COMP1531
🐶 Software Engineering
5.3 - Development - Persistence
Author: Hayden Smith 2021
In this lecture
Why?
- Data is a critical part of nearly every software system, so let's understand it's interactions
What?
- Data
- Persistence
- Persistence in python
Data
Data: Facts that can be recorded and have implicit meaning
From data (raw) was can find insights (information) that allow us to make decisions.
Data (and "big data") are becoming huge topics in the world of computing and mathematics. This course does not address these topics.
Data in Applications
Data is part of every part of software (e.g. variables).
However, often when we refer to "Data" in software we're referring to a "Data Layer" - a part of the software that is focused solely on housing data.
Business Logic
Services Layer
Data Layer
Often stateless
Often stateless
Often has State
Interface layer
Often stateless
Receiving and responding to requests
Executing behaviour defined by the stakeholders
Generic system or user defined libraries
Storage of data
Data Layers ("Databases")
Database: A word used to describe a store of data. Databases are typically what a data layer consists of.
There are 3 main ways to store data:
- In-memory (non-persistent)
- In-file (filesystem direct storage)
- In-database (Relational SQL, NoSQL)
As you move down the list, barrier to entry becomes higher, but so does performance.
To learn more about relational SQL, study COMP3311.
Storing Data: Persistence
Persistence: When program state outlives the process that created it. This is achieved by storing the state as data in computer data storage.
Persistence can be interpreted very broadly, though in this course we will define it as storing data to disk.
Storing Data: Persistence
Can we modify our project server to persistently store data? How would we do that?
Python specific - pickling
A very common and popular method of storing data in python is to "pickle" the file.
- Pickling a file is a lot like creating a .zip file for a variable.
- This "variable" often consists of many nested data structures (a lot like your iteration 2 data)
Let's look at an example
pickle_it.py
unpickle_it.py
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