Chapter 2. Reading and Writing to MongoDB with Python
MongoDB is a document-oriented database. This is different from a relational database in two significant ways. Firstly, not all entries must adhere to the same schema. Secondly you can embed entries inside of one another. Despite these major differences, there are analogs to SQL concepts in MongoDB. A logical group of entries in a SQL database is termed a table. In MongoDB, the analogous term is a collection. A single entry in a SQL databse is termed a row. In MongoDB, the analog is a document.
Table 2-1. Comparison of SQL/RDBMS and MongoDB Concepts and Terms
Concept | SQL | MongoDB |
---|---|---|
One User | One Row | One Document |
All Users | Users Table | Users Collection |
One Username Per User (1-to-1) | Username Column | Username Property |
Many Emails Per User (1-to-many) | SQL JOIN with Emails Table | Embed relevant email doc in User Document |
Many Items Owned by Many Users (many-to-many) | SQL JOIN with Items Table | Programmatically Join with Items Collection |
Hence, in MongoDB, you are mostly operating on documents and collections of documents. If you are familiar with JSON, a MongoDB document is essentially a JSON document with a few extra features. From a Python perspective, it is a Python dictionary.
Consider the following example of a user document with a username, first name, surname, date of birth, email address and score:
from datetime import datetime user_doc = { "username" : "janedoe", "firstname" : "Jane", "surname" : "Doe", "dateofbirth" : datetime(1974, 4, 12), "email" : ...
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