my.emfit: cleanup and pass cpu pool

my/emfit/__init__.py

@@ -8,21 +8,29 @@ REQUIRES = [
     'git+https://github.com/karlicoss/emfitexport',
 ]
 
+from contextlib import contextmanager
+import dataclasses
+from datetime import datetime, time, timedelta
+import inspect
 from pathlib import Path
-from typing import Dict, List, Iterable, Any, Optional
+from typing import Any, Dict, Iterable, Iterator, List, Optional
 
-from ..core import get_files
-from ..core.common import mcachew
-from ..core.cachew import cache_dir
-from ..core.error import Res, set_error_datetime, extract_error_datetime
-from ..core.pandas import DataFrameT
+from my.core import (
+    get_files,
+    stat,
+    Res,
+    Stats,
+)
+from my.core.common import mcachew
+from my.core.cachew import cache_dir
+from my.core.error import set_error_datetime, extract_error_datetime
+from my.core.pandas import DataFrameT
 
 from my.config import emfit as config
 
-
 import emfitexport.dal as dal
-# todo ugh. need to make up my mind on log vs logger naming... I guessl ogger makes more sense
-logger = dal.log
+
+
 Emfit = dal.Emfit
 
 
@@ -39,13 +47,22 @@ def _cachew_depends_on():
 # TODO take __file__ into account somehow?
 @mcachew(cache_path=cache_dir() / 'emfit.cache', depends_on=_cachew_depends_on)
 def datas() -> Iterable[Res[Emfit]]:
-    import dataclasses
-
     # data from emfit is coming in UTC. There is no way (I think?) to know the 'real' timezone, and local times matter more for sleep analysis
-    # TODO actually this is wrong?? check this..
+    # TODO actually this is wrong?? there is some sort of local offset in the export
     emfit_tz = config.timezone
 
-    for x in dal.sleeps(config.export_path):
+    ## backwards compatibility (old DAL didn't have cpu_pool argument)
+    cpu_pool_arg = 'cpu_pool'
+    pass_cpu_pool = cpu_pool_arg in inspect.signature(dal.sleeps).parameters
+    if pass_cpu_pool:
+        from my.core._cpu_pool import get_cpu_pool
+
+        kwargs = {cpu_pool_arg: get_cpu_pool()}
+    else:
+        kwargs = {}
+    ##
+
+    for x in dal.sleeps(config.export_path, **kwargs):
         if isinstance(x, Exception):
             yield x
         else:
@@ -54,6 +71,7 @@ def datas() -> Iterable[Res[Emfit]]:
                 continue
             # TODO maybe have a helper to 'patch up' all dattetimes in a namedtuple/dataclass?
             # TODO do the same for jawbone data?
+            # fmt: off
             x = dataclasses.replace(
                 x,
                 start      =x.start      .astimezone(emfit_tz),
@@ -61,6 +79,7 @@ def datas() -> Iterable[Res[Emfit]]:
                 sleep_start=x.sleep_start.astimezone(emfit_tz),
                 sleep_end  =x.sleep_end  .astimezone(emfit_tz),
             )
+            # fmt: on
             yield x
 
 
@@ -78,7 +97,7 @@ def pre_dataframe() -> Iterable[Res[Emfit]]:
             yield r
         else:
             err = RuntimeError(f'Multiple sleeps per night, not supported yet: {g}')
-            set_error_datetime(err, dt=g[0].date)
+            set_error_datetime(err, dt=datetime.combine(g[0].date, time.min))
             g.clear()
             yield err
 
@@ -94,7 +113,6 @@ def pre_dataframe() -> Iterable[Res[Emfit]]:
 
 
 def dataframe() -> DataFrameT:
-    from datetime import timedelta
     dicts: List[Dict[str, Any]] = []
     last: Optional[Emfit] = None
     for s in pre_dataframe():
@@ -117,6 +135,7 @@ def dataframe() -> DataFrameT:
 
             # todo ugh. get rid of hardcoding, just generate the schema automatically
             # TODO use 'workdays' provider....
+            # fmt: off
             d = {
                 'date'       : dd,
 
@@ -133,25 +152,24 @@ def dataframe() -> DataFrameT:
                 'hrv_change' : hrv_change,
                 'respiratory_rate_avg': s.respiratory_rate_avg,
             }
+            # fmt: on
             last = s  # meh
         dicts.append(d)
 
-
     import pandas
+
     return pandas.DataFrame(dicts)
 
 
-from ..core import stat, Stats
 def stats() -> Stats:
     return stat(pre_dataframe)
 
 
-from contextlib import contextmanager
-from typing import Iterator
 @contextmanager
 def fake_data(nights: int = 500) -> Iterator:
     from my.core.cfg import tmp_config
     from tempfile import TemporaryDirectory
+
     with TemporaryDirectory() as td:
         tdir = Path(td)
         gen = dal.FakeData()
@@ -169,4 +187,6 @@ def fake_data(nights: int=500) -> Iterator:
 def get_datas() -> List[Emfit]:
     # todo ugh. run lint properly
     return list(sorted(datas(), key=lambda e: e.start))  # type: ignore
+
+
 # TODO move away old entries if there is a diff??