# Copyright 2025 The Feast Authors

#

# Licensed under the Apache License, Version 2.0 (the "License");

# you may not use this file except in compliance with the License.

# You may obtain a copy of the License at

#

# https://www.apache.org/licenses/LICENSE-2.0

#

# Unless required by applicable law or agreed to in writing, software

# distributed under the License is distributed on an "AS IS" BASIS,

# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.

# See the License for the specific language governing permissions and

# limitations under the License.

import asyncio

import os

import sys

import threading

import time

import traceback

from collections import defaultdict

from contextlib import asynccontextmanager

from datetime import datetime

from importlib import resources as importlib_resources

from types import SimpleNamespace

from typing import Any, DefaultDict, Dict, List, NamedTuple, Optional, Set, Union

import pandas as pd

import psutil

from dateutil import parser

from fastapi import (

Depends,

FastAPI,

Request,

Response,

WebSocket,

WebSocketDisconnect,

status,

)

from fastapi.concurrency import run_in_threadpool

from fastapi.logger import logger

from fastapi.responses import JSONResponse

from fastapi.staticfiles import StaticFiles

from google.protobuf.json_format import MessageToDict

from prometheus_client import Gauge, start_http_server

from pydantic import BaseModel

import feast

from feast import proto_json, utils

from feast.constants import DEFAULT_FEATURE_SERVER_REGISTRY_TTL

from feast.data_source import PushMode

from feast.errors import (

FeastError,

FeatureViewNotFoundException,

)

from feast.feast_object import FeastObject

from feast.permissions.action import WRITE, AuthzedAction

from feast.permissions.security_manager import assert_permissions

from feast.permissions.server.rest import inject_user_details

from feast.permissions.server.utils import (

ServerType,

init_auth_manager,

init_security_manager,

str_to_auth_manager_type,

)

# Define prometheus metrics

cpu_usage_gauge = Gauge(

"feast_feature_server_cpu_usage", "CPU usage of the Feast feature server"

)

memory_usage_gauge = Gauge(

"feast_feature_server_memory_usage", "Memory usage of the Feast feature server"

)

# TODO: deprecate this in favor of push features

class WriteToFeatureStoreRequest(BaseModel):

feature_view_name: str

df: dict

allow_registry_cache: bool = True

transform_on_write: bool = True

class PushFeaturesRequest(BaseModel):

push_source_name: str

df: dict

allow_registry_cache: bool = True

to: str = "online"

transform_on_write: bool = True

class MaterializeRequest(BaseModel):

start_ts: Optional[str] = None

end_ts: Optional[str] = None

feature_views: Optional[List[str]] = None

disable_event_timestamp: bool = False

full_feature_names: bool = False

class MaterializeIncrementalRequest(BaseModel):

end_ts: str

feature_views: Optional[List[str]] = None

full_feature_names: bool = False

class GetOnlineFeaturesRequest(BaseModel):

entities: Dict[str, List[Any]]

feature_service: Optional[str] = None

features: List[str] = []

full_feature_names: bool = False

class GetOnlineDocumentsRequest(BaseModel):

feature_service: Optional[str] = None

features: List[str] = []

full_feature_names: bool = False

top_k: Optional[int] = None

query: Optional[List[float]] = None

query_string: Optional[str] = None

api_version: Optional[int] = 1

class ChatMessage(BaseModel):

role: str

content: str

class ChatRequest(BaseModel):

messages: List[ChatMessage]

class ReadDocumentRequest(BaseModel):

file_path: str

class SaveDocumentRequest(BaseModel):

file_path: str

data: dict

async def _get_features(

request: Union[GetOnlineFeaturesRequest, GetOnlineDocumentsRequest],

store: "feast.FeatureStore",

):

if request.feature_service:

feature_service = await run_in_threadpool(

store.get_feature_service, request.feature_service, allow_cache=True

)

assert_permissions(

resource=feature_service, actions=[AuthzedAction.READ_ONLINE]

)

features = feature_service # type: ignore

else:

all_feature_views, all_on_demand_feature_views = await run_in_threadpool(

utils._get_feature_views_to_use,

store.registry,

store.project,

request.features,

allow_cache=True,

hide_dummy_entity=False,

)

for feature_view in all_feature_views:

assert_permissions(

resource=feature_view, actions=[AuthzedAction.READ_ONLINE]

)

for od_feature_view in all_on_demand_feature_views:

assert_permissions(

resource=od_feature_view, actions=[AuthzedAction.READ_ONLINE]

)

features = request.features # type: ignore

return features

async def load_static_artifacts(app: FastAPI, store):

"""

Load static artifacts (models, lookup tables, etc.) into app.state.

This function can be extended to load various types of static artifacts:

- Small ML models (scikit-learn, small neural networks)

- Lookup tables and reference data

- Configuration parameters

- Pre-computed embeddings

Note: Not recommended for large language models - use dedicated

model serving solutions (vLLM, TGI, etc.) for those.

"""

try:

# Import here to avoid loading heavy dependencies unless needed

import importlib.util

import inspect

from pathlib import Path

# Look for static artifacts loading in the feature repository

# This allows templates and users to define their own artifact loading

repo_path = Path(store.repo_path) if store.repo_path else Path.cwd()

artifacts_file = repo_path / "static_artifacts.py"

if artifacts_file.exists():

# Load and execute custom static artifacts loading

spec = importlib.util.spec_from_file_location(

"static_artifacts", artifacts_file

)

if spec and spec.loader:

artifacts_module = importlib.util.module_from_spec(spec)

spec.loader.exec_module(artifacts_module)

# Look for load_artifacts function

if hasattr(artifacts_module, "load_artifacts"):

load_func = artifacts_module.load_artifacts

if inspect.iscoroutinefunction(load_func):

await load_func(app)

else:

load_func(app)

logger.info("Loaded static artifacts from static_artifacts.py")

except Exception as e:

# Non-fatal error - feature server should still start

logger.warning(f"Failed to load static artifacts: {e}")

def get_app(

store: "feast.FeatureStore",

registry_ttl_sec: int = DEFAULT_FEATURE_SERVER_REGISTRY_TTL,

):

"""

Creates a FastAPI app that can be used to start a feature server.

Args:

store: The FeatureStore to use for serving features

registry_ttl_sec: The TTL in seconds for the registry cache

Returns:

A FastAPI app

Example:

```python

from feast import FeatureStore

store = FeatureStore(repo_path="feature_repo")

app = get_app(store)

```

The app provides the following endpoints:

- `/get-online-features`: Get online features

- `/retrieve-online-documents`: Retrieve online documents

- `/push`: Push features to the feature store

- `/write-to-online-store`: Write to the online store

- `/health`: Health check

- `/materialize`: Materialize features

- `/materialize-incremental`: Materialize features incrementally

- `/chat`: Chat UI

- `/ws/chat`: WebSocket endpoint for chat

MCP Support:

- If MCP is enabled in feature server configuration, MCP endpoints will be added automatically

"""

proto_json.patch()

# Asynchronously refresh registry, notifying shutdown and canceling the active timer if the app is shutting down

registry_proto = None

shutting_down = False

active_timer: Optional[threading.Timer] = None

# --- Offline write batching config and batcher ---

fs_cfg = getattr(store.config, "feature_server", None)

batching_cfg = None

if fs_cfg is not None:

enabled = getattr(fs_cfg, "offline_push_batching_enabled", False)

batch_size = getattr(fs_cfg, "offline_push_batching_batch_size", None)

batch_interval_seconds = getattr(

fs_cfg, "offline_push_batching_batch_interval_seconds", None

)

if enabled is True:

size_ok = isinstance(batch_size, int) and not isinstance(batch_size, bool)

interval_ok = isinstance(batch_interval_seconds, int) and not isinstance(

batch_interval_seconds, bool

)

if size_ok and interval_ok:

batching_cfg = SimpleNamespace(

enabled=True,

batch_size=batch_size,

batch_interval_seconds=batch_interval_seconds,

)

else:

logger.warning(

"Offline write batching enabled but missing or invalid numeric values; "

"disabling batching (batch_size=%r, batch_interval_seconds=%r)",

batch_size,

batch_interval_seconds,

)

offline_batcher: Optional[OfflineWriteBatcher] = None

if batching_cfg is not None and batching_cfg.enabled is True:

offline_batcher = OfflineWriteBatcher(store=store, cfg=batching_cfg)

logger.debug("Offline write batching is ENABLED")

else:

logger.debug("Offline write batching is DISABLED")

def stop_refresh():

nonlocal shutting_down

shutting_down = True

if active_timer:

active_timer.cancel()

def async_refresh():

if shutting_down:

return

store.refresh_registry()

nonlocal registry_proto

registry_proto = store.registry.proto()

if registry_ttl_sec:

nonlocal active_timer

active_timer = threading.Timer(registry_ttl_sec, async_refresh)

active_timer.start()

@asynccontextmanager

async def lifespan(app: FastAPI):

# Load static artifacts before initializing store

await load_static_artifacts(app, store)

await store.initialize()

async_refresh()

try:

yield

finally:

stop_refresh()

if offline_batcher is not None:

offline_batcher.shutdown()

await store.close()

app = FastAPI(lifespan=lifespan)

@app.post(

"/get-online-features",

dependencies=[Depends(inject_user_details)],

)

async def get_online_features(request: GetOnlineFeaturesRequest) -> Dict[str, Any]:

# Initialize parameters for FeatureStore.get_online_features(...) call

features = await _get_features(request, store)

read_params = dict(

features=features,

entity_rows=request.entities,

full_feature_names=request.full_feature_names,

)

if store._get_provider().async_supported.online.read:

response = await store.get_online_features_async(**read_params) # type: ignore

else:

response = await run_in_threadpool(

lambda: store.get_online_features(**read_params) # type: ignore

)

# Convert the Protobuf object to JSON and return it

response_dict = await run_in_threadpool(

MessageToDict,

response.proto,

preserving_proto_field_name=True,

float_precision=18,

)

return response_dict

@app.post(

"/retrieve-online-documents",

dependencies=[Depends(inject_user_details)],

)

async def retrieve_online_documents(

request: GetOnlineDocumentsRequest,

) -> Dict[str, Any]:

logger.warning(

"This endpoint is in alpha and will be moved to /get-online-features when stable."

)

# Initialize parameters for FeatureStore.retrieve_online_documents_v2(...) call

features = await _get_features(request, store)

read_params = dict(features=features, query=request.query, top_k=request.top_k)

if request.api_version == 2 and request.query_string is not None:

read_params["query_string"] = request.query_string

if request.api_version == 2:

response = await run_in_threadpool(

lambda: store.retrieve_online_documents_v2(**read_params) # type: ignore

)

else:

response = await run_in_threadpool(

lambda: store.retrieve_online_documents(**read_params) # type: ignore

)

# Convert the Protobuf object to JSON and return it

response_dict = await run_in_threadpool(

MessageToDict,

response.proto,

preserving_proto_field_name=True,

float_precision=18,

)

return response_dict

@app.post("/push", dependencies=[Depends(inject_user_details)])

async def push(request: PushFeaturesRequest) -> Response:

df = pd.DataFrame(request.df)

actions = []

if request.to == "offline":

to = PushMode.OFFLINE

actions = [AuthzedAction.WRITE_OFFLINE]

elif request.to == "online":

to = PushMode.ONLINE

actions = [AuthzedAction.WRITE_ONLINE]

elif request.to == "online_and_offline":

to = PushMode.ONLINE_AND_OFFLINE

actions = WRITE

else:

raise ValueError(

f"{request.to} is not a supported push format. Please specify one of these ['online', 'offline', 'online_and_offline']."

)

from feast.data_source import PushSource

all_fvs = store.list_feature_views(

allow_cache=request.allow_registry_cache

) + store.list_stream_feature_views(allow_cache=request.allow_registry_cache)

fvs_with_push_sources = {

fv

for fv in all_fvs

if (

fv.stream_source is not None

and isinstance(fv.stream_source, PushSource)

and fv.stream_source.name == request.push_source_name

)

}

for feature_view in fvs_with_push_sources:

assert_permissions(resource=feature_view, actions=actions)

async def _push_with_to(push_to: PushMode) -> None:

"""

Helper for performing a single push operation.

NOTE:

- Feast providers **do not currently support async offline writes**.

- Therefore:

* ONLINE and ONLINE_AND_OFFLINE → may be async, depending on provider.async_supported.online.write

* OFFLINE → always synchronous, but executed via run_in_threadpool when called from HTTP handlers.

- The OfflineWriteBatcher handles offline writes directly in its own background thread, but the offline store writes are currently synchronous only.

"""

push_source_name = request.push_source_name

allow_registry_cache = request.allow_registry_cache

transform_on_write = request.transform_on_write

# Async currently only applies to online store writes (ONLINE / ONLINE_AND_OFFLINE paths) as theres no async for offline store

if push_to in (PushMode.ONLINE, PushMode.ONLINE_AND_OFFLINE) and (

store._get_provider().async_supported.online.write

):

await store.push_async(

push_source_name=push_source_name,

df=df,

allow_registry_cache=allow_registry_cache,

to=push_to,

transform_on_write=transform_on_write,

)

else:

await run_in_threadpool(

lambda: store.push(

push_source_name=push_source_name,

df=df,

allow_registry_cache=allow_registry_cache,

to=push_to,

transform_on_write=transform_on_write,

)

)

needs_online = to in (PushMode.ONLINE, PushMode.ONLINE_AND_OFFLINE)

needs_offline = to in (PushMode.OFFLINE, PushMode.ONLINE_AND_OFFLINE)

status_code = status.HTTP_200_OK

if offline_batcher is None or not needs_offline:

await _push_with_to(to)

else:

if needs_online:

await _push_with_to(PushMode.ONLINE)

offline_batcher.enqueue(

push_source_name=request.push_source_name,

df=df,

allow_registry_cache=request.allow_registry_cache,

transform_on_write=request.transform_on_write,

)

status_code = status.HTTP_202_ACCEPTED

return Response(status_code=status_code)

async def _get_feast_object(

feature_view_name: str, allow_registry_cache: bool

) -> FeastObject:

# FIXME: this logic repeated at least 3 times in the codebase - should be centralized

# in logging, in server and in feature_store (Python SDK)

try:

return await run_in_threadpool(

store.get_feature_view,

feature_view_name,

allow_registry_cache=allow_registry_cache,

)

except FeatureViewNotFoundException:

try:

return await run_in_threadpool(

store.get_on_demand_feature_view,

feature_view_name,

allow_registry_cache=allow_registry_cache,

)

except FeatureViewNotFoundException:

return await run_in_threadpool(

store.get_stream_feature_view,

feature_view_name,

allow_registry_cache=allow_registry_cache,

)

@app.post("/write-to-online-store", dependencies=[Depends(inject_user_details)])

async def write_to_online_store(request: WriteToFeatureStoreRequest) -> None:

df = pd.DataFrame(request.df)

feature_view_name = request.feature_view_name

allow_registry_cache = request.allow_registry_cache

resource = await _get_feast_object(feature_view_name, allow_registry_cache)

assert_permissions(resource=resource, actions=[AuthzedAction.WRITE_ONLINE])

await run_in_threadpool(

store.write_to_online_store,

feature_view_name=feature_view_name,

df=df,

allow_registry_cache=allow_registry_cache,

transform_on_write=request.transform_on_write,

)

@app.get("/health")

async def health():

return (

Response(status_code=status.HTTP_200_OK)

if registry_proto

else Response(status_code=status.HTTP_503_SERVICE_UNAVAILABLE)

)

@app.post("/chat")

async def chat(request: ChatRequest):

# Process the chat request

# For now, just return dummy text

return {"response": "This is a dummy response from the Feast feature server."}

@app.post("/read-document", dependencies=[Depends(inject_user_details)])

async def read_document_endpoint(request: ReadDocumentRequest):

try:

import os

if not os.path.exists(request.file_path):

return {"error": f"File not found: {request.file_path}"}

with open(request.file_path, "r", encoding="utf-8") as file:

content = file.read()

return {"content": content, "file_path": request.file_path}

except Exception as e:

return {"error": str(e)}

@app.post("/save-document", dependencies=[Depends(inject_user_details)])

async def save_document_endpoint(request: SaveDocumentRequest):

try:

import json

import os

from pathlib import Path

file_path = Path(request.file_path).resolve()

if not str(file_path).startswith(os.getcwd()):

return {"error": "Invalid file path"}

base_name = file_path.stem

labels_file = file_path.parent / f"{base_name}-labels.json"

with open(labels_file, "w", encoding="utf-8") as file:

json.dump(request.data, file, indent=2, ensure_ascii=False)

return {"success": True, "saved_to": str(labels_file)}

except Exception as e:

return {"error": str(e)}

@app.get("/chat")

async def chat_ui():

# Serve the chat UI

static_dir_ref = importlib_resources.files(__spec__.parent) / "static/chat" # type: ignore[name-defined, arg-type]

with importlib_resources.as_file(static_dir_ref) as static_dir:

with open(os.path.join(static_dir, "index.html")) as f:

content = f.read()

return Response(content=content, media_type="text/html")

@app.post("/materialize", dependencies=[Depends(inject_user_details)])

async def materialize(request: MaterializeRequest) -> None:

for feature_view in request.feature_views or []:

resource = await _get_feast_object(feature_view, True)

assert_permissions(

resource=resource,

actions=[AuthzedAction.WRITE_ONLINE],

)

if request.disable_event_timestamp:

# Query all available data and use current datetime as event timestamp

now = datetime.now()

start_date = datetime(

1970, 1, 1

) # Beginning of time to capture all historical data

end_date = now

else:

if not request.start_ts or not request.end_ts:

raise ValueError(

"start_ts and end_ts are required when disable_event_timestamp is False"

)

start_date = utils.make_tzaware(parser.parse(request.start_ts))

end_date = utils.make_tzaware(parser.parse(request.end_ts))

await run_in_threadpool(

store.materialize,

start_date,

end_date,

request.feature_views,

disable_event_timestamp=request.disable_event_timestamp,

full_feature_names=request.full_feature_names,

)

@app.post("/materialize-incremental", dependencies=[Depends(inject_user_details)])

async def materialize_incremental(request: MaterializeIncrementalRequest) -> None:

for feature_view in request.feature_views or []:

resource = await _get_feast_object(feature_view, True)

assert_permissions(

resource=resource,

actions=[AuthzedAction.WRITE_ONLINE],

)

await run_in_threadpool(

store.materialize_incremental,

utils.make_tzaware(parser.parse(request.end_ts)),

request.feature_views,

full_feature_names=request.full_feature_names,

)

@app.exception_handler(Exception)

async def rest_exception_handler(request: Request, exc: Exception):

# Print the original exception on the server side

logger.exception(traceback.format_exc())

if isinstance(exc, FeastError):

return JSONResponse(

status_code=exc.http_status_code(),

content=exc.to_error_detail(),

)

else:

return JSONResponse(

status_code=500,

content=str(exc),

)

# Chat WebSocket connection manager

class ConnectionManager:

def __init__(self):

self.active_connections: List[WebSocket] = []

async def connect(self, websocket: WebSocket):

await websocket.accept()

self.active_connections.append(websocket)

def disconnect(self, websocket: WebSocket):

self.active_connections.remove(websocket)

async def send_message(self, message: str, websocket: WebSocket):

await websocket.send_text(message)

manager = ConnectionManager()

MAX_WS_CONNECTIONS = 5

MAX_MESSAGE_SIZE = 4096

MAX_MESSAGES_PER_MINUTE = 60

WS_READ_TIMEOUT_SEC = 60

@app.websocket("/ws/chat")

async def websocket_endpoint(websocket: WebSocket):

if len(manager.active_connections) >= MAX_WS_CONNECTIONS:

await websocket.close(code=status.WS_1008_POLICY_VIOLATION)

return

await manager.connect(websocket)

message_timestamps: List[float] = []

try:

while True:

try:

message = await asyncio.wait_for(

websocket.receive_text(), timeout=WS_READ_TIMEOUT_SEC

)

except asyncio.TimeoutError:

await websocket.close(code=status.WS_1001_GOING_AWAY)

return

if len(message) > MAX_MESSAGE_SIZE:

await websocket.close(code=status.WS_1009_MESSAGE_TOO_BIG)

return

now = time.time()

cutoff = now - 60

message_timestamps = [ts for ts in message_timestamps if ts >= cutoff]

if len(message_timestamps) >= MAX_MESSAGES_PER_MINUTE:

await websocket.close(code=status.WS_1008_POLICY_VIOLATION)

return

message_timestamps.append(now)

# Process the received message (currently unused but kept for future implementation)

# For now, just return dummy text

response = f"You sent: '{message}'. This is a dummy response from the Feast feature server."

# Stream the response word by word

words = response.split()

for word in words:

await manager.send_message(word + " ", websocket)

await asyncio.sleep(0.1) # Add a small delay between words

except WebSocketDisconnect:

manager.disconnect(websocket)

# Mount static files

static_dir_ref = importlib_resources.files(__spec__.parent) / "static" # type: ignore[name-defined, arg-type]

with importlib_resources.as_file(static_dir_ref) as static_dir:

app.mount("/static", StaticFiles(directory=static_dir), name="static")

# Add MCP support if enabled in feature server configuration

_add_mcp_support_if_enabled(app, store)

return app

def _add_mcp_support_if_enabled(app, store: "feast.FeatureStore"):

"""Add MCP support to the FastAPI app if enabled in configuration."""

try:

# Check if MCP is enabled in feature server config

if (

store.config.feature_server

and hasattr(store.config.feature_server, "type")

and store.config.feature_server.type == "mcp"

and getattr(store.config.feature_server, "mcp_enabled", False)

):

from feast.infra.mcp_servers.mcp_server import add_mcp_support_to_app

mcp_server = add_mcp_support_to_app(app, store, store.config.feature_server)

if mcp_server:

logger.info("MCP support has been enabled for the Feast feature server")

else:

logger.warning("MCP support was requested but could not be enabled")

else:

logger.debug("MCP support is not enabled in feature server configuration")

except Exception as e:

logger.error(f"Error checking/adding MCP support: {e}")

# Don't fail the entire server if MCP fails to initialize

if sys.platform != "win32":

import gunicorn.app.base

class FeastServeApplication(gunicorn.app.base.BaseApplication):

def __init__(self, store: "feast.FeatureStore", **options):

self._app = get_app(

store=store,

registry_ttl_sec=options["registry_ttl_sec"],

)

self._options = options

super().__init__()

def load_config(self):

for key, value in self._options.items():

if key.lower() in self.cfg.settings and value is not None:

self.cfg.set(key.lower(), value)

self.cfg.set("worker_class", "uvicorn_worker.UvicornWorker")

def load(self):

return self._app

def monitor_resources(self, interval: int = 5):

"""Function to monitor and update CPU and memory usage metrics."""

logger.debug(f"Starting resource monitoring with interval {interval} seconds")

p = psutil.Process()

logger.debug(f"PID is {p.pid}")

while True:

with p.oneshot():

cpu_usage = p.cpu_percent()

memory_usage = p.memory_percent()

logger.debug(f"CPU usage: {cpu_usage}%, Memory usage: {memory_usage}%")

logger.debug(f"CPU usage: {cpu_usage}%, Memory usage: {memory_usage}%")

cpu_usage_gauge.set(cpu_usage)

memory_usage_gauge.set(memory_usage)

time.sleep(interval)

def start_server(

store: "feast.FeatureStore",

host: str,

port: int,

no_access_log: bool,

workers: int,

worker_connections: int,

max_requests: int,

max_requests_jitter: int,

keep_alive_timeout: int,

registry_ttl_sec: int,

tls_key_path: str,

tls_cert_path: str,

metrics: bool,

):

if (tls_key_path and not tls_cert_path) or (not tls_key_path and tls_cert_path):

raise ValueError(

"Both key and cert file paths are required to start server in TLS mode."

)

if metrics:

logger.info("Starting Prometheus Server")

start_http_server(8000)

logger.debug("Starting background thread to monitor CPU and memory usage")

monitoring_thread = threading.Thread(

target=monitor_resources, args=(5,), daemon=True

)

monitoring_thread.start()

logger.debug("start_server called")

auth_type = str_to_auth_manager_type(store.config.auth_config.type)

logger.info(f"Auth type: {auth_type}")

init_security_manager(auth_type=auth_type, fs=store)

logger.debug("Security manager initialized successfully")

init_auth_manager(

auth_type=auth_type,

server_type=ServerType.REST,

auth_config=store.config.auth_config,

)

logger.debug("Auth manager initialized successfully")

if sys.platform != "win32":

options = {

"bind": f"{host}:{port}",

"accesslog": None if no_access_log else "-",

"workers": workers,

"worker_connections": worker_connections,

"max_requests": max_requests,

"max_requests_jitter": max_requests_jitter,

"keepalive": keep_alive_timeout,

"registry_ttl_sec": registry_ttl_sec,

}

# Add SSL options if the paths exist

if tls_key_path and tls_cert_path:

options["keyfile"] = tls_key_path

options["certfile"] = tls_cert_path

FeastServeApplication(store=store, **options).run()

else:

import uvicorn

app = get_app(store, registry_ttl_sec)

if tls_key_path and tls_cert_path:

uvicorn.run(

app,

host=host,

port=port,

access_log=(not no_access_log),

ssl_keyfile=tls_key_path,

ssl_certfile=tls_cert_path,

)

else:

uvicorn.run(app, host=host, port=port, access_log=(not no_access_log))

class _OfflineBatchKey(NamedTuple):

push_source_name: str

allow_registry_cache: bool

transform_on_write: bool

class OfflineWriteBatcher:

"""

In-process offline write batcher for /push requests.

- Buffers DataFrames per (push_source_name, allow_registry_cache, transform_on_write)

- Flushes when either:

* total rows in a buffer >= batch_size, or

* time since last flush >= batch_interval_seconds

- Flush runs in a dedicated background thread so the HTTP event loop stays unblocked.

"""

def __init__(self, store: "feast.FeatureStore", cfg: Any):

self._store = store

self._cfg = cfg

# Buffers and timestamps keyed by batch key

self._buffers: DefaultDict[_OfflineBatchKey, List[pd.DataFrame]] = defaultdict(

list

)

self._last_flush: DefaultDict[_OfflineBatchKey, float] = defaultdict(time.time)

self._inflight: Set[_OfflineBatchKey] = set()

self._lock = threading.Lock()

self._stop_event = threading.Event()

# Start background flusher thread

self._thread = threading.Thread(

target=self._run, name="offline_write_batcher", daemon=True

)

self._thread.start()

logger.debug(

"OfflineWriteBatcher initialized: batch_size=%s, batch_interval_seconds=%s",

getattr(cfg, "batch_size", None),

getattr(cfg, "batch_interval_seconds", None),

)

# ---------- Public API ----------

def enqueue(

self,

push_source_name: str,

df: pd.DataFrame,

allow_registry_cache: bool,

transform_on_write: bool,

) -> None:

"""

Enqueue a dataframe for offline write, grouped by push source + flags.

Cheap and non-blocking; heavy I/O happens in background thread.

"""

key = _OfflineBatchKey(

push_source_name=push_source_name,

allow_registry_cache=allow_registry_cache,

transform_on_write=transform_on_write,

)

with self._lock:

self._buffers[key].append(df)

total_rows = sum(len(d) for d in self._buffers[key])

should_flush = total_rows >= self._cfg.batch_size

if should_flush:

# Size-based flush

logger.debug(

"OfflineWriteBatcher size threshold reached for %s: %s rows",

key,

total_rows,

)

self._flush(key)

def flush_all(self) -> None:

"""

Flush all buffers synchronously. Intended for graceful shutdown.

"""

with self._lock:

keys = list(self._buffers.keys())

for key in keys:

self._flush(key)

def shutdown(self, timeout: float = 5.0) -> None:

"""

Stop the background thread and perform a best-effort flush.

"""

logger.debug("Shutting down OfflineWriteBatcher")

self._stop_event.set()

try:

self._thread.join(timeout=timeout)

except Exception:

logger.exception("Error joining OfflineWriteBatcher thread")

# Best-effort final flush

try:

self.flush_all()

except Exception:

logger.exception("Error during final OfflineWriteBatcher flush")

# ---------- Internal helpers ----------

def _run(self) -> None:

"""

Background loop: periodically checks for buffers that should be flushed

based on time since last flush.

"""

interval = max(1, int(getattr(self._cfg, "batch_interval_seconds", 30)))

logger.debug(

"OfflineWriteBatcher background loop started with check interval=%s",

interval,

)

while not self._stop_event.wait(timeout=interval):

now = time.time()

try:

with self._lock:

keys_to_flush: List[_OfflineBatchKey] = []

for key, dfs in list(self._buffers.items()):

if not dfs:

continue

last = self._last_flush[

key

] # this will also init the default timestamp

age = now - last

if age >= self._cfg.batch_interval_seconds:

logger.debug(

"OfflineWriteBatcher time threshold reached for %s: age=%s",

key,

age,

)