def cross_trainer_data():
# FIXME some manual entries in python
# I guess just convert them to org
from porg import Org
# FIXME should use all org notes and just query from them?
wlog = Org.from_file(config.workout_log)
cross_table = wlog.xpath('//org[heading="Cross training"]//table')
def maybe(f):
def parse(s):
if len(s) == 0:
return None
return f(s)
return parse
def parse_mm_ss(x: str) -> timedelta:
hs, ms = x.split(':')
return timedelta(seconds=int(hs) * 60 + int(ms))
# todo eh. not sure if there is a way of getting around writing code...
# I guess would be nice to have a means of specifying type in the column? maybe multirow column names??
# need to look up org-mode standard..
from ...core.orgmode import parse_org_datetime
mappers = {
'duration': lambda s: parse_mm_ss(s),
'date': lambda s: tzify(parse_org_datetime(s)),
'comment': str,
}
for row in cross_table.lines:
# todo make more defensive, fallback on nan for individual fields??
try:
d = {}
for k, v in row.items():
# todo have something smarter... e.g. allow pandas to infer the type??
mapper = mappers.get(k, maybe(float))
d[k] = mapper(v) # type: ignore[operator]
yield d
except Exception as e:
# todo add parsing context
yield {'error': str(e)}
def query_all(self, query):
res: List[Org] = []
for of in self.files:
org = Org.from_file(str(of))
res.extend(query(org))
return res
def _load_test_file(name: str) -> Org:
return Org.from_file(Path(__file__).parent / 'data' / name)
def query_all(self, query):
for of in self.files:
org = Org.from_file(str(of))
yield from query(org)
def _iterate(self, f: Path) -> Iterable[OrgNote]:
o = Org.from_file(f)
for x in o.iterate():
yield to_note(x)