db = client['mydatabase']

# Access a collection
collection = db['employees']

# Insert a single document
employee = {
    "name": "John Doe",
    "age": 28,
    "position": "Software Engineer"
}
collection.insert_one(employee)

# Insert multiple documents
employees = [
    {"name": "Jane Smith", "age": 32, "position": "Project Manager"},
    {"name": "Mike Johnson", "age": 45, "position": "CTO"},
    {"name": "Emma Davis", "age": 29, "position": "Data Scientist"}
]
collection.insert_many(employees)

# Query a single document
employee = collection.find_one({"name": "John Doe"})
print("Single document query result:", employee)

# Query multiple documents
employees = collection.find({"age": {"$gt": 30}})
print("Multiple document query results:")
for emp in employees:
    print(emp)

# Update a single document
collection.update_one(
    {"name": "John Doe"},
    {"$set": {"age": 29}}
)

# Update multiple documents
collection.update_many(
    {"age": {"$gt": 30}},
    {"$set": {"position": "Experienced Employee"}}
)

# Delete a single document
collection.delete_one({"name": "John Doe"})

# Delete multiple documents
collection.delete_many({"age": {"$gt": 30}})

# Create an index on the "name" field
collection.create_index("name")

print("Operations completed")

Conclusion

Using MongoDB with Python is straightforward with the pymongo library. By following the steps outlined above, you can easily connect to a MongoDB database, create collections, insert, query, update, and delete documents, and create indexes to optimize your queries. This provides a solid foundation for managing and analyzing your data programmatically using Python.