sector_pulse.py

#!/usr/bin/env python3
"""
sector-pulse — Multi-sector investment signal aggregator.

Tracks funding rounds, milestones, and key companies across:
TechBio/Biotech, Fusion Energy, Quantum Computing, AI Agents, Space Tech.

Pure Python 3 stdlib. No pip installs required.
"""

import argparse
import json
import sys
import textwrap
from datetime import datetime

# ─────────────────────────────────────────────────────────────
# DATA — Curated 2026-02-16
# ─────────────────────────────────────────────────────────────

SECTORS = {
    "fusion": {
        "name": "Fusion Energy",
        "emoji": "☀️",
        "companies": [
            {
                "name": "Helion Energy",
                "funding": "$425M+",
                "status": "150 million °C plasma milestone achieved",
                "stage": "Series E",
                "signal": "🟢 Strong",
            },
            {
                "name": "Commonwealth Fusion Systems",
                "funding": "$863M+",
                "status": "Building SPARC tokamak; world-record HTS magnets",
                "stage": "Series B",
                "signal": "🟢 Strong",
            },
            {
                "name": "Type One Energy",
                "funding": "$250M raising",
                "status": "Stellarator approach; fundraising in progress",
                "stage": "Series B",
                "signal": "🟡 Watch",
            },
            {
                "name": "Inertia Enterprises",
                "funding": "$450M Series A",
                "status": "Stealth-ish; massive Series A signals deep-tech bet",
                "stage": "Series A",
                "signal": "🟢 Strong",
            },
            {
                "name": "TAE Technologies",
                "funding": "$1.2B+ total",
                "status": "Exploring going public; beam-driven FRC approach",
                "stage": "Late",
                "signal": "🟡 Watch",
            },
        ],
        "thesis": (
            "Fusion is transitioning from science project to engineering challenge. "
            "Multiple companies have hit plasma milestones previously thought decades away. "
            "Key catalysts: HTS magnet breakthroughs (CFS), record temperatures (Helion), "
            "and massive private capital ($6B+ deployed sector-wide). "
            "The 2028-2035 window is when net-energy demos should land. "
            "Risk: physics works but engineering/economics may lag. "
            "Opportunity: first-mover in baseload clean energy = generational company."
        ),
        "search_queries": [
            "fusion energy funding 2026",
            "Helion Energy milestone 2026",
            "Commonwealth Fusion SPARC update",
            "fusion startup Series A B 2026",
        ],
    },
    "quantum": {
        "name": "Quantum Computing",
        "emoji": "⚛️",
        "companies": [
            {
                "name": "IBM",
                "funding": "Public (NYSE: IBM)",
                "status": "Unveiled 2 new quantum supercomputers; 1000+ qubit roadmap",
                "stage": "Public",
                "signal": "🟢 Strong",
            },
            {
                "name": "Google (Willow)",
                "funding": "Public (NASDAQ: GOOGL)",
                "status": "Willow chip: breakthrough in quantum error correction",
                "stage": "Public",
                "signal": "🟢 Strong",
            },
            {
                "name": "IonQ",
                "funding": "Public (NYSE: IONQ)",
                "status": "Trapped-ion approach; enterprise partnerships growing",
                "stage": "Public",
                "signal": "🟡 Watch",
            },
            {
                "name": "Rigetti Computing",
                "funding": "Public (NASDAQ: RGTI)",
                "status": "Superconducting qubits; cloud-accessible QPUs",
                "stage": "Public",
                "signal": "🟡 Watch",
            },
            {
                "name": "PsiQuantum",
                "funding": "$700M+",
                "status": "Photonic approach; GlobalFoundries manufacturing deal",
                "stage": "Late Private",
                "signal": "🟡 Watch",
            },
        ],
        "thesis": (
            "Quantum computing hit an inflection point with Google's Willow demonstrating "
            "real error correction and IBM pushing past 1000 logical qubits. "
            "We're in the 'useful but not universal' phase — quantum advantage for specific "
            "workloads (pharma simulation, optimization, crypto) is 2-4 years out. "
            "Public plays (IBM, GOOGL) offer exposure with less risk. "
            "Private bets (PsiQuantum) are higher-risk/higher-reward on alternative architectures. "
            "Key risk: decoherence and error rates may plateau. "
            "Key catalyst: first commercial quantum advantage demonstration."
        ),
        "search_queries": [
            "quantum computing funding 2026",
            "IBM quantum supercomputer 2026",
            "Google Willow quantum chip",
            "quantum computing startup funding round",
        ],
    },
    "techbio": {
        "name": "TechBio / Longevity",
        "emoji": "🧬",
        "companies": [
            {
                "name": "Life Biosciences",
                "funding": "$500M+",
                "status": "FDA clinical trial for longevity-adjacent therapeutic",
                "stage": "Clinical",
                "signal": "🟢 Strong",
            },
            {
                "name": "Altos Labs",
                "funding": "$3B",
                "status": "Cellular reprogramming; Yamanaka factors research",
                "stage": "Series A (mega)",
                "signal": "🟢 Strong",
            },
            {
                "name": "NewLimit",
                "funding": "$130M+",
                "status": "Epigenetic reprogramming; Brian Armstrong-backed",
                "stage": "Series A",
                "signal": "🟡 Watch",
            },
            {
                "name": "Retro Biosciences",
                "funding": "$180M+",
                "status": "Sam Altman-backed; autophagy, plasma, reprogramming",
                "stage": "Early",
                "signal": "🟡 Watch",
            },
            {
                "name": "Recursion Pharmaceuticals",
                "funding": "Public (NASDAQ: RXRX)",
                "status": "AI-driven drug discovery; massive dataset moat",
                "stage": "Public",
                "signal": "🟢 Strong",
            },
            {
                "name": "Isomorphic Labs",
                "funding": "Alphabet-backed",
                "status": "DeepMind spinout; AlphaFold for drug design",
                "stage": "Private (corporate)",
                "signal": "🟢 Strong",
            },
        ],
        "thesis": (
            "TechBio is the convergence of AI/ML with biological research — and longevity is "
            "its most ambitious frontier. Altos Labs ($3B!) and Isomorphic Labs represent "
            "big-tech conviction that AI can crack biology. Life Biosciences entering FDA trials "
            "is a major de-risking event. Recursion's AI-first approach is generating real pipeline. "
            "Key risk: biology is still incredibly hard; 90%+ clinical failure rates persist. "
            "Key catalyst: first AI-discovered drug approval, or reprogramming proof in humans. "
            "This sector rewards patience — 5-10 year horizon for the biggest wins."
        ),
        "search_queries": [
            "techbio longevity funding 2026",
            "Life Biosciences FDA trial",
            "Altos Labs reprogramming update",
            "AI drug discovery startup 2026",
        ],
    },
    "ai-agents": {
        "name": "AI Agents",
        "emoji": "🤖",
        "companies": [
            {
                "name": "OpenClaw / OpenAI Ecosystem",
                "funding": "Open-source + Foundation",
                "status": "180K GitHub stars; building agent infrastructure layer",
                "stage": "Foundation/OSS",
                "signal": "🟢 Strong",
            },
            {
                "name": "Manufact (MCP)",
                "funding": "$6.3M",
                "status": "Model Context Protocol tooling; early but strategic",
                "stage": "Seed",
                "signal": "🟡 Watch",
            },
            {
                "name": "Cognition (Devin)",
                "funding": "$175M+ (Series A)",
                "status": "AI software engineer; polarizing but category-defining",
                "stage": "Series A",
                "signal": "🟡 Watch",
            },
        ],
        "thesis": (
            "AI agents are the next platform shift after LLMs — from 'AI that answers' to "
            "'AI that acts.' The MCP (Model Context Protocol) ecosystem is emerging as a "
            "connective tissue standard. OpenClaw's 180K stars signal massive developer interest "
            "in agent infrastructure. Cognition's Devin proved the category exists even if V1 "
            "is rough. Key risk: reliability — agents that fail 20% of the time aren't useful. "
            "Key catalyst: agents that reliably complete multi-step real-world tasks. "
            "This is early innings — like web apps in 1996. Infrastructure plays > application plays."
        ),
        "search_queries": [
            "AI agent startup funding 2026",
            "MCP model context protocol",
            "AI coding agent startup",
            "autonomous AI agent funding round",
        ],
    },
    "space": {
        "name": "Space Tech",
        "emoji": "🚀",
        "companies": [
            {
                "name": "SpaceX",
                "funding": "$10B+ (private, ~$210B valuation)",
                "status": "Starship progress; Starlink dominant; Mars timeline",
                "stage": "Late Private",
                "signal": "🟢 Strong",
            },
            {
                "name": "Relativity Space",
                "funding": "$1.3B+",
                "status": "3D-printed rockets; Terran R in development",
                "stage": "Late Private",
                "signal": "🟡 Watch",
            },
            {
                "name": "Rocket Lab",
                "funding": "Public (NASDAQ: RKLB)",
                "status": "Electron workhorse; Neutron medium-lift in dev",
                "stage": "Public",
                "signal": "🟢 Strong",
            },
            {
                "name": "Astra",
                "funding": "Public (NASDAQ: ASTR)",
                "status": "Pivoting to spacecraft/propulsion after launch struggles",
                "stage": "Public",
                "signal": "🔴 Caution",
            },
        ],
        "thesis": (
            "Space is bifurcating: SpaceX dominates launch, everyone else fights for niches. "
            "Rocket Lab is the best public pure-play — reliable Electron + Neutron upside. "
            "Relativity's 3D-printing approach is either genius or a dead end (Terran R will tell). "
            "The real opportunity may be in space infrastructure (comms, debris removal, "
            "in-space manufacturing) rather than launch. "
            "Key risk: SpaceX moat is enormous; commoditized launch kills margins. "
            "Key catalyst: Starship fully operational changes the economics of everything in orbit."
        ),
        "search_queries": [
            "space tech startup funding 2026",
            "SpaceX Starship update 2026",
            "Rocket Lab Neutron progress",
            "space startup Series A B 2026",
        ],
    },
}

VALID_SECTORS = list(SECTORS.keys())

# ─────────────────────────────────────────────────────────────
# DISPLAY HELPERS
# ─────────────────────────────────────────────────────────────

WIDTH = 72
DIVIDER = "─" * WIDTH
DOUBLE_DIVIDER = "═" * WIDTH


def header(text):
    print(f"\n{DOUBLE_DIVIDER}")
    print(f"  {text}")
    print(DOUBLE_DIVIDER)


def section(text):
    print(f"\n{DIVIDER}")
    print(f"  {text}")
    print(DIVIDER)


def wrap(text, indent=4):
    wrapped = textwrap.fill(text, width=WIDTH - indent, initial_indent=" " * indent, subsequent_indent=" " * indent)
    print(wrapped)


def company_card(c, index):
    print(f"\n  {index}. {c['name']}  {c['signal']}")
    print(f"     Funding: {c['funding']}  |  Stage: {c['stage']}")
    print(f"     Status:  {c['status']}")


# ─────────────────────────────────────────────────────────────
# COMMANDS
# ─────────────────────────────────────────────────────────────


def cmd_companies(args):
    """Display curated watchlist of key companies per sector."""
    sectors_to_show = VALID_SECTORS
    if hasattr(args, "sector") and args.sector:
        if args.sector not in SECTORS:
            print(f"Unknown sector: {args.sector}")
            print(f"Valid sectors: {', '.join(VALID_SECTORS)}")
            sys.exit(1)
        sectors_to_show = [args.sector]

    header("📊 SECTOR PULSE — Company Watchlist")
    print(f"  Last updated: 2026-02-16  |  {len(SECTORS)} sectors tracked")

    for key in sectors_to_show:
        s = SECTORS[key]
        section(f"{s['emoji']}  {s['name'].upper()}  ({len(s['companies'])} companies)")
        for i, c in enumerate(s["companies"], 1):
            company_card(c, i)

    print(f"\n{DIVIDER}")
    print("  Signal legend: 🟢 Strong conviction  🟡 Watch/monitor  🔴 Caution")
    print(DIVIDER)
    print()


def cmd_thesis(args):
    """Print investment thesis summary per sector."""
    sectors_to_show = VALID_SECTORS
    if hasattr(args, "sector") and args.sector:
        if args.sector not in SECTORS:
            print(f"Unknown sector: {args.sector}")
            print(f"Valid sectors: {', '.join(VALID_SECTORS)}")
            sys.exit(1)
        sectors_to_show = [args.sector]

    header("📝 SECTOR PULSE — Investment Theses")

    for key in sectors_to_show:
        s = SECTORS[key]
        section(f"{s['emoji']}  {s['name'].upper()}")
        print()
        wrap(s["thesis"])

    print(f"\n{DOUBLE_DIVIDER}")
    print("  Disclaimer: Not financial advice. DYOR.")
    print(DOUBLE_DIVIDER)
    print()


def cmd_scan(args):
    """Show search queries for a sector (designed for web_search integration)."""
    sector = args.sector
    if sector not in SECTORS:
        print(f"Unknown sector: {sector}")
        print(f"Valid sectors: {', '.join(VALID_SECTORS)}")
        sys.exit(1)

    s = SECTORS[sector]
    header(f"🔍 SECTOR PULSE — Scan: {s['name']}")
    print()
    print("  Suggested search queries for latest signals:")
    print()
    for i, q in enumerate(s["search_queries"], 1):
        print(f"    {i}. {q}")
    print()
    print("  Companies to monitor:")
    for c in s["companies"]:
        print(f"    • {c['name']}")
    print()
    print(f"  💡 Run these queries in your preferred search tool or use")
    print(f"     web_search for automated scanning.")
    print()


def cmd_all(args):
    """Run all sectors and generate summary."""
    header("🌐 SECTOR PULSE — Full Report")
    now = datetime.now().strftime("%Y-%m-%d %H:%M")
    print(f"  Generated: {now}")

    # Summary table
    section("SECTOR OVERVIEW")
    print()
    print(f"  {'Sector':<25} {'Companies':>10} {'Strong':>8} {'Watch':>8} {'Caution':>8}")
    print(f"  {'─'*25} {'─'*10} {'─'*8} {'─'*8} {'─'*8}")

    total_companies = 0
    total_strong = 0

    for key in VALID_SECTORS:
        s = SECTORS[key]
        companies = s["companies"]
        strong = sum(1 for c in companies if "Strong" in c["signal"])
        watch = sum(1 for c in companies if "Watch" in c["signal"])
        caution = sum(1 for c in companies if "Caution" in c["signal"])
        total_companies += len(companies)
        total_strong += strong
        print(f"  {s['emoji']} {s['name']:<23} {len(companies):>10} {strong:>8} {watch:>8} {caution:>8}")

    print(f"  {'─'*25} {'─'*10} {'─'*8} {'─'*8} {'─'*8}")
    print(f"  {'TOTAL':<25} {total_companies:>10} {total_strong:>8}")

    # Top signals
    section("🔥 TOP SIGNALS")
    print()
    all_strong = []
    for key in VALID_SECTORS:
        s = SECTORS[key]
        for c in s["companies"]:
            if "Strong" in c["signal"]:
                all_strong.append((s["emoji"], s["name"], c["name"], c["status"]))

    for emoji, sector, name, status in all_strong:
        print(f"  {emoji} [{sector}] {name}")
        print(f"     → {status}")
        print()

    # Key themes
    section("📌 KEY THEMES")
    print()
    themes = [
        "Fusion energy hitting engineering milestones — multiple companies at plasma temperatures",
        "Quantum error correction breakthroughs (Google Willow) shifting timeline left",
        "AI agents emerging as next platform — infrastructure plays (MCP, OpenClaw) leading",
        "TechBio convergence: AI + biology = accelerated drug discovery pipeline",
        "Space bifurcation: SpaceX dominance vs. niche opportunity for others",
    ]
    for i, t in enumerate(themes, 1):
        wrap(f"{i}. {t}", indent=4)

    print(f"\n{DOUBLE_DIVIDER}")
    print(f"  End of report  |  {total_companies} companies across {len(SECTORS)} sectors")
    print(DOUBLE_DIVIDER)
    print()


# ─────────────────────────────────────────────────────────────
# CLI
# ─────────────────────────────────────────────────────────────


def main():
    parser = argparse.ArgumentParser(
        prog="sector-pulse",
        description="Multi-sector investment signal aggregator",
        formatter_class=argparse.RawDescriptionHelpFormatter,
        epilog=textwrap.dedent("""\
            sectors: fusion, quantum, techbio, ai-agents, space

            examples:
              sector-pulse companies            Show all company watchlists
              sector-pulse companies --sector fusion   Show fusion companies only
              sector-pulse thesis               Investment theses for all sectors
              sector-pulse scan fusion          Search queries for fusion sector
              sector-pulse all                  Full report across all sectors
        """),
    )

    subparsers = parser.add_subparsers(dest="command", help="Command to run")

    # companies
    p_companies = subparsers.add_parser("companies", help="Display curated company watchlist")
    p_companies.add_argument("--sector", "-s", choices=VALID_SECTORS, help="Filter to a single sector")

    # thesis
    p_thesis = subparsers.add_parser("thesis", help="Print investment thesis per sector")
    p_thesis.add_argument("--sector", "-s", choices=VALID_SECTORS, help="Filter to a single sector")

    # scan
    p_scan = subparsers.add_parser("scan", help="Show search queries for a sector")
    p_scan.add_argument("sector", choices=VALID_SECTORS, help="Sector to scan")

    # all
    p_all = subparsers.add_parser("all", help="Full report across all sectors")

    args = parser.parse_args()

    if args.command is None:
        parser.print_help()
        sys.exit(0)

    commands = {
        "companies": cmd_companies,
        "thesis": cmd_thesis,
        "scan": cmd_scan,
        "all": cmd_all,
    }

    commands[args.command](args)


if __name__ == "__main__":
    main()