Move files

src/great_ai/persistence/parallel_tinydb_driver.py

@@ -0,0 +1,112 @@
+from datetime import datetime
+from multiprocessing import Lock
+from pathlib import Path
+from typing import Any, Callable, Dict, List, Optional, Sequence, Tuple, cast
+
+import pandas as pd
+from tinydb import TinyDB
+
+from ..views import Filter, SortBy, Trace
+from .tracing_database_driver import TracingDatabaseDriver
+
+DEFAULT_TRACING_DB_FILENAME = "tracing_database.json"
+lock = Lock()
+
+
+operator_mapping = {"=": "eq", "!=": "ne", "<": "lt", "<=": "le", ">": "gt", ">=": "ge"}
+
+
+class ParallelTinyDbDriver(TracingDatabaseDriver):
+    is_production_ready = False
+    path_to_db = Path(DEFAULT_TRACING_DB_FILENAME)
+
+    def save(self, trace: Trace) -> str:
+        return self._safe_execute(lambda db: db.insert(trace.dict()))
+
+    def save_batch(self, documents: List[Trace]) -> List[str]:
+        traces = [d.dict() for d in documents]
+        return self._safe_execute(lambda db: db.insert_multiple(traces))
+
+    def get(self, id: str) -> Optional[Trace]:
+        value = self._safe_execute(lambda db: db.get(lambda d: d["trace_id"] == id))
+        if value:
+            value = Trace.parse_obj(value)
+        return value
+
+    def query(
+        self,
+        *,
+        skip: int = 0,
+        take: Optional[int] = None,
+        conjunctive_filters: Sequence[Filter] = [],
+        conjunctive_tags: Sequence[str] = [],
+        since: Optional[datetime] = None,
+        until: Optional[datetime] = None,
+        has_feedback: Optional[bool] = None,
+        sort_by: Sequence[SortBy] = []
+    ) -> Tuple[List[Trace], int]:
+        def does_match(d: Dict[str, Any]) -> bool:
+            return (
+                not set(conjunctive_tags) - set(d["tags"])
+                and (
+                    since is None
+                    or cast(datetime, datetime.fromisoformat(d["created"])) >= since
+                )
+                and (
+                    until is None
+                    or cast(datetime, datetime.fromisoformat(d["created"])) <= until
+                )
+                and (
+                    has_feedback is None or has_feedback == (d["feedback"] is not None)
+                )
+            )
+
+        documents: List[Trace] = [
+            Trace.parse_obj(t)
+            for t in self._safe_execute(lambda db: db.search(does_match))
+        ]
+
+        if not documents:
+            return [], 0
+
+        df = pd.DataFrame([d.to_flat_dict() for d in documents])
+
+        for f in conjunctive_filters:
+            operator = f.operator.lower()
+            if operator in operator_mapping:
+                df = df.loc[
+                    getattr(df[f.property], operator_mapping[f.operator])(f.value)
+                ]
+            elif operator == "contains":
+                df = df.loc[df[f.property].str.contains(f.value, case=False)]
+
+        if sort_by:
+            df.sort_values(
+                [col.column_id for col in sort_by],
+                ascending=[col.direction == "asc" for col in sort_by],
+                inplace=True,
+            )
+
+        count = len(df)
+        result = df.iloc[skip:] if take is None else df.iloc[skip : skip + take]
+        return [
+            next(d for d in documents if d.trace_id == trace_id)
+            for trace_id in result["trace_id"]
+        ], count
+
+    def update(self, id: str, new_version: Trace) -> None:
+        self._safe_execute(
+            lambda db: db.update(new_version.dict(), lambda d: d["trace_id"] == id)
+        )
+
+    def delete(self, id: str) -> None:
+        self._safe_execute(lambda db: db.remove(lambda d: d["trace_id"] == id))
+
+    def delete_batch(self, ids: List[str]) -> List[str]:
+        for i in ids:
+            self.delete(i)
+
+    def _safe_execute(self, func: Callable[[TinyDB], Any]) -> Any:
+        with lock:
+            with TinyDB(self.path_to_db) as db:
+                return func(db)