Features/dft

folding/miners/dft_miner.py

@@ -0,0 +1,70 @@
+import os
+import time
+import json
+import random
+import asyncio
+import requests
+import traceback
+import concurrent.futures
+from collections import defaultdict
+
+from typing import Any
+
+import psi4
+
+from folding.miners.miner_mixin import MinerMixin
+from folding.base.miner import BaseMinerNeuron
+from folding.utils.logger import logger
+
+
+class DFTMiner(BaseMinerNeuron, MinerMixin):
+    def __init__(self, config=None):
+        super().__init__(config=config)
+
+        # TODO: There needs to be a timeout manager. Right now, if
+        # the simulation times out, the only time the memory is freed is when the miner
+        # is restarted, or sampled again.
+
+        self.miner_data_path = os.path.join(self.project_path, "miner-data")
+        self.base_data_path = os.path.join(
+            self.miner_data_path, self.wallet.hotkey.ss58_address[:8]
+        )
+        self.local_db_address = os.getenv("RQLITE_HTTP_ADDR")
+        self.simulations = DFTMiner.create_default_dict()
+
+        self.max_workers = self.config.neuron.max_workers
+        logger.info(f"🚀 Starting DFTMiner that handles {self.max_workers} workers 🚀")
+
+        self.executor = concurrent.futures.ProcessPoolExecutor(
+            max_workers=self.max_workers
+        )  # remove one for safety
+
+        self.mock = None
+        self.generate_random_seed = lambda: random.randint(0, 1000)
+        asyncio.run(self.start_rqlite())
+        time.sleep(5)
+
+    @staticmethod
+    def create_default_dict():
+        def nested_dict():
+            return defaultdict(
+                lambda: None
+            )  # allows us to set the desired attribute to anything.
+
+        return defaultdict(nested_dict)
+
+    def response_to_dict(self, response) -> dict[str, Any]:
+        response = response.json()["results"][0]
+
+        if "error" in response.keys():
+            raise ValueError(f"Failed to get all PDBs: {response['error']}")
+        elif "values" not in response.keys():
+            return {}
+
+        columns = response["columns"]
+        values = response["values"]
+        data = [dict(zip(columns, row)) for row in values]
+        return data
+
+    def run(self):
+        pass