A PostgreSQL wrapper similar to diskcache
Project description
PgCache and AsyncPgCache Usage Guide
Introduction
PgCache
and AsyncPgCache
are cache management classes for PostgreSQL databases. PgCache
provides synchronous
operations, while AsyncPgCache
offers asynchronous operations. They allow you to cache data in a PostgreSQL database
and provide functionalities to set, get, delete, and import/export cache entries.
Installation
Before using these classes, ensure you have the following Python packages installed:
pip install -r requirements.txt
or pip install pg-cache
Usage
PgCache
Initialization
from pg_cache import PgCache
db_url = "postgresql://user:password@localhost/dbname"
table_name = "cache_table"
cache = PgCache(db_url, table_name)
cache.init_db()
Set Cache
cache.set("my_key", "my_value", expire_after_seconds=3600)
Set Bulk Cache
entries
= [
{"key": "key1", "value": "value1"},
{"key": "key2", "value": "value2"}
]
cache.set_bulk(entries, expire_after_seconds=3600)
Get Cache
value = cache.get("my_key")
Delete Cache
cache.delete("my_key")
Delete Bulk Cache
keys = ["key1", "key2"]
cache.delete_bulk(keys)
Flush Cache
cache.flushdb()
Export Cache to File
cache.export_to_file("cache_backup.json")
Import Cache from File
cache.import_from_file("cache_backup.json")
AsyncPgCache
Initialization
import asyncio
from your_module import AsyncPgCache
db_url = "postgresql+asyncpg://user:password@localhost/dbname"
table_name = "cache_table"
cache = AsyncPgCache(db_url, table_name)
async def init():
await cache.init_db()
asyncio.run(init())
Set Cache
async def set_cache():
await cache.set("my_key", "my_value", expire_after_seconds=3600)
asyncio.run(set_cache())
Set Bulk Cache
entries = [
{"key": "key1", "value": "value1"},
{"key": "key2", "value": "value2"}
]
async def set_bulk_cache():
await cache.set_bulk(entries, expire_after_seconds=3600)
asyncio.run(set_bulk_cache())
Get Cache
async def get_cache():
value = await cache.get("my_key")
print(value)
asyncio.run(get_cache())
Delete Cache
async def delete_cache():
await cache.delete("my_key")
asyncio.run(delete_cache())
Delete Bulk Cache
keys = ["key1", "key2"]
async def delete_bulk_cache():
await cache.delete_bulk(keys)
asyncio.run(delete_bulk_cache())
Flush Cache
async def flush_cache():
await cache.flushdb()
asyncio.run(flush_cache())
Export Cache to File
async def export_cache():
await cache.export_to_file("cache_backup.json")
asyncio.run(export_cache())
Import Cache from File
async def import_cache():
await cache.import_from_file("cache_backup.json")
asyncio.run(import_cache())
Logging
You can control the logging level by setting the log_level
parameter when initializing PgCache
or AsyncPgCache
.
For example:
cache = PgCache(db_url, table_name, log_level=logging.INFO)
Conclusion
PgCache
and AsyncPgCache
provide powerful cache management functionalities suitable for applications that need to
cache data in a PostgreSQL database. With both synchronous and asynchronous implementations, you can choose the
appropriate method based on your needs.
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