Seamless Integration: Building Python Applications with MongoDB

Seamless Integration: Building Python Applications with MongoDB

Building applications that interact with MongoDB using Python is a seamless process thanks to libraries like PyMongo. Python's versatility and MongoDB's flexibility complement each other, allowing you to create dynamic and data-driven applications.

1. Creating Python Applications with MongoDB:
Python applications can easily interact with MongoDB databases to perform a variety of tasks, from storing and retrieving data to performing complex data analysis. This integration is facilitated by PyMongo's intuitive API.

from pymongo import MongoClient

# Connect to MongoDB
client = MongoClient()
db = client['mydatabase']
collection = db['mycollection']

# Insert a document
new_doc = {"name": "Ajit", "age": 28}
collection.insert_one(new_doc) 

# Query documents
result = collection.find({"age": {"$gt": 25}}) 

for doc in result:
    print(doc)

2. Utilising Python Classes for Modelling:
Python's object-oriented capabilities can be leveraged to model MongoDB documents as Python classes, providing a structured and intuitive way to interact with data.

class Person:
    def __init__(self, name, age):
        self.name = name
        self.age = age


    def save_to_db(self):
        collection.insert_one({"name": self.name, "age": self.age})



# Create and save a Person object
alice = Person("Ajit", 28)
alice.save_to_db()


# Query and display Person objects
result = collection.find({"age": {"$gt": 25}})


for doc in result:
    person = Person(doc["name"], doc["age"])
    print(person.name, person.age)

By creating Python classes that mirror your MongoDB document structure, you can encapsulate data and operations, making your code more organized and maintainable.