dankmemer.py

Release candidate Notice:

dankmemer.py is currently in its release candidate stage. At this stage, all routes are implemented however they may be a few bugs present.

dankmemer.py is a lightweight asynchronous Python wrapper for the DankAlert API — it allows you to easily access Dank Memer-related data (such as items and NPCs) using powerful filtering and built-in caching.

🚀 Features

• Built-in caching with configurable TTL
• Powerful filtering with support for exact, fuzzy, membership (IN), and numeric range queries
• Anti-rate-limit handling

📦 Installation

You can install the project using either of the following aliases:

pip install dankmemer
pip install dankmemer.py

💡 Basic Usage Example

Below are two examples that demonstrate filtering using the new interfaces.

Example 1: Filtering Items

# This example prints the names of items where the 'name' field contains either "melmsie" or "appl"
print(
    [
        e.name for e in (
            await client.items.query(ItemsFilter(name=IN("melmsie", "appl")))
        )
    ]
)

Example 2: Filtering NPCs

# This example prints the names of NPCs whose name contains the substring "chad"
print(
    [
        e.name for e in (
            await client.npcs.query(NPCsFilter(name=IN("chad")))
        )
    ]
)

Quick Start:

Below is a minimal example that shows how to use the client with filtering:

import asyncio
from dankmemer import DankMemerClient, ItemsFilter, NPCsFilter, Fuzzy, IN

async def main():
    async with DankMemerClient() as client:
        # Query all items (no filtering)
        all_items = await client.items.query()
        print("All items:", all_items)

        # Query items with fuzzy matching on name.
        filtered_items = await client.items.query(ItemsFilter(name=Fuzzy("trash", cutoff=80)))
        print("Filtered items:", filtered_items)

        # Query NPCs with membership filtering on name.
        filtered_npcs = await client.npcs.query(NPCsFilter(name=IN("chad")))
        print("Filtered NPCs:", filtered_npcs)

asyncio.run(main())

Documentation:

Full documentation is under development and will soon be available on Read the Docs at:

https://dankmemerpy.readthedocs.io

Feel free to test, report issues, and contribute to this alpha release!