MongoDB Mechanics

Model. Query. Optimise NoSQL.

Dive into the core mechanics of MongoDB through Python-based implementations using PyMongo. This repository offers hands-on examples covering CRUD operations, schema design strategies, indexing techniques, and the powerful aggregation framework. From simple queries to optimised NoSQL architectures, this is your toolkit for mastering document-based databases in practical contexts.

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1. Getting Started with MongoDB

1.1 Introduction to MongoDB and NoSQL Concepts

1.2 Installing & Setting Up MongoDB (Local & Cloud)

1.3 Connecting to MongoDB with Python (PyMongo, MongoEngine)

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2. Working with Documents & Collections

2.1 CRUD Operations (Insert, Find, Update, Delete)

✦ Querying JSON Documents in MongoDB Using Python
✦ Updating JSON Documents in MongoDB Using Python

2.2 Data Modeling and Schema Design

2.3 Indexes and Unique Constraints

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3. Advanced Queries & Aggregations

3.1 Query Operators and Expressions

3.2 Aggregation, Grouping, Sorting, and Projection

✦ Grouping and Aggregation in MongoDB Using Python
✦ CRUD Operations, Grouping & Aggregation in MongoDB Using Python
✦ Order Trends Analysis Using Grouping & Aggregation

3.3 Text Search, Geospatial Queries, and Array Operators

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4. Data Import, Export, and Management

4.1 Importing & Exporting Data (CSV, JSON, BSON)

4.2 Bulk Operations and Data Migration

4.3 Data Validation and Schema Enforcement

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