Prototype out writing `1Sec` OHLCV data

piker/data/marketstore.py

@@ -23,7 +23,8 @@
 - todo: tick sequence stream-cloning for testing
 
 '''
-from contextlib import asynccontextmanager
+from contextlib import asynccontextmanager as acm
+from pprint import pformat
 from typing import (
     Any,
     Optional,
@@ -33,12 +34,13 @@ from typing import (
 import time
 from math import isnan
 
+from bidict import bidict
 import msgpack
 import numpy as np
 import pandas as pd
 import tractor
 from trio_websocket import open_websocket_url
-from anyio_marketstore import open_marketstore_client, MarketstoreClient
+from anyio_marketstore import open_marketstore_client, MarketstoreClient, Params
 
 from ..log import get_logger, get_console_log
 from .feed import maybe_open_feed
@@ -164,12 +166,17 @@ def timestamp(date, **kwargs) -> int:
     return int(pd.Timestamp(date, **kwargs).value)
 
 
-@asynccontextmanager
+@acm
 async def get_client(
     host: str = 'localhost',
     port: int = 5995
 
 ) -> MarketstoreClient:
+    '''
+    Load a ``anyio_marketstore`` grpc client connected
+    to an existing ``marketstore`` server.
+
+    '''
     async with open_marketstore_client(
         host,
         port
@@ -192,6 +199,41 @@ async def get_client(
 #                 raise MarketStoreError(err)
 
 
+tf_in_1s = bidict({
+    1: '1Sec',
+    60: '1Min',
+    60*5: '5Min',
+    60*15: '15Min',
+    60*30: '30Min',
+    60*60: '1H',
+    60*60*24: '1D',
+})
+
+
+# @acm
+async def load_history(
+    symbol: Symbol,
+    period: int = 1,  # in seconds
+
+) -> np.ndarray:
+
+    async with get_client() as client:
+
+        tfstr = tf_in_1s[period]
+        result = await client.query(
+            Params(fqsn, tf_in_1s, 'OHLCV',)
+        )
+        # Dig out `numpy` results map
+        arrays = {}
+        await tractor.breakpoint()
+        # for qr in [onem, fivem]:
+        #     for name, data_set in qr.by_symbols().items():
+        #         arrays[(name, qr)] = data_set.array
+
+        # # TODO: backfiller loop
+        # array = arrays[(fqsn, qr)]
+
+
 async def backfill_history(
     # symbol: Symbol
 
@@ -201,28 +243,32 @@ async def backfill_history(
     # - take ``Symbol`` as input
     # - backtrack into history using backend helper endpoint
 
-    # broker = 'ib'
+    broker = 'ib'
-    # symbol = 'mnq.globex'
+    symbol = 'mnq.globex'
 
-    broker = 'binance'
+    # broker = 'binance'
-    symbol = 'btcusdt'
+    # symbol = 'btcusdt'
 
     fqsn = mk_fqsn(broker, symbol)
 
+    print('yo')
     async with (
-        get_client() as msclient,
+        get_client() as client,
         maybe_open_feed(
             broker,
             [symbol],
             loglevel='info',
             # backpressure=False,
             start_stream=False,
+
         ) as (feed, stream),
     ):
+        print('yo')
         ohlcv = feed.shm.array
         mkts_dt = np.dtype(_ohlcv_dt)
 
-        syms = await msclient.list_symbols()
+        print('yo')
+        syms = await client.list_symbols()
         log.info(f'Existing symbol set:\n{pformat(syms)}')
 
         # build mkts schema compat array
@@ -240,14 +286,39 @@ async def backfill_history(
             'volume',
         ]]
 
+        key = (fqsn, '1Sec', 'OHLCV')
+        tbk = mk_tbk(key)
+
+        # diff vs. existing array and append new history
+        # TODO:
+
         # write to db
-        resp = await msclient.write(
+        resp = await client.write(
             mkts_array,
-            tbk=f'{fqsn}/1Min/OHLCV',
+            tbk=tbk,
-            isvariablelength=True,
+            # NOTE: will will append duplicates
+            # for the same timestamp-index.
+            # isvariablelength=True,
         )
+        # TODO: should be no error?
+        # assert not resp.responses
+
+        # # Dig out `numpy` results map
+        qr = await client.query(
+            Params(fqsn, '1Min`', 'OHLCV',)
+        )
+        qr = await client.query(
+            # Params(fqsn, '1Sec`', 'OHLCV',)
+            Params(*key),
+        )
+        arrays = {}
+        # for qr in [onem, fivem]:
+        for name, data_set in qr.by_symbols().items():
+            arrays[(name, qr)] = data_set.array
 
         # TODO: backfiller loop
+        array = arrays[(fqsn, qr)]
+        await tractor.breakpoint()
 
 
 async def ingest_quote_stream(
@@ -315,24 +386,6 @@ async def ingest_quote_stream(
             #         await ms_client.write(symbol, a)
 
 
-# async def stream_quotes(
-#     symbols: list[str],
-#     timeframe: str = '1Min',
-#     attr_group: str = 'TICK',
-#     host: str = 'localhost',
-#     port: int = 5993,
-#     loglevel: str = None
-
-# ) -> None:
-#     '''
-#     Open a symbol stream from a running instance of marketstore and
-#     log to console.
-
-#     '''
-#     tbks: dict[str, str] = {
-#         sym: f'{sym}/{timeframe}/{attr_group}' for sym in symbols}
-
-
 async def stream_quotes(
     symbols: list[str],
     host: str = 'localhost',