Introduction

Documents are the records of MongoDB, stored in an efficient binary form called BSON, allowing record manipulation that is cosmetically similar to JSON. In Python these are typically represented as dictionaries, Python's native mapping type. Marrow Mongo provides a Document mapping type that is directly compatible with and substitutable anywhere PyMongo uses dictionaries.

This package utilizes the Marrow Schema declarative schema toolkit and extends it to encompass MongoDB data storage concerns. Its documentation may assist you in understanding the processes involved in Marrow Mongo. At a fundamental level you define data models by importing classes describing the various components of a collection, such as Document, ObjectId, or String, then compose them into a declarative class model whose attributes describe the data structure, constraints, etc.

Field types and Document mix-in classes (traits) meant for general use are registered using Python standard entry points and are directly importable from the marrow.mongo.field and marrow.mongo.trait package namespaces respectively.

Within this guide fields are broadly organized into three categories:

• Simple fields are fields that hold scalar values, variables that can only hold one value at a time. This covers most datatypes you use without thinking: strings, integers, floating point or decimal values, etc.

• Complex fields cover most of what's left: variables that can contain multiple values. This includes arrays (list in Python, Array in JavaScript), compound mappings (embedded documents), etc.

• Complicated fields are represented by fields with substantial additional logic associated with them, typically through complex typecasting, or by including wrapping objects containing additional functionality. These are separate as they represent substantial additions to core MongoDB capabilities, possibly with additional external dependencies.