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Master MongoDB CRUD operations, document insertion, querying, updating, and deletion. Learn BSON format, ObjectId, data types, and basic operations. Use when working with documents, collections, and fundamental MongoDB operations.

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SKILL.md

name mongodb-crud-operations
version 2.1.0
description Master MongoDB CRUD operations, document insertion, querying, updating, and deletion. Learn BSON format, ObjectId, data types, and basic operations. Use when working with documents, collections, and fundamental MongoDB operations.
sasmp_version 1.3.0
bonded_agent 01-mongodb-fundamentals
bond_type PRIMARY_BOND
capabilities document-insertion, document-querying, document-updating, document-deletion, bulk-operations, atomic-operations
input_validation [object Object]
output_format [object Object]
error_handling [object Object]
prerequisites [object Object]
testing [object Object]

MongoDB CRUD Operations

Master fundamental MongoDB Create, Read, Update, Delete operations.

Quick Start

Connect to MongoDB

const { MongoClient } = require('mongodb');

const client = new MongoClient('mongodb://localhost:27017');
await client.connect();

const db = client.db('myapp');
const users = db.collection('users');

Create Documents

// Insert one document
const result = await users.insertOne({
  name: 'John Doe',
  email: 'john@example.com',
  age: 30,
  createdAt: new Date()
});
console.log('Inserted ID:', result.insertedId);

// Insert multiple documents
await users.insertMany([
  { name: 'Alice', email: 'alice@example.com' },
  { name: 'Bob', email: 'bob@example.com' }
]);

Read Documents

// Find one document
const user = await users.findOne({ email: 'john@example.com' });

// Find all documents
const allUsers = await users.find({}).toArray();

// Find with filter
const activeUsers = await users.find({ status: 'active' }).toArray();

// Find by ObjectId
const { ObjectId } = require('mongodb');
const user = await users.findOne({ _id: new ObjectId('...') });

Update Documents

// Update one document
const result = await users.updateOne(
  { email: 'john@example.com' },
  { $set: { age: 31, updatedAt: new Date() } }
);

// Update multiple documents
await users.updateMany(
  { status: 'inactive' },
  { $set: { lastNotified: new Date() } }
);

// Replace entire document
await users.replaceOne(
  { _id: userId },
  { name: 'New Name', email: 'new@example.com' }
);

Delete Documents

// Delete one document
await users.deleteOne({ email: 'john@example.com' });

// Delete multiple documents
await users.deleteMany({ status: 'deleted' });

// Delete all documents (careful!)
await users.deleteMany({});

BSON Data Types

// String
{ name: 'John' }

// Number (int32, int64, double)
{ age: 30, price: 19.99 }

// Boolean
{ isActive: true }

// Date
{ createdAt: new Date() }

// Array
{ tags: ['mongodb', 'database', 'nosql'] }

// Object (embedded document)
{ address: { city: 'New York', zip: '10001' } }

// ObjectId (default _id field)
{ _id: ObjectId('507f1f77bcf86cd799439011') }

// Null
{ description: null }

// Binary Data
{ image: Buffer.from('data') }

// Regular Expression
{ email: /.*@example\.com/ }

Key Concepts

  • _id Field: Automatically generated ObjectId, unique identifier
  • Collections: Tables equivalent in SQL
  • Documents: JSON-like records (up to 16MB)
  • Field Names: Case-sensitive, cannot start with $
  • Operators: $set, $inc, $push, $pull, $unset, etc.

Python Example (PyMongo)

from pymongo import MongoClient
from datetime import datetime

client = MongoClient('mongodb://localhost:27017')
db = client['myapp']
users = db['users']

# Insert
result = users.insert_one({
    'name': 'John',
    'email': 'john@example.com',
    'createdAt': datetime.now()
})

# Read
user = users.find_one({'email': 'john@example.com'})

# Update
users.update_one(
    {'_id': result.inserted_id},
    {'$set': {'age': 30}}
)

# Delete
users.delete_one({'_id': result.inserted_id})

Best Practices

✅ Always handle errors with try-catch ✅ Use connection pooling ✅ Close connections properly ✅ Use ObjectId for _id fields ✅ Validate data before insertion ✅ Use appropriate write concerns ✅ Index frequently queried fields ✅ Plan for schema evolution