Cache backends (memory, Redis, Memcached) in Django - Step-by-Step Execution

Concept Flow - Cache backends (memory, Redis, Memcached)

Request comes in

↓

Check cache backend

↓

Memory Cache?

Yes→Look in memory cache

↓

Return cached data

↓

Redis Cache?

Yes→Look in Redis

↓

Return cached data

↓

Memcached?

Yes→Look in Memcached

↓

Return cached data

↓

Cache miss

↓

Generate data

↓

Store data in cache backend

↓

Return data to user

When a request needs data, Django checks the configured cache backend (memory, Redis, or Memcached). If data is found, it returns it immediately. If not, it generates the data, stores it in the cache, then returns it.

Execution Sample

Django

from django.core.cache import cache

# Try to get data from cache
data = cache.get('my_key')
if data is None:
    data = 'expensive data'
    cache.set('my_key', data, timeout=60)

This code tries to get 'my_key' from the cache. If missing, it sets 'expensive data' in the cache for 60 seconds.

Execution Table

Step	Action	Cache Backend	Cache Get Result	Cache Set Action	Output
1	cache.get('my_key')	Memory/Redis/Memcached	None (cache miss)	No	None
2	Check if data is None	-	True	-	Proceed to generate data
3	Set data = 'expensive data'	-	-	-	'expensive data'
4	cache.set('my_key', data, 60)	Memory/Redis/Memcached	-	Store 'expensive data' with 60s timeout	-
5	Return data	-	-	-	'expensive data'

💡 Data was not in cache initially, so it was generated and stored; then returned.

Variable Tracker

Variable	Start	After Step 1	After Step 3	After Step 5
data	undefined	None	'expensive data'	'expensive data'

Key Moments - 3 Insights

Why does cache.get return None at first?

Because the key 'my_key' is not yet stored in the cache backend, so cache.get returns None indicating a cache miss (see execution_table step 1).

What happens if we don't set the cache after a miss?

The data would be generated every time, causing slower responses. Setting cache stores the data for future quick access (see execution_table step 4).

Can the cache backend affect how data is stored or retrieved?

Yes, different backends like memory, Redis, or Memcached have different storage methods and performance, but Django's cache API works the same way for all (see concept_flow).

Visual Quiz - 3 Questions

Look at the execution_table, what is the value of 'data' after step 1?

A 'expensive data'

B None

C Undefined

D Cache backend object

💡 Hint

Check the 'Cache Get Result' and 'Output' columns at step 1 in execution_table.

At which step is the cache updated with new data?

A Step 4

B Step 3

C Step 2

D Step 5

💡 Hint

Look for 'Cache Set Action' column in execution_table.

If the cache backend was Redis instead of memory, how would the execution_table change?

A Output would be different

B Cache Get Result would be different

C Cache Set Action would mention Redis specifically

D No change in the table content

💡 Hint

Refer to the 'Cache Backend' and 'Cache Set Action' columns in execution_table.

Concept Snapshot

Django cache backends store data for quick reuse.
Use cache.get(key) to read cached data.
If None, generate data and cache.set(key, data, timeout).
Backends include memory, Redis, Memcached.
All use same API but differ in storage and speed.
Cache reduces repeated expensive operations.

Full Transcript

This visual execution shows how Django uses cache backends like memory, Redis, or Memcached. When a request asks for data, Django first checks the cache with cache.get. If the data is missing (cache miss), it generates the data, stores it in the cache with cache.set, then returns it. The execution table traces these steps, showing the variable 'data' starting as None, then being set to 'expensive data' and cached. Key moments clarify why cache.get returns None initially and why setting the cache is important. The quiz tests understanding of cache state at each step and backend differences. This helps beginners see how caching speeds up repeated data access in Django.