https://github.com/lingfromsh/psychic-spoon
A tool for managing chaos cache keys.
https://github.com/lingfromsh/psychic-spoon
Last synced: 4 months ago
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A tool for managing chaos cache keys.
- Host: GitHub
- URL: https://github.com/lingfromsh/psychic-spoon
- Owner: lingfromSh
- Created: 2022-02-14T02:43:33.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2022-06-28T08:04:36.000Z (almost 3 years ago)
- Last Synced: 2025-01-09T03:50:19.454Z (5 months ago)
- Language: Python
- Homepage:
- Size: 67.4 KB
- Stars: 2
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Psychic Spoon
## Introduction
Cache key management always is a tough task during developing.
Cache a data may involve generating keys, converting data to right struct, assigning expiration, converting raw to
proper python type and handling failures.
The purpose of `Psychic Spoon` is to keep your plenty of cache keys clear.
## Concepts
In KV databases, a key is used as the unique identification to access the value. In practice, keys with the same pattern
are generally designed as a kind of data with the same structure. And Various KV databases almost are same.
Therefore, `Psychic Spoon` provides:
1. a key object to describe key's pattern and data structure.
2. a type object to describe data in python.
3. a backend object to describe how data in python to store in database.
### Key
```python
from psychic_spoon.key import Key
```
### Type
- Boolean
- Dict (support nested)
- Float
- Integer
- List (support nested)
- Set (support nested)
- String
### Backend
- RedisBackend
- RedisStringBackend
- RedisSetBackend
## Usage
For example, we need a redis string to store a user's session dict.
```python
from datetime import timedelta
from psychic_spoon.key import Key
from psychic_spoon.types.dict import Dict
from psychic_spoon.types.integer import Integer
from psychic_spoon.types.set import Set
from psychic_spoon.types.string import String
from psychic_spoon.backends.redis_backend import RedisStringBackend
backend = RedisStringBackend(host="localhost", port=6379)
user_session_cache = Key("user:{id}:session",
datatype=Dict(
username=String,
name=String,
age=Integer,
roles=Set(Integer),
ip_address=Dict(
type=String,
address=String
)
),
backend=backend,
ttl=timedelta(hours=12))
key = user_session_cache.build_key(id=1)
user_dict = {
"username": "jame-curtis",
"name": "James Curtis",
"age": 26,
"roles": {15, 82, 81},
"ip_address": {
"type": "ipv4",
"address": "192.168.1.1"
}
}
# Save your cache
user_session_cache.set(key, user_dict)
# Fetch your cache
user_dict = user_session_cache.get(key)
```
## Roadmap
- [ ] An event loop to handling success/failure callback
- [ ] Replace pottery with RedisBackend
- [ ] More support to redis model