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The user noticed the "Annual spending" field was a no-op for Trinity,
GK, VPW, VPW+floor — the strategies internally hardcoded the year-0
withdrawal as `initial_portfolio × initial_rate` (4% / 5.5%) and
ignored what the user typed. Two fixes:
(1) Trinity + GK now use state.initial_withdrawal (= the user's
spending_target) as the year-0 draw. GK's guardrail anchor
becomes the implied initial rate (initial_withdrawal /
initial_portfolio), so the rule shape adapts to the user's
chosen rate. Both strategies still fall back to their preset
rate × initial_portfolio when initial_withdrawal isn't set
(test paths). VPW and VPW+floor stay algorithmic — they're
"withdraw-what's-sustainable" by design and don't take a
spending input.
(2) New "custom" preset (SpendingPlanStrategy) exposing all the
knobs:
- initial_spend = "Annual spending" input
- annual_real_adjust_pct = scale last year's withdrawal by N%
each year (0 = constant real £, +0.02 = 2%/yr healthcare
creep, -0.005 = -0.5%/yr slow-down with age)
- guardrail_threshold_pct = if portfolio falls below X% of
starting NW, trigger a cut (None = disabled)
- guardrail_cut_pct = cut last year's withdrawal by Y% each
triggered year
Adjust applies first, then guardrail cut — so a triggered year in
+2% adjust mode goes 40k → 40.8k → 36.7k.
UI: "custom" added to the strategy dropdown; when selected, three
extra fields appear (annual real adjustment %, guardrail trigger
threshold, guardrail cut size) with hints. The existing inputs
(spending, NW seed) drive year 0 across all strategies that use
them. About-the-model panel updated.
10 new tests on SpendingPlanStrategy + adjusted GK tests for the
new spending_target-aware behaviour. 209 backend tests + 7
frontend tests. mypy + ruff + tsc all pass.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
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| alembic | ||
| fire_planner | ||
| frontend | ||
| tests | ||
| .dockerignore | ||
| .gitignore | ||
| .woodpecker.yml | ||
| alembic.ini | ||
| Dockerfile | ||
| PLAYBOOK_VIKTOR.md | ||
| poetry.lock | ||
| pyproject.toml | ||
| README.md | ||
fire-planner
Risk-adjusted, tax-minimised FIRE retirement planner. Consumes today's
portfolio, savings rate, and RSU vest schedule from sibling services
(wealthfolio, payslip-ingest, hmrc-sync) and returns the after-tax
probability of success for each combination of jurisdiction, withdrawal
strategy, and "year you break UK tax residency".
Layout
fire_planner/— packagetax/— per-jurisdiction tax engines (UK, nomad, Malaysia, Thailand, Cyprus, Bulgaria)returns/— Shiller 1871+ data + block bootstrap samplerstrategies/— Trinity 4% SWR, Guyton-Klinger guardrails, VPWingest/— pulls fromwealthfolio/payslip-ingest/hmrc-syncsimulator.py— vectorised NumPy MC enginescenarios.py— Cartesian product over (jurisdiction × strategy × leave-UK-year × glide)app.py— FastAPI on-demand/recompute__main__.py—clickCLI:ingest,simulate,recompute-all,migrate
Common commands
poetry install
pytest -v
mypy .
ruff check .
yapf --recursive .
# Run migrations against the local DB:
DB_CONNECTION_STRING=postgresql+asyncpg://... alembic upgrade head
# CLI
DB_CONNECTION_STRING=... python -m fire_planner ingest
DB_CONNECTION_STRING=... python -m fire_planner simulate --scenario=cyprus-vpw-leave-y3
DB_CONNECTION_STRING=... python -m fire_planner recompute-all
Schema
Six tables in fire_planner schema on pg-cluster-rw:
account_snapshot— daily NW per account (Wealthfolio)scenario— Cartesian-product scenario definitionmc_run— execution metadata + summary stats per (scenario, run_at)mc_path— sparse storage (top decile, bottom decile, median)projection_yearly— deterministic point projection per scenarioscenario_summary— denormalised fast-read for Grafana