Beginner’s guide to pymongo using Spotify Top50 2019 songs

Beginner’s guide to pymongo using Spotify Top50 2019 songs

This post aims to explain how can pymongo be used in order to interface with mongoDB to perform CRUD operations. In order to follow through this post, it’s recommended but not compulsory if you have a basic working knowledge of mongoDB and what it is.

This post aims to explain how can pymongo be used in order to interface with mongoDB to perform CRUD operations. In order to follow through this post, it’s recommended but not compulsory if you have a basic working knowledge of mongoDB and what it is. The topics covered in this post are as follows

If you’re interested only in a specific section, click on the topic above to navigate directly to the respective section.

Photo by Akshay Chauhan on Unsplash

Introduction

MongoDB is a NoSQL (Not only SQL) database which is one of the most widely used databases. It’s natively written in C++ which makes it quite fast and efficient while performing CRUD applications.

To be specific, MongoDB is a document database in which records or entries are stored as documents in a key-value format, very similar to how json or python dictionaries are; thereby allowing the use of object notation to retrieve data from the database.

One of the plus points of using mongoDB is that being a NoSQL database, one isn’t constrained by the type of data that could be stored in the database as long as it follows a key-value pair. In SQL, there’s a very strict schema that every record has to adhere to making it very rigid whereas MongoDB allows full flexibility in that aspect. In some applications, we don’t know ahead of time what & how much data would come and yet need to store it to the database; mongoDB is the way to go about tackling such use cases.

A comparative analysis of terminologies involved in mongoDB and SQL can give a better understanding of the mongoDB service for storing data; this is as follows:

  • Database is a group of data which is stored on the server; it is referred to as database in both mongoDB and SQL.
  • A database is made up of quantum of smaller groups called collections in mongoDB or table in SQL.
  • A row in SQL consists of records or rows holding data of certain datatypes which is also referred to as document in mongoDB.
  • A column in SQL consists of a feature which can hold data of a certain datatype; this is referred to as a field in mongoDB. The key difference is that in mongoDB, fields across documents could be different whereas for a SQL table, the columns must be the same for all rows.

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