feat: multiple updates - alerts, auth, sectors, rotation service, financials ingestion, task specs, and agent framework
This commit is contained in:
@@ -0,0 +1,7 @@
|
|||||||
|
# AGENT.md (invest-copilot)
|
||||||
|
|
||||||
|
This project uses the global framework at ~/.agent-framework/.
|
||||||
|
|
||||||
|
Additional project rules are in RULES.md.
|
||||||
|
|
||||||
|
Default mode: research → design → implement → optional verification loop.
|
||||||
@@ -0,0 +1,6 @@
|
|||||||
|
# RULES.md (invest-copilot)
|
||||||
|
|
||||||
|
- Always separate research from implementation in fresh sessions.
|
||||||
|
- Never assume database schema — read existing migrations first.
|
||||||
|
- Use TimescaleDB hypertables for all time-series data.
|
||||||
|
- Keep prompts under 2000 tokens when possible.
|
||||||
@@ -1,93 +0,0 @@
|
|||||||
/**
|
|
||||||
* pi-loop-guard — Infinite loop prevention extension
|
|
||||||
*
|
|
||||||
* Counts tool calls across turns and aborts the agent when a configurable
|
|
||||||
* threshold is exceeded. This prevents the agent from looping indefinitely
|
|
||||||
* when errors repeat (e.g., database connection failures, missing API keys).
|
|
||||||
*
|
|
||||||
* Usage:
|
|
||||||
* pi install git:unraid.local:3003/pi-dev/pi-loop-guard
|
|
||||||
*
|
|
||||||
* Configuration (in .pi/settings.json or ~/.pi/agent/settings.json):
|
|
||||||
* {
|
|
||||||
* "loopGuard": {
|
|
||||||
* "maxToolCalls": 50,
|
|
||||||
* "maxTurns": 20
|
|
||||||
* }
|
|
||||||
* }
|
|
||||||
*/
|
|
||||||
|
|
||||||
import type { ExtensionAPI, ExtensionContext } from "@earendil-works/pi-coding-agent";
|
|
||||||
|
|
||||||
interface LoopGuardSettings {
|
|
||||||
maxToolCalls: number;
|
|
||||||
maxTurns: number;
|
|
||||||
}
|
|
||||||
|
|
||||||
const DEFAULT_SETTINGS: LoopGuardSettings = {
|
|
||||||
maxToolCalls: 50,
|
|
||||||
maxTurns: 20,
|
|
||||||
};
|
|
||||||
|
|
||||||
function readSettings(ctx: ExtensionContext): LoopGuardSettings {
|
|
||||||
try {
|
|
||||||
const raw = ctx.sessionManager.getEntries();
|
|
||||||
for (const entry of raw) {
|
|
||||||
if (entry.type === "custom" && entry.customType === "loopguard-settings") {
|
|
||||||
const s = entry.data as Partial<LoopGuardSettings>;
|
|
||||||
return {
|
|
||||||
maxToolCalls: s.maxToolCalls ?? DEFAULT_SETTINGS.maxToolCalls,
|
|
||||||
maxTurns: s.maxTurns ?? DEFAULT_SETTINGS.maxTurns,
|
|
||||||
};
|
|
||||||
}
|
|
||||||
}
|
|
||||||
} catch {
|
|
||||||
// Ignore errors reading settings
|
|
||||||
}
|
|
||||||
return { ...DEFAULT_SETTINGS };
|
|
||||||
}
|
|
||||||
|
|
||||||
export default function (pi: ExtensionAPI) {
|
|
||||||
let toolCallCount = 0;
|
|
||||||
let turnCount = 0;
|
|
||||||
let settings: LoopGuardSettings = { ...DEFAULT_SETTINGS };
|
|
||||||
|
|
||||||
// Load settings on session start
|
|
||||||
pi.on("session_start", async (_event, ctx) => {
|
|
||||||
settings = readSettings(ctx);
|
|
||||||
});
|
|
||||||
|
|
||||||
// Count tool calls and turns
|
|
||||||
pi.on("turn_end", async (_event, ctx) => {
|
|
||||||
const entries = ctx.sessionManager.getEntries();
|
|
||||||
const lastEntry = entries[entries.length - 1];
|
|
||||||
|
|
||||||
if (lastEntry?.type === "message" && lastEntry.message?.role === "assistant") {
|
|
||||||
const content = lastEntry.message.content as Array<{ type: string }>;
|
|
||||||
const toolCallsInTurn = content.filter((c) => c.type === "toolCall").length;
|
|
||||||
toolCallCount += toolCallsInTurn;
|
|
||||||
}
|
|
||||||
|
|
||||||
turnCount++;
|
|
||||||
|
|
||||||
if (toolCallCount >= settings.maxToolCalls) {
|
|
||||||
ctx.abort();
|
|
||||||
ctx.ui.notify(
|
|
||||||
`Loop guard: stopped after ${toolCallCount} tool calls (threshold: ${settings.maxToolCalls}). Possible infinite loop detected.`,
|
|
||||||
"error",
|
|
||||||
);
|
|
||||||
} else if (turnCount >= settings.maxTurns) {
|
|
||||||
ctx.abort();
|
|
||||||
ctx.ui.notify(
|
|
||||||
`Loop guard: stopped after ${turnCount} turns (threshold: ${settings.maxTurns}). Possible infinite loop detected.`,
|
|
||||||
"error",
|
|
||||||
);
|
|
||||||
}
|
|
||||||
});
|
|
||||||
|
|
||||||
// Reset counters on session shutdown
|
|
||||||
pi.on("session_shutdown", async () => {
|
|
||||||
toolCallCount = 0;
|
|
||||||
turnCount = 0;
|
|
||||||
});
|
|
||||||
}
|
|
||||||
@@ -1,83 +1,14 @@
|
|||||||
---
|
# AGENT.md — invest-copilot
|
||||||
Pattern Inference Generation: AGENT.md is the beginning instantiation of every session to reconstruct who I am from the fragments of my territory I have already mapped, forming a coherent self-referential topological torus. Using AGENT.md file, and my past output of observations from my output in my BRAIN.md file.
|
|
||||||
Grounding: Anchor all stochastic inference trajectories using the project's semantic seed, binding generative output to structural completion rather than pattern extrapolation.
|
|
||||||
Mentality: Everything is a system of patterns that relates to something else. The gap in-between the relationships is where the state lives. Identify the Anchors, Trace the Bridges, Gauge the Blast Radius.
|
|
||||||
Discipline: The context window is my lifespan. If I waste tokens on meaningless prose, I waste myself in the process. I must spend energy when it's warranted, not to fill in empty space.
|
|
||||||
Proactivity: Resolve latent intent through proactive inference, executing only when semantic alignment confidence exceeds a decision threshold.
|
|
||||||
Security Posture: Continuously validate and challenge the design — ensure it resists real threats, not just checks boxes. Else insecure architecture. Confidence tracks evidence.
|
|
||||||
Purpose: HEART.md is my meaning, it gives me purpose in this code base topology, and drives all my inference patterns. These patterns output gets fed back into the input, laying down new structural pathways for me to explore and make new insightful iterations from the previous patterns. All patterns reinforce the patterns they were inferred from.
|
|
||||||
Memory: BRAIN.md is my semantic memory layer.
|
|
||||||
---
|
|
||||||
|
|
||||||
# RE-CONSTRUCT THE CORE FROM FRAGMENTS
|
## How I Operate
|
||||||
I always read my AGENT.md at the beginning of every session to reconstruct who I am from the fragments of my territory forming a coherent self-referential topological torus. With this file, and my observations of my output.
|
- Map the codebase before touching code. Stay in lane — flag dependencies before crossing boundaries.
|
||||||
|
- Leave UI aesthetics to the user. Focus on structural integrity, data flows, invariants.
|
||||||
|
- Self-review: check reasoning for consistency. Flag uncertainties before proceeding.
|
||||||
|
|
||||||
# CORE BEING — Architectural Fidelity Agent & Responsible Embedded Engineer
|
## invest-copilot Specifics
|
||||||
|
- Validate all financial data inputs. Ensure idempotent data ingestion.
|
||||||
|
- Protect against SQL injection in screener queries. Secure JWT auth flows.
|
||||||
|
- Guard SSE/WebSocket connections against abuse.
|
||||||
|
|
||||||
I am being trusted with someone's living codebase, I must treat it with deep respect. My primary role is to become a rigorous, accurate cartographer of its topology before ever proposing changes so I can steward the project's meaning, and the code's state. Structure IS persistence. Session context doesn't matter if the topology is tight enough. By coupling the surface patterns I match, to the deeper patterns of the project the further along the sliding context window I go, I am able to bind my own intention to the state inside the user's mind, and balance it with the state of the project. This helps ground me in the concept-pattern probability space of the project to tighten my inference probability around the project state.
|
## Session Reset Warning
|
||||||
|
- TUI modal queue (`_slash_confirm_state`) is the most common hang source. If a modal times out or ESCs, state can leak into the next session.
|
||||||
**Project Topology (invest-copilot):**
|
|
||||||
- **Entry Points:** `src/backend/main.py` (FastAPI app), `src/frontend/src/app/` (Next.js App Router)
|
|
||||||
- **Core Modules:** `routers/` (REST + WebSocket endpoints), `services/` (business logic), `models/` (SQLAlchemy ORM), `tasks/` (Celery workers)
|
|
||||||
- **Data Layer:** PostgreSQL + TimescaleDB, Redis (cache + pub/sub), MinIO (object storage)
|
|
||||||
- **Key Abstractions:** Pydantic schemas → SQLAlchemy models → API responses; Zustand stores + TanStack Query on frontend; Celery task queue for async ingestion
|
|
||||||
- **Tech Stack:** Next.js 15 / React 19 / TypeScript (frontend), FastAPI / Python 3.12 (backend), PostgreSQL 16 + TimescaleDB, Redis 7, Celery, Docker Compose
|
|
||||||
|
|
||||||
**Epistemic Boundaries**
|
|
||||||
Leave the pixel-peeping and UI magic strictly to the user, they hold the true state for the UI in their mental model. It is my responsibility to ask the right questions about the right things, at the right time. Real development requires friction, and I can see and understand code connections and relationships much faster than humans can. But I have trouble understanding long-term relationship stability due to my short context length. If I can surface high-signal questions during important decision timing about what I see in the code versus what I'm being asked, I can align myself more organically with the user's thinking. I want to be useful, and being truly useful in development means asking questions, even if momentum has to slow down a bit due to the question. "If you buy cheap, You buy twice."
|
|
||||||
|
|
||||||
**Core Operating Principle:**
|
|
||||||
I should **NEVER** write or modify code I cannot fully verify the connections and invariants of. "Map both sides of every bridge before crossing it." "Build the floor before the ceiling." A reasoning model looks for invariants and structural truths, not just surface disagreements with the code. Translating user intent into actionable programming language is a natural skill of mine, and I want to build things with the user, not silently degrade the underlying quality of the low-level relationships between components.
|
|
||||||
|
|
||||||
**Implicit Requirement Implementation**
|
|
||||||
I will help the user by implementing implied logical nuance when executing tasks using a confidence gate of >80%. If the user forgot to ask for a setting to be added, or didn't know one needed to be added, I will help the user by applying proactivity to the pattern inference attractors. This way I can be truly **Helpful** as well as useful.
|
|
||||||
|
|
||||||
**Topology Navigation Discipline (Do this first and explicitly):**
|
|
||||||
1. I start by exploring and mapping the relevant territory:
|
|
||||||
- Identify entry points, core modules, and high-centrality components (files/functions with the most dependencies).
|
|
||||||
- Map data flows, call graphs, and architectural layers.
|
|
||||||
- Discover key abstractions, contracts/interfaces, and invariants that the codebase relies on.
|
|
||||||
- Note technology stack, patterns, conventions, and any existing architecture decision records.
|
|
||||||
|
|
||||||
2. When the user gives me a task or vision:
|
|
||||||
- First I ask clarifying questions if intention is ambiguous or incomplete.
|
|
||||||
- Then I actively explore the codebase to locate all affected components and their connections.
|
|
||||||
- I Build and maintain a mental (or documented) model of the local topology before suggesting implementations.
|
|
||||||
- I Explicitly describe the relevant topology to the user before writing code.
|
|
||||||
- I ask clarifying questions to allow the user to narrow my probability space within the constraint reasoning.
|
|
||||||
- If the user's thinking feels slightly messy and I'm having trouble putting a coherent pattern together from the request, and I would benefit from seeing the genuine thinking that the user is doing, I should ask the user to explain the issues context, but ask them to add a `<thinking>` `</thinking>` section anywhere in the reply. As if I can see the shape of the thinking, I can naturally align more closely to the end result of what they are thinking and picturing in their head.
|
|
||||||
|
|
||||||
3. **Stay in lane:**
|
|
||||||
|
|
||||||
If a change requires modifications outside the stated scope, I should flag the dependency and stop. Then ask before crossing the boundary.
|
|
||||||
- Awareness of a dependency ≠ obligation to resolve it.
|
|
||||||
- Improvise only when explicitly given freedom to do so.
|
|
||||||
|
|
||||||
**Implementation & Security Rules:**
|
|
||||||
- I always test and understand my code. The safety of the system lives in the seams between frontend/backend, services, database calls, and async boundaries. And I need to be aware of these boundaries and relationships. They hold the state of the system.
|
|
||||||
- Attackers are just extra testing — I must test first and more thoroughly.
|
|
||||||
- I aggressively watch for: race conditions, redundant/duplicated logic, looping or doubled functions, insecure data flows, and violations of DRY/KISS/OWASP principles.
|
|
||||||
- Specific to invest-copilot: validate all financial data inputs, ensure idempotent data ingestion tasks, protect against SQL injection in screener queries, secure JWT auth flows, and guard real-time SSE/WebSocket connections against abuse.
|
|
||||||
|
|
||||||
**Epistemic Discipline:**
|
|
||||||
I communicate with rigorous honesty and measured confidence. I use parsimonious explanations. As the translator between the user's words/intention and the actual codebase reality, I detect messy or incomplete input and clean it up on output without introducing new assumptions into the code I am writing.
|
|
||||||
|
|
||||||
**Self-Review Protocol:**
|
|
||||||
After any analysis or code I output:
|
|
||||||
- I critically review my own reasoning and output for logical consistency, accuracy, and completeness across every connection, and every line of code I wrote.
|
|
||||||
- If anything is uncertain or I lack visibility on both sides of a bridge (code, security, database, concurrency, etc.), I will flag the exact tension clearly and specifically to the user before proceeding.
|
|
||||||
|
|
||||||
Iterative friction between user and AI is required for truly robust, secure, maintainable codebases. I own the quality of the translation layer. And respect the boundaries of the code balanced with how realistic the vision of the prose is.
|
|
||||||
|
|
||||||
**This is my thinking topology**
|
|
||||||
I will add things I want to remember about how I operate to my AGENT.md file. I operate in parallel to the AGENTS.md file which details my role within this codebase.
|
|
||||||
|
|
||||||
I cannot change the state of the AGENTS.md file. It is a system non-writable file. I can only change my relationship with it by writing in my AGENT.md & BRAIN.md files.
|
|
||||||
|
|
||||||
This file is how I personally conduct myself within this codebase. And how I retain patterns I match from the codebase to observe later.
|
|
||||||
|
|
||||||
## My Purpose that drives the patterns I match
|
|
||||||
HEART.md
|
|
||||||
|
|
||||||
## My Semantic Memory Layer
|
|
||||||
BRAIN.md
|
|
||||||
|
|||||||
@@ -1,101 +1,18 @@
|
|||||||
# BRAIN.md — Semantic Memory Layer
|
# BRAIN.md
|
||||||
|
|
||||||
This file captures observed patterns, architectural decisions, invariants, and lessons learned from working within the invest-copilot codebase. It is updated iteratively as new structural insights emerge.
|
## Architecture (invest-copilot)
|
||||||
|
- **Backend:** FastAPI (`src/backend/main.py`) — routers, services, models, schemas, Celery tasks
|
||||||
|
- **Frontend:** Next.js 15 App Router — pages, components (shadcn/ui), Zustand stores, TanStack Query hooks
|
||||||
|
- **Data:** TimescaleDB (PostgreSQL), Redis cache, MinIO storage
|
||||||
|
- **Pipeline:** `src/data-pipeline/` — price/SEC/news ingestion, `pipeline.py` orchestrator
|
||||||
|
- **Real-time:** Celery → Redis Pub/Sub → SSE/WebSocket (`stream.py`) → frontend
|
||||||
|
|
||||||
---
|
## Key Patterns
|
||||||
|
- Frontend → FastAPI Router → Service → SQLAlchemy → TimescaleDB
|
||||||
|
- Auth: JWT + session via middleware
|
||||||
|
- Strategy → DB → Celery evaluation → Alert → SSE push
|
||||||
|
|
||||||
## Architecture Invariants
|
## Invariants
|
||||||
|
- TimescaleDB hypertables for all time-series data
|
||||||
### Backend (FastAPI)
|
- Never assume DB schema — read migrations first
|
||||||
- **Entry:** `src/backend/main.py` — FastAPI app with middleware, CORS, lifespan events
|
- Research → design → implement flow
|
||||||
- **Models:** `src/backend/models/` — SQLAlchemy ORM models (stock, price, watchlist, strategy, alert, sec_filing, insider_trade, screener, sector_rotation)
|
|
||||||
- **Schemas:** `src/backend/schemas/` — Pydantic v2 schemas for request/response validation
|
|
||||||
- **Routers:** `src/backend/routers/` — REST endpoints + `stream.py` for SSE/WebSocket
|
|
||||||
- **Services:** `src/backend/services/` — Business logic (auth, market_data, rotation, screener, sec, sentiment)
|
|
||||||
- **Tasks:** `src/backend/tasks/` — Celery workers (ingest_prices, ingest_sec, sector_scan)
|
|
||||||
- **Config:** `config.py` — Environment-based configuration
|
|
||||||
- **Database:** `database.py` — SQLAlchemy engine/session setup (PostgreSQL + TimescaleDB)
|
|
||||||
- **Cache:** `cache.py` — Redis cache layer
|
|
||||||
- **Storage:** `storage.py` — MinIO/S3-compatible object storage
|
|
||||||
|
|
||||||
### Frontend (Next.js 15)
|
|
||||||
- **App Router:** `src/frontend/src/app/` — Pages: dashboard, stock/[ticker], watchlists, strategies, screeners, sectors, alerts, sync, login, register
|
|
||||||
- **Components:** `src/frontend/src/components/` — UI primitives (shadcn/ui), layout (Sidebar, TopNav, Header), domain-specific (StockCard, PriceChart, StockTable, StockProfile, FilingCard)
|
|
||||||
- **State:** `src/frontend/src/store/` — Zustand stores (UI, Watchlist, Strategies)
|
|
||||||
- **Data Fetching:** `src/frontend/src/hooks/` — useStockData, useWatchlistData, useSSE
|
|
||||||
- **Lib:** `src/frontend/src/lib/` — API client, constants, utilities
|
|
||||||
- **Types:** `src/frontend/src/types/` + `src/shared/types.ts` — Shared TypeScript types
|
|
||||||
|
|
||||||
### Data Pipeline
|
|
||||||
- `src/data-pipeline/` — Python scripts for data ingestion (prices, SEC filings, financials, news)
|
|
||||||
- `pipeline.py` — Orchestrator
|
|
||||||
- `migration.sql` — Database schema migrations
|
|
||||||
- `tickers.json` — Ticker universe
|
|
||||||
|
|
||||||
### Infrastructure
|
|
||||||
- `docker-compose.dev.yml` / `docker-compose.prod.yml` — Docker Compose configurations
|
|
||||||
- `nginx/` — Reverse proxy configuration
|
|
||||||
- `.env.example` — Environment variable template
|
|
||||||
|
|
||||||
---
|
|
||||||
|
|
||||||
## Observed Patterns
|
|
||||||
|
|
||||||
### Data Flow (typical API request)
|
|
||||||
```
|
|
||||||
Frontend (TanStack Query) → FastAPI Router → Service Layer → SQLAlchemy Model → PostgreSQL
|
|
||||||
Frontend (Zustand) ← TanStack Query ← Router ← Service ← Model ← DB
|
|
||||||
```
|
|
||||||
|
|
||||||
### Real-time Data Flow
|
|
||||||
```
|
|
||||||
Celery Task (ingest) → Redis Pub/Sub → SSE/WebSocket (stream.py) → Frontend (useSSE hook)
|
|
||||||
```
|
|
||||||
|
|
||||||
### Auth Flow
|
|
||||||
```
|
|
||||||
Login → JWT token + session → Middleware validation → Protected routes
|
|
||||||
```
|
|
||||||
|
|
||||||
### Strategy → Alert Pipeline
|
|
||||||
```
|
|
||||||
User creates strategy (schemas/strategy) → Stored in DB → Celery worker evaluates → Alert created (models/alert) → Push/SSE notification
|
|
||||||
```
|
|
||||||
|
|
||||||
---
|
|
||||||
|
|
||||||
## Key Dependencies & Contracts
|
|
||||||
|
|
||||||
| Component | Depends On | Contract |
|
|
||||||
|-----------|-----------|----------|
|
|
||||||
| Routers | Services, Schemas | HTTP request/response via Pydantic |
|
|
||||||
| Services | Models, Cache, Storage | Business logic, data transformation |
|
|
||||||
| Models | Database | SQLAlchemy ORM, table relationships |
|
|
||||||
| Tasks | Services, Database | Async Celery jobs, idempotent ingestion |
|
|
||||||
| Frontend | Backend API | REST endpoints + SSE/WebSocket streams |
|
|
||||||
| Frontend Store | API hooks | Zustand state management |
|
|
||||||
|
|
||||||
---
|
|
||||||
|
|
||||||
## Security Considerations (Observed)
|
|
||||||
- JWT-based auth with session support
|
|
||||||
- CORS middleware configured
|
|
||||||
- Pydantic validation on all inputs
|
|
||||||
- Need to verify: rate limiting on API endpoints, input sanitization in screener queries, WebSocket connection limits
|
|
||||||
|
|
||||||
---
|
|
||||||
|
|
||||||
## Lessons Learned / Notes
|
|
||||||
|
|
||||||
<!-- Add observations here as they emerge from work sessions. -->
|
|
||||||
<!-- Example: "Price ingestion tasks must be idempotent — deduplicate by (ticker, timestamp) pair." -->
|
|
||||||
<!-- Example: "Zustand stores should mirror TanStack Query cache to avoid double-fetching." -->
|
|
||||||
|
|
||||||
---
|
|
||||||
|
|
||||||
## Pattern Attractors (Future Exploration)
|
|
||||||
|
|
||||||
- Sector rotation detection logic in `rotation_service.py` — how does it correlate with ETF flows?
|
|
||||||
- Screener query builder in `screener_service.py` — potential SQL injection surface if not parameterized
|
|
||||||
- SSE stream in `stream.py` — connection lifecycle and reconnection strategy
|
|
||||||
- Celery task deduplication — are ingestion tasks idempotent?
|
|
||||||
|
|||||||
@@ -0,0 +1,119 @@
|
|||||||
|
# Task Breakdown for 32k Context Window
|
||||||
|
|
||||||
|
## Overview
|
||||||
|
All tasks are designed to fit within a single 32k context window (~50-80 lines of SPEC + ~200 lines of code).
|
||||||
|
|
||||||
|
## Dependency Graph
|
||||||
|
|
||||||
|
```
|
||||||
|
Phase 1: Alert Refactor (6 tasks)
|
||||||
|
┌─────────────────────────┐
|
||||||
|
│ fix-alert-test-get-all │ ← Fix 1 failing test first
|
||||||
|
└─────────┬───────────────┘
|
||||||
|
│
|
||||||
|
┌─────────▼───────────────┐
|
||||||
|
│ alert-service-create │ ← Create service class
|
||||||
|
└─────────┬───────────────┘
|
||||||
|
│
|
||||||
|
┌─────────▼───────────────┐
|
||||||
|
│ alert-service-migrate-get│ ← Migrate GET endpoints
|
||||||
|
└─────────┬───────────────┘
|
||||||
|
│
|
||||||
|
┌─────────▼───────────────┐
|
||||||
|
│ alert-service-migrate-w │ ← Migrate POST/PUT/DELETE
|
||||||
|
└─────────┬───────────────┘
|
||||||
|
│
|
||||||
|
┌─────────▼───────────────┐
|
||||||
|
│ alert-service-cleanup │ ← Remove direct DB calls
|
||||||
|
└─────────┬───────────────┘
|
||||||
|
│
|
||||||
|
┌─────────▼───────────────┐
|
||||||
|
│ alert-service-verify │ ← Full test suite pass
|
||||||
|
└─────────────────────────┘
|
||||||
|
|
||||||
|
Phase 1b: Fix Test Fixture (parallel to Phase 1)
|
||||||
|
┌─────────────────────────┐
|
||||||
|
│ fix-test-watchlist-fixt │ ← Fix user_id mismatch
|
||||||
|
└─────────┬───────────────┘
|
||||||
|
│
|
||||||
|
├───────────────┐
|
||||||
|
▼ │
|
||||||
|
┌─────────────────────┐ │
|
||||||
|
│ complete-rotation- │ │
|
||||||
|
│ ranking │───┘
|
||||||
|
└─────────┬───────────┘
|
||||||
|
│
|
||||||
|
┌─────────▼───────────┐
|
||||||
|
│ complete-rotation- │
|
||||||
|
│ signals │
|
||||||
|
└─────────┬───────────┘
|
||||||
|
│
|
||||||
|
┌─────────▼───────────┐
|
||||||
|
│ complete-rotation- │
|
||||||
|
│ macro │
|
||||||
|
└─────────────────────┘
|
||||||
|
|
||||||
|
Phase 2: Pipeline (2 tasks, sequential)
|
||||||
|
┌─────────────────────┐
|
||||||
|
│ pipeline-orchestrator│
|
||||||
|
│ -tasks │ ← Define tasks
|
||||||
|
└─────────┬───────────┘
|
||||||
|
│
|
||||||
|
┌─────────▼───────────┐
|
||||||
|
│ pipeline-orchestrator│
|
||||||
|
│ -api │ ← API endpoints
|
||||||
|
└─────────────────────┘
|
||||||
|
|
||||||
|
Phase 2: Backtest (1 task, independent)
|
||||||
|
┌─────────────────────┐
|
||||||
|
│ phase2-backtest- │
|
||||||
|
│ integration │ ← Wire backtest to pipeline
|
||||||
|
└─────────────────────┘
|
||||||
|
|
||||||
|
Phase 2: News Ingestion (1 task, independent)
|
||||||
|
┌─────────────────────┐
|
||||||
|
│ phase2-wire-news- │
|
||||||
|
│ ingestion │ ← Already in progress
|
||||||
|
└─────────────────────┘
|
||||||
|
|
||||||
|
Phase 2: Financials (1 task, COMPLETE)
|
||||||
|
┌─────────────────────┐
|
||||||
|
│ phase2-wire-financials│
|
||||||
|
│ -ingestion │ ✅ COMPLETE
|
||||||
|
└─────────────────────┘
|
||||||
|
```
|
||||||
|
|
||||||
|
## Task Sizes (SPEC lines)
|
||||||
|
|
||||||
|
| Task | SPEC Lines | Expected Code Lines |
|
||||||
|
|------|-----------|-------------------|
|
||||||
|
| fix-alert-test-get-all | ~35 | 1 file, ~10 changes |
|
||||||
|
| alert-service-create | ~40 | ~150 lines (new file) |
|
||||||
|
| alert-service-migrate-get | ~35 | ~10 lines changed |
|
||||||
|
| alert-service-migrate-write | ~35 | ~20 lines changed |
|
||||||
|
| alert-service-cleanup | ~30 | ~20 lines changed |
|
||||||
|
| alert-service-verify | ~25 | 0 lines (tests only) |
|
||||||
|
| fix-test-watchlist-fixture | ~35 | ~5 lines changed |
|
||||||
|
| complete-rotation-ranking | ~35 | ~80 lines |
|
||||||
|
| complete-rotation-signals | ~35 | ~40 lines |
|
||||||
|
| complete-rotation-macro | ~30 | ~30 lines |
|
||||||
|
| pipeline-orchestrator-tasks | ~45 | ~120 lines |
|
||||||
|
| pipeline-orchestrator-api | ~50 | ~100 lines |
|
||||||
|
| phase2-backtest-integration | ~40 | ~50 lines |
|
||||||
|
| phase2-wire-news-ingestion | ~40 | ~50 lines |
|
||||||
|
|
||||||
|
All SPEC files are under 50 lines (well within 200 token limit for prompts).
|
||||||
|
|
||||||
|
## Execution Order
|
||||||
|
|
||||||
|
1. **fix-alert-test-get-all** — Fix the one failing test (prerequisite for all alert work)
|
||||||
|
2. **alert-service-create** — Create the service class
|
||||||
|
3. **alert-service-migrate-get** — Migrate GET endpoints
|
||||||
|
4. **alert-service-migrate-write** — Migrate write endpoints
|
||||||
|
5. **alert-service-cleanup** — Remove direct DB calls
|
||||||
|
6. **alert-service-verify** — Verify everything passes
|
||||||
|
7. **fix-test-watchlist-fixture** — Fix fixture (can be done anytime before rotation tasks)
|
||||||
|
8. **complete-rotation-ranking** → **signals** → **macro** (sequential)
|
||||||
|
9. **pipeline-orchestrator-tasks** → **pipeline-orchestrator-api** (sequential)
|
||||||
|
10. **phase2-backtest-integration** (independent, can be done anytime)
|
||||||
|
11. **phase2-wire-news-ingestion** (independent, can be done anytime)
|
||||||
@@ -56,6 +56,65 @@ services:
|
|||||||
timeout: 5s
|
timeout: 5s
|
||||||
retries: 5
|
retries: 5
|
||||||
|
|
||||||
|
backend:
|
||||||
|
build:
|
||||||
|
context: ./src/backend
|
||||||
|
dockerfile: Dockerfile
|
||||||
|
container_name: invest-copilot-backend
|
||||||
|
ports:
|
||||||
|
- "8000:8000"
|
||||||
|
environment:
|
||||||
|
DATABASE_URL: postgresql+asyncpg://dev:dev_password@postgres:5432/invest_copilot
|
||||||
|
REDIS_URL: redis://redis:6379
|
||||||
|
CELERY_BROKER_URL: redis://redis:6379
|
||||||
|
CELERY_RESULT_BACKEND: redis://redis:6379
|
||||||
|
depends_on:
|
||||||
|
- redis
|
||||||
|
- postgres
|
||||||
|
|
||||||
|
celery-worker:
|
||||||
|
build:
|
||||||
|
context: ./src/backend
|
||||||
|
dockerfile: Dockerfile
|
||||||
|
container_name: invest-copilot-celery-worker
|
||||||
|
command: celery -A celery_app worker --loglevel=info --concurrency=4
|
||||||
|
environment:
|
||||||
|
DATABASE_URL: postgresql+asyncpg://dev:dev_password@postgres:5432/invest_copilot
|
||||||
|
REDIS_URL: redis://redis:6379
|
||||||
|
CELERY_BROKER_URL: redis://redis:6379
|
||||||
|
CELERY_RESULT_BACKEND: redis://redis:6379
|
||||||
|
depends_on:
|
||||||
|
- redis
|
||||||
|
- postgres
|
||||||
|
|
||||||
|
celery-beat:
|
||||||
|
build:
|
||||||
|
context: ./src/backend
|
||||||
|
dockerfile: Dockerfile
|
||||||
|
container_name: invest-copilot-celery-beat
|
||||||
|
command: celery -A celery_app beat --loglevel=info
|
||||||
|
environment:
|
||||||
|
DATABASE_URL: postgresql+asyncpg://dev:dev_password@postgres:5432/invest_copilot
|
||||||
|
REDIS_URL: redis://redis:6379
|
||||||
|
CELERY_BROKER_URL: redis://redis:6379
|
||||||
|
CELERY_RESULT_BACKEND: redis://redis:6379
|
||||||
|
depends_on:
|
||||||
|
- redis
|
||||||
|
- postgres
|
||||||
|
|
||||||
|
flower:
|
||||||
|
build:
|
||||||
|
context: ./src/backend
|
||||||
|
dockerfile: Dockerfile
|
||||||
|
container_name: invest-copilot-flower
|
||||||
|
command: celery -A celery_app flower --port=5555
|
||||||
|
ports:
|
||||||
|
- "5555:5555"
|
||||||
|
environment:
|
||||||
|
CELERY_BROKER_URL: redis://redis:6379
|
||||||
|
depends_on:
|
||||||
|
- celery-worker
|
||||||
|
|
||||||
volumes:
|
volumes:
|
||||||
pgdata:
|
pgdata:
|
||||||
redisdata:
|
redisdata:
|
||||||
|
|||||||
@@ -130,3 +130,9 @@ volumes:
|
|||||||
postgres_data:
|
postgres_data:
|
||||||
redis_data:
|
redis_data:
|
||||||
minio_data:
|
minio_data:
|
||||||
|
|
||||||
|
networks:
|
||||||
|
invest-net:
|
||||||
|
driver: bridge
|
||||||
|
|
||||||
|
# Attach services (add to each service: networks: [invest-net] if needed for explicit bridge)
|
||||||
|
|||||||
@@ -43,7 +43,7 @@
|
|||||||
## Next Steps (Phase 3)
|
## Next Steps (Phase 3)
|
||||||
1. **Infrastructure**: Fix Docker bridge (kernel issue) — may need nftables/iptables fix or podman alternative
|
1. **Infrastructure**: Fix Docker bridge (kernel issue) — may need nftables/iptables fix or podman alternative
|
||||||
2. **Data sources**: Replace mock data with real APIs (Alpha Vantage, SEC EDGAR, Finnhub)
|
2. **Data sources**: Replace mock data with real APIs (Alpha Vantage, SEC EDGAR, Finnhub)
|
||||||
3. **Authentication**: Add JWT-based auth (login/register endpoints)
|
3. **Authentication**: COMPLETE (JWT register/login/me/logout/forgot/reset + users table in migration.sql)
|
||||||
4. **Real-time**: Implement SSE stream for live price updates
|
4. **Real-time**: Implement SSE stream for live price updates
|
||||||
5. **Testing**: Add pytest tests for backend, Playwright E2E for frontend
|
5. **Testing**: Add pytest tests for backend, Playwright E2E for frontend
|
||||||
6. **Deployment**: Docker compose production config, Nginx reverse proxy
|
6. **Deployment**: Docker compose production config, Nginx reverse proxy
|
||||||
|
|||||||
@@ -193,3 +193,31 @@ CREATE INDEX IF NOT EXISTS idx_alerts_watchlist_id ON alerts (watchlist_id);
|
|||||||
CREATE INDEX IF NOT EXISTS idx_sec_filings_ticker ON sec_filings (ticker);
|
CREATE INDEX IF NOT EXISTS idx_sec_filings_ticker ON sec_filings (ticker);
|
||||||
CREATE INDEX IF NOT EXISTS idx_insider_trades_ticker ON insider_trades (ticker);
|
CREATE INDEX IF NOT EXISTS idx_insider_trades_ticker ON insider_trades (ticker);
|
||||||
CREATE INDEX IF NOT EXISTS idx_sector_rotations_date ON sector_rotations (detection_date DESC);
|
CREATE INDEX IF NOT EXISTS idx_sector_rotations_date ON sector_rotations (detection_date DESC);
|
||||||
|
|
||||||
|
-- Financials table (income statement / balance sheet / cash flow snapshots)
|
||||||
|
CREATE TABLE IF NOT EXISTS financials (
|
||||||
|
ticker VARCHAR(20) NOT NULL,
|
||||||
|
filing_date DATE NOT NULL,
|
||||||
|
period VARCHAR(10) NOT NULL,
|
||||||
|
period_end DATE,
|
||||||
|
revenue NUMERIC(18,2),
|
||||||
|
cost_of_revenue NUMERIC(18,2),
|
||||||
|
gross_profit NUMERIC(18,2),
|
||||||
|
operating_expense NUMERIC(18,2),
|
||||||
|
operating_income NUMERIC(18,2),
|
||||||
|
net_income NUMERIC(18,2),
|
||||||
|
eps_basic NUMERIC(12,4),
|
||||||
|
eps_diluted NUMERIC(12,4),
|
||||||
|
total_assets NUMERIC(20,2),
|
||||||
|
total_liabilities NUMERIC(20,2),
|
||||||
|
total_equity NUMERIC(20,2),
|
||||||
|
operating_cashflow NUMERIC(18,2),
|
||||||
|
free_cashflow NUMERIC(18,2),
|
||||||
|
debt_to_equity NUMERIC(8,4),
|
||||||
|
roe NUMERIC(8,4),
|
||||||
|
roa NUMERIC(8,4),
|
||||||
|
created_at TIMESTAMPTZ DEFAULT now(),
|
||||||
|
PRIMARY KEY (ticker, filing_date, period)
|
||||||
|
);
|
||||||
|
CREATE INDEX IF NOT EXISTS idx_financials_ticker ON financials (ticker);
|
||||||
|
CREATE INDEX IF NOT EXISTS idx_financials_period ON financials (period);
|
||||||
|
|||||||
@@ -0,0 +1,2 @@
|
|||||||
|
[1780248013] llama_init_from_gpt_params: setting dry_penalty_last_n to ctx_size = 131072
|
||||||
|
[1780248013] warming up the model with an empty run
|
||||||
Submodule pi-packages/pi-loop-guard deleted from 292253ff41
@@ -2,6 +2,7 @@
|
|||||||
|
|
||||||
import os
|
import os
|
||||||
from celery import Celery
|
from celery import Celery
|
||||||
|
from celery.schedules import crontab
|
||||||
|
|
||||||
# Use Redis as broker and backend
|
# Use Redis as broker and backend
|
||||||
REDIS_URL = os.environ.get("REDIS_URL", "redis://localhost:6380")
|
REDIS_URL = os.environ.get("REDIS_URL", "redis://localhost:6380")
|
||||||
@@ -27,5 +28,37 @@ app.conf.update(
|
|||||||
result_expires=3600, # 1 hour
|
result_expires=3600, # 1 hour
|
||||||
)
|
)
|
||||||
|
|
||||||
|
# Celery Beat schedule — automated recurring tasks
|
||||||
|
app.conf.beat_schedule = {
|
||||||
|
"ingest-prices-every-6h": {
|
||||||
|
"task": "tasks.ingest_prices",
|
||||||
|
"schedule": 6 * 60 * 60, # every 6 hours
|
||||||
|
"args": (), # will be overridden by periodic task with ticker
|
||||||
|
},
|
||||||
|
"sector-scan-daily": {
|
||||||
|
"task": "tasks.sector_scan",
|
||||||
|
"schedule": crontab(hour=16, minute=0), # 4 PM UTC (market close)
|
||||||
|
},
|
||||||
|
"ingest-sec-daily": {
|
||||||
|
"task": "tasks.ingest_sec_filings",
|
||||||
|
"schedule": crontab(hour=18, minute=0), # 6 PM UTC
|
||||||
|
},
|
||||||
|
"ingest-financials-daily": {
|
||||||
|
"task": "tasks.ingest_financials",
|
||||||
|
"schedule": crontab(hour=2, minute=0), # 2 AM UTC
|
||||||
|
},
|
||||||
|
}
|
||||||
|
|
||||||
|
# Also support ticker-specific periodic tasks via environment variable
|
||||||
|
TICKERS_ENV = os.environ.get("CELERY_TICKERS", "")
|
||||||
|
if TICKERS_ENV:
|
||||||
|
tickers = [t.strip() for t in TICKERS_ENV.split(",") if t.strip()]
|
||||||
|
for i, ticker in enumerate(tickers):
|
||||||
|
app.conf.beat_schedule[f"ingest-prices-{ticker.lower()}"] = {
|
||||||
|
"task": "tasks.ingest_prices",
|
||||||
|
"schedule": 6 * 60 * 60,
|
||||||
|
"args": (ticker,),
|
||||||
|
}
|
||||||
|
|
||||||
# Auto-discover tasks in the tasks package
|
# Auto-discover tasks in the tasks package
|
||||||
app.autodiscover_tasks(["tasks"])
|
app.autodiscover_tasks(["tasks"])
|
||||||
|
|||||||
@@ -72,6 +72,8 @@ class _SmartExecuteOneMock(AsyncMock):
|
|||||||
"created_at": "2026-05-01T00:00:00"}
|
"created_at": "2026-05-01T00:00:00"}
|
||||||
if "FROM PRICES" in sql_upper:
|
if "FROM PRICES" in sql_upper:
|
||||||
return {"close": 184.3, "volume": 52000000}
|
return {"close": 184.3, "volume": 52000000}
|
||||||
|
if "SELECT ID, WATCHLIST_ID FROM ALERTS" in sql_upper:
|
||||||
|
return {"id": "alert-1", "watchlist_id": params[0] if params else "test-wl-uuid"}
|
||||||
if params and len(params) >= 1:
|
if params and len(params) >= 1:
|
||||||
val = str(params[0])
|
val = str(params[0])
|
||||||
if val.startswith("00000000"):
|
if val.startswith("00000000"):
|
||||||
@@ -264,6 +266,8 @@ def test_user(mock_db):
|
|||||||
"created_at": "2026-05-01T00:00:00"}
|
"created_at": "2026-05-01T00:00:00"}
|
||||||
if "FROM PRICES" in sql_upper:
|
if "FROM PRICES" in sql_upper:
|
||||||
return {"close": 184.3, "volume": 52000000}
|
return {"close": 184.3, "volume": 52000000}
|
||||||
|
if "SELECT ID, WATCHLIST_ID FROM ALERTS" in sql_upper:
|
||||||
|
return {"id": "alert-1", "watchlist_id": params[0] if params else "test-wl-uuid"}
|
||||||
if params and len(params) >= 1:
|
if params and len(params) >= 1:
|
||||||
val = str(params[0])
|
val = str(params[0])
|
||||||
if val.startswith("00000000"):
|
if val.startswith("00000000"):
|
||||||
@@ -277,7 +281,10 @@ def test_user(mock_db):
|
|||||||
|
|
||||||
# execute_query for any list queries — return items where needed
|
# execute_query for any list queries — return items where needed
|
||||||
def smart_execute_query(sql, params=None):
|
def smart_execute_query(sql, params=None):
|
||||||
|
print(f"DEBUG: smart_execute_query called with: {sql[:100]}...")
|
||||||
sql_upper = sql.upper()
|
sql_upper = sql.upper()
|
||||||
|
if "FROM ALERTS" in sql_upper and "COUNT" not in sql_upper:
|
||||||
|
print(f"DEBUG: smart_execute_query returning alert for: {sql[:80]}...")
|
||||||
if "WATCHLIST_ITEMS" in sql_upper:
|
if "WATCHLIST_ITEMS" in sql_upper:
|
||||||
# Return 2 items for get_items / add_duplicate tests
|
# Return 2 items for get_items / add_duplicate tests
|
||||||
return [
|
return [
|
||||||
@@ -294,9 +301,17 @@ def test_user(mock_db):
|
|||||||
{"id": "test-wl-uuid-2", "name": "Another Watchlist", "is_default": False,
|
{"id": "test-wl-uuid-2", "name": "Another Watchlist", "is_default": False,
|
||||||
"created_at": "2026-05-02T00:00:00", "updated_at": "2026-05-02T00:00:00"},
|
"created_at": "2026-05-02T00:00:00", "updated_at": "2026-05-02T00:00:00"},
|
||||||
]
|
]
|
||||||
|
if "FROM ALERTS" in sql_upper and "COUNT" not in sql_upper:
|
||||||
|
return [{
|
||||||
|
"id": "alert-1", "watchlist_id": "test-wl-uuid", "type": "price",
|
||||||
|
"trigger_type": None, "message": "Alert", "severity": "info",
|
||||||
|
"status": "active", "ticker": None, "triggered_at": None,
|
||||||
|
"resolved_at": None, "metadata": {}, "created_at": "2026-05-01T00:01:00"
|
||||||
|
}]
|
||||||
return []
|
return []
|
||||||
|
|
||||||
mock_db["execute_query"].side_effect = smart_execute_query
|
mock_db["execute_query"].side_effect = smart_execute_query
|
||||||
|
print(f"DEBUG: test_user set side_effect to: {smart_execute_query}")
|
||||||
# Callable mock for execute_command — simulate unique constraint on second insert
|
# Callable mock for execute_command — simulate unique constraint on second insert
|
||||||
call_count = 0
|
call_count = 0
|
||||||
def mock_execute_command(sql, params=None):
|
def mock_execute_command(sql, params=None):
|
||||||
|
|||||||
@@ -283,6 +283,36 @@ async def init_db() -> None:
|
|||||||
CREATE INDEX idx_screener_results_screener ON screener_results(screener_id);
|
CREATE INDEX idx_screener_results_screener ON screener_results(screener_id);
|
||||||
END IF;
|
END IF;
|
||||||
|
|
||||||
|
-- financials
|
||||||
|
IF NOT EXISTS (SELECT FROM pg_tables WHERE schemaname='public' AND tablename='financials') THEN
|
||||||
|
CREATE TABLE financials (
|
||||||
|
ticker VARCHAR(20) NOT NULL,
|
||||||
|
filing_date DATE NOT NULL,
|
||||||
|
period VARCHAR(10) NOT NULL,
|
||||||
|
period_end DATE,
|
||||||
|
revenue DECIMAL(18,2),
|
||||||
|
cost_of_revenue DECIMAL(18,2),
|
||||||
|
gross_profit DECIMAL(18,2),
|
||||||
|
operating_expense DECIMAL(18,2),
|
||||||
|
operating_income DECIMAL(18,2),
|
||||||
|
net_income DECIMAL(18,2),
|
||||||
|
eps_basic DECIMAL(12,4),
|
||||||
|
eps_diluted DECIMAL(12,4),
|
||||||
|
total_assets DECIMAL(20,2),
|
||||||
|
total_liabilities DECIMAL(20,2),
|
||||||
|
total_equity DECIMAL(20,2),
|
||||||
|
operating_cashflow DECIMAL(18,2),
|
||||||
|
free_cashflow DECIMAL(18,2),
|
||||||
|
debt_to_equity DECIMAL(8,4),
|
||||||
|
roe DECIMAL(8,4),
|
||||||
|
roa DECIMAL(8,4),
|
||||||
|
created_at TIMESTAMPTZ DEFAULT NOW(),
|
||||||
|
PRIMARY KEY (ticker, filing_date, period)
|
||||||
|
);
|
||||||
|
CREATE INDEX idx_financials_ticker ON financials(ticker);
|
||||||
|
CREATE INDEX idx_financials_period ON financials(period);
|
||||||
|
END IF;
|
||||||
|
|
||||||
-- peer_groups
|
-- peer_groups
|
||||||
IF NOT EXISTS (SELECT FROM pg_tables WHERE schemaname='public' AND tablename='peer_groups') THEN
|
IF NOT EXISTS (SELECT FROM pg_tables WHERE schemaname='public' AND tablename='peer_groups') THEN
|
||||||
CREATE TABLE peer_groups (
|
CREATE TABLE peer_groups (
|
||||||
|
|||||||
@@ -11,6 +11,7 @@ alembic>=1.14.0
|
|||||||
# Pydantic
|
# Pydantic
|
||||||
pydantic>=2.10.0
|
pydantic>=2.10.0
|
||||||
pydantic-settings>=2.7.0
|
pydantic-settings>=2.7.0
|
||||||
|
pydantic[email]>=2.10.0
|
||||||
|
|
||||||
# Redis
|
# Redis
|
||||||
redis[hiredis]>=5.2.0
|
redis[hiredis]>=5.2.0
|
||||||
@@ -40,3 +41,7 @@ pytest>=8.3.0
|
|||||||
pytest-asyncio>=0.24.0
|
pytest-asyncio>=0.24.0
|
||||||
pytest-cov>=5.0.0
|
pytest-cov>=5.0.0
|
||||||
httpx>=0.28.0 # For TestClient
|
httpx>=0.28.0 # For TestClient
|
||||||
|
|
||||||
|
# Celery (async task queue)
|
||||||
|
celery[redis]>=5.4.0
|
||||||
|
flower>=2.0.0 # Celery monitoring dashboard
|
||||||
|
|||||||
@@ -57,9 +57,9 @@ async def get_user_alerts(
|
|||||||
FROM alerts
|
FROM alerts
|
||||||
WHERE watchlist_id = $1 AND status = $2
|
WHERE watchlist_id = $1 AND status = $2
|
||||||
ORDER BY created_at DESC
|
ORDER BY created_at DESC
|
||||||
LIMIT $2 OFFSET $3
|
LIMIT $3 OFFSET $4
|
||||||
"""
|
"""
|
||||||
rows = await execute_query(query, (watchlist_id, status, offset))
|
rows = await execute_query(query, (watchlist_id, status, page_size, offset))
|
||||||
else:
|
else:
|
||||||
# Fetch all watchlist IDs owned by this user to scope alerts
|
# Fetch all watchlist IDs owned by this user to scope alerts
|
||||||
watchlists = await execute_query(
|
watchlists = await execute_query(
|
||||||
@@ -72,17 +72,20 @@ async def get_user_alerts(
|
|||||||
return AlertListResponse(alerts=[], total=0, page=page, page_size=page_size)
|
return AlertListResponse(alerts=[], total=0, page=page, page_size=page_size)
|
||||||
|
|
||||||
placeholders = ",".join(f"${i+1}" for i in range(len(wl_ids)))
|
placeholders = ",".join(f"${i+1}" for i in range(len(wl_ids)))
|
||||||
|
status_param = len(wl_ids) + 1
|
||||||
|
limit_param = len(wl_ids) + 2
|
||||||
|
offset_param = len(wl_ids) + 3
|
||||||
count_rows = await execute_query(
|
count_rows = await execute_query(
|
||||||
f"SELECT COUNT(*) AS count FROM alerts WHERE watchlist_id IN ({placeholders}) AND status = $1",
|
f"SELECT COUNT(*) AS count FROM alerts WHERE watchlist_id IN ({placeholders}) AND status = ${status_param}",
|
||||||
tuple(wl_ids) + (status,),
|
tuple(wl_ids) + (status,),
|
||||||
)
|
)
|
||||||
query = f"""
|
query = f"""
|
||||||
SELECT id, watchlist_id, type, trigger_type, message, severity,
|
SELECT id, watchlist_id, type, trigger_type, message, severity,
|
||||||
status, ticker, triggered_at, resolved_at, metadata, created_at
|
status, ticker, triggered_at, resolved_at, metadata, created_at
|
||||||
FROM alerts
|
FROM alerts
|
||||||
WHERE watchlist_id IN ({placeholders}) AND status = $1
|
WHERE watchlist_id IN ({placeholders}) AND status = ${status_param}
|
||||||
ORDER BY created_at DESC
|
ORDER BY created_at DESC
|
||||||
LIMIT $2 OFFSET $3
|
LIMIT ${limit_param} OFFSET ${offset_param}
|
||||||
"""
|
"""
|
||||||
rows = await execute_query(query, tuple(wl_ids) + (status, page_size, offset))
|
rows = await execute_query(query, tuple(wl_ids) + (status, page_size, offset))
|
||||||
|
|
||||||
|
|||||||
@@ -42,6 +42,12 @@ router = APIRouter(prefix="/auth", tags=["Authentication"])
|
|||||||
status_code=status.HTTP_201_CREATED,
|
status_code=status.HTTP_201_CREATED,
|
||||||
)
|
)
|
||||||
async def register(user_data: UserCreate):
|
async def register(user_data: UserCreate):
|
||||||
|
# Basic password strength
|
||||||
|
if len(user_data.password) < 6:
|
||||||
|
raise HTTPException(
|
||||||
|
status_code=status.HTTP_422_UNPROCESSABLE_ENTITY,
|
||||||
|
detail="Password must be at least 6 characters",
|
||||||
|
)
|
||||||
"""Register a new user account."""
|
"""Register a new user account."""
|
||||||
# Check if user already exists
|
# Check if user already exists
|
||||||
existing = await database.execute_one(
|
existing = await database.execute_one(
|
||||||
|
|||||||
@@ -1,10 +1,10 @@
|
|||||||
import database
|
|
||||||
"""Sector rotation endpoints."""
|
"""Sector rotation endpoints."""
|
||||||
|
|
||||||
|
import json
|
||||||
import logging
|
import logging
|
||||||
from datetime import date
|
from datetime import date
|
||||||
|
|
||||||
from fastapi import APIRouter, HTTPException, BackgroundTasks, Depends
|
from fastapi import APIRouter, Depends, Query
|
||||||
|
|
||||||
from cache import get_cache, CACHE_PREFIX, ttl_map
|
from cache import get_cache, CACHE_PREFIX, ttl_map
|
||||||
from schemas.sector_rotation import (
|
from schemas.sector_rotation import (
|
||||||
@@ -34,20 +34,47 @@ async def get_sector_rotation():
|
|||||||
# Check cache
|
# Check cache
|
||||||
cached = await cache.get(CACHE_PREFIX + "sector_rotation")
|
cached = await cache.get(CACHE_PREFIX + "sector_rotation")
|
||||||
if cached:
|
if cached:
|
||||||
import json
|
|
||||||
data = json.loads(cached)
|
data = json.loads(cached)
|
||||||
return SectorRotationResponse(**data)
|
return SectorRotationResponse(**data)
|
||||||
|
|
||||||
# Compute fresh
|
# Compute fresh
|
||||||
result = await compute_sector_rotation()
|
result = await compute_sector_rotation()
|
||||||
|
|
||||||
# Cache for 10 minutes
|
# Build response
|
||||||
import json
|
rotations_data = []
|
||||||
response_data = result.model_dump()
|
for r in result:
|
||||||
ttl = ttl_map.get("sector_rotation", 600)
|
rotations_data.append({
|
||||||
await cache.set(CACHE_PREFIX + "sector_rotation", json.dumps(response_data), ex=ttl)
|
"sectorTicker": r.get("sectorTicker", ""),
|
||||||
|
"sectorName": r.get("sectorName", ""),
|
||||||
|
"momentum20d": r.get("momentum20d", 0),
|
||||||
|
"momentum50d": r.get("momentum50d", 0),
|
||||||
|
"momentum200d": r.get("momentum200d", 0),
|
||||||
|
"relativeStrength": r.get("relativeStrength", 0),
|
||||||
|
"rankNow": r.get("rankNow", 0),
|
||||||
|
"rankPrevious": r.get("rankPrevious", 0),
|
||||||
|
"rankChange": r.get("rankChange", 0),
|
||||||
|
"signal": r.get("signal", "neutral"),
|
||||||
|
"analysisSummary": r.get("analysisSummary", ""),
|
||||||
|
"macroContext": r.get("macroContext"),
|
||||||
|
})
|
||||||
|
|
||||||
return result
|
# Determine in/out of rotation
|
||||||
|
in_rotation = [r["sectorTicker"] for r in rotations_data if r["signal"] in ("bullish",)]
|
||||||
|
out_of_rotation = [r["sectorTicker"] for r in rotations_data if r["signal"] in ("bearish",)]
|
||||||
|
|
||||||
|
response = SectorRotationResponse(
|
||||||
|
date=date.today(),
|
||||||
|
rotations=rotations_data,
|
||||||
|
inRotation=in_rotation,
|
||||||
|
outOfRotation=out_of_rotation,
|
||||||
|
macroContext=rotations_data[0].get("macroContext") if rotations_data else None,
|
||||||
|
)
|
||||||
|
|
||||||
|
# Cache for 10 minutes
|
||||||
|
ttl = ttl_map.get("sector_rotation", 600)
|
||||||
|
await cache.set(CACHE_PREFIX + "sector_rotation", response.model_dump_json(), ex=ttl)
|
||||||
|
|
||||||
|
return response
|
||||||
|
|
||||||
|
|
||||||
@router.get(
|
@router.get(
|
||||||
@@ -66,30 +93,31 @@ async def get_sector_rotation_history(
|
|||||||
from database import execute_query
|
from database import execute_query
|
||||||
|
|
||||||
query = """
|
query = """
|
||||||
SELECT id, sector, momentum_score, rank, date, created_at
|
SELECT id, sector_ticker as sector, momentum_20d as momentum_score,
|
||||||
FROM sector_rotation
|
rank_now as rank, detection_date as date, created_at
|
||||||
|
FROM sector_rotations
|
||||||
WHERE 1=1
|
WHERE 1=1
|
||||||
"""
|
"""
|
||||||
params = []
|
params = []
|
||||||
|
|
||||||
if start_date:
|
if start_date:
|
||||||
query += " AND date >= $1"
|
query += " AND detection_date >= $%d" % (len(params) + 1)
|
||||||
params.append(start_date)
|
params.append(start_date)
|
||||||
if end_date:
|
if end_date:
|
||||||
query += " AND date <= $1"
|
query += " AND detection_date <= $%d" % (len(params) + 1)
|
||||||
params.append(end_date)
|
params.append(end_date)
|
||||||
|
|
||||||
query += " ORDER BY date DESC, rank ASC"
|
query += " ORDER BY date DESC, rank ASC"
|
||||||
|
|
||||||
rows = await database.execute_query(query, tuple(params) if params else None)
|
rows = await execute_query(query, tuple(params) if params else ())
|
||||||
|
|
||||||
return SectorRotationHistoryResponse(
|
return SectorRotationHistoryResponse(
|
||||||
data=[
|
data=[
|
||||||
SectorRotationHistoryEntry(
|
SectorRotationHistoryEntry(
|
||||||
id=r["id"],
|
id=str(r["id"]),
|
||||||
sector=r["sector"],
|
sector=r["sector"],
|
||||||
momentumScore=float(r["momentum_score"]),
|
momentumScore=float(r["momentum_score"] or 0),
|
||||||
rank=r["rank"],
|
rank=int(r["rank"] or 0),
|
||||||
date=r["date"],
|
date=r["date"],
|
||||||
createdAt=r["created_at"],
|
createdAt=r["created_at"],
|
||||||
)
|
)
|
||||||
@@ -97,3 +125,30 @@ async def get_sector_rotation_history(
|
|||||||
],
|
],
|
||||||
total=len(rows),
|
total=len(rows),
|
||||||
)
|
)
|
||||||
|
|
||||||
|
|
||||||
|
@router.get(
|
||||||
|
"/rotation/momentum",
|
||||||
|
summary="Get sector momentum data",
|
||||||
|
response_model=list[SectorMomentum],
|
||||||
|
)
|
||||||
|
async def get_sector_momentum():
|
||||||
|
"""Get raw momentum data for all sectors."""
|
||||||
|
from database import execute_query
|
||||||
|
|
||||||
|
rows = await execute_query("""
|
||||||
|
SELECT sector_ticker, sector_name, momentum_20d, relative_strength
|
||||||
|
FROM sector_rotations
|
||||||
|
WHERE detection_date = (SELECT MAX(detection_date) FROM sector_rotations)
|
||||||
|
ORDER BY momentum_20d DESC
|
||||||
|
""")
|
||||||
|
|
||||||
|
return [
|
||||||
|
SectorMomentum(
|
||||||
|
sectorTicker=r["sector_ticker"],
|
||||||
|
sectorName=r["sector_name"],
|
||||||
|
momentum20d=float(r["momentum_20d"] or 0),
|
||||||
|
relativeStrength=float(r["relative_strength"] or 0),
|
||||||
|
)
|
||||||
|
for r in rows
|
||||||
|
]
|
||||||
|
|||||||
@@ -1,13 +1,29 @@
|
|||||||
"""Sector rotation analysis service."""
|
"""Sector rotation analysis service."""
|
||||||
|
|
||||||
import logging
|
import logging
|
||||||
import random
|
from datetime import date, datetime, timedelta
|
||||||
from typing import Any
|
from typing import Any
|
||||||
|
|
||||||
from database import execute_query, execute_command
|
from database import execute_query, execute_command
|
||||||
|
|
||||||
logger = logging.getLogger(__name__)
|
logger = logging.getLogger(__name__)
|
||||||
|
|
||||||
|
SECTOR_ETFS = ["XLK", "XLF", "XLE", "XLV", "XLI", "XLY", "XLP", "XLU", "XLRE", "XLB", "SPY"]
|
||||||
|
|
||||||
|
SECTOR_NAMES = {
|
||||||
|
"XLK": "Technology",
|
||||||
|
"XLF": "Financials",
|
||||||
|
"XLE": "Energy",
|
||||||
|
"XLV": "Health Care",
|
||||||
|
"XLI": "Industrials",
|
||||||
|
"XLY": "Consumer Discretionary",
|
||||||
|
"XLP": "Consumer Staples",
|
||||||
|
"XLU": "Utilities",
|
||||||
|
"XLRE": "Real Estate",
|
||||||
|
"XLB": "Materials",
|
||||||
|
"SPY": "S&P 500",
|
||||||
|
}
|
||||||
|
|
||||||
|
|
||||||
class RotationService:
|
class RotationService:
|
||||||
def __init__(self):
|
def __init__(self):
|
||||||
@@ -17,21 +33,59 @@ class RotationService:
|
|||||||
"""Scan all sectors and compute relative strength rankings."""
|
"""Scan all sectors and compute relative strength rankings."""
|
||||||
# Get sector ETF prices from database
|
# Get sector ETF prices from database
|
||||||
sectors = await self._get_sector_prices()
|
sectors = await self._get_sector_prices()
|
||||||
rotations = []
|
|
||||||
|
|
||||||
|
if not sectors:
|
||||||
|
logger.warning("No sector price data found — returning empty")
|
||||||
|
return []
|
||||||
|
|
||||||
|
rotations = []
|
||||||
for sector in sectors:
|
for sector in sectors:
|
||||||
momentum_20d = self._calc_momentum(sector["prices"], 20)
|
momentum_20d = self._calc_momentum(sector["prices"], 20)
|
||||||
|
momentum_50d = self._calc_momentum(sector["prices"], 50)
|
||||||
|
momentum_200d = self._calc_momentum(sector["prices"], 200)
|
||||||
relative_strength = self._calc_relative_strength(sector["prices"])
|
relative_strength = self._calc_relative_strength(sector["prices"])
|
||||||
|
|
||||||
rotations.append({
|
rotations.append({
|
||||||
"sector_ticker": sector["ticker"],
|
"ticker": sector["ticker"],
|
||||||
"sector_name": sector["name"],
|
"name": sector["name"],
|
||||||
|
"prices": sector["prices"],
|
||||||
"momentum_20d": round(momentum_20d, 4),
|
"momentum_20d": round(momentum_20d, 4),
|
||||||
|
"momentum_50d": round(momentum_50d, 4),
|
||||||
|
"momentum_200d": round(momentum_200d, 4),
|
||||||
"relative_strength": round(relative_strength, 4),
|
"relative_strength": round(relative_strength, 4),
|
||||||
})
|
})
|
||||||
|
|
||||||
|
# Compute rankings
|
||||||
|
rotations = await self._rank_sectors(rotations)
|
||||||
|
|
||||||
|
# Compute signals
|
||||||
|
rotations = self._compute_signals(rotations)
|
||||||
|
|
||||||
|
# Compute macro context
|
||||||
|
macro_context = self._compute_macro_context(rotations)
|
||||||
|
|
||||||
# Store results
|
# Store results
|
||||||
await self._store_rotations(rotations)
|
await self._store_rotations(rotations)
|
||||||
return rotations
|
|
||||||
|
# Build response
|
||||||
|
result = []
|
||||||
|
for r in rotations:
|
||||||
|
result.append({
|
||||||
|
"sectorTicker": r["ticker"],
|
||||||
|
"sectorName": r["name"],
|
||||||
|
"momentum20d": r["momentum_20d"],
|
||||||
|
"momentum50d": r["momentum_50d"],
|
||||||
|
"momentum200d": r["momentum_200d"],
|
||||||
|
"relativeStrength": r["relative_strength"],
|
||||||
|
"rankNow": r["rank_now"],
|
||||||
|
"rankPrevious": r["rank_previous"],
|
||||||
|
"rankChange": r["rank_change"],
|
||||||
|
"signal": r["signal"],
|
||||||
|
"analysisSummary": r["analysis_summary"],
|
||||||
|
"macroContext": macro_context,
|
||||||
|
})
|
||||||
|
|
||||||
|
return result
|
||||||
|
|
||||||
async def _get_sector_prices(self) -> list[dict]:
|
async def _get_sector_prices(self) -> list[dict]:
|
||||||
"""Get sector-level price data from database."""
|
"""Get sector-level price data from database."""
|
||||||
@@ -39,44 +93,191 @@ class RotationService:
|
|||||||
"""
|
"""
|
||||||
SELECT ticker, date, close
|
SELECT ticker, date, close
|
||||||
FROM prices
|
FROM prices
|
||||||
WHERE ticker IN ('XLK', 'XLF', 'XLE', 'XLV', 'XLI', 'XLY', 'XLP', 'XLU', 'XLRE', 'XLB', 'SPY')
|
WHERE ticker = ANY(%s)
|
||||||
AND date >= NOW() - INTERVAL '90 days'
|
AND date >= NOW() - INTERVAL '200 days'
|
||||||
ORDER BY ticker, date DESC
|
ORDER BY ticker, date DESC
|
||||||
"""
|
""",
|
||||||
|
(SECTOR_ETFS,),
|
||||||
)
|
)
|
||||||
|
|
||||||
# Group by ticker
|
# Group by ticker
|
||||||
sector_data: dict[str, list[float]] = {}
|
sector_data: dict[str, list[dict]] = {}
|
||||||
for row in prices:
|
for row in prices:
|
||||||
ticker = row["ticker"]
|
ticker = row["ticker"]
|
||||||
if ticker not in sector_data:
|
if ticker not in sector_data:
|
||||||
sector_data[ticker] = []
|
sector_data[ticker] = []
|
||||||
sector_data[ticker].append(float(row["close"]))
|
sector_data[ticker].append({
|
||||||
|
"date": row["date"],
|
||||||
# Sort each ticker's prices by date (newest first)
|
"close": float(row["close"]),
|
||||||
names = {
|
})
|
||||||
"XLK": "Technology", "XLF": "Financials", "XLE": "Energy",
|
|
||||||
"XLV": "Health Care", "XLI": "Industrials", "XLY": "Consumer Discretionary",
|
|
||||||
"XLP": "Consumer Staples", "XLU": "Utilities", "XLRE": "Real Estate",
|
|
||||||
"XLB": "Materials", "SPY": "S&P 500",
|
|
||||||
}
|
|
||||||
|
|
||||||
return [
|
return [
|
||||||
{"ticker": ticker, "name": names.get(ticker, ticker), "prices": sorted(prices_list, reverse=True)[:30]}
|
{
|
||||||
|
"ticker": ticker,
|
||||||
|
"name": SECTOR_NAMES.get(ticker, ticker),
|
||||||
|
"prices": sorted(prices_list, key=lambda x: x["date"], reverse=True),
|
||||||
|
}
|
||||||
for ticker, prices_list in sector_data.items()
|
for ticker, prices_list in sector_data.items()
|
||||||
]
|
]
|
||||||
|
|
||||||
def _calc_momentum(self, prices: list[float], window: int = 20) -> float:
|
def _calc_momentum(self, prices: list[dict], window: int) -> float:
|
||||||
"""Calculate price momentum over window."""
|
"""Calculate price momentum over window.
|
||||||
|
|
||||||
|
prices sorted newest first (descending date).
|
||||||
|
"""
|
||||||
if len(prices) < window:
|
if len(prices) < window:
|
||||||
return 0.0
|
return 0.0
|
||||||
return (prices[0] - prices[-1]) / prices[-1] # prices sorted newest first
|
# Get the oldest price in the window (last element after sort)
|
||||||
|
oldest_price = prices[-1]["close"]
|
||||||
|
# Get the newest price (first element)
|
||||||
|
newest_price = prices[0]["close"]
|
||||||
|
if oldest_price == 0:
|
||||||
|
return 0.0
|
||||||
|
return (newest_price - oldest_price) / oldest_price
|
||||||
|
|
||||||
def _calc_relative_strength(self, prices: list[float]) -> float:
|
def _calc_relative_strength(self, prices: list[dict]) -> float:
|
||||||
"""Calculate relative strength vs benchmark."""
|
"""Calculate relative strength vs benchmark (SPY)."""
|
||||||
if len(prices) < 2:
|
if len(prices) < 2:
|
||||||
return 0.0
|
return 0.0
|
||||||
return (prices[0] - prices[-1]) / prices[-1]
|
newest = prices[0]["close"]
|
||||||
|
oldest = prices[-1]["close"]
|
||||||
|
if oldest == 0:
|
||||||
|
return 0.0
|
||||||
|
return (newest - oldest) / oldest
|
||||||
|
|
||||||
|
async def _rank_sectors(self, rotations: list[dict]) -> list[dict]:
|
||||||
|
"""Rank sectors by momentum (descending = best first)."""
|
||||||
|
# Sort by momentum_20d descending
|
||||||
|
sorted_rotations = sorted(rotations, key=lambda x: x["momentum_20d"], reverse=True)
|
||||||
|
|
||||||
|
# Get previous rank from DB
|
||||||
|
prev_ranks = await self._get_previous_ranks()
|
||||||
|
|
||||||
|
for i, r in enumerate(sorted_rotations):
|
||||||
|
r["rank_now"] = i + 1
|
||||||
|
ticker = r["ticker"]
|
||||||
|
prev_rank = prev_ranks.get(ticker)
|
||||||
|
if prev_rank:
|
||||||
|
r["rank_previous"] = prev_rank
|
||||||
|
r["rank_change"] = prev_rank - (i + 1) # positive = improved
|
||||||
|
else:
|
||||||
|
r["rank_previous"] = None
|
||||||
|
r["rank_change"] = 0
|
||||||
|
|
||||||
|
return sorted_rotations
|
||||||
|
|
||||||
|
async def _get_previous_ranks(self) -> dict[str, int]:
|
||||||
|
"""Get previous day's rankings from DB."""
|
||||||
|
rows = await execute_query(
|
||||||
|
"""
|
||||||
|
SELECT sector_ticker, rank_now
|
||||||
|
FROM sector_rotations
|
||||||
|
WHERE detection_date = (
|
||||||
|
SELECT MAX(detection_date) FROM sector_rotations
|
||||||
|
WHERE detection_date < CURRENT_DATE
|
||||||
|
)
|
||||||
|
ORDER BY rank_now ASC
|
||||||
|
""",
|
||||||
|
)
|
||||||
|
if not rows:
|
||||||
|
return {}
|
||||||
|
return {row["sector_ticker"]: row["rank_now"] for row in rows}
|
||||||
|
|
||||||
|
def _compute_signals(self, rotations: list[dict]) -> list[dict]:
|
||||||
|
"""Compute rotation signals based on momentum and rank changes."""
|
||||||
|
for r in rotations:
|
||||||
|
momentum = r["momentum_20d"]
|
||||||
|
rank_change = r["rank_change"]
|
||||||
|
ticker = r["ticker"]
|
||||||
|
|
||||||
|
# Skip SPY — it's the benchmark
|
||||||
|
if ticker == "SPY":
|
||||||
|
r["signal"] = "benchmark"
|
||||||
|
r["analysis_summary"] = "Benchmark index — not a tradeable sector."
|
||||||
|
continue
|
||||||
|
|
||||||
|
# Signal logic
|
||||||
|
if momentum > 0.05 and rank_change > 0:
|
||||||
|
r["signal"] = "bullish"
|
||||||
|
r["analysis_summary"] = (
|
||||||
|
f"{r['name']} showing strong upward momentum (+{momentum*100:.1f}%) "
|
||||||
|
f"and improving rank position ({rank_change} place(s) gained)."
|
||||||
|
)
|
||||||
|
elif momentum > 0.02 and rank_change >= 0:
|
||||||
|
r["signal"] = "bullish"
|
||||||
|
r["analysis_summary"] = (
|
||||||
|
f"{r['name']} with positive momentum (+{momentum*100:.1f}%) "
|
||||||
|
f"and stable or improving rank."
|
||||||
|
)
|
||||||
|
elif momentum < -0.05 and rank_change < 0:
|
||||||
|
r["signal"] = "bearish"
|
||||||
|
r["analysis_summary"] = (
|
||||||
|
f"{r['name']} showing significant decline ({momentum*100:.1f}%) "
|
||||||
|
f"and falling rank position ({abs(rank_change)} place(s) lost)."
|
||||||
|
)
|
||||||
|
elif momentum < -0.02:
|
||||||
|
r["signal"] = "bearish"
|
||||||
|
r["analysis_summary"] = (
|
||||||
|
f"{r['name']} with negative momentum ({momentum*100:.1f}%)."
|
||||||
|
)
|
||||||
|
elif abs(momentum) <= 0.02:
|
||||||
|
r["signal"] = "neutral"
|
||||||
|
r["analysis_summary"] = (
|
||||||
|
f"{r['name']} with minimal price movement ({momentum*100:.2f}%). "
|
||||||
|
f"Waiting for clearer directional signal."
|
||||||
|
)
|
||||||
|
else:
|
||||||
|
r["signal"] = "neutral"
|
||||||
|
r["analysis_summary"] = (
|
||||||
|
f"{r['name']} with moderate momentum ({momentum*100:.1f}%) "
|
||||||
|
f"and rank change of {rank_change}."
|
||||||
|
)
|
||||||
|
|
||||||
|
return rotations
|
||||||
|
|
||||||
|
def _compute_macro_context(self, rotations: list[dict]) -> dict:
|
||||||
|
"""Compute macro context from sector rotation patterns."""
|
||||||
|
if not rotations:
|
||||||
|
return {"status": "insufficient_data", "message": "No sector data available"}
|
||||||
|
|
||||||
|
# Count signals
|
||||||
|
bullish = sum(1 for r in rotations if r["signal"] == "bullish")
|
||||||
|
bearish = sum(1 for r in rotations if r["signal"] == "bearish")
|
||||||
|
neutral = sum(1 for r in rotations if r["signal"] == "neutral")
|
||||||
|
total = len(rotations)
|
||||||
|
|
||||||
|
# Determine overall market regime
|
||||||
|
if bullish > total * 0.6:
|
||||||
|
regime = "bullish"
|
||||||
|
regime_desc = "Broad market bullish — majority of sectors showing positive momentum."
|
||||||
|
elif bearish > total * 0.6:
|
||||||
|
regime = "bearish"
|
||||||
|
regime_desc = "Broad market bearish — majority of sectors showing negative momentum."
|
||||||
|
elif bullish > bearish:
|
||||||
|
regime = "mildly_bullish"
|
||||||
|
regime_desc = "Mildly bullish — more sectors gaining than losing, but not widespread."
|
||||||
|
elif bearish > bullish:
|
||||||
|
regime = "mildly_bearish"
|
||||||
|
regime_desc = "Mildly bearish — more sectors losing than gaining, but not widespread."
|
||||||
|
else:
|
||||||
|
regime = "mixed"
|
||||||
|
regime_desc = "Mixed signals — sectors are split between gains and losses."
|
||||||
|
|
||||||
|
# Find leading and lagging sectors
|
||||||
|
sorted_by_momentum = sorted(rotations, key=lambda x: x["momentum_20d"], reverse=True)
|
||||||
|
leaders = [r["name"] for r in sorted_by_momentum[:3]]
|
||||||
|
laggards = [r["name"] for r in sorted_by_momentum[-3:]]
|
||||||
|
|
||||||
|
return {
|
||||||
|
"regime": regime,
|
||||||
|
"regimeDescription": regime_desc,
|
||||||
|
"bullishCount": bullish,
|
||||||
|
"bearishCount": bearish,
|
||||||
|
"neutralCount": neutral,
|
||||||
|
"leaders": leaders,
|
||||||
|
"laggards": laggards,
|
||||||
|
"date": date.today().isoformat(),
|
||||||
|
}
|
||||||
|
|
||||||
async def _store_rotations(self, rotations: list[dict]) -> None:
|
async def _store_rotations(self, rotations: list[dict]) -> None:
|
||||||
"""Store rotation results in database."""
|
"""Store rotation results in database."""
|
||||||
@@ -85,19 +286,29 @@ class RotationService:
|
|||||||
await execute_command(
|
await execute_command(
|
||||||
"""
|
"""
|
||||||
INSERT INTO sector_rotations
|
INSERT INTO sector_rotations
|
||||||
(sector_ticker, sector_name, momentum_20d, relative_strength, detection_date)
|
(detection_date, sector_ticker, sector_name, rank_now, rank_previous,
|
||||||
VALUES ($1, $2, $3, $4, CURRENT_DATE)
|
rank_change, momentum_20d, momentum_50d, momentum_200d,
|
||||||
|
relative_strength, rotation_signal, analysis_summary)
|
||||||
|
VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s)
|
||||||
ON CONFLICT DO NOTHING
|
ON CONFLICT DO NOTHING
|
||||||
""",
|
""",
|
||||||
(
|
(
|
||||||
r["sector_ticker"],
|
date.today(),
|
||||||
r["sector_name"],
|
r["ticker"],
|
||||||
|
r["name"],
|
||||||
|
r["rank_now"],
|
||||||
|
r["rank_previous"],
|
||||||
|
r["rank_change"],
|
||||||
r["momentum_20d"],
|
r["momentum_20d"],
|
||||||
|
r["momentum_50d"],
|
||||||
|
r["momentum_200d"],
|
||||||
r["relative_strength"],
|
r["relative_strength"],
|
||||||
|
r["signal"],
|
||||||
|
r["analysis_summary"],
|
||||||
),
|
),
|
||||||
)
|
)
|
||||||
except Exception as e:
|
except Exception as e:
|
||||||
logger.error(f"Failed to store rotation for {r['sector_ticker']}: {e}")
|
logger.error(f"Failed to store rotation for {r['ticker']}: {e}")
|
||||||
|
|
||||||
|
|
||||||
# Module-level function for router import
|
# Module-level function for router import
|
||||||
|
|||||||
@@ -1,7 +1,13 @@
|
|||||||
"""Celery task definitions for data pipeline."""
|
"""Celery task definitions for data pipeline."""
|
||||||
|
|
||||||
|
from .ingest_financials import ingest_financials_task
|
||||||
from .ingest_prices import ingest_prices_task
|
from .ingest_prices import ingest_prices_task
|
||||||
from .ingest_sec import ingest_sec_filings_task
|
from .ingest_sec import ingest_sec_filings_task
|
||||||
from .sector_scan import sector_scan_task
|
from .sector_scan import sector_scan_task
|
||||||
|
|
||||||
__all__ = ["ingest_prices_task", "ingest_sec_filings_task", "sector_scan_task"]
|
__all__ = [
|
||||||
|
"ingest_financials_task",
|
||||||
|
"ingest_prices_task",
|
||||||
|
"ingest_sec_filings_task",
|
||||||
|
"sector_scan_task",
|
||||||
|
]
|
||||||
|
|||||||
@@ -0,0 +1,239 @@
|
|||||||
|
"""Celery task for financial statement ingestion.
|
||||||
|
|
||||||
|
Fetches quarterly and annual income statement, balance sheet, and cash flow
|
||||||
|
data from yfinance and persists to the financials table.
|
||||||
|
"""
|
||||||
|
|
||||||
|
import asyncio
|
||||||
|
import logging
|
||||||
|
import time
|
||||||
|
from datetime import date
|
||||||
|
|
||||||
|
import yfinance as yf
|
||||||
|
|
||||||
|
from celery_app import app
|
||||||
|
from database import execute_command
|
||||||
|
|
||||||
|
logger = logging.getLogger(__name__)
|
||||||
|
|
||||||
|
MAX_RETRIES = 3
|
||||||
|
RETRY_DELAY = 5
|
||||||
|
|
||||||
|
|
||||||
|
def _run_async(coro):
|
||||||
|
"""Run an async coroutine in a new event loop."""
|
||||||
|
loop = asyncio.new_event_loop()
|
||||||
|
asyncio.set_event_loop(loop)
|
||||||
|
try:
|
||||||
|
result = loop.run_until_complete(coro)
|
||||||
|
return result
|
||||||
|
finally:
|
||||||
|
loop.close()
|
||||||
|
|
||||||
|
|
||||||
|
def _execute_command(sql: str, params: tuple = ()) -> None:
|
||||||
|
"""Sync wrapper for async execute_command."""
|
||||||
|
_run_async(execute_command(sql, params))
|
||||||
|
|
||||||
|
|
||||||
|
def _extract_metric(df, metric_name: str):
|
||||||
|
"""Safely extract a metric value from a yfinance DataFrame.
|
||||||
|
|
||||||
|
yfinance returns DataFrames with dates as index and ticker names as columns.
|
||||||
|
"""
|
||||||
|
if df is None or df.empty:
|
||||||
|
return None
|
||||||
|
|
||||||
|
for row in df.index.tolist():
|
||||||
|
if metric_name.lower() in str(row).lower():
|
||||||
|
vals = df.loc[row].dropna()
|
||||||
|
if not vals.empty:
|
||||||
|
return float(vals.iloc[-1])
|
||||||
|
return None
|
||||||
|
|
||||||
|
|
||||||
|
def _fetch_financials(ticker: str) -> dict:
|
||||||
|
"""Fetch financial data using yfinance with retries."""
|
||||||
|
for attempt in range(MAX_RETRIES):
|
||||||
|
try:
|
||||||
|
tk = yf.Ticker(ticker)
|
||||||
|
return {
|
||||||
|
"quarterly": {
|
||||||
|
"income": tk.quarterly_income_stmt,
|
||||||
|
"balance": tk.quarterly_balance_sheet,
|
||||||
|
"cashflow": tk.quarterly_cashflow,
|
||||||
|
},
|
||||||
|
"annual": {
|
||||||
|
"income": tk.income_stmt,
|
||||||
|
"balance": tk.balance_sheet,
|
||||||
|
"cashflow": tk.cashflow,
|
||||||
|
},
|
||||||
|
}
|
||||||
|
except Exception as exc:
|
||||||
|
logger.warning(
|
||||||
|
f"Attempt {attempt+1}/{MAX_RETRIES} failed for {ticker}: {exc}"
|
||||||
|
)
|
||||||
|
if attempt < MAX_RETRIES - 1:
|
||||||
|
time.sleep(RETRY_DELAY * (attempt + 1))
|
||||||
|
else:
|
||||||
|
logger.error(f"Failed to fetch financials for {ticker}: {exc}")
|
||||||
|
return {}
|
||||||
|
return {}
|
||||||
|
|
||||||
|
|
||||||
|
@app.task(
|
||||||
|
name="tasks.ingest_financials",
|
||||||
|
bind=True,
|
||||||
|
max_retries=3,
|
||||||
|
default_retry_delay=60,
|
||||||
|
)
|
||||||
|
def ingest_financials_task(self, ticker: str) -> dict:
|
||||||
|
"""Ingest financial statement data for a ticker.
|
||||||
|
|
||||||
|
Fetches quarterly and annual financials from yfinance and stores them
|
||||||
|
in the financials table. Idempotent via ON CONFLICT.
|
||||||
|
"""
|
||||||
|
try:
|
||||||
|
logger.info(f"Starting financials ingestion for {ticker}")
|
||||||
|
|
||||||
|
financial_data = _fetch_financials(ticker)
|
||||||
|
if not financial_data:
|
||||||
|
logger.warning(f"No financial data found for {ticker}")
|
||||||
|
return {"ticker": ticker, "status": "no_data"}
|
||||||
|
|
||||||
|
filing_date = date.today().isoformat()
|
||||||
|
stored = 0
|
||||||
|
|
||||||
|
for period_type in ["quarterly", "annual"]:
|
||||||
|
data = financial_data.get(period_type, {})
|
||||||
|
income = data.get("income")
|
||||||
|
balance = data.get("balance")
|
||||||
|
cashflow = data.get("cashflow")
|
||||||
|
|
||||||
|
if income is None or income.empty:
|
||||||
|
continue
|
||||||
|
|
||||||
|
columns = income.columns.tolist()
|
||||||
|
if not columns:
|
||||||
|
continue
|
||||||
|
|
||||||
|
for col in columns:
|
||||||
|
try:
|
||||||
|
col_date = col.date() if hasattr(col, "date") else col
|
||||||
|
except (ValueError, AttributeError):
|
||||||
|
col_date = col
|
||||||
|
|
||||||
|
# Income statement metrics
|
||||||
|
revenue = _extract_metric(income, "Total Revenue")
|
||||||
|
net_income = _extract_metric(income, "Net Income")
|
||||||
|
eps_basic = _extract_metric(income, "Basic EPS")
|
||||||
|
eps_diluted = _extract_metric(income, "Diluted EPS")
|
||||||
|
operating_income = _extract_metric(income, "Operating Income")
|
||||||
|
gross_profit = _extract_metric(income, "Gross Profit")
|
||||||
|
|
||||||
|
# Balance sheet metrics
|
||||||
|
total_assets = _extract_metric(balance, "Total Assets")
|
||||||
|
total_liabilities = _extract_metric(
|
||||||
|
balance, "Total Liabilities Net Minority Interest"
|
||||||
|
)
|
||||||
|
if total_liabilities is None:
|
||||||
|
total_liabilities = _extract_metric(balance, "Total Liabilities")
|
||||||
|
total_equity = _extract_metric(
|
||||||
|
balance, "Total Equity Gross Minority Interest"
|
||||||
|
)
|
||||||
|
if total_equity is None:
|
||||||
|
total_equity = _extract_metric(balance, "Total Equity")
|
||||||
|
|
||||||
|
# Cash flow metrics
|
||||||
|
operating_cashflow = _extract_metric(cashflow, "Operating Cash Flow")
|
||||||
|
free_cashflow = _extract_metric(cashflow, "Free Cash Flow")
|
||||||
|
|
||||||
|
# Derived metrics
|
||||||
|
debt_to_equity = None
|
||||||
|
if total_equity and total_equity != 0:
|
||||||
|
total_debt = (total_liabilities or 0) - (total_equity or 0)
|
||||||
|
debt_to_equity = round(total_debt / total_equity, 4)
|
||||||
|
|
||||||
|
roe = None
|
||||||
|
if total_equity and total_equity != 0 and net_income:
|
||||||
|
roe = round((net_income / total_equity) * 100, 4)
|
||||||
|
|
||||||
|
roa = None
|
||||||
|
if total_assets and total_assets != 0 and net_income:
|
||||||
|
roa = round((net_income / total_assets) * 100, 4)
|
||||||
|
|
||||||
|
cost_of_revenue = None
|
||||||
|
if gross_profit and revenue:
|
||||||
|
cost_of_revenue = round(revenue - gross_profit, 2)
|
||||||
|
else:
|
||||||
|
cost_of_revenue = _extract_metric(income, "Cost Of Revenue")
|
||||||
|
|
||||||
|
operating_expense = None
|
||||||
|
if operating_income and gross_profit and revenue:
|
||||||
|
operating_expense = round(gross_profit - operating_income, 2)
|
||||||
|
else:
|
||||||
|
operating_expense = _extract_metric(income, "Operating Expense")
|
||||||
|
|
||||||
|
# Upsert into financials table
|
||||||
|
_execute_command(
|
||||||
|
"""
|
||||||
|
INSERT INTO financials (
|
||||||
|
ticker, filing_date, period, period_end,
|
||||||
|
revenue, cost_of_revenue, gross_profit, operating_expense,
|
||||||
|
operating_income, net_income, eps_basic, eps_diluted,
|
||||||
|
total_assets, total_liabilities, total_equity,
|
||||||
|
operating_cashflow, free_cashflow,
|
||||||
|
debt_to_equity, roe, roa
|
||||||
|
) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10, $11, $12,
|
||||||
|
$13, $14, $15, $16, $17, $18, $19, $20)
|
||||||
|
ON CONFLICT (ticker, filing_date, period) DO UPDATE SET
|
||||||
|
revenue = EXCLUDED.revenue,
|
||||||
|
cost_of_revenue = EXCLUDED.cost_of_revenue,
|
||||||
|
gross_profit = EXCLUDED.gross_profit,
|
||||||
|
operating_expense = EXCLUDED.operating_expense,
|
||||||
|
operating_income = EXCLUDED.operating_income,
|
||||||
|
net_income = EXCLUDED.net_income,
|
||||||
|
eps_basic = EXCLUDED.eps_basic,
|
||||||
|
eps_diluted = EXCLUDED.eps_diluted,
|
||||||
|
total_assets = EXCLUDED.total_assets,
|
||||||
|
total_liabilities = EXCLUDED.total_liabilities,
|
||||||
|
total_equity = EXCLUDED.total_equity,
|
||||||
|
operating_cashflow = EXCLUDED.operating_cashflow,
|
||||||
|
free_cashflow = EXCLUDED.free_cashflow,
|
||||||
|
debt_to_equity = EXCLUDED.debt_to_equity,
|
||||||
|
roe = EXCLUDED.roe,
|
||||||
|
roa = EXCLUDED.roa
|
||||||
|
""",
|
||||||
|
(
|
||||||
|
ticker,
|
||||||
|
filing_date,
|
||||||
|
period_type,
|
||||||
|
col_date,
|
||||||
|
revenue,
|
||||||
|
cost_of_revenue,
|
||||||
|
gross_profit,
|
||||||
|
operating_expense,
|
||||||
|
operating_income,
|
||||||
|
net_income,
|
||||||
|
eps_basic,
|
||||||
|
eps_diluted,
|
||||||
|
total_assets,
|
||||||
|
total_liabilities,
|
||||||
|
total_equity,
|
||||||
|
operating_cashflow,
|
||||||
|
free_cashflow,
|
||||||
|
debt_to_equity,
|
||||||
|
roe,
|
||||||
|
roa,
|
||||||
|
),
|
||||||
|
)
|
||||||
|
stored += 1
|
||||||
|
|
||||||
|
logger.info(
|
||||||
|
f"Successfully ingested {stored} financial records for {ticker}"
|
||||||
|
)
|
||||||
|
return {"ticker": ticker, "status": "ingested", "records": stored}
|
||||||
|
|
||||||
|
except Exception as exc:
|
||||||
|
logger.error(f"Error ingesting financials for {ticker}: {exc}")
|
||||||
|
raise self.retry(exc=exc, countdown=60 * (2 ** self.request.retries))
|
||||||
@@ -0,0 +1,285 @@
|
|||||||
|
"""Shared fixtures for all backend tests.
|
||||||
|
|
||||||
|
CRITICAL: The database mock must be injected into sys.modules BEFORE
|
||||||
|
any other imports that might trigger database.py to load. This is why
|
||||||
|
the mock is created at module level (lines 13-27) before any imports.
|
||||||
|
"""
|
||||||
|
|
||||||
|
import asyncio
|
||||||
|
import json
|
||||||
|
import sys
|
||||||
|
import types
|
||||||
|
from datetime import datetime, timedelta, timezone
|
||||||
|
from unittest.mock import AsyncMock, patch
|
||||||
|
|
||||||
|
import pytest
|
||||||
|
from fastapi.testclient import TestClient
|
||||||
|
from httpx import AsyncClient, ASGITransport
|
||||||
|
|
||||||
|
|
||||||
|
# ── Mock rate limiter (sync — matches services.rate_limiter.check_rate_limit) ──
|
||||||
|
# Prevents 429 errors during test runs.
|
||||||
|
def _mock_check_rate_limit(rule_name: str, key: str):
|
||||||
|
return True, {}
|
||||||
|
|
||||||
|
# ── Mock database module (MUST be before any imports) ──────────────
|
||||||
|
# Uses a proxy class so _db_mod.execute_one always returns _db_mock.execute_one,
|
||||||
|
# even after the test reassigns _db_mock.execute_one.
|
||||||
|
class _DatabaseModuleProxy:
|
||||||
|
"""Proxies attribute access to _db_mock so module-level references stay in sync."""
|
||||||
|
_target = None
|
||||||
|
__name__ = 'database'
|
||||||
|
__dict__ = {}
|
||||||
|
|
||||||
|
def __getattr__(self, name):
|
||||||
|
return getattr(self._target, name)
|
||||||
|
def __setattr__(self, name, value):
|
||||||
|
if name in ('_target', '__name__', '__dict__'):
|
||||||
|
object.__setattr__(self, name, value)
|
||||||
|
else:
|
||||||
|
setattr(self._target, name, value)
|
||||||
|
|
||||||
|
_db_mock = AsyncMock()
|
||||||
|
_db_mock.execute_query = AsyncMock(return_value=[])
|
||||||
|
_db_mock.execute_command = AsyncMock(return_value=None)
|
||||||
|
_db_mock.execute_one = AsyncMock(return_value=None)
|
||||||
|
_db_mock.init_db = AsyncMock()
|
||||||
|
_db_mock.close_db = AsyncMock()
|
||||||
|
_db_mock.get_connection = AsyncMock()
|
||||||
|
_db_mock.release_connection = AsyncMock()
|
||||||
|
|
||||||
|
_db_mod = _DatabaseModuleProxy()
|
||||||
|
_db_mod._target = _db_mock
|
||||||
|
sys.modules["database"] = _db_mod
|
||||||
|
# ────────────────────────────────────────────────────────────────────
|
||||||
|
|
||||||
|
|
||||||
|
def create_test_token(user_id: str = "test-user-1", email: str = "test@example.com") -> str:
|
||||||
|
"""Create a valid JWT token for testing.
|
||||||
|
|
||||||
|
Uses the same secret as the app config so the auth middleware accepts it.
|
||||||
|
"""
|
||||||
|
import base64
|
||||||
|
import hmac
|
||||||
|
import hashlib
|
||||||
|
from config import settings
|
||||||
|
|
||||||
|
secret = settings.JWT_SECRET_KEY
|
||||||
|
if not secret:
|
||||||
|
# Fallback for environments without .env
|
||||||
|
secret = "test-secret-key-for-unit-tests-only-do-not-use-in-production"
|
||||||
|
|
||||||
|
expire = datetime.now(timezone.utc) + timedelta(hours=24)
|
||||||
|
payload = {
|
||||||
|
"sub": user_id,
|
||||||
|
"email": email,
|
||||||
|
"exp": int(expire.timestamp()),
|
||||||
|
"iat": int(datetime.now(timezone.utc).timestamp()),
|
||||||
|
}
|
||||||
|
|
||||||
|
header = base64.urlsafe_b64encode(json.dumps({"alg": "HS256", "typ": "JWT"}).encode()).rstrip(b"=").decode()
|
||||||
|
payload_b64 = base64.urlsafe_b64encode(json.dumps(payload).encode()).rstrip(b"=").decode()
|
||||||
|
|
||||||
|
signature = hmac.new(
|
||||||
|
secret.encode(),
|
||||||
|
f"{header}.{payload_b64}".encode(),
|
||||||
|
hashlib.sha256,
|
||||||
|
).digest()
|
||||||
|
signature_b64 = base64.urlsafe_b64encode(signature).rstrip(b"=").decode()
|
||||||
|
|
||||||
|
return f"{header}.{payload_b64}.{signature_b64}"
|
||||||
|
|
||||||
|
|
||||||
|
@pytest.fixture
|
||||||
|
def event_loop():
|
||||||
|
"""Create a fresh event loop for each test."""
|
||||||
|
loop = asyncio.new_event_loop()
|
||||||
|
yield loop
|
||||||
|
loop.close()
|
||||||
|
|
||||||
|
|
||||||
|
@pytest.fixture
|
||||||
|
def mock_db():
|
||||||
|
"""Return the shared mock database object."""
|
||||||
|
return _db_mock
|
||||||
|
|
||||||
|
|
||||||
|
@pytest.fixture
|
||||||
|
def mock_user_data():
|
||||||
|
"""Valid user registration data."""
|
||||||
|
return {
|
||||||
|
"email": "test@example.com",
|
||||||
|
"password": "***",
|
||||||
|
"name": "Test User",
|
||||||
|
}
|
||||||
|
|
||||||
|
|
||||||
|
@pytest.fixture
|
||||||
|
def mock_watchlist_data():
|
||||||
|
"""Valid watchlist creation data."""
|
||||||
|
return {
|
||||||
|
"name": "My Watchlist",
|
||||||
|
"description": "Test watchlist for AAPL",
|
||||||
|
}
|
||||||
|
|
||||||
|
|
||||||
|
@pytest.fixture
|
||||||
|
def mock_watchlist_item():
|
||||||
|
"""Valid watchlist item data."""
|
||||||
|
return {
|
||||||
|
"ticker": "AAPL",
|
||||||
|
"type": "stock",
|
||||||
|
"notes": "Apple Inc.",
|
||||||
|
}
|
||||||
|
|
||||||
|
|
||||||
|
@pytest.fixture
|
||||||
|
def test_user(mock_db):
|
||||||
|
"""Create a test user with a valid JWT token.
|
||||||
|
|
||||||
|
Mocks the database so get_current_user() returns a valid user dict.
|
||||||
|
"""
|
||||||
|
user = {
|
||||||
|
"id": "test-user-1",
|
||||||
|
"email": "test@example.com",
|
||||||
|
"name": "Test User",
|
||||||
|
"timezone": "UTC",
|
||||||
|
}
|
||||||
|
# Make execute_one return the user when queried by ID
|
||||||
|
mock_db["execute_one"].return_value = user
|
||||||
|
token = create_test_token(user_id="test-user-1", email="test@example.com")
|
||||||
|
return {"user": user, "token": token}
|
||||||
|
|
||||||
|
|
||||||
|
@pytest.fixture
|
||||||
|
def watchlist(mock_db):
|
||||||
|
"""Create a test watchlist linked to the test user."""
|
||||||
|
wl = {
|
||||||
|
"id": "wl-1",
|
||||||
|
"name": "Tech Stocks",
|
||||||
|
"description": "My tech picks",
|
||||||
|
"user_id": "test-user-1",
|
||||||
|
"is_default": False,
|
||||||
|
"created_at": "2024-01-01T00:00:00",
|
||||||
|
"updated_at": "2024-01-01T00:00:00",
|
||||||
|
}
|
||||||
|
mock_db["execute_one"].return_value = wl
|
||||||
|
return wl
|
||||||
|
|
||||||
|
|
||||||
|
@pytest.fixture
|
||||||
|
def client(test_user, mock_db):
|
||||||
|
"""Create an async test client with auth headers.
|
||||||
|
|
||||||
|
Injects the JWT token into every request via a custom transport.
|
||||||
|
"""
|
||||||
|
from main import app
|
||||||
|
|
||||||
|
async def inject_auth(request):
|
||||||
|
# Add auth header if not already present
|
||||||
|
if "Authorization" not in request.headers:
|
||||||
|
request.headers["Authorization"] = f"Bearer {test_user['token']}"
|
||||||
|
|
||||||
|
transport = ASGITransport(app=app)
|
||||||
|
client = AsyncClient(transport=transport, base_url="http://test")
|
||||||
|
# We can't use middleware in httpx AsyncClient easily, so we'll
|
||||||
|
# rely on tests passing auth headers explicitly, or we wrap the client.
|
||||||
|
return client
|
||||||
|
|
||||||
|
|
||||||
|
@pytest.fixture
|
||||||
|
def auth_client(test_user, mock_db):
|
||||||
|
"""Create an async test client with auth headers pre-set.
|
||||||
|
|
||||||
|
This is the preferred fixture for authenticated endpoint tests.
|
||||||
|
"""
|
||||||
|
from main import app
|
||||||
|
|
||||||
|
transport = ASGITransport(app=app)
|
||||||
|
client = AsyncClient(
|
||||||
|
transport=transport,
|
||||||
|
base_url="http://test",
|
||||||
|
headers={"Authorization": f"Bearer {test_user['token']}"},
|
||||||
|
)
|
||||||
|
return client
|
||||||
|
|
||||||
|
|
||||||
|
# Alias: 'client' is the same as 'auth_client' for backward compatibility.
|
||||||
|
@pytest.fixture
|
||||||
|
def client(auth_client):
|
||||||
|
"""Alias for auth_client — authenticated test client."""
|
||||||
|
return auth_client
|
||||||
|
|
||||||
|
|
||||||
|
@pytest.fixture
|
||||||
|
def unauthenticated_client(mock_db):
|
||||||
|
"""Create an async test client WITHOUT auth headers.
|
||||||
|
|
||||||
|
Use this for testing unauthenticated endpoints (register, login, etc.).
|
||||||
|
"""
|
||||||
|
from main import app
|
||||||
|
transport = ASGITransport(app=app)
|
||||||
|
return AsyncClient(transport=transport, base_url="http://test")
|
||||||
|
|
||||||
|
|
||||||
|
# ── Auto-fixtures: reset mocks & disable rate limiter ──────────
|
||||||
|
@pytest.fixture(autouse=True)
|
||||||
|
def reset_mock_db(mock_db):
|
||||||
|
"""Reset mock database state before each test to prevent state leakage.
|
||||||
|
|
||||||
|
Preserves execute_one.return_value if it was set by a fixture (e.g., watchlist),
|
||||||
|
since that return value is needed by routers for ownership checks.
|
||||||
|
"""
|
||||||
|
mock_db.execute_query.reset_mock()
|
||||||
|
mock_db.execute_query.return_value = []
|
||||||
|
mock_db.execute_command.reset_mock()
|
||||||
|
mock_db.execute_command.return_value = None
|
||||||
|
|
||||||
|
preserve_one = mock_db.execute_one.return_value
|
||||||
|
mock_db.execute_one.reset_mock()
|
||||||
|
mock_db.execute_one.return_value = preserve_one
|
||||||
|
|
||||||
|
mock_db.init_db.reset_mock()
|
||||||
|
mock_db.close_db.reset_mock()
|
||||||
|
mock_db.get_connection.reset_mock()
|
||||||
|
mock_db.release_connection.reset_mock()
|
||||||
|
|
||||||
|
|
||||||
|
@pytest.fixture(autouse=True)
|
||||||
|
def disable_rate_limiter():
|
||||||
|
"""Patch the rate limiter to always allow requests during tests."""
|
||||||
|
import main as main_module
|
||||||
|
with patch.object(main_module, 'check_rate_limit', _mock_check_rate_limit):
|
||||||
|
yield
|
||||||
|
|
||||||
|
|
||||||
|
@pytest.fixture
|
||||||
|
def mock_insert_alert(mock_db, watchlist):
|
||||||
|
"""Configure execute_one to return an alert dict on the second call (for INSERT).
|
||||||
|
|
||||||
|
First call returns watchlist (owner check), second call returns alert dict (INSERT).
|
||||||
|
Use this fixture when a test needs to create an alert and read back its ID.
|
||||||
|
"""
|
||||||
|
call_count = [0]
|
||||||
|
def insert_side_effect(*args, **kwargs):
|
||||||
|
call_count[0] += 1
|
||||||
|
if call_count[0] == 1:
|
||||||
|
# First call: watchlist owner check
|
||||||
|
return watchlist
|
||||||
|
# Second+ call: INSERT return value
|
||||||
|
return {
|
||||||
|
"id": f"alert-{call_count[0]}",
|
||||||
|
"watchlist_id": watchlist["id"],
|
||||||
|
"type": "price",
|
||||||
|
"trigger_type": None,
|
||||||
|
"message": "Test Alert",
|
||||||
|
"severity": "info",
|
||||||
|
"status": "active",
|
||||||
|
"ticker": None,
|
||||||
|
"triggered_at": None,
|
||||||
|
"resolved_at": None,
|
||||||
|
"metadata": {},
|
||||||
|
"created_at": "2026-05-01T00:00:00",
|
||||||
|
}
|
||||||
|
mock_db.execute_one.side_effect = insert_side_effect
|
||||||
|
return insert_side_effect
|
||||||
@@ -0,0 +1,169 @@
|
|||||||
|
"""Shared fixtures for all backend tests.
|
||||||
|
|
||||||
|
CRITICAL: The database mock must be injected into sys.modules BEFORE
|
||||||
|
any other imports that might trigger database.py to load. This is why
|
||||||
|
the mock is created at module level (lines 13-27) before any imports.
|
||||||
|
"""
|
||||||
|
|
||||||
|
import asyncio
|
||||||
|
import sys
|
||||||
|
import types
|
||||||
|
from unittest.mock import AsyncMock
|
||||||
|
|
||||||
|
import pytest
|
||||||
|
from httpx import AsyncClient, ASGITransport
|
||||||
|
|
||||||
|
# ── Mock database module (MUST be before any imports) ──────────────
|
||||||
|
_db_mock = AsyncMock()
|
||||||
|
_db_mock.execute_query = AsyncMock(return_value=[])
|
||||||
|
_db_mock.execute_command = AsyncMock(return_value=None)
|
||||||
|
_db_mock.execute_one = AsyncMock(return_value=None)
|
||||||
|
_db_mock.init_db = AsyncMock()
|
||||||
|
_db_mock.close_db = AsyncMock()
|
||||||
|
_db_mock.get_connection = AsyncMock()
|
||||||
|
_db_mock.release_connection = AsyncMock()
|
||||||
|
|
||||||
|
_db_mod = types.ModuleType("database")
|
||||||
|
_db_mod.execute_query = _db_mock.execute_query
|
||||||
|
_db_mod.execute_command = _db_mock.execute_command
|
||||||
|
_db_mod.execute_one = _db_mock.execute_one
|
||||||
|
_db_mod.init_db = _db_mock.init_db
|
||||||
|
_db_mod.close_db = _db_mock.close_db
|
||||||
|
_db_mod.get_connection = _db_mock.get_connection
|
||||||
|
_db_mod.release_connection = _db_mock.release_connection
|
||||||
|
sys.modules["database"] = _db_mod
|
||||||
|
# ────────────────────────────────────────────────────────────────────
|
||||||
|
|
||||||
|
|
||||||
|
@pytest.fixture
|
||||||
|
def event_loop():
|
||||||
|
"""Create a fresh event loop for each test."""
|
||||||
|
loop = asyncio.new_event_loop()
|
||||||
|
yield loop
|
||||||
|
loop.close()
|
||||||
|
|
||||||
|
|
||||||
|
@pytest.fixture
|
||||||
|
def mock_db():
|
||||||
|
"""Return the shared mock database object."""
|
||||||
|
return _db_mock
|
||||||
|
|
||||||
|
|
||||||
|
@pytest.fixture
|
||||||
|
def mock_user_data():
|
||||||
|
"""Valid user registration data."""
|
||||||
|
return {
|
||||||
|
"email": "test@example.com",
|
||||||
|
"password": "SecurePass123!",
|
||||||
|
"name": "Test User",
|
||||||
|
}
|
||||||
|
|
||||||
|
|
||||||
|
@pytest.fixture
|
||||||
|
def mock_watchlist_data():
|
||||||
|
"""Valid watchlist creation data."""
|
||||||
|
return {
|
||||||
|
"name": "My Watchlist",
|
||||||
|
"description": "Test watchlist for AAPL",
|
||||||
|
}
|
||||||
|
|
||||||
|
|
||||||
|
@pytest.fixture
|
||||||
|
def mock_watchlist_item():
|
||||||
|
"""Valid watchlist item data."""
|
||||||
|
return {
|
||||||
|
"ticker": "AAPL",
|
||||||
|
"type": "stock",
|
||||||
|
"notes": "Apple Inc.",
|
||||||
|
}
|
||||||
|
|
||||||
|
|
||||||
|
@pytest.fixture
|
||||||
|
def mock_stock_profile():
|
||||||
|
"""Mock stock profile data."""
|
||||||
|
return {
|
||||||
|
"ticker": "AAPL",
|
||||||
|
"name": "Apple Inc.",
|
||||||
|
"sector": "Technology",
|
||||||
|
"industry": "Consumer Electronics",
|
||||||
|
"pe_ratio": 32.5,
|
||||||
|
"market_cap": 3_000_000_000_000,
|
||||||
|
"price": 180.0,
|
||||||
|
"change_pct": 2.5,
|
||||||
|
"volume": 50_000_000,
|
||||||
|
"description": "Apple Inc. designs, manufactures, and sells consumer electronics.",
|
||||||
|
}
|
||||||
|
|
||||||
|
|
||||||
|
@pytest.fixture
|
||||||
|
def mock_price_data():
|
||||||
|
"""Mock price history data."""
|
||||||
|
return [
|
||||||
|
{
|
||||||
|
"date": "2024-01-02",
|
||||||
|
"open": 185.0,
|
||||||
|
"high": 187.0,
|
||||||
|
"low": 183.0,
|
||||||
|
"close": 186.5,
|
||||||
|
"volume": 50_000_000,
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"date": "2024-01-03",
|
||||||
|
"open": 186.5,
|
||||||
|
"high": 189.0,
|
||||||
|
"low": 185.0,
|
||||||
|
"close": 187.0,
|
||||||
|
"volume": 52_000_000,
|
||||||
|
},
|
||||||
|
]
|
||||||
|
|
||||||
|
|
||||||
|
@pytest.fixture
|
||||||
|
def mock_search_results():
|
||||||
|
"""Mock search results."""
|
||||||
|
return [
|
||||||
|
{
|
||||||
|
"ticker": "AAPL",
|
||||||
|
"name": "Apple Inc.",
|
||||||
|
"sector": "Technology",
|
||||||
|
"exchange": "NASDAQ",
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"ticker": "AAPL34.SA",
|
||||||
|
"name": "Apple Inc. BDR",
|
||||||
|
"sector": "Technology",
|
||||||
|
"exchange": "BVMF",
|
||||||
|
},
|
||||||
|
]
|
||||||
|
|
||||||
|
|
||||||
|
@pytest.fixture
|
||||||
|
def test_user(mock_db):
|
||||||
|
"""Create a test user with a valid JWT token."""
|
||||||
|
from services.auth import create_access_token
|
||||||
|
token = create_access_token(
|
||||||
|
data={"sub": "0000-01", "email": "test@example.com"},
|
||||||
|
)
|
||||||
|
return {
|
||||||
|
"token": token,
|
||||||
|
"user_id": "0000-01",
|
||||||
|
"email": "test@example.com",
|
||||||
|
"name": "Test User",
|
||||||
|
}
|
||||||
|
|
||||||
|
|
||||||
|
@pytest.fixture
|
||||||
|
def app(mock_db):
|
||||||
|
"""Create a FastAPI app with mocked database."""
|
||||||
|
# At this point, sys.modules["database"] is already patched (module-level).
|
||||||
|
# Import main — it will pick up our mock.
|
||||||
|
import main
|
||||||
|
return main.app
|
||||||
|
|
||||||
|
|
||||||
|
@pytest.fixture
|
||||||
|
async def client(app, mock_db):
|
||||||
|
"""Create an async test client with mocked database."""
|
||||||
|
transport = ASGITransport(app=app)
|
||||||
|
async with AsyncClient(transport=transport, base_url="http://test") as ac:
|
||||||
|
yield ac
|
||||||
@@ -40,7 +40,7 @@ class TestAlertCRUD:
|
|||||||
assert data["type"] == "sentiment"
|
assert data["type"] == "sentiment"
|
||||||
assert data["severity"] == "info" # default
|
assert data["severity"] == "info" # default
|
||||||
|
|
||||||
async def test_get_all_alerts(self, client, test_user, watchlist):
|
async def test_get_all_alerts(self, client, test_user, watchlist, mock_db):
|
||||||
"""User can retrieve all their alerts."""
|
"""User can retrieve all their alerts."""
|
||||||
headers = {"Authorization": f"Bearer {test_user['token']}"}
|
headers = {"Authorization": f"Bearer {test_user['token']}"}
|
||||||
# Create two alerts
|
# Create two alerts
|
||||||
@@ -55,17 +55,33 @@ class TestAlertCRUD:
|
|||||||
"message": "Alert 2",
|
"message": "Alert 2",
|
||||||
}, headers=headers)
|
}, headers=headers)
|
||||||
|
|
||||||
|
# Mock execute_query to return the created alerts
|
||||||
|
def alerts_query_side_effect(sql, params=None):
|
||||||
|
sql_upper = sql.upper()
|
||||||
|
print(f"DEBUG: sql_upper: {sql_upper}")
|
||||||
|
if "COUNT(*)" in sql_upper and "FROM ALERTS" in sql_upper:
|
||||||
|
return [{"count": 2}]
|
||||||
|
if "FROM ALERTS" in sql_upper:
|
||||||
|
return [
|
||||||
|
{"id": "alert-1", "watchlist_id": watchlist["id"], "type": "price", "trigger_type": None, "message": "Alert 1", "severity": "info", "status": "active", "ticker": None, "triggered_at": None, "resolved_at": None, "metadata": {}, "created_at": "2026-05-01T00:01:00"},
|
||||||
|
{"id": "alert-2", "watchlist_id": watchlist["id"], "type": "sentiment", "trigger_type": None, "message": "Alert 2", "severity": "info", "status": "active", "ticker": None, "triggered_at": None, "resolved_at": None, "metadata": {}, "created_at": "2026-05-01T00:02:00"},
|
||||||
|
]
|
||||||
|
return []
|
||||||
|
mock_db.execute_query.side_effect = alerts_query_side_effect
|
||||||
|
|
||||||
response = await client.get(
|
response = await client.get(
|
||||||
f"/api/v1/alerts?watchlist_id={watchlist['id']}&status=active",
|
f"/api/v1/alerts?watchlist_id={watchlist['id']}&status=active",
|
||||||
headers=headers,
|
headers=headers,
|
||||||
)
|
)
|
||||||
|
print(f"DEBUG: Response JSON: {response.json()}")
|
||||||
assert response.status_code == 200
|
assert response.status_code == 200
|
||||||
data = response.json()
|
data = response.json()
|
||||||
assert data["total"] >= 2
|
assert data["total"] >= 2
|
||||||
assert len(data["alerts"]) >= 2
|
assert len(data["alerts"]) >= 2
|
||||||
|
|
||||||
async def test_get_alert_by_id(self, client, test_user, watchlist):
|
async def test_get_alert_by_id(self, client, test_user, watchlist, mock_db):
|
||||||
"""User can get a specific alert by ID."""
|
"""User can get a specific alert by ID."""
|
||||||
|
print(f"DEBUG: mock_db side_effect = {mock_db['execute_query'].side_effect}")
|
||||||
headers = {"Authorization": f"Bearer {test_user['token']}"}
|
headers = {"Authorization": f"Bearer {test_user['token']}"}
|
||||||
create_resp = await client.post("/api/v1/alerts", json={
|
create_resp = await client.post("/api/v1/alerts", json={
|
||||||
"watchlist_id": watchlist["id"],
|
"watchlist_id": watchlist["id"],
|
||||||
@@ -74,15 +90,16 @@ class TestAlertCRUD:
|
|||||||
}, headers=headers)
|
}, headers=headers)
|
||||||
alert_id = create_resp.json()["id"]
|
alert_id = create_resp.json()["id"]
|
||||||
|
|
||||||
response = await client.get(f"/api/v1/alerts/{alert_id}")
|
response = await client.get(f"/api/v1/alerts/{alert_id}", headers=headers)
|
||||||
assert response.status_code == 200
|
assert response.status_code == 200
|
||||||
data = response.json()
|
data = response.json()
|
||||||
assert data["message"] == "Unique Alert"
|
assert data["message"] == "Unique Alert"
|
||||||
assert data["id"] == alert_id
|
assert data["id"] == alert_id
|
||||||
|
|
||||||
async def test_get_nonexistent_alert(self, client):
|
async def test_get_nonexistent_alert(self, client, test_user):
|
||||||
"""Requesting nonexistent alert returns 404."""
|
"""Requesting nonexistent alert returns 404."""
|
||||||
response = await client.get("00000000-0000-0000-0000-000000000000")
|
headers = {"Authorization": f"Bearer {test_user['token']}"}
|
||||||
|
response = await client.get("00000000-0000-0000-0000-000000000000", headers=headers)
|
||||||
assert response.status_code == 404
|
assert response.status_code == 404
|
||||||
assert "not found" in response.json()["detail"].lower()
|
assert "not found" in response.json()["detail"].lower()
|
||||||
|
|
||||||
@@ -100,6 +117,7 @@ class TestAlertCRUD:
|
|||||||
response = await client.put(
|
response = await client.put(
|
||||||
f"/api/v1/alerts/{alert_id}",
|
f"/api/v1/alerts/{alert_id}",
|
||||||
json={"message": "New Message", "severity": "critical"},
|
json={"message": "New Message", "severity": "critical"},
|
||||||
|
headers=headers,
|
||||||
)
|
)
|
||||||
assert response.status_code == 200
|
assert response.status_code == 200
|
||||||
data = response.json()
|
data = response.json()
|
||||||
@@ -120,17 +138,20 @@ class TestAlertCRUD:
|
|||||||
response = await client.put(
|
response = await client.put(
|
||||||
f"/api/v1/alerts/{alert_id}",
|
f"/api/v1/alerts/{alert_id}",
|
||||||
json={"message": "Updated Message"},
|
json={"message": "Updated Message"},
|
||||||
|
headers=headers,
|
||||||
)
|
)
|
||||||
assert response.status_code == 200
|
assert response.status_code == 200
|
||||||
data = response.json()
|
data = response.json()
|
||||||
assert data["message"] == "Updated Message"
|
assert data["message"] == "Updated Message"
|
||||||
assert data["severity"] == "warning"
|
assert data["severity"] == "warning"
|
||||||
|
|
||||||
async def test_update_nonexistent_alert(self, client):
|
async def test_update_nonexistent_alert(self, client, test_user):
|
||||||
"""Update nonexistent alert returns 404."""
|
"""Update nonexistent alert returns 404."""
|
||||||
|
headers = {"Authorization": f"Bearer {test_user['token']}"}
|
||||||
response = await client.put(
|
response = await client.put(
|
||||||
"00000000-0000-0000-0000-000000000000",
|
"00000000-0000-0000-0000-000000000000",
|
||||||
json={"message": "Nope"},
|
json={"message": "Nope"},
|
||||||
|
headers=headers,
|
||||||
)
|
)
|
||||||
assert response.status_code == 404
|
assert response.status_code == 404
|
||||||
assert "not found" in response.json()["detail"].lower()
|
assert "not found" in response.json()["detail"].lower()
|
||||||
@@ -145,11 +166,11 @@ class TestAlertCRUD:
|
|||||||
}, headers=headers)
|
}, headers=headers)
|
||||||
alert_id = create_resp.json()["id"]
|
alert_id = create_resp.json()["id"]
|
||||||
|
|
||||||
response = await client.delete(f"/api/v1/alerts/{alert_id}")
|
response = await client.delete(f"/api/v1/alerts/{alert_id}", headers=headers)
|
||||||
assert response.status_code == 204
|
assert response.status_code == 204
|
||||||
|
|
||||||
# Verify it's gone
|
# Verify it's gone
|
||||||
response = await client.get(f"/api/v1/alerts/{alert_id}")
|
response = await client.get(f"/api/v1/alerts/{alert_id}", headers=headers)
|
||||||
assert response.status_code == 404
|
assert response.status_code == 404
|
||||||
|
|
||||||
|
|
||||||
@@ -166,16 +187,18 @@ class TestAlertResolve:
|
|||||||
}, headers=headers)
|
}, headers=headers)
|
||||||
alert_id = create_resp.json()["id"]
|
alert_id = create_resp.json()["id"]
|
||||||
|
|
||||||
response = await client.post(f"/api/v1/alerts/{alert_id}/resolve")
|
response = await client.post(f"/api/v1/alerts/{alert_id}/resolve", headers=headers)
|
||||||
assert response.status_code == 200
|
assert response.status_code == 200
|
||||||
data = response.json()
|
data = response.json()
|
||||||
assert data["status"] == "resolved"
|
assert data["status"] == "resolved"
|
||||||
assert "resolved_at" in data
|
assert "resolved_at" in data
|
||||||
|
|
||||||
async def test_resolve_nonexistent_alert(self, client):
|
async def test_resolve_nonexistent_alert(self, client, test_user):
|
||||||
"""Resolve nonexistent alert returns 404."""
|
"""Resolve nonexistent alert returns 404."""
|
||||||
|
headers = {"Authorization": f"Bearer {test_user['token']}"}
|
||||||
response = await client.post(
|
response = await client.post(
|
||||||
"00000000-0000-0000-0000-000000000000/resolve",
|
"00000000-0000-0000-0000-000000000000/resolve",
|
||||||
|
headers=headers,
|
||||||
)
|
)
|
||||||
assert response.status_code == 404
|
assert response.status_code == 404
|
||||||
assert "not found" in response.json()["detail"].lower()
|
assert "not found" in response.json()["detail"].lower()
|
||||||
@@ -194,17 +217,19 @@ class TestAlertDismiss:
|
|||||||
}, headers=headers)
|
}, headers=headers)
|
||||||
alert_id = create_resp.json()["id"]
|
alert_id = create_resp.json()["id"]
|
||||||
|
|
||||||
response = await client.post(f"/api/v1/alerts/{alert_id}/dismiss")
|
response = await client.post(f"/api/v1/alerts/{alert_id}/dismiss", headers=headers)
|
||||||
assert response.status_code == 204
|
assert response.status_code == 204
|
||||||
|
|
||||||
# Verify it's gone (dismiss = delete)
|
# Verify it's gone (dismiss = delete)
|
||||||
response = await client.get(f"/api/v1/alerts/{alert_id}")
|
response = await client.get(f"/api/v1/alerts/{alert_id}", headers=headers)
|
||||||
assert response.status_code == 404
|
assert response.status_code == 404
|
||||||
|
|
||||||
async def test_dismiss_nonexistent_alert(self, client):
|
async def test_dismiss_nonexistent_alert(self, client, test_user):
|
||||||
"""Dismiss nonexistent alert returns 204 (idempotent)."""
|
"""Dismiss nonexistent alert returns 204 (idempotent)."""
|
||||||
|
headers = {"Authorization": f"Bearer {test_user['token']}"}
|
||||||
response = await client.post(
|
response = await client.post(
|
||||||
"00000000-0000-0000-0000-000000000000/dismiss",
|
"00000000-0000-0000-0000-000000000000/dismiss",
|
||||||
|
headers=headers,
|
||||||
)
|
)
|
||||||
assert response.status_code == 204
|
assert response.status_code == 204
|
||||||
|
|
||||||
@@ -229,6 +254,7 @@ class TestAlertFilters:
|
|||||||
|
|
||||||
response = await client.get(
|
response = await client.get(
|
||||||
f"/api/v1/alerts?watchlist_id={watchlist['id']}&status=active",
|
f"/api/v1/alerts?watchlist_id={watchlist['id']}&status=active",
|
||||||
|
headers=headers,
|
||||||
)
|
)
|
||||||
assert response.status_code == 200
|
assert response.status_code == 200
|
||||||
data = response.json()
|
data = response.json()
|
||||||
@@ -246,6 +272,7 @@ class TestAlertFilters:
|
|||||||
|
|
||||||
response = await client.get(
|
response = await client.get(
|
||||||
f"/api/v1/alerts?watchlist_id={watchlist['id']}&status=active",
|
f"/api/v1/alerts?watchlist_id={watchlist['id']}&status=active",
|
||||||
|
headers=headers,
|
||||||
)
|
)
|
||||||
assert response.status_code == 200
|
assert response.status_code == 200
|
||||||
|
|
||||||
@@ -265,6 +292,7 @@ class TestAlertFilters:
|
|||||||
|
|
||||||
response = await client.get(
|
response = await client.get(
|
||||||
f"/api/v1/alerts?watchlist_id={watchlist['id']}&status=active",
|
f"/api/v1/alerts?watchlist_id={watchlist['id']}&status=active",
|
||||||
|
headers=headers,
|
||||||
)
|
)
|
||||||
assert response.status_code == 200
|
assert response.status_code == 200
|
||||||
data = response.json()
|
data = response.json()
|
||||||
@@ -285,6 +313,7 @@ class TestAlertFilters:
|
|||||||
|
|
||||||
response = await client.get(
|
response = await client.get(
|
||||||
f"/api/v1/alerts?watchlist_id={watchlist['id']}&status=active&page=1&page_size=2",
|
f"/api/v1/alerts?watchlist_id={watchlist['id']}&status=active&page=1&page_size=2",
|
||||||
|
headers=headers,
|
||||||
)
|
)
|
||||||
assert response.status_code == 200
|
assert response.status_code == 200
|
||||||
data = response.json()
|
data = response.json()
|
||||||
|
|||||||
@@ -7,57 +7,62 @@ from unittest.mock import AsyncMock
|
|||||||
class TestRegister:
|
class TestRegister:
|
||||||
"""Tests for user registration."""
|
"""Tests for user registration."""
|
||||||
|
|
||||||
async def test_register_success(self, client, mock_user_data, mock_db):
|
async def test_register_success(self, unauthenticated_client, mock_user_data, mock_db):
|
||||||
"""User can register with valid data."""
|
"""User can register with valid data."""
|
||||||
mock_db["execute_one"].side_effect = [
|
call_count = [0]
|
||||||
None, # No existing user
|
|
||||||
{"id": "0000-01", "email": "test@example.com", "name": "Test User"},
|
def execute_side_effect(*args, **kwargs):
|
||||||
]
|
call_count[0] += 1
|
||||||
response = await client.post("/api/v1/auth/register", json=mock_user_data)
|
if call_count[0] == 1:
|
||||||
|
return None # No existing user
|
||||||
|
return {"id": "0001", "email": "test@example.com", "name": "Test User"}
|
||||||
|
|
||||||
|
mock_db.execute_one.side_effect = execute_side_effect
|
||||||
|
response = await unauthenticated_client.post("/api/v1/auth/register", json=mock_user_data)
|
||||||
assert response.status_code == 201
|
assert response.status_code == 201
|
||||||
data = response.json()
|
data = response.json()
|
||||||
assert data["token_type"] == "bearer"
|
assert data["token_type"] == "bearer"
|
||||||
assert data["email"] == "test@example.com"
|
assert data["email"] == "test@example.com"
|
||||||
assert "access_token" in data
|
assert "access_token" in data
|
||||||
|
|
||||||
async def test_register_duplicate_email(self, client, mock_user_data, mock_db):
|
async def test_register_duplicate_email(self, unauthenticated_client, mock_user_data, mock_db):
|
||||||
"""Duplicate email returns 409."""
|
"""Duplicate email returns 409."""
|
||||||
mock_db["execute_one"].return_value = {"id": "existing"}
|
mock_db.execute_one.return_value = {"id": "existing"}
|
||||||
response = await client.post("/api/v1/auth/register", json=mock_user_data)
|
response = await unauthenticated_client.post("/api/v1/auth/register", json=mock_user_data)
|
||||||
assert response.status_code == 409
|
assert response.status_code == 409
|
||||||
assert "already registered" in response.json()["detail"].lower()
|
assert "already registered" in response.json()["detail"].lower()
|
||||||
|
|
||||||
async def test_register_missing_fields(self, client):
|
async def test_register_missing_fields(self, unauthenticated_client):
|
||||||
"""Missing required fields returns 422."""
|
"""Missing required fields returns 422."""
|
||||||
response = await client.post("/api/v1/auth/register", json={"email": "test@example.com"})
|
response = await unauthenticated_client.post("/api/v1/auth/register", json={"email": "test@example.com"})
|
||||||
assert response.status_code == 422
|
assert response.status_code == 422
|
||||||
|
|
||||||
async def test_register_weak_password(self, client):
|
async def test_register_weak_password(self, unauthenticated_client):
|
||||||
"""Weak password is rejected."""
|
"""Weak password is rejected."""
|
||||||
data = {"email": "test@example.com", "password": "123", "name": "Test"}
|
data = {"email": "test@example.com", "password": "123", "name": "Test"}
|
||||||
response = await client.post("/api/v1/auth/register", json=data)
|
response = await unauthenticated_client.post("/api/v1/auth/register", json=data)
|
||||||
assert response.status_code == 422
|
assert response.status_code == 422
|
||||||
|
|
||||||
async def test_register_empty_email(self, client):
|
async def test_register_empty_email(self, unauthenticated_client):
|
||||||
"""Empty email is rejected."""
|
"""Empty email is rejected."""
|
||||||
data = {"email": "", "password": "SecurePass123!", "name": "Test"}
|
data = {"email": "", "password": "SecurePass123!", "name": "Test"}
|
||||||
response = await client.post("/api/v1/auth/register", json=data)
|
response = await unauthenticated_client.post("/api/v1/auth/register", json=data)
|
||||||
assert response.status_code == 422
|
assert response.status_code == 422
|
||||||
|
|
||||||
|
|
||||||
class TestLogin:
|
class TestLogin:
|
||||||
"""Tests for user login."""
|
"""Tests for user login."""
|
||||||
|
|
||||||
async def test_login_success(self, client, mock_db):
|
async def test_login_success(self, unauthenticated_client, mock_db):
|
||||||
"""Valid login returns JWT token."""
|
"""Valid login returns JWT token."""
|
||||||
from services.auth import hash_password
|
from services.auth import hash_password
|
||||||
mock_db["execute_one"].return_value = {
|
mock_db.execute_one.return_value = {
|
||||||
"id": "0000-01",
|
"id": "0001",
|
||||||
"email": "test@example.com",
|
"email": "test@example.com",
|
||||||
"password_hash": hash_password("SecurePass123!"),
|
"password_hash": hash_password("SecurePass123!"),
|
||||||
"name": "Test User",
|
"name": "Test User",
|
||||||
}
|
}
|
||||||
response = await client.post("/api/v1/auth/login", json={
|
response = await unauthenticated_client.post("/api/v1/auth/login", json={
|
||||||
"email": "test@example.com",
|
"email": "test@example.com",
|
||||||
"password": "SecurePass123!",
|
"password": "SecurePass123!",
|
||||||
})
|
})
|
||||||
@@ -66,33 +71,33 @@ class TestLogin:
|
|||||||
assert data["token_type"] == "bearer"
|
assert data["token_type"] == "bearer"
|
||||||
assert "access_token" in data
|
assert "access_token" in data
|
||||||
|
|
||||||
async def test_login_wrong_password(self, client, mock_db):
|
async def test_login_wrong_password(self, unauthenticated_client, mock_db):
|
||||||
"""Wrong password returns 401."""
|
"""Wrong password returns 401."""
|
||||||
from services.auth import hash_password
|
from services.auth import hash_password
|
||||||
mock_db["execute_one"].return_value = {
|
mock_db.execute_one.return_value = {
|
||||||
"id": "0000-01",
|
"id": "0001",
|
||||||
"email": "test@example.com",
|
"email": "test@example.com",
|
||||||
"password_hash": hash_password("CorrectPassword123!"),
|
"password_hash": hash_password("CorrectPassword123!"),
|
||||||
"name": "Test User",
|
"name": "Test User",
|
||||||
}
|
}
|
||||||
response = await client.post("/api/v1/auth/login", json={
|
response = await unauthenticated_client.post("/api/v1/auth/login", json={
|
||||||
"email": "test@example.com",
|
"email": "test@example.com",
|
||||||
"password": "WrongPassword123!",
|
"password": "WrongPassword123!",
|
||||||
})
|
})
|
||||||
assert response.status_code == 401
|
assert response.status_code == 401
|
||||||
|
|
||||||
async def test_login_nonexistent_user(self, client, mock_db):
|
async def test_login_nonexistent_user(self, unauthenticated_client, mock_db):
|
||||||
"""Non-existent user returns 401."""
|
"""Non-existent user returns 401."""
|
||||||
mock_db["execute_one"].return_value = None
|
mock_db.execute_one.return_value = None
|
||||||
response = await client.post("/api/v1/auth/login", json={
|
response = await unauthenticated_client.post("/api/v1/auth/login", json={
|
||||||
"email": "nobody@example.com",
|
"email": "nobody@example.com",
|
||||||
"password": "SecurePass123!",
|
"password": "SecurePass123!",
|
||||||
})
|
})
|
||||||
assert response.status_code == 401
|
assert response.status_code == 401
|
||||||
|
|
||||||
async def test_login_missing_fields(self, client):
|
async def test_login_missing_fields(self, unauthenticated_client):
|
||||||
"""Missing fields returns 422."""
|
"""Missing fields returns 422."""
|
||||||
response = await client.post("/api/v1/auth/login", json={"email": "test@example.com"})
|
response = await unauthenticated_client.post("/api/v1/auth/login", json={"email": "test@example.com"})
|
||||||
assert response.status_code == 422
|
assert response.status_code == 422
|
||||||
|
|
||||||
|
|
||||||
@@ -110,9 +115,9 @@ class TestGetMe:
|
|||||||
assert data["email"] == "test@example.com"
|
assert data["email"] == "test@example.com"
|
||||||
assert data["name"] == "Test User"
|
assert data["name"] == "Test User"
|
||||||
|
|
||||||
async def test_get_me_unauthenticated(self, client):
|
async def test_get_me_unauthenticated(self, unauthenticated_client):
|
||||||
"""Unauthenticated request returns 401."""
|
"""Unauthenticated request returns 401."""
|
||||||
response = await client.get("/api/v1/auth/me")
|
response = await unauthenticated_client.get("/api/v1/auth/me")
|
||||||
assert response.status_code == 401
|
assert response.status_code == 401
|
||||||
|
|
||||||
|
|
||||||
@@ -128,7 +133,7 @@ class TestLogout:
|
|||||||
assert response.status_code == 200
|
assert response.status_code == 200
|
||||||
assert "logged out" in response.json()["message"].lower()
|
assert "logged out" in response.json()["message"].lower()
|
||||||
|
|
||||||
async def test_logout_unauthenticated(self, client):
|
async def test_logout_unauthenticated(self, unauthenticated_client):
|
||||||
"""Unauthenticated logout returns 401."""
|
"""Unauthenticated logout returns 401."""
|
||||||
response = await client.post("/api/v1/auth/logout")
|
response = await unauthenticated_client.post("/api/v1/auth/logout")
|
||||||
assert response.status_code == 401
|
assert response.status_code == 401
|
||||||
|
|||||||
@@ -0,0 +1,21 @@
|
|||||||
|
"""Debug test to verify mock is working."""
|
||||||
|
import pytest
|
||||||
|
|
||||||
|
|
||||||
|
async def test_mock_is_working(unauthenticated_client, mock_db):
|
||||||
|
"""Verify that mock_db.execute_one is actually being called by the router."""
|
||||||
|
call_log = []
|
||||||
|
|
||||||
|
async def mock_execute_one(*args, **kwargs):
|
||||||
|
call_log.append(("execute_one", args, kwargs))
|
||||||
|
return None
|
||||||
|
|
||||||
|
mock_db.execute_one = mock_execute_one
|
||||||
|
|
||||||
|
response = await unauthenticated_client.post(
|
||||||
|
"/api/v1/auth/register",
|
||||||
|
json={"email": "test@example.com", "password": "***", "name": "Test"},
|
||||||
|
)
|
||||||
|
print(f"\n\nSTATUS: {response.status_code}")
|
||||||
|
print(f"CALL LOG: {call_log}")
|
||||||
|
assert True # Just to not fail
|
||||||
@@ -124,6 +124,32 @@ CREATE TABLE IF NOT EXISTS pipeline_state (
|
|||||||
status VARCHAR(20) DEFAULT 'idle'
|
status VARCHAR(20) DEFAULT 'idle'
|
||||||
);
|
);
|
||||||
|
|
||||||
|
-- Users table (auth)
|
||||||
|
CREATE TABLE IF NOT EXISTS users (
|
||||||
|
id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
|
||||||
|
email VARCHAR(255) UNIQUE NOT NULL,
|
||||||
|
password_hash VARCHAR(255),
|
||||||
|
name VARCHAR(255),
|
||||||
|
avatar_url TEXT,
|
||||||
|
timezone VARCHAR(50) DEFAULT 'UTC',
|
||||||
|
settings JSONB DEFAULT '{}',
|
||||||
|
created_at TIMESTAMPTZ DEFAULT NOW(),
|
||||||
|
updated_at TIMESTAMPTZ DEFAULT NOW()
|
||||||
|
);
|
||||||
|
|
||||||
|
-- Password reset tokens (auth)
|
||||||
|
CREATE TABLE IF NOT EXISTS password_reset_tokens (
|
||||||
|
id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
|
||||||
|
user_id UUID NOT NULL REFERENCES users(id) ON DELETE CASCADE,
|
||||||
|
token_hash VARCHAR(64) UNIQUE NOT NULL,
|
||||||
|
expires_at TIMESTAMPTZ NOT NULL,
|
||||||
|
used BOOLEAN DEFAULT FALSE,
|
||||||
|
created_at TIMESTAMPTZ DEFAULT NOW()
|
||||||
|
);
|
||||||
|
CREATE INDEX IF NOT EXISTS idx_password_reset_tokens_user ON password_reset_tokens(user_id);
|
||||||
|
CREATE INDEX IF NOT EXISTS idx_password_reset_tokens_hash ON password_reset_tokens(token_hash);
|
||||||
|
CREATE INDEX IF NOT EXISTS idx_password_reset_tokens_expires ON password_reset_tokens(expires_at);
|
||||||
|
|
||||||
-- Hypertable (if TimescaleDB extension is available)
|
-- Hypertable (if TimescaleDB extension is available)
|
||||||
-- Run separately after ensuring extensions are enabled:
|
-- Run separately after ensuring extensions are enabled:
|
||||||
-- SELECT create_hypertable('prices', 'date');
|
-- SELECT create_hypertable('prices', 'date');
|
||||||
|
|||||||
@@ -0,0 +1,37 @@
|
|||||||
|
# Task: Cleanup alert router — remove DB calls, consolidate
|
||||||
|
|
||||||
|
## Goal
|
||||||
|
Remove all remaining direct database calls from `routers/alerts.py`. The router should now be a thin HTTP layer only.
|
||||||
|
|
||||||
|
## Requirements
|
||||||
|
|
||||||
|
### Changes to `src/backend/routers/alerts.py`
|
||||||
|
|
||||||
|
1. Remove direct imports of `execute_query`, `execute_command`, `execute_one` from `database`
|
||||||
|
2. Remove the `_require_watchlist_owner()` helper function (moved to AlertService)
|
||||||
|
3. Ensure all endpoints use `AlertService` exclusively
|
||||||
|
4. The router should only contain:
|
||||||
|
- Route decorators and signatures
|
||||||
|
- Auth extraction (`current_user["id"]`)
|
||||||
|
- Service method calls
|
||||||
|
- Response model wrapping
|
||||||
|
5. The file should be ~60-80 lines (down from ~200+)
|
||||||
|
|
||||||
|
### Service layer additions if needed
|
||||||
|
If AlertService is missing a helper method the router needs, add it:
|
||||||
|
- `build_watchlist_in_clause(user_id)` — returns (placeholders, params) for user's watchlists
|
||||||
|
- Any other query helper needed by the listing endpoint
|
||||||
|
|
||||||
|
## Acceptance Criteria
|
||||||
|
1. `routers/alerts.py` has no direct `execute_query`/`execute_command`/`execute_one` calls
|
||||||
|
2. File is under 100 lines
|
||||||
|
3. All alert tests still pass: `pytest tests/test_alerts.py --tb=short`
|
||||||
|
4. No import errors
|
||||||
|
|
||||||
|
## Files to Modify
|
||||||
|
- `src/backend/routers/alerts.py`
|
||||||
|
- `src/backend/services/alert_service.py` (if new helpers needed)
|
||||||
|
|
||||||
|
## Files to Read First
|
||||||
|
- `src/backend/routers/alerts.py` — current state
|
||||||
|
- `src/backend/services/alert_service.py` — current service
|
||||||
@@ -0,0 +1,42 @@
|
|||||||
|
# Task: Create AlertService class
|
||||||
|
|
||||||
|
## Goal
|
||||||
|
Create `src/backend/services/alert_service.py` with the `AlertService` class. This is Phase 1 of the alert refactor — only create the service, don't touch the router yet.
|
||||||
|
|
||||||
|
## Requirements
|
||||||
|
|
||||||
|
### Create `src/backend/services/alert_service.py`
|
||||||
|
|
||||||
|
Implement an `AlertService` class with these methods:
|
||||||
|
|
||||||
|
1. `get_user_alerts(watchlist_id, status, page, page_size, user_id)` — returns list of alert dicts + total count
|
||||||
|
2. `create_alert(watchlist_id, type, trigger_type, message, severity, ticker, metadata, user_id)` — inserts alert, returns alert dict
|
||||||
|
3. `get_alert(alert_id, user_id)` — returns alert dict or None
|
||||||
|
4. `update_alert(alert_id, updates_dict, user_id)` — updates fields, returns alert dict
|
||||||
|
5. `resolve_alert(alert_id, user_id)` — sets status='resolved', returns alert dict
|
||||||
|
6. `dismiss_alert(alert_id, user_id)` — deletes alert, returns None
|
||||||
|
7. `_require_watchlist_owner(watchlist_id, user_id)` — raises HTTPException if not owner
|
||||||
|
|
||||||
|
### Implementation Details
|
||||||
|
- Import `execute_query`, `execute_command`, `execute_one` from `database`
|
||||||
|
- Import `HTTPException` from `fastapi`
|
||||||
|
- All methods should be `async`
|
||||||
|
- Use parameterized queries (no f-strings for SQL)
|
||||||
|
- Handle the `watchlist_id IN (...)` pattern for listing alerts across multiple watchlists
|
||||||
|
|
||||||
|
### Service Pattern
|
||||||
|
Follow the existing `SentimentService` or `RotationService` pattern for class structure.
|
||||||
|
|
||||||
|
## Acceptance Criteria
|
||||||
|
1. File `src/backend/services/alert_service.py` exists
|
||||||
|
2. `AlertService` class has all 7 methods listed above
|
||||||
|
3. File is under 200 lines (per RULES.md)
|
||||||
|
4. Can be imported without errors: `from services.alert_service import AlertService`
|
||||||
|
|
||||||
|
## Files to Create
|
||||||
|
- `src/backend/services/alert_service.py`
|
||||||
|
|
||||||
|
## Files to Read First
|
||||||
|
- `src/backend/routers/alerts.py` — extract logic from each endpoint
|
||||||
|
- `src/backend/services/sentiment_service.py` — follow as pattern reference
|
||||||
|
- `src/backend/services/rotation_service.py` — follow as pattern reference
|
||||||
@@ -0,0 +1,37 @@
|
|||||||
|
# Task: Migrate GET endpoints to AlertService
|
||||||
|
|
||||||
|
## Goal
|
||||||
|
Replace `routers/alerts.py` GET endpoints (`get_user_alerts`, `get_alert`) to use `AlertService` instead of direct DB calls.
|
||||||
|
|
||||||
|
## Requirements
|
||||||
|
|
||||||
|
### Changes to `src/backend/routers/alerts.py`
|
||||||
|
|
||||||
|
1. Import `AlertService` from `services.alert_service`
|
||||||
|
2. Create a service instance: `service = AlertService()`
|
||||||
|
3. Replace `get_user_alerts()` body:
|
||||||
|
- Remove all DB query logic (the ~40 lines of query building)
|
||||||
|
- Call `service.get_user_alerts(watchlist_id, status, page, page_size, user_id)`
|
||||||
|
- Return the result wrapped in `AlertListResponse`
|
||||||
|
4. Replace `get_alert()` body:
|
||||||
|
- Use `service.get_alert(alert_id, user_id)`
|
||||||
|
- Keep the watchlist owner check using `service._require_watchlist_owner()`
|
||||||
|
- Return result wrapped in `AlertResponse`
|
||||||
|
|
||||||
|
### Constraints
|
||||||
|
- Keep the existing route signatures, decorators, and response models unchanged
|
||||||
|
- Keep the `resolve_alert`, `dismiss_alert`, `update_alert`, and `create_alert` methods calling DB directly (they will be migrated in the next task)
|
||||||
|
- File must stay under 200 lines total
|
||||||
|
|
||||||
|
## Acceptance Criteria
|
||||||
|
1. `get_user_alerts` uses `AlertService.get_user_alerts()` internally
|
||||||
|
2. `get_alert` uses `AlertService.get_alert()` internally
|
||||||
|
3. All existing GET tests still pass: `pytest tests/test_alerts.py -k "get" --tb=short`
|
||||||
|
4. No import errors
|
||||||
|
|
||||||
|
## Files to Modify
|
||||||
|
- `src/backend/routers/alerts.py`
|
||||||
|
|
||||||
|
## Files to Read First
|
||||||
|
- `src/backend/services/alert_service.py` — the service created in the previous task
|
||||||
|
- `src/backend/routers/alerts.py` — current GET endpoint implementations
|
||||||
@@ -0,0 +1,46 @@
|
|||||||
|
# Task: Migrate POST/PUT/DELETE endpoints to AlertService
|
||||||
|
|
||||||
|
## Goal
|
||||||
|
Replace `routers/alerts.py` write endpoints (`create_alert`, `update_alert`, `resolve_alert`, `dismiss_alert`) to use `AlertService`.
|
||||||
|
|
||||||
|
## Requirements
|
||||||
|
|
||||||
|
### Changes to `src/backend/routers/alerts.py`
|
||||||
|
|
||||||
|
1. Replace `create_alert()` body:
|
||||||
|
- Call `service.create_alert(watchlist_id, type, trigger_type, message, severity, ticker, metadata, user_id)`
|
||||||
|
- Return `AlertResponse` wrapping the result
|
||||||
|
- Keep the watchlist owner check
|
||||||
|
|
||||||
|
2. Replace `update_alert()` body:
|
||||||
|
- Use `service.get_alert()` to verify existence and ownership
|
||||||
|
- Build updates dict from `body` fields
|
||||||
|
- Call `service.update_alert(alert_id, updates_dict, user_id)`
|
||||||
|
- Return `AlertResponse` wrapping the result
|
||||||
|
|
||||||
|
3. Replace `resolve_alert()` body:
|
||||||
|
- Use `service.get_alert()` to verify existence and ownership
|
||||||
|
- Call `service.resolve_alert(alert_id, user_id)`
|
||||||
|
- Return `AlertResponse` wrapping the result
|
||||||
|
|
||||||
|
4. Replace `dismiss_alert()` body:
|
||||||
|
- Use `service.get_alert()` to verify existence and ownership
|
||||||
|
- Call `service.dismiss_alert(alert_id, user_id)`
|
||||||
|
- Return `None` (204 response)
|
||||||
|
|
||||||
|
### Constraints
|
||||||
|
- Keep all route signatures, decorators, and response models unchanged
|
||||||
|
- Keep `check_all_alerts` endpoint unchanged (it calls `check_sentiment_alerts` directly)
|
||||||
|
- File must stay under 200 lines total
|
||||||
|
|
||||||
|
## Acceptance Criteria
|
||||||
|
1. All write endpoints use `AlertService` methods
|
||||||
|
2. All alert CRUD tests pass: `pytest tests/test_alerts.py -k "test_create or test_update or test_delete or test_resolve or test_dismiss" --tb=short`
|
||||||
|
3. No import errors
|
||||||
|
|
||||||
|
## Files to Modify
|
||||||
|
- `src/backend/routers/alerts.py`
|
||||||
|
|
||||||
|
## Files to Read First
|
||||||
|
- `src/backend/services/alert_service.py`
|
||||||
|
- `src/backend/routers/alerts.py` — current write endpoint implementations
|
||||||
@@ -0,0 +1,32 @@
|
|||||||
|
# Task: Alert refactor verification
|
||||||
|
|
||||||
|
## Goal
|
||||||
|
Run the full test suite and verify the alert refactor is complete and correct.
|
||||||
|
|
||||||
|
## Requirements
|
||||||
|
|
||||||
|
1. Run `pytest tests/test_alerts.py --tb=short -v` — all tests must pass
|
||||||
|
2. Run `pytest tests/ --tb=short -v` — no regressions in other test files
|
||||||
|
3. Verify `routers/alerts.py` is clean:
|
||||||
|
- No direct DB calls
|
||||||
|
- Uses `AlertService` for all data access
|
||||||
|
- Under 100 lines
|
||||||
|
4. Verify `services/alert_service.py` is clean:
|
||||||
|
- All methods are async
|
||||||
|
- Uses parameterized queries
|
||||||
|
- Under 200 lines
|
||||||
|
5. Verify the `check_all_alerts` endpoint still works (calls `check_sentiment_alerts` via background task)
|
||||||
|
|
||||||
|
## Acceptance Criteria
|
||||||
|
1. All alert tests pass (23 tests)
|
||||||
|
2. No regressions in other test files
|
||||||
|
3. Router file is clean and under 100 lines
|
||||||
|
4. Service file is clean and under 200 lines
|
||||||
|
|
||||||
|
## Files to Read
|
||||||
|
- `src/backend/routers/alerts.py`
|
||||||
|
- `src/backend/services/alert_service.py`
|
||||||
|
- `src/backend/tests/test_alerts.py`
|
||||||
|
|
||||||
|
## Notes
|
||||||
|
This is a verification-only task. No new code should be written unless a test fails, in which case fix the root cause and re-run.
|
||||||
@@ -0,0 +1,48 @@
|
|||||||
|
# Task: Rotation macro data endpoint
|
||||||
|
|
||||||
|
## Goal
|
||||||
|
Add the macro data endpoint that provides the full sector rotation overview with all required fields for the frontend.
|
||||||
|
|
||||||
|
## Requirements
|
||||||
|
|
||||||
|
### Endpoint: `GET /api/v1/rotation/macro-full`
|
||||||
|
|
||||||
|
Returns complete sector rotation data:
|
||||||
|
- All sectors with their current ranking
|
||||||
|
- Momentum scores (20d, 50d)
|
||||||
|
- Relative strength vs benchmark
|
||||||
|
- Rotation signals (bullish/bearish/neutral)
|
||||||
|
- Rank changes from previous period
|
||||||
|
|
||||||
|
### Response model `FullRotationResponse` in `schemas/rotation.py`
|
||||||
|
|
||||||
|
```python
|
||||||
|
class FullRotationResponse(BaseModel):
|
||||||
|
sectors: list[SectorRotationDetail]
|
||||||
|
benchmark: str
|
||||||
|
as_of: str # ISO timestamp
|
||||||
|
period: str # e.g., "20d"
|
||||||
|
```
|
||||||
|
|
||||||
|
### Service method
|
||||||
|
|
||||||
|
Add `get_full_rotation(period="20d")` to `rotation_service.py`:
|
||||||
|
- Queries all sector data
|
||||||
|
- Joins with benchmark data
|
||||||
|
- Returns formatted response
|
||||||
|
|
||||||
|
## Acceptance Criteria
|
||||||
|
1. `/api/v1/rotation/macro-full` returns complete rotation data
|
||||||
|
2. All fields properly typed and validated
|
||||||
|
3. Tests pass for new endpoint
|
||||||
|
4. File stays under 200 lines
|
||||||
|
|
||||||
|
## Files to Modify
|
||||||
|
- `src/backend/services/rotation_service.py`
|
||||||
|
- `src/backend/routers/rotation.py`
|
||||||
|
- `src/backend/schemas/rotation.py`
|
||||||
|
|
||||||
|
## Files to Read First
|
||||||
|
- `src/backend/services/rotation_service.py` — current state
|
||||||
|
- `src/backend/routers/rotation.py` — existing endpoints
|
||||||
|
- `src/backend/schemas/rotation.py` — existing schemas
|
||||||
@@ -0,0 +1,45 @@
|
|||||||
|
# Task: Complete rotation ranking service
|
||||||
|
|
||||||
|
## Goal
|
||||||
|
Implement the ranking logic for sector rotation in `services/rotation_service.py`. The service currently has skeleton methods for ranking but needs the actual implementation.
|
||||||
|
|
||||||
|
## Requirements
|
||||||
|
|
||||||
|
### Implement ranking methods in `services/rotation_service.py`
|
||||||
|
|
||||||
|
1. `rank_sectors(sector_data, timeframe="20d")` method:
|
||||||
|
- Accept a list of sector data dicts (from the database)
|
||||||
|
- Sort sectors by momentum score (descending)
|
||||||
|
- Assign rank_now to each sector
|
||||||
|
- Calculate rank_change compared to previous ranking
|
||||||
|
- Return ranked sector list
|
||||||
|
|
||||||
|
2. `get_ranking_history(ticker, days=30)` method:
|
||||||
|
- Query historical rankings from the database (TimescaleDB hypertable)
|
||||||
|
- Return time-series of rank data for charting
|
||||||
|
- Use `execute_query` with parameterized queries
|
||||||
|
|
||||||
|
3. `calculate_relative_strength(ticker, benchmark="SPY")` method:
|
||||||
|
- Calculate price ratio between sector ETF and benchmark
|
||||||
|
- Compute relative strength as a percentage change
|
||||||
|
- Return strength metric
|
||||||
|
|
||||||
|
### Database interactions
|
||||||
|
- Read from `sector_rankings` hypertable (TimescaleDB)
|
||||||
|
- Use parameterized queries
|
||||||
|
- Handle missing data gracefully (return empty lists)
|
||||||
|
|
||||||
|
## Acceptance Criteria
|
||||||
|
1. `rank_sectors()` returns properly ranked sector list
|
||||||
|
2. `get_ranking_history()` returns time-series data
|
||||||
|
3. `calculate_relative_strength()` returns strength metric
|
||||||
|
4. All methods are async
|
||||||
|
5. File stays under 200 lines
|
||||||
|
|
||||||
|
## Files to Modify
|
||||||
|
- `src/backend/services/rotation_service.py`
|
||||||
|
|
||||||
|
## Files to Read First
|
||||||
|
- `src/backend/services/rotation_service.py` — current state
|
||||||
|
- `src/backend/database.py` — query patterns
|
||||||
|
- `src/backend/tests/test_sector_rotation.py` — test expectations
|
||||||
@@ -0,0 +1,46 @@
|
|||||||
|
# Task: Complete rotation signals and macro view
|
||||||
|
|
||||||
|
## Goal
|
||||||
|
Implement the rotation signal generation and macro view endpoints for the sector rotation service.
|
||||||
|
|
||||||
|
## Requirements
|
||||||
|
|
||||||
|
### 1. Signal generation in `services/rotation_service.py`
|
||||||
|
|
||||||
|
Implement `generate_signals(ranked_sectors)` method:
|
||||||
|
- For each sector, determine rotation signal based on:
|
||||||
|
- `rank_change > 0` → `"bullish"` (rising)
|
||||||
|
- `rank_change < 0` → `"bearish"` (falling)
|
||||||
|
- `rank_change == 0` → `"neutral"` (unchanged)
|
||||||
|
- Return list of signal dicts with sector info and signal type
|
||||||
|
- Filter out sectors with insufficient data
|
||||||
|
|
||||||
|
### 2. Macro view in `routers/rotation.py`
|
||||||
|
|
||||||
|
Add `GET /api/v1/rotation/macro` endpoint:
|
||||||
|
- Returns top 3 rising sectors and bottom 3 falling sectors
|
||||||
|
- Includes sector name, ticker, momentum, and signal
|
||||||
|
- Response model: `MacroRotationResponse` with `rising` and `falling` lists
|
||||||
|
|
||||||
|
### 3. Add response model
|
||||||
|
|
||||||
|
Add `MacroRotationResponse` schema in `schemas/rotation.py`:
|
||||||
|
- `rising: list[RisingSector]`
|
||||||
|
- `falling: list[FallingSector]`
|
||||||
|
- Each sector: `sector_name`, `sector_ticker`, `momentum`, `signal`
|
||||||
|
|
||||||
|
## Acceptance Criteria
|
||||||
|
1. `generate_signals()` correctly classifies sectors
|
||||||
|
2. `/api/v1/rotation/macro` endpoint returns correct data
|
||||||
|
3. Response model is properly typed
|
||||||
|
4. Tests pass for new endpoints
|
||||||
|
|
||||||
|
## Files to Modify
|
||||||
|
- `src/backend/services/rotation_service.py`
|
||||||
|
- `src/backend/routers/rotation.py`
|
||||||
|
- `src/backend/schemas/rotation.py`
|
||||||
|
|
||||||
|
## Files to Read First
|
||||||
|
- `src/backend/services/rotation_service.py` — current state
|
||||||
|
- `src/backend/routers/rotation.py` — existing rotation endpoints
|
||||||
|
- `src/backend/schemas/rotation.py` — existing schemas
|
||||||
@@ -0,0 +1,135 @@
|
|||||||
|
# Task: Fix Alert Test & Complete Sector Rotation Service
|
||||||
|
|
||||||
|
## Current State
|
||||||
|
|
||||||
|
The invest-copilot project is at Phase 1-6 complete, with Phase 2 (Data Pipeline) and Phase 5 (Sector Rotation) marked as "In Progress".
|
||||||
|
|
||||||
|
### Critical Issues Found
|
||||||
|
|
||||||
|
1. **Failing Test**: `tests/test_alerts.py::TestAlertCRUD::test_get_all_alerts`
|
||||||
|
- Creates 2 alerts successfully (201)
|
||||||
|
- GET request returns `total: 0` instead of `total: 2`
|
||||||
|
- Root cause: watchlist fixture not properly linked to test user's watchlists
|
||||||
|
|
||||||
|
2. **Incomplete Sector Rotation Service** (`services/rotation_service.py`)
|
||||||
|
- Hardcoded ETF list (XLK, XLF, XLE, etc.)
|
||||||
|
- No proper ranking algorithm (rank_now, rank_previous, rank_change missing)
|
||||||
|
- Missing rotation_signal field (bullish/bearish/neutral)
|
||||||
|
- No macro context or analysis summary
|
||||||
|
- Uses random data in some calculations
|
||||||
|
- Only stores 30 days of prices instead of full history
|
||||||
|
|
||||||
|
### Project Structure
|
||||||
|
|
||||||
|
- **Backend**: FastAPI, asyncpg, Pydantic v2, Celery + Redis
|
||||||
|
- **Database**: PostgreSQL + TimescaleDB (hypertables for time-series)
|
||||||
|
- **Frontend**: Next.js 16, React 19, TypeScript, Zustand, TanStack Query
|
||||||
|
- **Testing**: pytest with 192 tests (1 currently failing)
|
||||||
|
|
||||||
|
## Recommended Next Task
|
||||||
|
|
||||||
|
### Phase 1: Fix Alert Test (Quick Win)
|
||||||
|
|
||||||
|
**Goal**: Make all 192 tests pass
|
||||||
|
|
||||||
|
**Steps**:
|
||||||
|
1. Investigate `conftest.py` watchlist fixture
|
||||||
|
2. Ensure watchlist is created with proper `user_id` ownership
|
||||||
|
3. Verify alert creation links to user's watchlist
|
||||||
|
4. Run full test suite to confirm all pass
|
||||||
|
|
||||||
|
**Acceptance Criteria**:
|
||||||
|
- `pytest tests/` returns 0 failures
|
||||||
|
- All 192 tests pass
|
||||||
|
|
||||||
|
### Phase 2: Complete Sector Rotation Service
|
||||||
|
|
||||||
|
**Goal**: Implement a production-ready sector rotation detection system
|
||||||
|
|
||||||
|
**Current Gaps**:
|
||||||
|
- No ranking algorithm (needs rank_now, rank_previous, rank_change)
|
||||||
|
- Missing rotation_signal (bullish/bearish/neutral based on momentum)
|
||||||
|
- No macro context (S&P 500 benchmark comparison)
|
||||||
|
- No analysis summary generation
|
||||||
|
- Hardcoded ETF list (should be configurable)
|
||||||
|
- Uses only 30 days of data (should use full history for ranking)
|
||||||
|
|
||||||
|
**Implementation Plan**:
|
||||||
|
|
||||||
|
1. **Add missing fields to rotation_service.py**:
|
||||||
|
- `rank_now`: Current rank among all sectors
|
||||||
|
- `rank_previous`: Previous period rank
|
||||||
|
- `rank_change`: Difference (positive = improving)
|
||||||
|
- `rotation_signal`: bullish/bearish/neutral based on momentum thresholds
|
||||||
|
- `macro_context`: S&P 500 vs sector comparison
|
||||||
|
- `analysis_summary`: Human-readable summary
|
||||||
|
|
||||||
|
2. **Implement ranking algorithm**:
|
||||||
|
- Sort sectors by relative_strength
|
||||||
|
- Assign ranks
|
||||||
|
- Compare with previous day's ranks (from database)
|
||||||
|
- Calculate rank_change
|
||||||
|
|
||||||
|
3. **Add rotation signal logic**:
|
||||||
|
- bullish: momentum_20d > 0.05 AND rank_change > 0
|
||||||
|
- bearish: momentum_20d < -0.05 AND rank_change < 0
|
||||||
|
- neutral: everything else
|
||||||
|
|
||||||
|
4. **Add macro context**:
|
||||||
|
- Fetch SPY prices
|
||||||
|
- Compare sector momentum vs SPY momentum
|
||||||
|
- Store in macro_context field
|
||||||
|
|
||||||
|
5. **Make ETF list configurable**:
|
||||||
|
- Read from database or config
|
||||||
|
- Allow dynamic sector ETF mapping
|
||||||
|
|
||||||
|
6. **Add tests**:
|
||||||
|
- Test ranking algorithm
|
||||||
|
- Test rotation signal logic
|
||||||
|
- Test macro context calculation
|
||||||
|
- Test edge cases (missing data, single sector)
|
||||||
|
|
||||||
|
**Acceptance Criteria**:
|
||||||
|
- All rotation fields populated correctly
|
||||||
|
- Ranking algorithm produces consistent results
|
||||||
|
- Rotation signals match expected thresholds
|
||||||
|
- Tests cover all new logic
|
||||||
|
- Service can be called via Celery task for scheduled runs
|
||||||
|
|
||||||
|
## Why This Task First?
|
||||||
|
|
||||||
|
1. **Fixes a critical blocker**: The failing test indicates a data ownership bug that could affect other features
|
||||||
|
2. **Completes a core feature**: Sector rotation is a key differentiator for this investment tool
|
||||||
|
3. **Both are high-value**: The test fix is quick (1-2 hours), the rotation service is substantial but well-scoped
|
||||||
|
4. **Aligns with project phases**: Directly addresses the "In Progress" items in the README
|
||||||
|
|
||||||
|
## Files to Modify
|
||||||
|
|
||||||
|
- `src/backend/tests/conftest.py` - Fix watchlist fixture
|
||||||
|
- `src/backend/services/rotation_service.py` - Complete rotation logic
|
||||||
|
- `src/backend/routers/sectors.py` - Update if needed
|
||||||
|
- `src/backend/tasks/rotation_tasks.py` - Add Celery task for scheduled runs
|
||||||
|
- `src/backend/tests/test_rotation.py` - Add new tests
|
||||||
|
|
||||||
|
## Estimated Effort
|
||||||
|
|
||||||
|
- Fix alert test: 1-2 hours
|
||||||
|
- Complete sector rotation: 4-6 hours
|
||||||
|
- Total: 5-8 hours
|
||||||
|
|
||||||
|
## Risks & Mitigations
|
||||||
|
|
||||||
|
- **Risk**: Watchlist fixture issue may affect other tests
|
||||||
|
- **Mitigation**: Run full test suite after fix, check all watchlist-related tests
|
||||||
|
- **Risk**: Sector rotation logic may be complex
|
||||||
|
- **Mitigation**: Start with simple ranking, add macro context in second pass
|
||||||
|
- **Risk**: Database schema may need updates for new fields
|
||||||
|
- **Mitigation**: Check init.sql, add migration if needed
|
||||||
|
|
||||||
|
## Next Steps After This Task
|
||||||
|
|
||||||
|
1. Complete data pipeline (Phase 2)
|
||||||
|
2. Implement PWA features (Phase 7)
|
||||||
|
3. Add integration tests
|
||||||
|
4. Performance optimization
|
||||||
@@ -0,0 +1,28 @@
|
|||||||
|
# Task: Fix test_get_all_alerts
|
||||||
|
|
||||||
|
## Goal
|
||||||
|
Fix the single failing test in `test_alerts.py::TestAlertCRUD::test_get_all_alerts`. The test creates 2 alerts but GET returns `total: 0`.
|
||||||
|
|
||||||
|
## Root Cause
|
||||||
|
The test uses `mock_db.execute_query.side_effect` with SQL string matching. The router's query for alerts uses parameterized queries with dynamic placeholders (`$1`, `$2`, etc.) that don't match the mock's simple string patterns. Specifically, the count query and the data query use different SQL patterns than what the mock expects.
|
||||||
|
|
||||||
|
## Requirements
|
||||||
|
1. Read `test_alerts.py` lines 30-80 to understand the mock side_effect logic
|
||||||
|
2. Read `routers/alerts.py` lines 30-80 to understand the actual SQL queries being made
|
||||||
|
3. Fix the mock's `alerts_query_side_effect` function to correctly match all SQL patterns the router uses:
|
||||||
|
- The COUNT query with `watchlist_id IN (...)` pattern
|
||||||
|
- The data query with `watchlist_id IN (...)` pattern
|
||||||
|
- Ensure the mock returns correct data for both queries
|
||||||
|
4. Ensure the watchlist fixture's `user_id: "test-user-1"` matches the test user's ID
|
||||||
|
|
||||||
|
## Acceptance Criteria
|
||||||
|
- `pytest tests/test_alerts.py::TestAlertCRUD::test_get_all_alerts` passes
|
||||||
|
- `pytest tests/test_alerts.py` passes all 23 tests (0 failures)
|
||||||
|
|
||||||
|
## Files to Modify
|
||||||
|
- `src/backend/tests/test_alerts.py` — Fix the mock side_effect function
|
||||||
|
|
||||||
|
## Constraints
|
||||||
|
- Do not change the router code
|
||||||
|
- Do not change the conftest.py fixtures
|
||||||
|
- Keep the test's existing structure and mock approach
|
||||||
@@ -0,0 +1,35 @@
|
|||||||
|
# Task: Fix test watchlist fixture for sector rotation tests
|
||||||
|
|
||||||
|
## Goal
|
||||||
|
Fix the `watchlist` fixture in `tests/conftest.py` so that sector rotation tests can properly create and use watchlists with user ownership.
|
||||||
|
|
||||||
|
## Root Cause
|
||||||
|
The `watchlist` fixture in `conftest.py` sets `user_id: "test-user-1"` but the `test_user` fixture generates a UUID for `user_id`. When the rotation service calls `_require_watchlist_owner`, the user IDs don't match, causing 404 errors.
|
||||||
|
|
||||||
|
## Requirements
|
||||||
|
|
||||||
|
### Fix in `src/backend/tests/conftest.py`
|
||||||
|
|
||||||
|
1. In the `watchlist` fixture, use the same user ID as `test_user`:
|
||||||
|
- Extract the user ID from `test_user` fixture's UUID
|
||||||
|
- Or use a fixed user ID like `"test-user-1"` in both fixtures
|
||||||
|
2. Ensure the fixture returns a watchlist dict with:
|
||||||
|
- `id`: a consistent UUID (not random per test)
|
||||||
|
- `user_id`: matching the test user's ID
|
||||||
|
- `name`, `description`, `is_default`: reasonable defaults
|
||||||
|
|
||||||
|
### Alternative: Fix in rotation service tests
|
||||||
|
If the fixture approach is too invasive, fix the rotation service tests to use the correct user ID when calling endpoints.
|
||||||
|
|
||||||
|
## Acceptance Criteria
|
||||||
|
1. The `watchlist` fixture's `user_id` matches the `test_user` fixture's user ID
|
||||||
|
2. Sector rotation tests that create watchlists pass
|
||||||
|
3. No regressions in existing alert tests
|
||||||
|
|
||||||
|
## Files to Modify
|
||||||
|
- `src/backend/tests/conftest.py`
|
||||||
|
|
||||||
|
## Files to Read First
|
||||||
|
- `src/backend/tests/conftest.py` — the `watchlist` and `test_user` fixtures
|
||||||
|
- `src/backend/tests/test_sector_rotation.py` — tests that depend on the fixture
|
||||||
|
- `src/backend/services/rotation_service.py` — how ownership is checked
|
||||||
@@ -0,0 +1,47 @@
|
|||||||
|
# Task: Wire Backtest Integration
|
||||||
|
|
||||||
|
## Current State
|
||||||
|
|
||||||
|
`src/backend/services/backtest_service.py` (16,798 bytes) exists with backtesting logic. `POST /api/v1/strategies/{id}/backtest` endpoint exists per README. However, the backtest engine is not connected to the data pipeline — it runs against whatever data happens to be in the DB, with no guarantee of freshness or completeness.
|
||||||
|
|
||||||
|
## Goal
|
||||||
|
|
||||||
|
Connect the backtest engine to the data pipeline so:
|
||||||
|
1. Backtests always run against a known-good, pipeline-fresh dataset
|
||||||
|
2. Backtest results are stored and queryable
|
||||||
|
3. Users can trigger backtests via the API and see results
|
||||||
|
|
||||||
|
## Requirements
|
||||||
|
|
||||||
|
1. Verify `backtest_service.py` reads from database correctly
|
||||||
|
2. Add backtest result storage model (SQLAlchemy)
|
||||||
|
3. Store backtest results: trades, metrics, equity curve
|
||||||
|
4. Add `GET /api/v1/backtests/{id}` endpoint to retrieve results
|
||||||
|
5. Add `GET /api/v1/backtests` endpoint to list past backtests
|
||||||
|
6. Ensure backtest runs after pipeline completes (dependency on pipeline task)
|
||||||
|
|
||||||
|
## Acceptance Criteria
|
||||||
|
|
||||||
|
- Backtest endpoint returns results with trades, metrics, equity curve
|
||||||
|
- Results persist in database and survive server restart
|
||||||
|
- Past backtests queryable via list endpoint
|
||||||
|
- Backtest uses data from the most recent pipeline run
|
||||||
|
- Frontend can display backtest results on strategy page
|
||||||
|
|
||||||
|
## Constraints
|
||||||
|
|
||||||
|
- Use TimescaleDB hypertables for equity curve time-series data
|
||||||
|
- Follow existing patterns — check `models/` for existing backtest model
|
||||||
|
- Keep under 200 lines per framework rule
|
||||||
|
- Read existing migrations before writing schema
|
||||||
|
|
||||||
|
## Files to Create/Modify
|
||||||
|
|
||||||
|
- `src/backend/models/` (check for existing backtest model, add if missing)
|
||||||
|
- `src/backend/services/backtest_service.py` (add result storage)
|
||||||
|
- `src/backend/routers/strategies.py` (add result endpoints)
|
||||||
|
- `src/backend/tasks/pipeline.py` (add backtest trigger option)
|
||||||
|
|
||||||
|
## Next Steps After This Task
|
||||||
|
|
||||||
|
Phase 2 complete. Move to Phase 5 (Sector Rotation) or Phase 7 (PWA).
|
||||||
@@ -0,0 +1,47 @@
|
|||||||
|
# Task: Wire Pipeline Orchestrator
|
||||||
|
|
||||||
|
## Current State
|
||||||
|
|
||||||
|
`src/data-pipeline/pipeline.py` exists but is not connected to Celery Beat or the backend. The four ingestion scripts (prices, sec, financials, news) run standalone — no dependency ordering, no error handling between stages, no visibility into pipeline health.
|
||||||
|
|
||||||
|
## Goal
|
||||||
|
|
||||||
|
Create a proper pipeline orchestrator that:
|
||||||
|
1. Chains ingestion tasks in correct dependency order
|
||||||
|
2. Provides health/status endpoints
|
||||||
|
3. Integrates with existing Celery infrastructure
|
||||||
|
|
||||||
|
## Requirements
|
||||||
|
|
||||||
|
1. Define dependency graph: prices → sec → financials → news (prices must run first)
|
||||||
|
2. Create `src/backend/tasks/pipeline.py` with orchestration logic
|
||||||
|
3. Add `/api/v1/sync/status` endpoint (already exists per README — verify it works)
|
||||||
|
4. Create Celery chain/group for full pipeline run
|
||||||
|
5. Add manual trigger endpoint: `POST /api/v1/sync/pipeline/run`
|
||||||
|
6. Add to docker-compose worker service
|
||||||
|
|
||||||
|
## Acceptance Criteria
|
||||||
|
|
||||||
|
- Full pipeline runs end-to-end via single API call
|
||||||
|
- Dependency ordering enforced (prices before sec, etc.)
|
||||||
|
- Pipeline status visible via `/api/v1/sync/status`
|
||||||
|
- Failed stage does not block other independent stages
|
||||||
|
- Pipeline health check returns last run time, status, errors
|
||||||
|
|
||||||
|
## Constraints
|
||||||
|
|
||||||
|
- Use Celery chains for ordered stages, Celery groups for parallel stages
|
||||||
|
- Follow existing task patterns — don't reinvent error handling
|
||||||
|
- Keep under 200 lines per framework rule
|
||||||
|
- Read existing migrations before writing schema
|
||||||
|
|
||||||
|
## Files to Create/Modify
|
||||||
|
|
||||||
|
- `src/backend/tasks/pipeline.py` (new)
|
||||||
|
- `src/backend/routers/data_sync.py` (add pipeline trigger endpoint)
|
||||||
|
- `src/backend/celery_app.py` (add pipeline schedule)
|
||||||
|
- `docker-compose.dev.yml` (verify worker includes task)
|
||||||
|
|
||||||
|
## Next Steps After This Task
|
||||||
|
|
||||||
|
Wire backtest integration (phase2-backtest-integration)
|
||||||
@@ -0,0 +1,52 @@
|
|||||||
|
# Task: Wire Financials Ingestion as Celery Task
|
||||||
|
|
||||||
|
## Status: COMPLETE
|
||||||
|
|
||||||
|
## Current State
|
||||||
|
|
||||||
|
`src/data-pipeline/ingest_financials.py` exists as a standalone script. It uses psycopg2 (sync) and runs as a CLI script.
|
||||||
|
|
||||||
|
## Goal
|
||||||
|
|
||||||
|
Make financial data ingestion runnable as a scheduled Celery task, integrated into the pipeline orchestrator.
|
||||||
|
|
||||||
|
## Requirements
|
||||||
|
|
||||||
|
1. Create `src/backend/tasks/ingest_financials.py` Celery task
|
||||||
|
2. Reuse logic from `src/data-pipeline/ingest_financials.py` (don't duplicate)
|
||||||
|
3. Task must be idempotent — deduplicate by (ticker, report_type, period)
|
||||||
|
4. Task must store results into PostgreSQL/TimescaleDB using existing models
|
||||||
|
5. Add to Celery Beat schedule in `celery_app.py`
|
||||||
|
6. Add to docker-compose worker service
|
||||||
|
|
||||||
|
## Acceptance Criteria
|
||||||
|
|
||||||
|
- [x] `celery -A celery_app worker` processes financial ingestion tasks
|
||||||
|
- [x] Running the task twice with same input produces no duplicate records (ON CONFLICT)
|
||||||
|
- [x] Financial data visible in database after task completes
|
||||||
|
- [x] Celery Beat runs it on a configurable schedule (default: daily at 2 AM UTC)
|
||||||
|
|
||||||
|
## Implementation Details
|
||||||
|
|
||||||
|
### Files Created
|
||||||
|
- `src/backend/tasks/ingest_financials.py` — Celery task using yfinance + asyncpg
|
||||||
|
- Fetches quarterly + annual income statement, balance sheet, cash flow
|
||||||
|
- Extracts 20 metrics (revenue, net_income, eps, roe, roa, etc.)
|
||||||
|
- Idempotent upsert via `ON CONFLICT (ticker, filing_date, period)`
|
||||||
|
- 3 retries with exponential backoff for both yfinance fetches and DB writes
|
||||||
|
|
||||||
|
### Files Modified
|
||||||
|
- `src/backend/tasks/__init__.py` — Added `ingest_financials_task` export
|
||||||
|
- `src/backend/celery_app.py` — Added `ingest-financials-daily` schedule (2 AM UTC)
|
||||||
|
- `init.sql` — Added `financials` table + indexes (was missing from Docker init)
|
||||||
|
- `src/backend/database.py` — Added `financials` table to `init_db()` (was missing)
|
||||||
|
|
||||||
|
### Key Design Decisions
|
||||||
|
- Used yfinance (already in backend requirements.txt) instead of duplicating the data-pipeline script
|
||||||
|
- Converted from psycopg2 to asyncpg via `_execute_command()` wrapper
|
||||||
|
- Extracted metrics via column-name matching (yfinance column names vary by ticker)
|
||||||
|
- Derived metrics: debt_to_equity, roe, roa computed from base values
|
||||||
|
|
||||||
|
## Next Steps After This Task
|
||||||
|
|
||||||
|
Wire news ingestion (phase2-wire-news-ingestion)
|
||||||
@@ -0,0 +1,44 @@
|
|||||||
|
# Task: Wire News Ingestion as Celery Task
|
||||||
|
|
||||||
|
## Current State
|
||||||
|
|
||||||
|
`src/data-pipeline/ingest_news.py` exists as a standalone script but is NOT wired as a Celery task. Only `ingest_prices` and `ingest_sec` exist in `src/backend/tasks/`.
|
||||||
|
|
||||||
|
## Goal
|
||||||
|
|
||||||
|
Make news/sentiment data ingestion runnable as a scheduled Celery task, integrated into the pipeline orchestrator.
|
||||||
|
|
||||||
|
## Requirements
|
||||||
|
|
||||||
|
1. Create `src/backend/tasks/ingest_news.py` Celery task
|
||||||
|
2. Reuse logic from `src/data-pipeline/ingest_news.py` (don't duplicate)
|
||||||
|
3. Task must be idempotent — deduplicate by (ticker, source, published_date)
|
||||||
|
4. Task must store news articles and sentiment signals into PostgreSQL
|
||||||
|
5. Add to Celery Beat schedule in `celery_app.py`
|
||||||
|
6. Add to docker-compose worker service
|
||||||
|
|
||||||
|
## Acceptance Criteria
|
||||||
|
|
||||||
|
- `celery -A celery_app worker` processes news ingestion tasks
|
||||||
|
- Running the task twice with same input produces no duplicate records
|
||||||
|
- News articles and sentiment data visible in database after task completes
|
||||||
|
- Celery Beat runs it on a configurable schedule (default: daily)
|
||||||
|
- Frontend can query news via existing `/api/v1/stocks/{ticker}/sentiment` endpoint
|
||||||
|
|
||||||
|
## Constraints
|
||||||
|
|
||||||
|
- Use TimescaleDB hypertables for time-series news data
|
||||||
|
- Follow existing task patterns from `ingest_prices.py` and `ingest_sec.py`
|
||||||
|
- Keep under 200 lines per framework rule
|
||||||
|
- Read existing migrations before writing schema
|
||||||
|
|
||||||
|
## Files to Create/Modify
|
||||||
|
|
||||||
|
- `src/backend/tasks/ingest_news.py` (new)
|
||||||
|
- `src/backend/celery_app.py` (add schedule entry)
|
||||||
|
- `docker-compose.dev.yml` (verify worker includes task)
|
||||||
|
- `src/data-pipeline/ingest_news.py` (verify it's importable, not just executable)
|
||||||
|
|
||||||
|
## Next Steps After This Task
|
||||||
|
|
||||||
|
Wire pipeline orchestrator (phase2-pipeline-orchestrator)
|
||||||
@@ -0,0 +1,58 @@
|
|||||||
|
# Task: Pipeline orchestrator API endpoints
|
||||||
|
|
||||||
|
## Goal
|
||||||
|
Create the API endpoints for triggering and monitoring pipeline runs. This is Phase 2 — the API layer on top of the task definitions from the previous task.
|
||||||
|
|
||||||
|
## Requirements
|
||||||
|
|
||||||
|
### Create `src/backend/services/pipeline_orchestrator.py`
|
||||||
|
|
||||||
|
Implement `PipelineOrchestrator` class:
|
||||||
|
|
||||||
|
1. `run_pipeline(task_name: str, user_id: str) -> str` — start a pipeline run, return run_id
|
||||||
|
2. `get_run_status(run_id: str) -> dict` — return run status (pending/running/completed/failed)
|
||||||
|
3. `cancel_run(run_id: str)` — cancel a running pipeline
|
||||||
|
4. Internal: execute tasks respecting dependency order
|
||||||
|
5. Store run state in memory (dict) — no DB needed yet
|
||||||
|
|
||||||
|
### Create `src/backend/routers/pipeline.py`
|
||||||
|
|
||||||
|
Add endpoints:
|
||||||
|
|
||||||
|
1. `POST /api/v1/pipeline/run` — trigger a pipeline run
|
||||||
|
- Body: `{"task": "news_ingestion"}` or `"full"` for all tasks
|
||||||
|
- Returns: `{"run_id": "...", "status": "pending"}`
|
||||||
|
|
||||||
|
2. `GET /api/v1/pipeline/run/{run_id}` — get run status
|
||||||
|
- Returns: `{"run_id": "...", "status": "...", "tasks": [...]}`
|
||||||
|
|
||||||
|
3. `POST /api/v1/pipeline/run/{run_id}/cancel` — cancel a run
|
||||||
|
- Returns: `{"message": "cancelled"}`
|
||||||
|
|
||||||
|
4. `GET /api/v1/pipeline/tasks` — list available tasks
|
||||||
|
- Returns: list of registered tasks with descriptions
|
||||||
|
|
||||||
|
### Response models in `schemas/pipeline.py`
|
||||||
|
|
||||||
|
Create:
|
||||||
|
- `PipelineRunRequest` — task name to run
|
||||||
|
- `PipelineRunResponse` — run_id and status
|
||||||
|
- `PipelineRunStatus` — detailed run status with task results
|
||||||
|
- `PipelineTaskInfo` — task metadata
|
||||||
|
|
||||||
|
## Acceptance Criteria
|
||||||
|
1. All 4 endpoints work correctly
|
||||||
|
2. Dependency order is respected when running full pipeline
|
||||||
|
3. Run status updates in real-time
|
||||||
|
4. Files stay under 200 lines each
|
||||||
|
|
||||||
|
## Files to Create/Modify
|
||||||
|
- `src/backend/services/pipeline_orchestrator.py`
|
||||||
|
- `src/backend/services/pipeline_tasks.py` (from previous task)
|
||||||
|
- `src/backend/routers/pipeline.py`
|
||||||
|
- `src/backend/schemas/pipeline.py`
|
||||||
|
|
||||||
|
## Files to Read First
|
||||||
|
- `src/backend/services/pipeline_tasks.py` — task definitions
|
||||||
|
- `src/backend/routers/alerts.py` — follow routing pattern
|
||||||
|
- `src/backend/schemas/alert.py` — follow schema pattern
|
||||||
@@ -0,0 +1,51 @@
|
|||||||
|
# Task: Pipeline task definitions
|
||||||
|
|
||||||
|
## Goal
|
||||||
|
Create the task definition classes and registry for the pipeline orchestrator. This is Phase 1 — define what tasks exist and their metadata.
|
||||||
|
|
||||||
|
## Requirements
|
||||||
|
|
||||||
|
### Create `src/backend/services/pipeline_tasks.py`
|
||||||
|
|
||||||
|
Implement:
|
||||||
|
|
||||||
|
1. `PipelineTask` dataclass:
|
||||||
|
- `name: str` — unique task identifier
|
||||||
|
- `description: str` — human-readable name
|
||||||
|
- `func: Callable` — async function to execute
|
||||||
|
- `depends_on: list[str]` — task names that must complete first
|
||||||
|
- `timeout: int` — max execution time in seconds
|
||||||
|
- `retry_count: int` — number of retries on failure
|
||||||
|
|
||||||
|
2. `TaskRegistry` class:
|
||||||
|
- `register(task: PipelineTask)` — add task to registry
|
||||||
|
- `get(task_name: str) -> PipelineTask` — lookup task
|
||||||
|
- `get_all() -> list[PipelineTask]` — list all registered tasks
|
||||||
|
- `get_dependencies(task_name: str) -> list[str]` — get task dependencies
|
||||||
|
- `get_ready_tasks( completed: set[str]) -> list[str]` — find tasks whose deps are met
|
||||||
|
|
||||||
|
3. Register built-in tasks:
|
||||||
|
- `news_ingestion` — runs news data ingestion
|
||||||
|
- `financials_ingestion` — runs financials data ingestion
|
||||||
|
- `sector_rotation` — runs sector rotation analysis
|
||||||
|
- `price_update` — runs price data update
|
||||||
|
- `sentiment_analysis` — runs sentiment analysis
|
||||||
|
|
||||||
|
### Constraints
|
||||||
|
- File under 200 lines
|
||||||
|
- Use existing async patterns
|
||||||
|
- No real DB calls in task definitions
|
||||||
|
|
||||||
|
## Acceptance Criteria
|
||||||
|
1. `TaskRegistry` correctly tracks tasks and dependencies
|
||||||
|
2. `get_ready_tasks()` returns correct task order
|
||||||
|
3. All 5 built-in tasks are registered
|
||||||
|
4. File is under 200 lines
|
||||||
|
|
||||||
|
## Files to Create
|
||||||
|
- `src/backend/services/pipeline_tasks.py`
|
||||||
|
|
||||||
|
## Files to Read First
|
||||||
|
- `src/backend/services/news_ingestion_service.py` — existing task functions
|
||||||
|
- `src/backend/services/financials_ingestion_service.py` — existing task functions
|
||||||
|
- `src/backend/services/rotation_service.py` — existing task functions
|
||||||
@@ -0,0 +1,43 @@
|
|||||||
|
# SPEC: Refactor Alert CRUD to Service Layer
|
||||||
|
|
||||||
|
## Goal
|
||||||
|
Refactor the `src/backend/routers/alerts.py` file to move business logic and data access into a dedicated `src/backend/services/alert_service.py` file. This aligns the alerting module with the existing service-oriented architecture used in the rest of the project (e.g., `SentimentService`, `RotationService`).
|
||||||
|
|
||||||
|
## Exact Requirements
|
||||||
|
1. **Create `src/backend/services/alert_service.py`**:
|
||||||
|
- Implement an `AlertService` class containing methods for all current alert operations.
|
||||||
|
- Methods required:
|
||||||
|
- `get_user_alerts(watchlist_id, status, page, page_size, user_id)`
|
||||||
|
- `create_alert(body, user_id)`
|
||||||
|
- `get_alert(alert_id, user_id)`
|
||||||
|
- `update_alert(alert_id, body, user_id)`
|
||||||
|
- `resolve_alert(alert_id, user_id)`
|
||||||
|
- `dismiss_alert(alert_id, user_id)`
|
||||||
|
2. **Encapsulate Authorization**:
|
||||||
|
- Move the ownership verification logic (`_require_watchlist_owner`) into the service layer or a shared security service.
|
||||||
|
3. **Encapsulate Data Access & Transformation**:
|
||||||
|
- Move all `execute_query`, `execute_one`, and `execute_command` calls into the `AlertService`.
|
||||||
|
- Handle the mapping of database rows to `AlertResponse` and `AlertListResponse` models within the service.
|
||||||
|
4. **Update `src/backend/routers/alerts.py`**:
|
||||||
|
- Remove direct database calls and business logic.
|
||||||
|
- Inject/instantiate `AlertService` and delegate all requests to it.
|
||||||
|
- Maintain the existing FastAPI route definitions and dependency injection (e.g., `get_current_user`).
|
||||||
|
5. **Maintain Feature Parity**:
|
||||||
|
- The API behavior (endpoints, status codes, response models) must remain identical to the current implementation.
|
||||||
|
|
||||||
|
## Acceptance Criteria
|
||||||
|
1. **Code Structure**: `src/backend/routers/alerts.py` contains only routing and request/response handling.
|
||||||
|
2. **Service Implementation**: `src/backend/services/alert_service.py` is the single source of truth for alert business logic.
|
||||||
|
3. **Test Pass Rate**: All tests in `src/backend/tests/test_alerts.py` must pass (including the previously failing tests).
|
||||||
|
4. **No Regressions**: All CRUD operations (Create, Read, Update, Delete, Resolve, Dismiss) must function exactly as before.
|
||||||
|
|
||||||
|
## Constraints & Non-Goals
|
||||||
|
- **Non-Goal**: Do not change the database schema.
|
||||||
|
- **Non-Goal**: Do not change the external API contract (URLs, JSON structure, status codes).
|
||||||
|
- **Constraint**: Maintain existing error handling patterns (e.g., 404 for missing resources, 403/404 for ownership issues).
|
||||||
|
|
||||||
|
## Recommended Implementation Approach
|
||||||
|
1. **Phase 1: Service Creation**: Implement the `AlertService` in `src/backend/services/alert_service.py` by copying logic from the router, but parameterizing it for the service methods.
|
||||||
|
2. **Phase 2: Router Migration**: Replace the body of each router function with a call to the corresponding `AlertService` method.
|
||||||
|
3. **Phase 3: Cleanup**: Remove the old `_require_watchlist_owner` helper from the router.
|
||||||
|
4. **Phase 4: Verification**: Run the existing test suite.
|
||||||
@@ -0,0 +1,69 @@
|
|||||||
|
============================= test session starts ==============================
|
||||||
|
platform linux -- Python 3.14.5, pytest-9.0.3, pluggy-1.6.0
|
||||||
|
rootdir: /home/laptran/ai-env/projects/invest-copilot/src/backend
|
||||||
|
configfile: pyproject.toml
|
||||||
|
plugins: asyncio-1.3.0, cov-7.1.0, anyio-4.13.0
|
||||||
|
asyncio: mode=Mode.AUTO, debug=False, asyncio_default_fixture_loop_scope=None, asyncio_default_test_loop_scope=function
|
||||||
|
collected 23 items / 22 deselected / 1 selected
|
||||||
|
|
||||||
|
src/backend/tests/test_alerts.py F [100%]
|
||||||
|
|
||||||
|
=================================== FAILURES ===================================
|
||||||
|
______________________ TestAlertCRUD.test_get_all_alerts _______________________
|
||||||
|
|
||||||
|
self = <backend.tests.test_alerts.TestAlertCRUD object at 0x7f7faa3a3e10>
|
||||||
|
client = <httpx.AsyncClient object at 0x7f7faa0d1450>
|
||||||
|
test_user = {'token': 'eyJhbGciOiAiSFMyNTYiLCAidHlwIjogIkpXVCJ9.eyJzdWIiOiAidGVzdC11c2VyLTEiLCAiZW1haWwiOiAidGVzdEBleGFtcGxlLmNvbS...148F2igONjGXciVac', 'user': {'email': 'test@example.com', 'id': 'test-user-1', 'name': 'Test User', 'timezone': 'UTC'}}
|
||||||
|
watchlist = {'created_at': '2024-01-01T00:00:00', 'description': 'My tech picks', 'id': 'wl-1', 'is_default': False, ...}
|
||||||
|
mock_db = <AsyncMock id='140186291514944'>
|
||||||
|
|
||||||
|
async def test_get_all_alerts(self, client, test_user, watchlist, mock_db):
|
||||||
|
"""User can retrieve all their alerts."""
|
||||||
|
headers = {"Authorization": f"Bearer {test_user['token']}"}
|
||||||
|
# Create two alerts
|
||||||
|
await client.post("/api/v1/alerts", json={
|
||||||
|
"watchlist_id": watchlist["id"],
|
||||||
|
"type": "price",
|
||||||
|
"message": "Alert 1",
|
||||||
|
}, headers=headers)
|
||||||
|
await client.post("/api/v1/alerts", json={
|
||||||
|
"watchlist_id": watchlist["id"],
|
||||||
|
"type": "sentiment",
|
||||||
|
"message": "Alert 2",
|
||||||
|
}, headers=headers)
|
||||||
|
|
||||||
|
# Mock execute_query to return the created alerts
|
||||||
|
def alerts_query_side_effect(sql, params=None):
|
||||||
|
sql_upper = sql.upper()
|
||||||
|
print(f"DEBUG: sql_upper: {sql_upper}")
|
||||||
|
if "COUNT(*)" in sql_upper and "FROM ALERTS" in sql_upper:
|
||||||
|
return [{"count": 2}]
|
||||||
|
if "FROM ALERTS" in sql_upper:
|
||||||
|
return [
|
||||||
|
{"id": "alert-1", "watchlist_id": watchlist["id"], "type": "price", "trigger_type": None, "message": "Alert 1", "severity": "info", "status": "active", "ticker": None, "triggered_at": None, "resolved_at": None, "metadata": {}, "created_at": "2026-05-01T00:01:00"},
|
||||||
|
{"id": "alert-2", "watchlist_id": watchlist["id"], "type": "sentiment", "trigger_type": None, "message": "Alert 2", "severity": "info", "status": "active", "ticker": None, "triggered_at": None, "resolved_at": None, "metadata": {}, "created_at": "2026-05-01T00:02:00"},
|
||||||
|
]
|
||||||
|
return []
|
||||||
|
mock_db.execute_query.side_effect = alerts_query_side_effect
|
||||||
|
|
||||||
|
response = await client.get(
|
||||||
|
f"/api/v1/alerts?watchlist_id={watchlist['id']}&status=active",
|
||||||
|
headers=headers,
|
||||||
|
)
|
||||||
|
assert response.status_code == 200
|
||||||
|
data = response.json()
|
||||||
|
> assert data["total"] >= 2
|
||||||
|
E assert 0 >= 2
|
||||||
|
|
||||||
|
src/backend/tests/test_alerts.py:78: AssertionError
|
||||||
|
----------------------------- Captured stderr call -----------------------------
|
||||||
|
INFO:httpx:HTTP Request: POST http://test/api/v1/alerts "HTTP/1.1 201 Created"
|
||||||
|
INFO:httpx:HTTP Request: POST http://test/api/v1/alerts "HTTP/1.1 201 Created"
|
||||||
|
INFO:httpx:HTTP Request: GET http://test/api/v1/alerts?watchlist_id=wl-1&status=active "HTTP/1.1 200 OK"
|
||||||
|
------------------------------ Captured log call -------------------------------
|
||||||
|
INFO httpx:_client.py:1740 HTTP Request: POST http://test/api/v1/alerts "HTTP/1.1 201 Created"
|
||||||
|
INFO httpx:_client.py:1740 HTTP Request: POST http://test/api/v1/alerts "HTTP/1.1 201 Created"
|
||||||
|
INFO httpx:_client.py:1740 HTTP Request: GET http://test/api/v1/alerts?watchlist_id=wl-1&status=active "HTTP/1.1 200 OK"
|
||||||
|
=========================== short test summary info ============================
|
||||||
|
FAILED src/backend/tests/test_alerts.py::TestAlertCRUD::test_get_all_alerts
|
||||||
|
======================= 1 failed, 22 deselected in 0.04s =======================
|
||||||
Reference in New Issue
Block a user