Pass in default history time of 1 min

Adjust all history query machinery to pass a `timeframe: int` in seconds
and set default of 60 (aka 1m) such that history views from here forward
will be 1m sampled OHLCV. Further when the tsdb is detected as up load
a full 10 years of data if possible on the 1m - backends will eventually
get a config section (`brokers.toml`) that allow user's to tune this.

piker/data/feed.py

@@ -29,7 +29,9 @@ from pprint import pformat
 from types import ModuleType
 from typing import (
     Any,
-    AsyncIterator, Optional,
+    AsyncIterator,
+    Callable,
+    Optional,
     Generator,
     Awaitable,
     TYPE_CHECKING,
@@ -252,6 +254,7 @@ async def start_backfill(
     mod: ModuleType,
     bfqsn: str,
     shm: ShmArray,
+    timeframe: float,
 
     last_tsdb_dt: Optional[datetime] = None,
     storage: Optional[Storage] = None,
@@ -262,11 +265,19 @@ async def start_backfill(
 
 ) -> int:
 
+    hist: Callable[
+        [int, datetime, datetime],
+        tuple[np.ndarray, str]
+    ]
+    config: dict[str, int]
     async with mod.open_history_client(bfqsn) as (hist, config):
 
         # get latest query's worth of history all the way
         # back to what is recorded in the tsdb
-        array, start_dt, end_dt = await hist(end_dt=None)
+        array, start_dt, end_dt = await hist(
+            timeframe,
+            end_dt=None,
+        )
 
         times = array['time']
 
@@ -304,8 +315,8 @@ async def start_backfill(
                 raise ValueError(
                     '`piker` only needs to support 1m and 1s sampling '
                     'but ur api is trying to deliver a longer '
-                    f'timeframe of {step_size_s} ' 'seconds.. so ye, dun '
-                    'do dat brudder.'
+                    f'timeframe of {step_size_s} seconds..\n'
+                    'So yuh.. dun do dat brudder.'
                 )
 
             # when no tsdb "last datum" is provided, we just load
@@ -319,7 +330,7 @@ async def start_backfill(
                 # do a decently sized backfill and load it into storage.
                 periods = {
                     1: {'days': 6},
-                    60: {'years': 2},
+                    60: {'years': 10},
                 }
 
             kwargs = periods[step_size_s]
@@ -390,7 +401,10 @@ async def start_backfill(
                 log.info(
                     f'Requesting {step_size_s}s frame ending in {input_end_dt}'
                 )
-                array, start_dt, end_dt = await hist(end_dt=input_end_dt)
+                array, start_dt, end_dt = await hist(
+                    timeframe,
+                    end_dt=input_end_dt,
+                )
                 assert array['time'][0] == start_dt.timestamp()
 
             except NoData:
@@ -640,6 +654,7 @@ async def start_backfill(
                         await storage.write_ohlcv(
                             f'{bfqsn}.{mod.name}',  # lul..
                             to_push,
+                            timeframe,
                         )
 
                 # TODO: can we only trigger this if the respective
@@ -660,6 +675,7 @@ async def manage_history(
     fqsn: str,
     some_data_ready: trio.Event,
     feed_is_live: trio.Event,
+    timeframe: float = 60,  # in seconds
 
     task_status: TaskStatus = trio.TASK_STATUS_IGNORED,
 
@@ -726,7 +742,10 @@ async def manage_history(
             # shm backfiller approach below.
 
             # start history anal and load missing new data via backend.
-            series, _, last_tsdb_dt = await storage.load(fqsn)
+            series, _, last_tsdb_dt = await storage.load(
+                fqsn,
+                timeframe=timeframe,
+            )
 
             broker, symbol, expiry = unpack_fqsn(fqsn)
             (
@@ -739,6 +758,7 @@ async def manage_history(
                     mod,
                     bfqsn,
                     hist_shm,
+                    timeframe=timeframe,
                     last_tsdb_dt=last_tsdb_dt,
                     tsdb_is_up=True,
                     storage=storage,
@@ -804,6 +824,7 @@ async def manage_history(
                     series = await storage.read_ohlcv(
                         fqsn,
                         end=end,
+                        timeframe=timeframe,
                     )
                     history = list(series.values())
                     fastest = history[0]
@@ -856,6 +877,7 @@ async def manage_history(
                 mod,
                 bfqsn,
                 hist_shm,
+                timeframe=timeframe,
             )
         )