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🧵1/
Pulled 12.5 years of @Fitbit weight data via @Google Takeout becuz muh acquisitions.
No clean export. Broken tables. Fragmented JSON payload, so I rolled it up myself 👇🏻
```
python3 - <<'PY'
import csv, glob, json, os
from datetime import datetime
files = sorted(glob.glob("weight-*.json"))
if not files:
raise SystemExit("No weight-*.json files found in this folder.")
def iter_dicts(x):
"""Yield dict records from any nested JSON structure."""
if isinstance(x, dict):
# if this dict itself looks like a record, yield it too
yield x
for v in x.values():
yield from iter_dicts(v)
elif isinstance(x, list):
for item in x:
yield from iter_dicts(item)
def parse_dt(rec):
for k in ("dateTime","datetime","date_time","timestamp","date"):
v = rec.get(k)
if isinstance(v, str) and v.strip():
for fmt in ("%Y-%m-%d %H:%M:%S","%Y-%m-%d %H:%M","%Y-%m-%dT%H:%M:%S","%Y-%m-%d"):
try:
return datetime.strptime(v.replace("Z",""), fmt)
except Exception:
pass
return None
def to_float(x):
try:
return float(x)
except Exception:
return None
rows, all_keys = [], set()
for fp in files:
with open(fp, "r", encoding="utf-8") as f:
obj = json.load(f)
# Collect candidate dicts that actually contain a weight-like field
candidates = []
for rec in iter_dicts(obj):
if not isinstance(rec, dict):
continue
if any(k in rec for k in ("weight","weightKg","weight_kg","value","Weight")):
candidates.append(rec)
print(f"{fp}: {len(candidates)} record(s)")
for rec in candidates:
dt = parse_dt(rec)
w = None
for k in ("weight","Weight","weightKg","weight_kg","value"):
if k in rec:
w = to_float(rec.get(k))
if w is not None:
break
out = dict(rec)
out["datetime_parsed"] = dt.isoformat(sep=" ") if dt else ""
out["weight_raw"] = f"{w:.3f}" if isinstance(w, (int, float)) else ""
out["source_file"] = fp
all_keys.update(out.keys())
rows.append(out)
preferred = ["datetime_parsed","weight_raw","bmi","fat","logId","source_file"]
fieldnames = preferred + sorted(k for k in all_keys if k not in preferred)
rows.sort(key=lambda r: r.get("datetime_parsed") or "9999-12-31 23:59:59")
with open("fitbit_weight_all.csv","w",newline="",encoding="utf-8") as f:
w = csv.DictWriter(f, fieldnames=fieldnames)
w.writeheader()
w.writerows(rows)
print(f"✅ Wrote fitbit_weight_all.csv with {len(rows)} total rows from {len(files)} files.")
PY
```
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