mirror of
https://github.com/andwati/ledga.git
synced 2026-10-18 03:12:55 +00:00
ngenohkevin
9600fa730c
Spending figures were inflated: Fuliza repayments double-counted the already-counted borrow-backed purchase, M-Shwari/KCB deposits counted own-money savings as spending, and reversed transactions never came back out of the total. All spending queries now exclude these. Also adds a month-by-month breakdown card to Trends (12 months, delta vs previous month) and captures the credited amount on standard-format reversal SMS instead of recording 0.0.
105 lines
3.6 KiB
Python
105 lines
3.6 KiB
Python
#!/usr/bin/env python3
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"""Analyze a Ledga export zip: real vs shown spending, month by month.
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Usage: python3 analyze_export.py <ledga-export.zip | data.json>
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"Shown" replicates the app's OLD Total Spending (all OUTFLOW rows).
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The breakdown columns show how much of that figure is:
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- reversed: outflows later reversed
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- fuliza: Fuliza repayments/auto-pay (double-counts the original spend)
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- savings: M-Shwari / KCB M-Pesa deposits (your own money moving)
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- unknown: unparsed SMS defaulted to spending
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- withdraw: agent/ATM cash-out (cash in hand, not yet spent)
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"real" = shown - reversed - fuliza - savings - unknown (withdrawals kept)
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The app now excludes reversed + fuliza + savings, so the in-app figure
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should equal REAL + unknown for any month.
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"""
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import json
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import sys
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import zipfile
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from collections import defaultdict
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from datetime import datetime
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FULIZA_REPAY = {"FULIZA_REPAYMENT", "FULIZA_AUTO_PAY"}
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SAVINGS = {"MSHWARI", "KCB_MPESA"}
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WITHDRAW = {"WITHDRAW_AGENT", "WITHDRAW_ATM"}
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def load(path):
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if path.endswith(".zip"):
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with zipfile.ZipFile(path) as z:
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name = next(n for n in z.namelist() if n.endswith("data.json"))
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with z.open(name) as f:
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return json.load(f)
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with open(path) as f:
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return json.load(f)
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def main(path):
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data = load(path)
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txns = data["transactions"]
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print(f"Transactions: {len(txns)} (exported {datetime.fromtimestamp(data.get('exportedAt', 0) / 1000):%Y-%m-%d %H:%M})\n")
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reversed_codes = {
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t["reversedTransactionCode"]
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for t in txns
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if t.get("reversedTransactionCode")
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}
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months = defaultdict(lambda: defaultdict(float))
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counts = defaultdict(int)
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for t in txns:
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if t["direction"] != "OUTFLOW":
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continue
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key = datetime.fromtimestamp(t["timestamp"] / 1000).strftime("%Y-%m")
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amt = t["amount"]
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m = months[key]
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m["shown"] += amt
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m["fees"] += t.get("transactionCost", 0.0)
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counts[key] += 1
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if t["transactionCode"] in reversed_codes:
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m["reversed"] += amt
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elif t["type"] in FULIZA_REPAY:
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m["fuliza"] += amt
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elif t["type"] in SAVINGS:
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m["savings"] += amt
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elif t["type"] == "UNKNOWN":
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m["unknown"] += amt
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elif t["type"] in WITHDRAW:
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m["withdraw"] += amt
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cols = ["shown", "reversed", "fuliza", "savings", "unknown", "withdraw"]
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header = f"{'Month':<9}{'Txns':>6}" + "".join(f"{c:>12}" for c in cols) + f"{'REAL':>12}{'fees':>9}"
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print(header)
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print("-" * len(header))
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totals = defaultdict(float)
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for key in sorted(months):
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m = months[key]
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real = m["shown"] - m["reversed"] - m["fuliza"] - m["savings"] - m["unknown"]
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row = f"{key:<9}{counts[key]:>6}" + "".join(f"{m[c]:>12,.0f}" for c in cols)
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print(row + f"{real:>12,.0f}{m['fees']:>9,.0f}")
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for c in cols + ["fees"]:
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totals[c] += m[c]
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totals["real"] += real
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print("-" * len(header))
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print(
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f"{'TOTAL':<9}{sum(counts.values()):>6}"
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+ "".join(f"{totals[c]:>12,.0f}" for c in cols)
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+ f"{totals['real']:>12,.0f}{totals['fees']:>9,.0f}"
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)
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if totals["shown"] > 0:
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inflation = totals["shown"] - totals["real"]
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print(
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f"\nShown spending is inflated by Ksh {inflation:,.0f} "
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f"({inflation / totals['shown'] * 100:.1f}% of the shown figure)."
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)
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print("REAL keeps cash withdrawals; subtract the withdraw column too if you treat cash-out as a transfer.")
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if __name__ == "__main__":
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if len(sys.argv) != 2:
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sys.exit(__doc__)
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main(sys.argv[1])
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