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A convenient Redis client wrapper with JSON and datetime support.

Project description

Redis Client Wrapper

A convenient Redis client wrapper with JSON and datetime support.

Installation

Requires Redis server and redis-py library:

pip install redis

Usage

Initialization

from dgredis.conf import RedisConfig
from dgredis import RedisClient

config = RedisCoonfig(
    host="localhost",
    port=6379,
    password=None
)

client = RedisClient(config)

Core Methods

JSON Operations

# Store JSON data
data = {"name": "John", "date": datetime.now()}
client.set_json_key("user:1", data, ttl=3600)

# Retrieve JSON data
result = client.get_json_key("user:1")

Basic Key Operations

# Set value
client.set_key("last_update", datetime.now(), ttl=60)

# Get value
last_update = client.get_key("last_update")

Key Type Check

key_type = client.get_key_type("user:1")

Features

  1. Automatic serialization/deserialization:

    • datetime/date objects to/from ISO format
    • Complex structures (dict, list, tuple, set) to/from JSON
  2. Time-to-live (TTL) support for keys

  3. Support for both JSON documents (*_json_key methods) and simple keys

Technical Details

Serialization Behavior

  • Dates and datetimes are stored in ISO8601 format (UTC)
  • Nested structures are automatically handled recursively
  • Original Redis types are preserved when possible

Error Handling

  • Invalid dates fall back to string values
  • JSON decode errors return raw values

Requirements

  1. Redis server 4.0+ for JSON functionality
  2. Python 3.7+ (uses datetime.fromisoformat())

Limitations

  1. JSON operations require RedisJSON module
  2. Custom classes are not automatically serialized
  3. Timezone-naive datetimes are assumed to be in local timezone

Examples

Working with Nested Structures

data = {
    "user": "Alice",
    "login_dates": [datetime(2023,1,1), datetime(2023,1,15)],
    "preferences": {"dark_mode": True}
}
client.set_json_key("user:alice", data)

TTL Management

# Set key with 5 minute expiration
client.set_key("temp_data", {"value": 42}, ttl=300)

# Check remaining TTL (using native redis client)
remaining_ttl = client.client.ttl("temp_data")

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