my.bluemaestro: minor cleanup

my/bluemaestro.py

@@ -4,13 +4,26 @@
 """
 
 # todo most of it belongs to DAL... but considering so few people use it I didn't bother for now
+from dataclasses import dataclass
 from datetime import datetime, timedelta
 from pathlib import Path
 import re
 import sqlite3
 from typing import Iterable, Sequence, Set, Optional
 
-from my.core import get_files, make_logger, dataclass, Res
+import pytz
+
+from my.core import (
+    get_files,
+    make_logger,
+    Res,
+    stat,
+    Stats,
+    influxdb,
+)
+from my.core.common import mcachew
+from my.core.error import unwrap
+from my.core.pandas import DataFrameT, as_dataframe
 from my.core.sqlite import sqlite_connect_immutable
 
 from my.config import bluemaestro as config
@@ -25,12 +38,13 @@ def inputs() -> Sequence[Path]:
 
 Celsius = float
 Percent = float
-mBar    = float
+mBar = float
+
 
 @dataclass
 class Measurement:
-    dt: datetime # todo aware/naive
-    temp    : Celsius
+    dt: datetime  # todo aware/naive
+    temp: Celsius
     humidity: Percent
     pressure: mBar
     dewpoint: Celsius
@@ -38,7 +52,6 @@ class Measurement:
 
 # fixme: later, rely on the timezone provider
 # NOTE: the timezone should be set with respect to the export date!!!
-import pytz
 tz = pytz.timezone('Europe/London')
 # TODO when I change tz, check the diff
 
@@ -49,9 +62,7 @@ def is_bad_table(name: str) -> bool:
     return False if delegate is None else delegate(name)
 
 
-from my.core.cachew import cache_dir
-from my.core.common import mcachew
-@mcachew(depends_on=inputs, cache_path=cache_dir('bluemaestro'))
+@mcachew(depends_on=inputs)
 def measurements() -> Iterable[Res[Measurement]]:
     # todo ideally this would be via arguments... but needs to be lazy
     dbs = inputs()
@@ -68,14 +79,16 @@ def measurements() -> Iterable[Res[Measurement]]:
         with sqlite_connect_immutable(f) as db:
             db_dt: Optional[datetime] = None
             try:
-                datas = db.execute(f'SELECT "{f.name}" as name, Time, Temperature, Humidity, Pressure, Dewpoint FROM data ORDER BY log_index')
+                datas = db.execute(
+                    f'SELECT "{f.name}" as name, Time, Temperature, Humidity, Pressure, Dewpoint FROM data ORDER BY log_index'
+                )
                 oldfmt = True
                 db_dts = list(db.execute('SELECT last_download FROM info'))[0][0]
                 if db_dts == 'N/A':
                     # ??? happens for 20180923-20180928
                     continue
                 if db_dts.endswith(':'):
-                    db_dts += '00' # wtf.. happens on some day
+                    db_dts += '00'  # wtf.. happens on some day
                 db_dt = tz.localize(datetime.strptime(db_dts, '%Y-%m-%d %H:%M:%S'))
             except sqlite3.OperationalError:
                 # Right, this looks really bad.
@@ -113,7 +126,7 @@ def measurements() -> Iterable[Res[Measurement]]:
                     f'SELECT "{t}" AS name, unix, tempReadings / 10.0, humiReadings / 10.0, pressReadings / 10.0, dewpReadings / 10.0 FROM {t}'
                     for t in log_tables
                 )
-                if len(log_tables) > 0: # ugh. otherwise end up with syntax error..
+                if len(log_tables) > 0:  # ugh. otherwise end up with syntax error..
                     query = f'SELECT * FROM ({query}) ORDER BY name, unix'
                 datas = db.execute(query)
                 oldfmt = False
@@ -139,8 +152,8 @@ def measurements() -> Iterable[Res[Measurement]]:
 
                 ## sanity checks (todo make defensive/configurable?)
                 # not sure how that happens.. but basically they'd better be excluded
-                lower = timedelta(days=6000 / 24) # ugh some time ago I only did it once in an hour.. in theory can detect from meta?
-                upper = timedelta(days=10) # kinda arbitrary
+                lower = timedelta(days=6000 / 24)  # ugh some time ago I only did it once in an hour.. in theory can detect from meta?
+                upper = timedelta(days=10)  # kinda arbitrary
                 if not (db_dt - lower < dt < db_dt + timedelta(days=10)):
                     # todo could be more defenive??
                     yield RuntimeError('timestamp too far out', f, name, db_dt, dt)
@@ -178,12 +191,11 @@ def measurements() -> Iterable[Res[Measurement]]:
     # for k, v in merged.items():
     #     yield Point(dt=k, temp=v) # meh?
 
-from my.core import stat, Stats
+
 def stats() -> Stats:
     return stat(measurements)
 
 
-from my.core.pandas import DataFrameT, as_dataframe
 def dataframe() -> DataFrameT:
     """
     %matplotlib gtk
@@ -197,7 +209,6 @@ def dataframe() -> DataFrameT:
 
 
 def fill_influxdb() -> None:
-    from my.core import influxdb
     influxdb.fill(measurements(), measurement=__name__)
 
 
@@ -205,7 +216,6 @@ def check() -> None:
     temps = list(measurements())
     latest = temps[:-2]
 
-    from my.core.error import unwrap
     prev = unwrap(latest[-2]).dt
     last = unwrap(latest[-1]).dt
 
@@ -215,12 +225,12 @@ def check() -> None:
     #
     # TODO also needs to be filtered out on processing, should be rejected on the basis of export date?
 
-    POINTS_STORED = 6000 # on device?
+    POINTS_STORED = 6000  # on device?
     FREQ_SEC = 60
     SECS_STORED = POINTS_STORED * FREQ_SEC
-    HOURS_STORED = POINTS_STORED / (60 * 60 / FREQ_SEC) # around 4 days
+    HOURS_STORED = POINTS_STORED / (60 * 60 / FREQ_SEC)  # around 4 days
     NOW = datetime.now()
     assert NOW - last < timedelta(hours=HOURS_STORED / 2), f'old backup! {last}'
 
-    assert last - prev  < timedelta(minutes=3), f'bad interval! {last - prev}'
+    assert last - prev < timedelta(minutes=3), f'bad interval! {last - prev}'
     single = (last - prev).seconds