edb4d11352
Some checks are pending
Add a Monte-Carlo "FIRE number" solver so the wealth dashboard can show a £ countdown to retirement across life-stage cases, in today's money. Viktor wants to see, per country, how far his net worth is from being able to retire for good under three cases — Solo (his spend ×1.5), Household (+Anca ×1.5), Family (+2 kids) — with cost-of-living re-scaling per country and a 99% Guyton-Klinger success bar. - spend_model: per-Case real-GBP spend, COL-scaled (rent + non-rent essentials scale by country; Holidays fixed), ×1.5 safety. Constants sourced live from actualbudget (Viktor) / on-record (Anca). - geo: city -> tax jurisdiction (nomad fallback). - fire_target: binary-search the smallest LIQUID net worth where GK reaches the bar; pension modelled as a tranche unlocking at ~57, kids ramp + optional home as cashflows. New fire_target table (migration 0007) + idempotent upsert. - recompute-fire-targets CLI: solve every Case x country and persist for Grafana. - CONTEXT.md glossary + ADR-0001 (why MC-threshold on liquid NW, not 25x spend). Reuses the existing simulator unchanged (its cashflow hooks already supported pension/kids/home). 345 tests pass; mypy + ruff clean. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
421 lines
23 KiB
Python
421 lines
23 KiB
Python
import os
|
||
from datetime import date, datetime
|
||
from decimal import Decimal
|
||
from typing import Any
|
||
|
||
from sqlalchemy import (
|
||
JSON,
|
||
TIMESTAMP,
|
||
Boolean,
|
||
Date,
|
||
Integer,
|
||
Numeric,
|
||
String,
|
||
UniqueConstraint,
|
||
func,
|
||
text,
|
||
)
|
||
from sqlalchemy.dialects.postgresql import JSONB
|
||
from sqlalchemy.ext.asyncio import AsyncEngine, async_sessionmaker, create_async_engine
|
||
from sqlalchemy.orm import DeclarativeBase, Mapped, mapped_column
|
||
|
||
SCHEMA_NAME = "fire_planner"
|
||
|
||
|
||
class Base(DeclarativeBase):
|
||
pass
|
||
|
||
|
||
# JSONB on Postgres, plain JSON on SQLite — tests use SQLite, prod uses Postgres.
|
||
JSON_TYPE = JSONB().with_variant(JSON(), "sqlite")
|
||
|
||
|
||
class AccountSnapshot(Base):
|
||
"""Daily NW per account from Wealthfolio (filled by ingest).
|
||
|
||
`external_id` is `wealthfolio:{account_id}:{date}` so re-runs on the same
|
||
day are idempotent — Wealthfolio keeps one snapshot per account per day.
|
||
"""
|
||
__tablename__ = "account_snapshot"
|
||
__table_args__ = {"schema": SCHEMA_NAME} # noqa: RUF012
|
||
|
||
id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
|
||
external_id: Mapped[str] = mapped_column(String, unique=True, nullable=False)
|
||
snapshot_date: Mapped[date] = mapped_column(Date, nullable=False, index=True)
|
||
account_id: Mapped[str] = mapped_column(String, nullable=False, index=True)
|
||
account_name: Mapped[str] = mapped_column(String, nullable=False)
|
||
account_type: Mapped[str] = mapped_column(String, nullable=False)
|
||
currency: Mapped[str] = mapped_column(String(3), nullable=False, server_default="GBP")
|
||
market_value: Mapped[Decimal] = mapped_column(Numeric(14, 2), nullable=False)
|
||
market_value_gbp: Mapped[Decimal] = mapped_column(Numeric(14, 2), nullable=False)
|
||
cost_basis_gbp: Mapped[Decimal | None] = mapped_column(Numeric(14, 2), nullable=True)
|
||
raw_extraction: Mapped[dict[str, Any] | None] = mapped_column(JSON_TYPE, nullable=True)
|
||
created_at: Mapped[datetime] = mapped_column(TIMESTAMP(timezone=True),
|
||
nullable=False,
|
||
server_default=func.now())
|
||
|
||
|
||
class Scenario(Base):
|
||
"""A simulation scenario.
|
||
|
||
Two kinds:
|
||
- `kind='cartesian'` — auto-generated from `scenarios.py` Cartesian
|
||
product; rebuilt every recompute, upserted on `external_id`.
|
||
- `kind='user'` — user-defined (named, optionally cloned from a base);
|
||
survives recomputes; `parent_scenario_id` points at the source if any.
|
||
"""
|
||
__tablename__ = "scenario"
|
||
__table_args__ = {"schema": SCHEMA_NAME} # noqa: RUF012
|
||
|
||
id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
|
||
external_id: Mapped[str] = mapped_column(String, unique=True, nullable=False)
|
||
kind: Mapped[str] = mapped_column(String(16),
|
||
nullable=False,
|
||
server_default=text("'cartesian'"))
|
||
name: Mapped[str | None] = mapped_column(String, nullable=True)
|
||
description: Mapped[str | None] = mapped_column(String, nullable=True)
|
||
parent_scenario_id: Mapped[int | None] = mapped_column(Integer, nullable=True)
|
||
jurisdiction: Mapped[str] = mapped_column(String(32), nullable=False, index=True)
|
||
strategy: Mapped[str] = mapped_column(String(32), nullable=False, index=True)
|
||
leave_uk_year: Mapped[int] = mapped_column(Integer, nullable=False)
|
||
glide_path: Mapped[str] = mapped_column(String(32), nullable=False)
|
||
spending_gbp: Mapped[Decimal] = mapped_column(Numeric(12, 2), nullable=False)
|
||
horizon_years: Mapped[int] = mapped_column(Integer, nullable=False, server_default=text("60"))
|
||
nw_seed_gbp: Mapped[Decimal] = mapped_column(Numeric(14, 2), nullable=False)
|
||
savings_per_year_gbp: Mapped[Decimal] = mapped_column(Numeric(12, 2),
|
||
nullable=False,
|
||
server_default=text("0"))
|
||
config_json: Mapped[dict[str, Any]] = mapped_column(JSON_TYPE, nullable=False)
|
||
created_at: Mapped[datetime] = mapped_column(TIMESTAMP(timezone=True),
|
||
nullable=False,
|
||
server_default=func.now())
|
||
|
||
|
||
class McRun(Base):
|
||
"""One MC execution per (scenario, run_at). Stores execution metadata +
|
||
summary statistics — enough to populate a Grafana cell without touching
|
||
the per-path tables."""
|
||
__tablename__ = "mc_run"
|
||
__table_args__ = {"schema": SCHEMA_NAME} # noqa: RUF012
|
||
|
||
id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
|
||
scenario_id: Mapped[int] = mapped_column(Integer, nullable=False, index=True)
|
||
run_at: Mapped[datetime] = mapped_column(TIMESTAMP(timezone=True),
|
||
nullable=False,
|
||
server_default=func.now())
|
||
n_paths: Mapped[int] = mapped_column(Integer, nullable=False)
|
||
seed: Mapped[int] = mapped_column(Integer, nullable=False)
|
||
success_rate: Mapped[Decimal] = mapped_column(Numeric(6, 4), nullable=False)
|
||
p10_ending_gbp: Mapped[Decimal] = mapped_column(Numeric(16, 2), nullable=False)
|
||
p50_ending_gbp: Mapped[Decimal] = mapped_column(Numeric(16, 2), nullable=False)
|
||
p90_ending_gbp: Mapped[Decimal] = mapped_column(Numeric(16, 2), nullable=False)
|
||
median_lifetime_tax_gbp: Mapped[Decimal] = mapped_column(Numeric(14, 2), nullable=False)
|
||
median_years_to_ruin: Mapped[Decimal | None] = mapped_column(Numeric(6, 2), nullable=True)
|
||
elapsed_seconds: Mapped[Decimal] = mapped_column(Numeric(8, 3), nullable=False)
|
||
sequence_risk_correlation: Mapped[Decimal | None] = mapped_column(Numeric(6, 4), nullable=True)
|
||
extra: Mapped[dict[str, Any] | None] = mapped_column(JSON_TYPE, nullable=True)
|
||
|
||
|
||
class McPath(Base):
|
||
"""Sparse per-path storage: top decile, bottom decile, and median paths
|
||
fully stored — enough for a fan chart, not 10k×60 ≈ 600k rows."""
|
||
__tablename__ = "mc_path"
|
||
__table_args__ = {"schema": SCHEMA_NAME} # noqa: RUF012
|
||
|
||
id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
|
||
mc_run_id: Mapped[int] = mapped_column(Integer, nullable=False, index=True)
|
||
path_idx: Mapped[int] = mapped_column(Integer, nullable=False)
|
||
bucket: Mapped[str] = mapped_column(String(16), nullable=False)
|
||
year_idx: Mapped[int] = mapped_column(Integer, nullable=False)
|
||
portfolio_gbp: Mapped[Decimal] = mapped_column(Numeric(16, 2), nullable=False)
|
||
withdrawal_gbp: Mapped[Decimal] = mapped_column(Numeric(12, 2), nullable=False)
|
||
tax_paid_gbp: Mapped[Decimal] = mapped_column(Numeric(12, 2), nullable=False)
|
||
real_portfolio_gbp: Mapped[Decimal] = mapped_column(Numeric(16, 2), nullable=False)
|
||
|
||
|
||
class ProjectionYearly(Base):
|
||
"""Deterministic point projection per scenario — per-year point estimates
|
||
that drive fan charts and the per-year Grafana table. One row per
|
||
(scenario, year)."""
|
||
__tablename__ = "projection_yearly"
|
||
__table_args__ = {"schema": SCHEMA_NAME} # noqa: RUF012
|
||
|
||
id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
|
||
mc_run_id: Mapped[int] = mapped_column(Integer, nullable=False, index=True)
|
||
year_idx: Mapped[int] = mapped_column(Integer, nullable=False)
|
||
p10_portfolio_gbp: Mapped[Decimal] = mapped_column(Numeric(16, 2), nullable=False)
|
||
p25_portfolio_gbp: Mapped[Decimal] = mapped_column(Numeric(16, 2), nullable=False)
|
||
p50_portfolio_gbp: Mapped[Decimal] = mapped_column(Numeric(16, 2), nullable=False)
|
||
p75_portfolio_gbp: Mapped[Decimal] = mapped_column(Numeric(16, 2), nullable=False)
|
||
p90_portfolio_gbp: Mapped[Decimal] = mapped_column(Numeric(16, 2), nullable=False)
|
||
p50_withdrawal_gbp: Mapped[Decimal] = mapped_column(Numeric(12, 2), nullable=False)
|
||
p50_tax_gbp: Mapped[Decimal] = mapped_column(Numeric(12, 2), nullable=False)
|
||
survival_rate: Mapped[Decimal] = mapped_column(Numeric(6, 4), nullable=False)
|
||
|
||
|
||
class ScenarioSummary(Base):
|
||
"""Denormalised fast-read for Grafana — one row per (scenario, latest run)."""
|
||
__tablename__ = "scenario_summary"
|
||
__table_args__ = {"schema": SCHEMA_NAME} # noqa: RUF012
|
||
|
||
id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
|
||
scenario_id: Mapped[int] = mapped_column(Integer, unique=True, nullable=False)
|
||
mc_run_id: Mapped[int] = mapped_column(Integer, nullable=False)
|
||
jurisdiction: Mapped[str] = mapped_column(String(32), nullable=False, index=True)
|
||
strategy: Mapped[str] = mapped_column(String(32), nullable=False, index=True)
|
||
leave_uk_year: Mapped[int] = mapped_column(Integer, nullable=False)
|
||
glide_path: Mapped[str] = mapped_column(String(32), nullable=False)
|
||
spending_gbp: Mapped[Decimal] = mapped_column(Numeric(12, 2), nullable=False)
|
||
success_rate: Mapped[Decimal] = mapped_column(Numeric(6, 4), nullable=False)
|
||
p10_ending_gbp: Mapped[Decimal] = mapped_column(Numeric(16, 2), nullable=False)
|
||
p50_ending_gbp: Mapped[Decimal] = mapped_column(Numeric(16, 2), nullable=False)
|
||
p90_ending_gbp: Mapped[Decimal] = mapped_column(Numeric(16, 2), nullable=False)
|
||
median_lifetime_tax_gbp: Mapped[Decimal] = mapped_column(Numeric(14, 2), nullable=False)
|
||
median_years_to_ruin: Mapped[Decimal | None] = mapped_column(Numeric(6, 2), nullable=True)
|
||
updated_at: Mapped[datetime] = mapped_column(TIMESTAMP(timezone=True),
|
||
nullable=False,
|
||
server_default=func.now())
|
||
|
||
|
||
class LifeEvent(Base):
|
||
"""A timed event in a user's plan: retirement, kid born, mortgage payoff,
|
||
sabbatical, etc. Attached to a scenario.
|
||
|
||
`year_start` and `year_end` are offsets from the scenario start year
|
||
(year 0 = today). For one-time events, leave `year_end` = `year_start`.
|
||
`delta_gbp_per_year` is the annual cashflow change while the event is
|
||
active (negative = expense, positive = income; 0 for events that just
|
||
mark a milestone like "retire").
|
||
|
||
Free-form `payload` carries event-kind-specific config that the
|
||
simulator hasn't yet learned to consume — graceful forward-compat.
|
||
"""
|
||
__tablename__ = "life_event"
|
||
__table_args__ = {"schema": SCHEMA_NAME} # noqa: RUF012
|
||
|
||
id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
|
||
scenario_id: Mapped[int] = mapped_column(Integer, nullable=False, index=True)
|
||
kind: Mapped[str] = mapped_column(String(32), nullable=False)
|
||
name: Mapped[str] = mapped_column(String, nullable=False)
|
||
year_start: Mapped[int] = mapped_column(Integer, nullable=False)
|
||
year_end: Mapped[int | None] = mapped_column(Integer, nullable=True)
|
||
delta_gbp_per_year: Mapped[Decimal] = mapped_column(Numeric(12, 2),
|
||
nullable=False,
|
||
server_default=text("0"))
|
||
one_time_amount_gbp: Mapped[Decimal | None] = mapped_column(Numeric(14, 2), nullable=True)
|
||
# Spending category for flex-spending classification:
|
||
# essential — never trimmed by flex rules (mortgage, food, kids)
|
||
# discretionary — trimmed when portfolio drops vs ATH (travel, dining)
|
||
# not_spending — informational only (a milestone marker that doesn't
|
||
# change cashflow, e.g. a kid graduating)
|
||
# Default is `essential` so existing rows keep their full spending impact.
|
||
category: Mapped[str] = mapped_column(String(16),
|
||
nullable=False,
|
||
server_default=text("'essential'"))
|
||
enabled: Mapped[bool] = mapped_column(Boolean, nullable=False, server_default=text("true"))
|
||
payload: Mapped[dict[str, Any] | None] = mapped_column(JSON_TYPE, nullable=True)
|
||
created_at: Mapped[datetime] = mapped_column(TIMESTAMP(timezone=True),
|
||
nullable=False,
|
||
server_default=func.now())
|
||
|
||
|
||
class IncomeStream(Base):
|
||
"""A typed, recurring source of income — first-class income object.
|
||
|
||
Modelled as a per-scenario row so a user can stack salary, dividends,
|
||
rental, pensions, RSUs, etc. The simulator routes the after-tax
|
||
amount through the jurisdiction's tax engine using `tax_treatment`
|
||
as the bucket hint (income / dividend / cgt / tax_free).
|
||
|
||
`start_year` / `end_year` are offsets from the scenario start year.
|
||
`growth_pct` is real growth; the simulator applies it geometrically.
|
||
"""
|
||
__tablename__ = "income_stream"
|
||
__table_args__ = {"schema": SCHEMA_NAME} # noqa: RUF012
|
||
|
||
id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
|
||
scenario_id: Mapped[int] = mapped_column(Integer, nullable=False, index=True)
|
||
kind: Mapped[str] = mapped_column(String(32), nullable=False)
|
||
name: Mapped[str] = mapped_column(String, nullable=False)
|
||
start_year: Mapped[int] = mapped_column(Integer, nullable=False, server_default=text("0"))
|
||
end_year: Mapped[int | None] = mapped_column(Integer, nullable=True)
|
||
amount_gbp_per_year: Mapped[Decimal] = mapped_column(Numeric(12, 2),
|
||
nullable=False,
|
||
server_default=text("0"))
|
||
growth_pct: Mapped[Decimal] = mapped_column(Numeric(6, 4),
|
||
nullable=False,
|
||
server_default=text("0"))
|
||
tax_treatment: Mapped[str] = mapped_column(String(16),
|
||
nullable=False,
|
||
server_default=text("'income'"))
|
||
enabled: Mapped[bool] = mapped_column(Boolean, nullable=False, server_default=text("true"))
|
||
payload: Mapped[dict[str, Any] | None] = mapped_column(JSON_TYPE, nullable=True)
|
||
created_at: Mapped[datetime] = mapped_column(TIMESTAMP(timezone=True),
|
||
nullable=False,
|
||
server_default=func.now())
|
||
|
||
|
||
class ColSnapshot(Base):
|
||
"""Cached cost-of-living snapshot per (city_slug, source).
|
||
|
||
Phase 2 of the COL subsystem. Replaces the previous "baseline-only"
|
||
lookup with cache-then-scrape semantics:
|
||
|
||
service.lookup_city(slug) → check ColSnapshot, return if fresh
|
||
→ else scrape Numbeo, upsert, return
|
||
→ if scrape fails, fall back to baseline.py
|
||
|
||
TTL default = 365 days (`expires_at = fetched_at + interval '365 day'`).
|
||
The user explicitly asked for 1y on 2026-05-21 — Numbeo data doesn't
|
||
move fast enough to need monthly refresh, and the API/scraper has rate-
|
||
limit risk we prefer to amortise. Phase-3 CronJob will run a nightly
|
||
refresh of stale rows so individual user requests never have to scrape.
|
||
|
||
`(city_slug, source_name)` is unique — we can store multiple sources
|
||
per city (Numbeo + Expatistan) and reconcile in service.py.
|
||
"""
|
||
__tablename__ = "col_snapshot"
|
||
__table_args__ = {"schema": SCHEMA_NAME} # noqa: RUF012
|
||
|
||
id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
|
||
city_slug: Mapped[str] = mapped_column(String(64), nullable=False, index=True)
|
||
city_display: Mapped[str] = mapped_column(String(128), nullable=False)
|
||
country: Mapped[str] = mapped_column(String(64), nullable=False)
|
||
source_name: Mapped[str] = mapped_column(String(32), nullable=False)
|
||
source_url: Mapped[str | None] = mapped_column(String, nullable=True)
|
||
snapshot_date: Mapped[date] = mapped_column(Date, nullable=False)
|
||
fetched_at: Mapped[datetime] = mapped_column(TIMESTAMP(timezone=True),
|
||
nullable=False,
|
||
server_default=func.now())
|
||
expires_at: Mapped[datetime] = mapped_column(TIMESTAMP(timezone=True), nullable=False)
|
||
total_no_rent_gbp: Mapped[Decimal] = mapped_column(Numeric(12, 2), nullable=False)
|
||
total_with_rent_gbp: Mapped[Decimal] = mapped_column(Numeric(12, 2), nullable=False)
|
||
rent_1bed_center_gbp: Mapped[Decimal] = mapped_column(Numeric(12, 2), nullable=False)
|
||
rent_1bed_outside_gbp: Mapped[Decimal | None] = mapped_column(Numeric(12, 2), nullable=True)
|
||
raw_currency: Mapped[str] = mapped_column(String(3), nullable=False, server_default="GBP")
|
||
gbp_per_unit: Mapped[Decimal] = mapped_column(Numeric(12, 8),
|
||
nullable=False,
|
||
server_default=text("1"))
|
||
by_category_json: Mapped[dict[str, Any] | None] = mapped_column(JSON_TYPE, nullable=True)
|
||
|
||
|
||
class RetirementGoal(Base):
|
||
"""A user-defined success criterion for a scenario.
|
||
|
||
Examples:
|
||
- target_nw: "have ≥£2M real GBP at year 25" → kind=target_nw,
|
||
target_amount_gbp=2_000_000, target_year=25, comparator='>='
|
||
- never_run_out: "never run out before age 95" → kind=never_run_out,
|
||
target_year=65 (years from start), no amount
|
||
- inheritance: "leave ≥£500k to heirs" → kind=inheritance,
|
||
target_amount_gbp=500_000, target_year=horizon, comparator='>='
|
||
|
||
`success_threshold` is the probability bar that counts as "passing"
|
||
(e.g. 0.95 = 95% of MC paths must satisfy the comparator).
|
||
"""
|
||
__tablename__ = "retirement_goal"
|
||
__table_args__ = {"schema": SCHEMA_NAME} # noqa: RUF012
|
||
|
||
id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
|
||
scenario_id: Mapped[int] = mapped_column(Integer, nullable=False, index=True)
|
||
kind: Mapped[str] = mapped_column(String(32), nullable=False)
|
||
name: Mapped[str] = mapped_column(String, nullable=False)
|
||
target_amount_gbp: Mapped[Decimal | None] = mapped_column(Numeric(16, 2), nullable=True)
|
||
target_year: Mapped[int | None] = mapped_column(Integer, nullable=True)
|
||
comparator: Mapped[str] = mapped_column(String(4), nullable=False, server_default=text("'>='"))
|
||
success_threshold: Mapped[Decimal] = mapped_column(Numeric(4, 3),
|
||
nullable=False,
|
||
server_default=text("0.95"))
|
||
enabled: Mapped[bool] = mapped_column(Boolean, nullable=False, server_default=text("true"))
|
||
payload: Mapped[dict[str, Any] | None] = mapped_column(JSON_TYPE, nullable=True)
|
||
created_at: Mapped[datetime] = mapped_column(TIMESTAMP(timezone=True),
|
||
nullable=False,
|
||
server_default=func.now())
|
||
|
||
|
||
class FireExample(Base):
|
||
"""One Reddit-sourced FIRE example.
|
||
|
||
`reddit_id` UNIQUE makes re-ingest idempotent. Fields are nullable
|
||
when the LLM couldn't extract them confidently — never inferred.
|
||
Currency normalisation (portfolio_gbp / annual_exp_gbp) happens at
|
||
extraction time using `fire_planner/fx.py`; `raw_currency` is kept
|
||
for traceability.
|
||
"""
|
||
__tablename__ = "fire_example"
|
||
__table_args__ = {"schema": SCHEMA_NAME} # noqa: RUF012
|
||
|
||
id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
|
||
reddit_id: Mapped[str] = mapped_column(String(16), unique=True, nullable=False)
|
||
source_sub: Mapped[str] = mapped_column(String(64), nullable=False)
|
||
post_url: Mapped[str] = mapped_column(String, nullable=False)
|
||
post_date: Mapped[date] = mapped_column(Date, nullable=False, index=True)
|
||
post_title: Mapped[str] = mapped_column(String, nullable=False)
|
||
country: Mapped[str | None] = mapped_column(String(64), nullable=True, index=True)
|
||
city: Mapped[str | None] = mapped_column(String(128), nullable=True)
|
||
portfolio_gbp: Mapped[Decimal | None] = mapped_column(Numeric(14, 2), nullable=True)
|
||
annual_exp_gbp: Mapped[Decimal | None] = mapped_column(Numeric(12, 2), nullable=True)
|
||
age: Mapped[int | None] = mapped_column(Integer, nullable=True)
|
||
family_size: Mapped[int | None] = mapped_column(Integer, nullable=True)
|
||
fi_status: Mapped[str | None] = mapped_column(String(24), nullable=True, index=True)
|
||
is_retired: Mapped[bool | None] = mapped_column(Boolean, nullable=True)
|
||
raw_currency: Mapped[str | None] = mapped_column(String(3), nullable=True)
|
||
raw_excerpt: Mapped[str | None] = mapped_column(String, nullable=True)
|
||
llm_model: Mapped[str] = mapped_column(String(64), nullable=False)
|
||
llm_confidence: Mapped[Decimal | None] = mapped_column(Numeric(3, 2), nullable=True)
|
||
extracted_at: Mapped[datetime] = mapped_column(TIMESTAMP(timezone=True),
|
||
nullable=False,
|
||
server_default=func.now())
|
||
ingested_at: Mapped[datetime] = mapped_column(TIMESTAMP(timezone=True),
|
||
nullable=False,
|
||
server_default=func.now())
|
||
|
||
|
||
class FireTarget(Base):
|
||
"""Solved FIRE number per (Case × country × with-home) for the countdown.
|
||
|
||
One row per combination; the Grafana countdown reads `target_nw_gbp` for the
|
||
selected country and diffs it against current liquid net worth. Seeded on
|
||
LIQUID net worth (the pension joins later as `pension_at_unlock_gbp`) — see
|
||
ADR-0001. `reached_bar=False` flags a combination that can't hit the bar
|
||
within the search range (target then holds the search ceiling).
|
||
"""
|
||
__tablename__ = "fire_target"
|
||
__table_args__ = (
|
||
UniqueConstraint("case", "country_slug", "with_home", "bar",
|
||
name="uq_fire_target_case_country_home_bar"),
|
||
{"schema": SCHEMA_NAME},
|
||
)
|
||
|
||
id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
|
||
case: Mapped[str] = mapped_column(String(16), nullable=False, index=True)
|
||
country_slug: Mapped[str] = mapped_column(String(64), nullable=False, index=True)
|
||
country_display: Mapped[str] = mapped_column(String(128), nullable=False)
|
||
jurisdiction: Mapped[str] = mapped_column(String(32), nullable=False)
|
||
with_home: Mapped[bool] = mapped_column(Boolean, nullable=False,
|
||
server_default=text("false"))
|
||
bar: Mapped[Decimal] = mapped_column(Numeric(4, 3), nullable=False,
|
||
server_default=text("0.99"))
|
||
strategy: Mapped[str] = mapped_column(String(32), nullable=False,
|
||
server_default=text("'guyton_klinger'"))
|
||
annual_spend_gbp: Mapped[Decimal] = mapped_column(Numeric(12, 2), nullable=False)
|
||
target_nw_gbp: Mapped[Decimal] = mapped_column(Numeric(16, 2), nullable=False)
|
||
pension_at_unlock_gbp: Mapped[Decimal] = mapped_column(Numeric(16, 2), nullable=False,
|
||
server_default=text("0"))
|
||
success_at_target: Mapped[Decimal] = mapped_column(Numeric(6, 4), nullable=False)
|
||
reached_bar: Mapped[bool] = mapped_column(Boolean, nullable=False,
|
||
server_default=text("true"))
|
||
horizon_years: Mapped[int] = mapped_column(Integer, nullable=False)
|
||
n_paths: Mapped[int] = mapped_column(Integer, nullable=False)
|
||
updated_at: Mapped[datetime] = mapped_column(TIMESTAMP(timezone=True),
|
||
nullable=False,
|
||
server_default=func.now())
|
||
|
||
|
||
def create_engine_from_env() -> AsyncEngine:
|
||
url = os.environ["DB_CONNECTION_STRING"]
|
||
return create_async_engine(url, pool_pre_ping=True)
|
||
|
||
|
||
def make_session_factory(engine: AsyncEngine) -> async_sessionmaker[Any]:
|
||
return async_sessionmaker(engine, expire_on_commit=False)
|