core/influxdb: add main method to create influx measurement and fill with values

allows running something like

    python3 -m my.core.influxdb populate my.zotero

my/core/common.py

@@ -596,7 +596,7 @@ datetime_aware = datetime
 def assert_subpackage(name: str) -> None:
     # can lead to some unexpected issues if you 'import cachew' which being in my/core directory.. so let's protect against it
     # NOTE: if we use overlay, name can be smth like my.origg.my.core.cachew ...
-    assert 'my.core' in name, f'Expected module __name__ ({name}) to start with my.core'
+    assert name == '__main__' or 'my.core' in name, f'Expected module __name__ ({name}) to be __main__ or start with my.core'
 
 
 # https://stackoverflow.com/a/10436851/706389

my/core/influxdb.py

@@ -15,7 +15,10 @@ class config:
     db = 'db'
 
 
-def fill(it: Iterable[Any], *, measurement: str, reset: bool=False, dt_col: str='dt') -> None:
+RESET_DEFAULT = False
+
+
+def fill(it: Iterable[Any], *, measurement: str, reset: bool=RESET_DEFAULT, dt_col: str='dt') -> None:
     # todo infer dt column automatically, reuse in stat?
     # it doesn't like dots, ends up some syntax error?
     measurement = measurement.replace('.', '_')
@@ -30,6 +33,7 @@ def fill(it: Iterable[Any], *, measurement: str, reset: bool=False, dt_col: str=
 
     # todo should be it be env variable?
     if reset:
+        logger.warning('deleting measurements: %s:%s', db, measurement)
         client.delete_series(database=db, measurement=measurement)
 
     # TODO need to take schema here...
@@ -79,14 +83,18 @@ def fill(it: Iterable[Any], *, measurement: str, reset: bool=False, dt_col: str=
     from more_itertools import chunked
     # "The optimal batch size is 5000 lines of line protocol."
     # some chunking is def necessary, otherwise it fails
+    inserted = 0
     for chi in chunked(dit(), n=5000):
         chl = list(chi)
+        inserted += len(chl)
         logger.debug('writing next chunk %s', chl[-1])
         client.write_points(chl, database=db)
+
+    logger.info('inserted %d points', inserted)
     # todo "Specify timestamp precision when writing to InfluxDB."?
 
 
-def magic_fill(it, *, name: Optional[str]=None) -> None:
+def magic_fill(it, *, name: Optional[str]=None, reset: bool=RESET_DEFAULT) -> None:
     if name is None:
         assert callable(it) # generators have no name/module
         name = f'{it.__module__}:{it.__name__}'
@@ -112,4 +120,31 @@ def magic_fill(it, *, name: Optional[str]=None) -> None:
     dtex = RuntimeError(f'expected single datetime field. schema: {schema}')
     dtf = one((f for f, t in schema.items() if t == datetime), too_short=dtex, too_long=dtex)
 
-    fill(it, measurement=name, reset=True, dt_col=dtf)
+    fill(it, measurement=name, reset=reset, dt_col=dtf)
+
+
+import click
+
+@click.group()
+def main() -> None:
+    pass
+
+
+@main.command(name='populate', short_help='populate influxdb')
+@click.option('--reset', is_flag=True, help='Reset Influx measurements before inserting', show_default=True)
+@click.argument('MODULE', type=str, required=True)
+def populate(module: str, reset: bool) -> None:
+    from .stats import guess_data_providers
+    providers = guess_data_providers(module)
+    # meh.. encapsulate in guess_data_providers?
+    if 'inputs' in providers:
+        del providers['inputs']
+    # todo could do interactive thing? same way as in hpi query
+    [(k, f)] = providers.items()
+    magic_fill(f, reset=reset)
+
+
+# todo later just add to hpi main?
+# not sure if want to couple
+if __name__ == '__main__':
+    main()

my/core/stats.py

@@ -6,7 +6,7 @@ import importlib
 import inspect
 import sys
 import typing
-from typing import Optional, Callable, Any, Iterator
+from typing import Optional, Callable, Any, Iterator, Sequence, Dict
 
 from .common import StatsFun, Stats, stat
 
@@ -14,16 +14,22 @@ from .common import StatsFun, Stats, stat
 # TODO maybe could be enough to annotate OUTPUTS or something like that?
 # then stats could just use them as hints?
 def guess_stats(module_name: str) -> Optional[StatsFun]:
-    module = importlib.import_module(module_name)
-    mfunctions = inspect.getmembers(module, inspect.isfunction)
-    functions = {k: v for k, v in mfunctions if is_data_provider(v)}
-    if len(functions) == 0:
+    providers = guess_data_providers(module_name)
+    if len(providers) == 0:
         return None
     def auto_stats() -> Stats:
-        return {k: stat(v) for k, v in functions.items()}
+        return {k: stat(v) for k, v in providers.items()}
     return auto_stats
 
 
+def guess_data_providers(module_name: str) -> Dict[str, Callable]:
+    module = importlib.import_module(module_name)
+    mfunctions = inspect.getmembers(module, inspect.isfunction)
+    return {k: v for k, v in mfunctions if is_data_provider(v)}
+
+
+# todo how to exclude deprecated stuff?
+# todo also exclude def inputs()?
 def is_data_provider(fun: Any) -> bool:
     """
     1. returns iterable or something like that

my/hypothesis.py

@@ -53,6 +53,7 @@ def _dal() -> dal.DAL:
     return dal.DAL(sources)
 
 
+# TODO they are in reverse chronological order...
 def highlights() -> List[Res[Highlight]]:
     # todo hmm. otherwise mypy complans
     key: Callable[[Highlight], datetime] = lambda h: h.created