Master MongoDB with Node.js Using Mongoose: Complete Guide


Working with MongoDB from Node.js using Mongoose

Your Magical Mongoose Pet That Makes MongoDB Super Easy For Beginner to Expert Level


Introduction

What is Mongoose?
Mongoose is a popular Object Data Modeling (ODM) library for MongoDB and Node.js. It allows developers to define data structures using schemas, enforce validation, manage relationships, and interact with MongoDB through clean, organized models instead of raw queries.

Why use Mongoose?
Without Mongoose, MongoDB data can become messy because documents don’t follow strict rules. Mongoose adds structure, validation, default values, middleware, population (relations), and many powerful features that make building scalable Node.js applications easier and safer.

What you will learn in this guide
In this tutorial, you’ll learn how to:

  • Connect Node.js with MongoDB using Mongoose
  • Create schemas, models, validations, and defaults
  • Perform CRUD operations with simple code
  • Use middleware, virtuals, population, and aggregation
  • Build a real Express API powered by MongoDB + Mongoose

Whether you are a beginner learning MongoDB or an advanced developer exploring Mongoose’s hidden powers, this guide will help you master it step by step.

Note: The jungle theme makes concepts more memorable, but the deeper sections of this guide use a clearer, more technical tone so both beginners and advanced developers get maximum value.



Table of Contents


Imagine MongoDB is a wild jungle full of treasure chests (documents). Node.js is your brave explorer. But the jungle is messy - chests can have wrong items, or get lost!

Mongoose is your cute, intelligent pet mongoose that:

  • Guards the jungle with rules (schemas)
  • Makes sure every treasure chest neat and safe
  • Adds superpowers like auto-validation, middleware magic, and easy relationships

Mongoose is the best way to use MongoDB in Node.js apps (Express, Next.js, games, APIs). It turns raw MongoDB into friendly, powerful objects.
This tutorial is a jungle adventure where we build a Hero Jungle App. Easy enough for students, but full of pro ninja moves for experts.

Let’s adopt our mongoose pet!


Part 1: Setup - Bring Your Pet Home

Make a new folder: hero-jungle
Open terminal there and run:

npm init -y
npm install mongoose

Optional (for a full app):

npm install express dotenv

You need MongoDB running (local or Atlas cloud).


Part 2: Connect to MongoDB - Call Your Pet!

Create index.js:

const mongoose = require('mongoose');

// Connect (local or Atlas)
mongoose.connect('mongodb://127.0.0.1:27017/heroJungle')
// For Atlas: 'mongodb+srv://user:pass@cluster0.xxxxx.mongodb.net/heroJungle'

const db = mongoose.connection;

db.on('error', console.error.bind(console, 'Connection error:'));
db.once('open', () => {
    console.log('๐Ÿฆฆ Mongoose pet is awake and connected! Jungle ready!');
});

Run:

node index.js

You did it! Your pet mongoose is now guarding the jungle.

From this point onward, we shall dial down the jungle metaphors a bit so you can focus on the technical details clearly, while still keeping the learning experience fun. The earlier story helps you visualize Mongoose, but the next sections will be more hands-on and code-focused.


Part 3: Define a Schema - Teach Your Pet Rules

Schema = Blueprint of how a hero should look.

const heroSchema = new mongoose.Schema({
    name: {
        type: String,
        required: true,
        trim: true,
        minlength: 2
    },
    power: {
        type: String,
        required: true,
        enum: ['Fire', 'Ice', 'Speed', 'Fly', 'Mind']
    },
    level: {
        type: Number,
        required: true,
        min: 1,
        max: 100
    },
    isActive: {
        type: Boolean,
        default: true
    },
    team: String,
    skills: [String],
    profile: {
        age: Number,
        city: String
    },
    createdAt: {
        type: Date,
        default: Date.now
    }
});

// Create model (collection will be "heroes")
const Hero = mongoose.model('Hero', heroSchema);

module.exports = Hero;

Magic Rules Your Pet Enforces Automatically:

  • Required fields
  • Data types
  • Min/max values
  • Valid options (enum)
  • Default values
  • Auto timestamps

Part 4: CRUD - Play With Your Pet!

Create app.js:

const mongoose = require('mongoose');
const Hero = require('./heroSchema'); 

mongoose.connect('mongodb://localhost:27017/heroJungle');

async function jungleAdventure() {
    // CREATE
    const aarav = await Hero.create({
        name: "Aarav",
        power: "Speed",
        level: 85,
        skills: ["run", "jump"],
        profile: { age: 14, city: "Mumbai" }
    });
    console.log("New hero:", aarav.name);

    const priya = new Hero({
        name: "Priya",
        power: "Invisible", // This will cause a validation error
        level: 92
    });
    await priya.save();

Note: If you want the power "Invisible" to be valid, update the schema enum to include it:

power: {
    type: String,
    required: true,
    enum: ['Fire', 'Ice', 'Speed', 'Fly', 'Mind', 'Invisible']
}
// READ const alphaTeam = await Hero.find({ team: "Alpha" }); console.log("Alpha team:", alphaTeam.map(h => h.name)); const hero = await Hero.findOne({ name: "Aarav" }); const strongHeroes = await Hero.find({ level: { $gt: 80 } }) .sort({ level: -1 }) .limit(5); // UPDATE await Hero.updateOne( { name: "Aarav" }, { $set: { level: 90 }, $push: { skills: "dash" } } ); const updated = await Hero.findOneAndUpdate( { name: "Priya" }, { $inc: { level: 5 } }, { new: true } ); // DELETE await Hero.deleteOne({ name: "Rohan" }); await Hero.deleteMany({ level: { $lt: 50 } }); } jungleAdventure();

Beginner Magic: create(), find(), updateOne() feel just like normal JavaScript!



Part 5: Validation - Your Pet Bites Bad Data!

(In simple terms: this means Mongoose handles validation and data rules behind the scenes.)

Try this bad hero:

try {
    await Hero.create({
        name: "A",
        power: "Magic",
        level: 150
    });
} catch (error) {
    console.log("Pet says NO!", error.message);
}

Custom Validation:

email: {
    type: String,
    validate: {
        validator: function(v) {
            return /\S+@\S+\.\S+/.test(v);
        },
        message: "Bad email!"
    }
}


Part 6: Middleware (Hooks) - Secret Pet Tricks!

// Auto-hash password before saving
heroSchema.pre('save', async function(next) {
    if (this.isModified('password')) {
        this.password = await bcrypt.hash(this.password, 10);
    }
    next();
});

// Log after save
heroSchema.post('save', function(doc) {
    console.log(`${doc.name} was saved to jungle!`);
});

Use Cases: Logging, password hashing, sending emails, updating timestamps.



Part 7: References & Population - Connect Different Collections!

// teamSchema.js
const teamSchema = new mongoose.Schema({
    name: String,
    motto: String,
    members: [{ type: mongoose.Schema.Types.ObjectId, ref: 'Hero' }]
});

const Team = mongoose.model('Team', teamSchema);

Add to hero:

team: { type: mongoose.Schema.Types.ObjectId, ref: 'Team' }

Populate (like JOIN):

const heroes = await Hero.find().populate('team');
console.log(heroes[0].team.motto);

Pro Tip: Use populate with select to get only needed fields.


Part 8: Aggregation - Ask Your Pet Smart Questions

const report = await Hero.aggregate([
    
    { $match: { level: { $gte: 80 } } },
    {
        $group: {
            _id: "$power",
            avgLevel: { $avg: "$level" },
            heroes: { $push: "$name" }
        }
    },
    { $sort: { avgLevel: -1 } }
]);

console.log("Power Rankings:", report);

Same power as mongosh, but in Node.js!


Part 9: Pro Ninja Features

Virtuals (Calculated Fields)

heroSchema.virtual('powerLevel').
    get(function() {
        return this.level > 90 ? 'Legend' : 'Hero';
    });

console.log(hero.powerLevel);

Indexes

heroSchema.index({ name: 1, team: 1 });
heroSchema.index({ location: "2dsphere" });

Plugins (Reusable Powers)
Use popular ones like mongoose-lean-virtuals, mongoose-autopopulate

Error Handling

try {
    await Hero.findById("bad-id");
} catch (err) {
    console.log("Mongoose error:", err.message);
}

Environment Variables (Never hardcode passwords!)

require('dotenv').config();
mongoose.connect(process.env.MONGO_URI);

Additional Best Practices for Advanced Mongoose Users

To make your Mongoose applications faster, safer, and more production-ready, here are some important best practices that every advanced developer should know. These techniques improve performance, clarity, and reliability at scale.

1. Use .lean() for Faster Read Queries

When you fetch documents that you only want to read (not modify), using .lean() returns plain JavaScript objects instead of full Mongoose documents. This increases query performance significantly.

// Faster read operation
const heroes = await Hero.find().lean();

Use .lean() for APIs that only return data and do not rely on Mongoose document methods or virtuals.


2. Use Proper Connection Options When Connecting to MongoDB

Adding connection options makes your database connection more stable and compatible across environments.

mongoose.connect(process.env.MONGO_URI, {
  useNewUrlParser: true,
  useUnifiedTopology: true,
});

These options improve connection handling and prevent deprecation warnings.


3. Understand and Configure Schema Strict Mode

Mongoose’s strict mode determines what happens when a field that is not defined in the schema is passed into a document.

// Strict mode enabled (default)
const heroSchema = new mongoose.Schema({}, { strict: true });
  • strict: true → Extra fields are ignored (recommended for safety)
  • strict: false → Extra fields are stored in the database
  • strict: "throw" → Throws an error if unknown fields are sent

Example:

// Will cause an error if strict is "throw"
const hero = await Hero.create({ name: "Aarav", unknownField: "oops" });

Strict mode is important for validating input, preventing bugs, and improving security, especially in APIs receiving user data.


Part 10: Mini Project - Build a Hero API with Express!

server.js:

const express = require('express');
const mongoose = require('mongoose');
const Hero = require('./heroSchema');

mongoose.connect('mongodb://localhost:27017/heroJungle');
const app = express();
app.use(express.json());

// GET all heroes
app.get('/heroes', async (req, res) => {
    const heroes = await Hero.find();
    res.json(heroes);
});

// POST new hero
app.post('/heroes', async (req, res) => {
    try {
        const hero = await Hero.create(req.body);
        res.status(201).json(hero);
    } catch (err) {
        res.status(400).json({ error: err.message });
    }
});

app.listen(3000, () => console.log('Hero API running on port 3000!'));

Test with Postman or curl!



More Realistic Use Cases with Mongoose

Now that you understand how Mongoose works in a hero-themed project, here are some real-world use cases where developers commonly use it. Adding these ideas gives you a clearer picture of how Mongoose fits into modern web applications:

  • Build a Blog with Mongoose
    Create posts, comments, authors, categories, and tags using schema relationships and population.
  • Create User Authentication with Mongoose
    Store users, hashed passwords, tokens, roles, and permissions. Mongoose middleware is perfect for password hashing and token generation.
  • Use Mongoose Inside Next.js API Routes
    Combine Next.js API routes with Mongoose models to build full-stack apps with server-side rendering and secure data access.
  • Manage E-commerce Products and Orders
    Mongoose handles inventories, product variants, cart systems, and order relationships easily.
  • Build Real-Time Apps with Socket.io + Mongoose
    Use MongoDB as the data layer for messaging, notifications, live dashboards, and multiplayer games.
  • Create Social Media Features
    Likes, followers, posts, chats, and comments can all be modeled cleanly with Mongoose references and population.
  • Develop REST APIs and Microservices
    Mongoose works perfectly with Express, Koa, Hapi, and Nest.js for building scalable APIs.

These examples show how Mongoose powers everything from personal projects to large-scale production apps. .


We’ve now gone through the detailed technical aspects: schemas, CRUD, validation, middleware, population, and more. Time to return to our fun jungle theme as we wrap things up!


Final Words

You’re a Mongoose Master Tamer!
You just learned:

  • Connect & connection
  • Schemas with validation & defaults
  • CRUD with create, find, populate
  • Middleware, virtuals, indexes
  • Aggregation & references
  • Built a real API

Your Mission:
Create a Villain model with:

  • Required name & evilPower
  • Array of evilPlans (embedded)
  • Reference to rival Hero

Then populate and display rival hero name!
You’re now a Certified Node.js + Mongoose Jungle King!


Resources:
Mongoose Docs
Free MongoDB Atlas
Mongoose Guide


Next Adventure: Build a full REST API or Next.js app with Mongoose!
Your pet mongoose is ready for anything! ๐Ÿฆฆ

If you want next Part, where we build authentication + JWT + refresh tokens with Mongoose, comment below.

PyMongo Tutorial: Connect Python to MongoDB, CRUD, Aggregation & Beginner Guide (2025)


Working with MongoDB from Python using PyMongo

Your Python Superhero Sidekick for MongoDB (For Beginners to Expert Level)


๐Ÿ“˜ Table of Contents


Introduction

Imagine MongoDB is a huge magic library full of superhero files. Python is your loyal robot assistant who can run into the library, grab files, add new ones, change details, or even make smart reports, all with a few words of command!

PyMongo is the official Python “remote control” for MongoDB. With it, you can build apps, games, websites, chatbots, anything that needs to remember data.

MongoDB + Python is one of the most powerful combinations used in real-world applications. With PyMongo, you can store, search, update, and manage data for all kinds of projects. Developers use this combo to build web apps, CRUD APIs, data processing pipelines, automation tools, desktop utilities, and even small games that need to save player progress. If your project needs fast, flexible, JSON-like storage, MongoDB and Python make an amazing team.

This tutorial is designed as a complete PyMongo tutorial that helps you understand how to connect Python to MongoDB and start building real apps. Whether you are searching for a MongoDB Python beginner guide, want to perform MongoDB CRUD Python operations, or you are looking for a MongoDB Atlas connection example, this tutorial covers everything step-by-step.

You’ll also learn PyMongo aggregation examples and even how to build a Python project with MongoDB from scratch. Perfect for students, beginners, and developers who want a clear and practical path.

This tutorial is a fun adventure where we build a Hero Manager App together. It’s written so a student can follow every step, but it also has pro secrets for experienced coders.

Let’s power up Python!



Part 1: Setup - Install PyMongo & Start Your Robot

This section helps you install PyMongo, prepare your environment, and get MongoDB ready on your system locally or in the cloud.

Open your terminal/command prompt and type:

pip install pymongo

If you want the latest features (recommended in 2025):

pip install "pymongo[srv]"   # For MongoDB Atlas connections

Beginner Tip: If you don’t have Python, download it from python.org (version 3.9+ is perfect).


You need MongoDB running:

Local (from earlier tutorials) → mongodb://localhost:27017
Or free cloud → Sign up at cloud.mongodb.com (takes 2 minutes)


⚠️ Best Practice: Use a virtual environment to avoid dependency conflicts.

python -m venv venv
source venv/bin/activate   # macOS/Linux
venv\Scripts\activate      # Windows

๐Ÿ’ก Helpful Notes for Setup:

PyMongo automatically handles reconnections. You don't need to manually reopen the database connection. PyMongo keeps it alive and reconnects when needed.

⚠️ Security Warning: Never paste plain-text MongoDB Atlas credentials (like username/password) directly in blogs, GitHub, or shared code. Always store your credentials safely using environment variables or a .env file.

You now have PyMongo installed and MongoDB ready, its time to make your first real connection!



Part 2: First Connection - Wake Up Your Robot!

Here you will establish your first connection between Python and MongoDB, select your database, and verify that everything works.

Create a file hero_manager.py and write:

from pymongo import MongoClient

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

# Or connect to MongoDB Atlas (cloud)
# client = MongoClient("mongodb+srv://username:password@cluster0.xxxxx.mongodb.net/")

# Test connection
print(client.server_info()['version'])  # Prints something like 7.0.5

# Choose database and collection
db = client.heroAcademy
heroes = db.heroes

print("Python robot is ready! ๐Ÿš€")

Run it:

python hero_manager.py

You did it! Your Python script just shook hands with MongoDB!

⚠️ Security Tip: Never hard-code MongoDB Atlas usernames or passwords in code. Use environment variables instead:


import os
uri = os.getenv("MONGO_URI")
client = MongoClient(uri)

Your Python script can now talk to MongoDB. Next up: working with actual data.



Part 3: CRUD Operations - The Four Magic Spells

CRUD stands for Create, Read, Update, Delete, the four basic operations every database app must support. You will perform each one with PyMongo.

๐Ÿ’ก Before we begin CRUD operations, here are a few important notes:

✔ Every document you insert automatically receives an _id field. This _id is a unique identifier generated by MongoDB using the ObjectId type.

PyMongo insert operations return an ObjectId, not a string. This value helps you keep track of the exact document that was inserted.

ObjectId Example:

656e8c91f9a12345bcd67890

This is not random text, it encodes timestamp + machine info + process ID + counter.


๐ŸŸข Insert One Document

This command inserts a single hero document into the database.

# Add one hero
hero = {
    "name": "Aarav",
    "power": "Super Speed",
    "level": 85,
    "team": "Alpha"
}

result = heroes.insert_one(hero)
print("New hero ID:", result.inserted_id)

Expected Output:

New hero ID: 656e8c91f9a12345bcd67890

๐ŸŸฉ Insert Many Documents

Use this when you want to insert multiple heroes at once.

# Add many heroes
new_heroes = [
    {"name": "Priya", "power": "Invisibility", "level": 92, "team": "Alpha"},
    {"name": "Rohan", "power": "Fire", "level": 78, "team": "Beta"},
    {"name": "Sanya", "power": "Telekinesis", "level": 88, "team": "Alpha"}
]

result = heroes.insert_many(new_heroes)
print("Inserted IDs:", result.inserted_ids)

Expected Output:

[ObjectId('656e8d23a9...'), ObjectId('656e8d23aa...'), ObjectId('656e8d23ab...')]

๐Ÿ” Find Documents

These commands help you search and display specific heroes from the collection.

# Find one hero
hero = heroes.find_one({"name": "Aarav"})
print(hero)

# Find many
for hero in heroes.find({"team": "Alpha"}):
    print(hero["name"], "-", hero["power"])

Example Output:

{'_id': ObjectId('656e8c91f9a12345bcd67890'), 'name': 'Aarav', 'power': 'Super Speed', 'level': 85, 'team': 'Alpha'}
Priya - Invisibility
Sanya - Telekinesis

๐Ÿ“ˆ Update Documents

These commands modify existing heroes by changing or incrementing fields.

# Update one
heroes.update_one(
    {"name": "Aarav"},
    {"$set": {"level": 90, "newPower": "Lightning Speed"}}
)

Expected Output: (nothing printed, but database is updated)


๐Ÿ—‘️ Delete Documents

Use these examples to remove heroes based on filters.

# Delete one
result = heroes.delete_one({"name": "Rohan"})
print(result.deleted_count)

Expected Output:

1     #1 document deleted
#PyMongo actually returns a result object.

You now know the four core database skills: inserting, reading, updating, and deleting data just like a real backend developer.




Part 4: Working with Nested Data & Arrays (Russian Dolls Again!)

MongoDB stores rich JSON-like documents. This section shows how to query and update nested objects and arrays effectively.

hero = {
    "name": "YouTheWizard",
    "profile": {
        "age": 100,
        "city": "CodeLand"
    },
    "skills": ["Python", "MongoDB", "Magic"],
    "missions": [
        {"name": "Save Tutorial", "reward": 1000, "completed": True}
    ]
}

heroes.insert_one(hero)

# Query nested
you = heroes.find_one({"profile.city": "CodeLand"})
print(you)

# Add new skill
heroes.update_one(
    {"name": "YouTheWizard"},
    {"$push": {"skills": "PyMongo Master"}}
)

⚠️ Note: Avoid very deep nested structures (more than 3 levels). This can slow down queries.

๐Ÿงน Removing Items from an Array Using $pull

You can also remove elements from an array. For example, this removes "Magic" from the hero's skills list.

heroes.update_one(
    {"name": "YouTheWizard"},
    {"$pull": {"skills": "Magic"}}
)

Expected Output:

1 document updated


Part 5: Aggregation - Make Smart Reports!

Aggregation lets you generate reports, leaderboards, analytics, and grouped summaries using powerful MongoDB pipelines.

⭐ Example: Team Leaderboard (Match → Group → Sort)

pipeline = [
    {"$match": {"level": {"$gte": 80}}},                    # Step 1: Filter strong heroes
    {"$group": {
        "_id": "$team",                                     # Step 2: Group by team
        "avgLevel": {"$avg": "$level"},
        "total": {"$sum": 1}
    }},
    {"$sort": {"avgLevel": -1}}                            # Step 3: Highest average first
]

import pprint
for report in heroes.aggregate(pipeline):
    pprint.pprint(report)

Example Output:

{'_id': 'Alpha', 'avgLevel': 90.0, 'total': 3}
{'_id': 'Beta', 'avgLevel': 78.0, 'total': 1}

You just made a leaderboard with 5 lines of code, learned how to generate meaningful insights from data using MongoDB’s aggregation pipeline.

๐Ÿง  Understanding the Aggregation Pipeline (Visual Breakdown)

The aggregation pipeline processes documents step-by-step. Here's the flow of the example pipeline:

1️⃣ $match - Filter documents first (like WHERE in SQL)

2️⃣ $group - Group heroes by team and calculate stats

3️⃣ $sort - Sort groups by average level (orders the results)


✨ Bonus: Aggregation with $project

$project lets you select or reshape fields in the result. Below example shows only name, power, and a computed field powerLength.

pipeline = [
    {"$match": {"team": "Alpha"}},   # Only Alpha heroes
    {"$project": {
        "_id": 0,                     # Hide _id
        "name": 1,
        "power": 1,
        "powerLength": {"$strLenCP": "$power"}  # New computed field
    }}
]

for hero in heroes.aggregate(pipeline):
    pprint.pprint(hero)

Example Output:

{'name': 'Aarav', 'power': 'Super Speed', 'powerLength': 11}
{'name': 'Priya', 'power': 'Invisibility', 'powerLength': 12}
{'name': 'Sanya', 'power': 'Telekinesis', 'powerLength': 12}


Part 6: Using MongoDB Compass with Python (Best of Both Worlds)

Write data with Python → instantly see it in Compass!
Perfect for debugging and learning.

Part 7: Error Handling & Safety (Don’t Let Your Robot Crash!)

Error handling helps your app stay stable even when the database is offline or when duplicate data appears.

from pymongo.errors import ConnectionFailure, DuplicateKeyError

try:
    client.admin.command('ping')
    print("MongoDB is alive!")
except ConnectionFailure:
    print("Server not available! Check if MongoDB is running.")

Add unique index and handle duplicates:

db.heroes.create_index("name", unique=True)

try:
    heroes.insert_one({"name": "Aarav"})  # Will fail if exists
except DuplicateKeyError:
    print("Hero already exists!")

⚠️ Recommended: Set a connection timeout to handle unreachable servers faster.


client = MongoClient(
    "mongodb://localhost:27017",
    serverSelectionTimeoutMS=3000
)


Part 8: Pro Features for Experienced Coders

This part is for advanced users, async operations for speed, transactions for reliability, and bulk operations for performance.

1. MongoDB Atlas (Cloud) Connection String Example

client = MongoClient(
    "mongodb+srv://myUser:myPassword@cluster0.abc123.mongodb.net/?retryWrites=true&w=majority"
)

2. Async PyMongo (Fast for Web Apps)

# pip install "motor"
import motor.motor_asyncio

client = motor.motor_asyncio.AsyncIOMotorClient("mongodb://localhost:27017")
db = client.heroAcademy
heroes = db.heroes

async def add_hero():
    await heroes.insert_one({"name": "Async Hero", "level": 99})

import asyncio
asyncio.run(add_hero())

3. Transactions (All or Nothing - Perfect for Banking/Games)

with client.start_session() as session:
    with session.start_transaction():
        heroes.update_one({"name": "A"}, {"$inc": {"gold": -100}}, session=session)
        heroes.update_one({"name": "B"}, {"$inc": {"gold": 100}}, session=session)

4. Bulk Operations (Super Fast for Big Data)

from pymongo import UpdateOne

requests = [
    UpdateOne({"name": "Aarav"}, {"$inc": {"level": 1}}),
    UpdateOne({"name": "Priya"}, {"$inc": {"level": 1}})
]

result = heroes.bulk_write(requests)
print(f"Modified {result.modified_count} heroes!")

⚠️ Security Warning: Never push MongoDB connection strings to GitHub. Use environment variables or secret managers.



Part 9: Mini Project - Build Your Own Hero Manager App!

Now you will build a real Hero Manager App using everything you have learned. CRUD, sorting, and live user input.

Create my_hero_app.py:

from pymongo import MongoClient
import pprint

client = MongoClient("mongodb://localhost:27017")
db = client.heroAcademy
heroes = db.heroes

def add_hero():
    name = input("Hero name: ")
    power = input("Power: ")
    level = int(input("Level (1-100): "))
    heroes.insert_one({"name": name, "power": power, "level": level})
    print("Hero added! ๐ŸŽ‰")

def show_top_heroes():
    print("\n๐Ÿ† TOP HEROES ๐Ÿ†")
    for hero in heroes.find().sort("level", -1).limit(5):
        pprint.pprint(hero)

while True:
    print("\n1. Add Hero\n2. Show Top 5\n3. Exit")
    choice = input("Choose: ")
    if choice == "1":
        add_hero()
    elif choice == "2":
        show_top_heroes()
    elif choice == "3":
        break

Run it and play! You just built a real app!

With your Hero Manager App complete, you have built a real Python + MongoDB application.




Part 10: Cheat Sheet (Print & Stick!)

# Connection
client = MongoClient("mongodb://localhost:27017")
db = client.mydb
coll = db.mycollection

# CRUD
coll.insert_one(doc)
coll.insert_many(docs)
coll.find_one(filter)
list(coll.find(filter))
coll.update_one(filter, update)
coll.update_many(filter, update)
coll.delete_one(filter)
coll.delete_many(filter)

# Common
coll.count_documents(filter)
coll.create_index("field") 
coll.aggregate(pipeline)

#projection
coll.find({}, {"_id": 0})   # projection example



Final Words

You Did It!

You now know how to:

  • Connect Python to MongoDB
  • Do all CRUD operations
  • Query, update nested data, aggregate
  • Build real apps
  • Use pro features like async, transactions, bulk writes

Your Python Mission:
Run the mini project, add yourself as a hero with level 100, then show the top heroes list.

You are now a Certified Python + MongoDB Superhero Developer!

Resources:
PyMongo Docs
MongoDB Atlas Free Tier
Motor for Async (Async MongoDB Driver)
Next Level: Working with MongoDB from Node.js using Mongoose

Disclaimer: Code examples are simplified for clarity. In production, always implement proper validation, schema design, and environment variable management.

Keep coding. The world needs more heroes like you! ๐Ÿš€

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