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TCS-COMMUNITY 🌏

The open community of TCS-PLATFORM β€” L1–L3 real-time macro signal pipeline + Discussions + Pro Trial. Built by TCS-PLATFORM Β· MIT License

Repo renamed 07/05/2026: tcs-macro-pulse β†’ TCS-COMMUNITY. The Python package on PyPI is still tcs-macro-pulse (no breaking change). Old GitHub links auto-redirect.

Python 3.11+ License: MIT ⭐ Star this repo


What is this?

tcs-macro-pulse is the open-source L1-L3 macro data pipeline powering TCS-PLATFORM β€” a Vietnamese investment intelligence system.

We open-source the data collection layer (L1-L3) so the community can:

  • Build their own macro dashboards
  • Contribute new data sources
  • Research macro-market correlations

What stays private: Our L4-L9 proprietary analysis engine (ThΓ‘i αΊ€t / TCI scoring system) β€” that's our IP.


Features (L1-L3 Open Source)

Layer Source What it fetches
L1 Macro FRED (US Federal Reserve) GDP, CPI, Fed Funds Rate, Unemployment, M2
L1 Macro World Bank Global GDP growth, Inflation by country
L2 News GDACS Natural disasters + severity scores
L2 News ACLED Conflict/protest events by country
L2 News ReliefWeb Humanitarian crisis updates
L3 Social RSS feeds Curated financial news sentiment (keyword-based)

Quick Start

# Install
pip install tcs-macro-pulse

# Or from source
git clone https://github.com/TCS-PLATFORM-OFFICIAL/TCS-COMMUNITY
cd tcs-macro-pulse
pip install -e .

# Fetch FRED macro data (no API key needed for basic indicators)
python -m tcs_macro_pulse.fetchers.fred --output macro_data.json

# Fetch GDACS disaster events
python -m tcs_macro_pulse.fetchers.gdacs --days 30 --output disasters.json

# Full pipeline
python examples/full_pipeline.py

⭐ Get 30-Day Pro Trial

Star this repo + open a Trial Request issue β†’ 30 days TCS-PLATFORM Pro free (worth $29)

Live demo: tcs-platform-rust.vercel.app

Pro tier includes:

  • L4-L9 TCI scoring (our proprietary engine)
  • 10 VN stocks + 5 global assets tracked daily
  • AI QuΓ’n SΖ° chatbot access
  • Risk alerts via Telegram/Zalo

Architecture

tcs-macro-pulse (OSS β€” this repo)
β”œβ”€β”€ L1: Macro data (FRED, World Bank, IMF)
β”œβ”€β”€ L2: News/events (GDACS, ACLED, ReliefWeb)  
└── L3: Social signals (RSS, keyword sentiment)

TCS-PLATFORM (Private β€” our SaaS)
β”œβ”€β”€ L4: Technical analysis
β”œβ”€β”€ L5: Sentiment scoring
β”œβ”€β”€ L6: Fundamental analysis
β”œβ”€β”€ L7: ThΓ‘i αΊ€t / ThiΓͺn CΖ‘ SΓ‘ch (PROPRIETARY β€” NOT in this repo)
β”œβ”€β”€ L8: Macro synthesis
└── L9: Final signal generation

Usage Examples

Fetch FRED data

from tcs_macro_pulse.fetchers.fred import FREDFetcher

fetcher = FREDFetcher()
data = fetcher.fetch_key_indicators()
print(data)
# {'fed_funds_rate': 5.33, 'cpi_yoy': 3.4, 'unemployment': 3.9, 'gdp_growth': 2.8}

Fetch GDACS disasters

from tcs_macro_pulse.fetchers.gdacs import GDACSSentinel

sentinel = GDACSSentinel()
events = sentinel.fetch_recent(days=7)
for e in events:
    print(f"{e['type']} Β· {e['country']} Β· severity {e['alert_level']}")

Keyword-based news sentiment

from tcs_macro_pulse.analysis.keyword_sentiment import KeywordSentiment

analyzer = KeywordSentiment()
result = analyzer.analyze_headlines(headlines=[
    "Fed signals rate cut in September",
    "China PMI falls below 50",
    "VN-Index hits 1300 resistance",
])
print(result)
# {'overall': 'NEUTRAL', 'bullish': 1, 'bearish': 1, 'neutral': 1, 'score': 0.0}

Contributing

  1. Fork β†’ branch feat/your-feature
  2. Add a new fetcher in tcs_macro_pulse/fetchers/
  3. Add tests in tests/
  4. PR with description of data source + license confirmation

Contribution ideas:

  • IMF World Economic Outlook fetcher
  • Eurostat GDP fetcher
  • Twitter/X financial sentiment (requires API key)
  • Crypto Fear & Greed Index
  • VN macro data (GSO, SBV)

License

MIT Β© 2026 TCS-PLATFORM. See LICENSE.

Data sources have their own terms of use β€” see each fetcher's docstring.


Disclaimer

This is a data collection tool only. No investment advice. Past data does not guarantee future results.

About

TCS-COMMUNITY - Open community for TCS-PLATFORM. L1-L3 macro pipeline (FRED/GDACS/ACLED) + Discussions + Trial Pro 30 days. Star to join.

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