use blood test data

body/blood.py

@@ -1,25 +1,55 @@
 #!/usr/bin/env python3
 from datetime import datetime
 from typing import Iterable, NamedTuple, Optional
+from itertools import chain
 
 import porg
 from kython import listify
 from kython.org import parse_org_date
+from kython.kerror import Res, echain
 
-from ..paths import LOGS
+from ..paths import LOGS, MY
+
+import pandas as pd # type: ignore
 
 
+blood_tests_log = MY / 'blood.org'
 blood_log = LOGS / 'blood.org'
 
 class Entry(NamedTuple):
     dt: datetime
-    ket: Optional[float]
+
-    glu: Optional[float]
+    ket: Optional[float]=None
-    extra: str
+    glu: Optional[float]=None
+
+    vitd: Optional[float]=None
+    b12: Optional[float]=None
+
+    hdl: Optional[float]=None
+    ldl: Optional[float]=None
+    trig: Optional[float]=None
+
+    extra: Optional[str]=None
 
 
-def iter_data() -> Iterable[Entry]:
+Result = Res[Entry]
-    o = porg.Org.from_file(blood_log)
+
+class ParseError(Exception):
+    pass
+
+
+def try_float(s: str) -> Optional[float]:
+    l = s.split()
+    if len(l) == 0:
+        return None
+    x = l[0].strip()
+    if len(x) == 0:
+        return None
+    return float(x)
+
+
+def iter_gluc_keto_data() -> Iterable[Result]:
+    o = porg.Org.from_file(str(blood_log))
     tbl = o.xpath('//table')
     for l in tbl.lines:
         kets = l['ket'].strip()
@@ -27,8 +57,8 @@ def iter_data() -> Iterable[Entry]:
         extra = l['notes']
         dt = parse_org_date(l['datetime'])
         assert isinstance(dt, datetime)
-        ket = None if len(kets) == 0 else float(kets)
+        ket = try_float(kets)
-        glu = None if len(glus) == 0 else float(glus)
+        glu = try_float(glus)
         yield Entry(
             dt=dt,
             ket=ket,
@@ -36,14 +66,51 @@ def iter_data() -> Iterable[Entry]:
             extra=extra,
         )
 
+
+def iter_tests_data() -> Iterable[Result]:
+    o = porg.Org.from_file(str(blood_tests_log))
+    tbl = o.xpath('//table')
+    for d in tbl.lines:
+        try:
+            dt = parse_org_date(d['datetime'])
+            assert isinstance(dt, datetime)
+            # TODO rest
+
+            F = lambda n: try_float(d[n])
+            yield Entry(
+                dt=dt,
+
+                vitd=F('VD nm/L'),
+                b12 =F('B12 pm/L'),
+
+                hdl =F('HDL mm/L'),
+                ldl =F('LDL mm/L'),
+                trig=F('Trig mm/L'),
+
+                extra=d['misc'],
+            )
+        except Exception as e:
+            print(e)
+            yield echain(ParseError(str(d)), e)
+
+
 def data():
-    datas = list(iter_data())
+    datas = list(chain(iter_gluc_keto_data(), iter_tests_data()))
-    return list(sorted(datas, key=lambda d: d.dt))
+    return list(sorted(datas, key=lambda d: getattr(d, 'dt', datetime.min)))
 
 
+@listify(wrapper=pd.DataFrame)
 def dataframe():
-    import pandas as pd
+    for d in data():
-    return pd.DataFrame(map(lambda e: e._asdict(), data()))
+        if isinstance(d, Exception):
+            yield {'error': str(d)}
+        else:
+            yield d._asdict()
+
+
+def test():
+    print(dataframe())
+    assert len(dataframe()) > 10
 
 
 def main():