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Data storage

Data storage is the retention of data on physical or logical media so it can be accessed or retrieved later.

How 2 Manning books explain it

Think Like a CTO

Data storage is the retention of data on physical or digital media so that it can be accessed and used later.

How it is used
Frames where data should reside as a long-term technology decision serving business use.
How deep it goes
Defines files, relational stores, and NoSQL stores, but stops short of a selection procedure.
Examples
Uses spreadsheets, JSON, XML, CSV, TXT, SQL tables, and document collections to make storage types concrete.
What you can do after
Evaluate/understand broad storage options and question whether cheap storage justifies retaining everything.

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A Pythonic Adventure: From Python basics to a working web app

Data storage is the retention of program data so that it can be retrieved after or beyond the current execution.

How it is used
Stores collected orders in orders.json so the application preserves them beyond its current run.
How deep it goes
Explains file existence checks, JSON loading and saving, missing-file fallback, and menu integration.
Examples
Uses orders.json, JSON order lists, os.path.exists(), and load_orders and save_orders functions.
What you can do after
Operate a file-backed order program by loading existing orders, appending confirmed orders, and saving them.

Read how A Pythonic Adventure: From Python basics to a working web app explains data storage →

Related concepts

These guides are generated from the text of Manning books by Manning's knowledge graph and link to the sections they draw on. The full books are available on liveBook and at manning.com.