FXMacroData Examples Hub

This directory is the source bundle for the public examples repository: https://github.com/fxmacrodata/examples

Use these projects to publish demos across app stores, template directories, and hosting platforms so developers discover FXMacroData quickly and then move to a paid plan at:

• https://fxmacrodata.com/subscribe

Public endpoints (USD announcements, forex, calendar, market sessions, data catalogue) can be used without an API key. Protected endpoints (non-USD announcements, COT, commodities) require a paid key from the subscribe flow.

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Deployable app matrix

App	Framework	Hosted on	Live URL
Central Bank Rate Monitor	Streamlit	Streamlit Community Cloud	deploy link
FX Trade Setup Studio	Web (Vanilla JS)	GitHub Pages / Netlify / Vercel Static	deploy link
FX & Macro Explorer	Gradio	Hugging Face Spaces	deploy link
FX Macro Heatmap	Plotly Dash	Render	deploy link
Macro Intelligence Dashboard	HoloViz Panel	Hugging Face Spaces	deploy link
FX Market Intelligence	Next.js	Vercel	deploy link
USD Macro Snapshot API	FastAPI	Railway/Render/Fly.io	deploy link
USD Macro Landing App	Flask	Render/Railway	deploy link
Edge Macro Widget Proxy	Cloudflare Worker	Cloudflare	deploy link
Netlify Macro Widget	Netlify Functions + static	Netlify	deploy link
Policy Rate Divergence	Backtrader	Local script	—
Policy Rate Divergence	Zipline	Local script	—
Macro Signal (BTC/USDT)	Freqtrade	Local strategy	—
FX Strategy Backtesting	VectorBT (Jupyter)	Run locally / JupyterHub	—
Macro Data Access	pandas-datareader	Local script	—
Macro Carry Scanner	CCXT	Local script	—
Carry Rebalance Bot	Blankly	Local strategy	—

Distribution-first publishing loop

1. Launch each app in the public examples repo.
2. Add a visible CTA to https://fxmacrodata.com/subscribe in app header/footer.
3. Submit links to framework galleries and community indexes.
4. Add badges/screenshots to this README once each app is live.

Suggested distribution targets:

• Vercel templates
• Streamlit gallery
• Hugging Face Spaces
• Netlify templates/examples
• Cloudflare Worker examples
• Plotly Dash Show and Tell
• Reddit (r/algotrading, r/quant, r/forex) and X build threads

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Key safety policy (required)

Never commit or print real API keys. Use only these patterns:

• Environment variables (FXMACRODATA_API_KEY)
• Host-level encrypted secrets (Vercel/Netlify/Render/Cloudflare)
• .env.example templates only (never real .env files)
• Optional user-entered key fields that stay in memory only

Before publishing, run a scan:

grep -RInE "(sk-|AIza|FXMACRODATA_API_KEY\s*=\s*['\"][^'\"]+)" . || true

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QuantConnect / LEAN Integration

Use FXMacroData as a custom data source inside QuantConnect backtests and live-trading algorithms.

cd quantconnect   # copy fxmacrodata/ into your LEAN project

See quantconnect/README.md for setup instructions and two example algorithms:

• Macro Monitor — plot USD indicators in QuantConnect charts (free, no key)
• Policy Rate Divergence — FX carry strategy driven by central-bank rate differentials

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Freqtrade Integration

Use FXMacroData as a macro signal source inside Freqtrade strategies.

cd freqtrade
cp fxmacrodata_ft.py MacroSignalStrategy.py \
   ~/.freqtrade/user_data/strategies/
freqtrade backtesting --strategy MacroSignalStrategy --timeframe 1d \
    --timerange 20200101-20251231 --pair BTC/USDT

See freqtrade/README.md for setup and the included Macro Signal strategy (BTC/USDT driven by the USD real policy rate).

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Zipline Integration

Use FXMacroData as a custom bundle and macro data source inside zipline-reloaded backtests.

cd zipline   && pip install -r requirements.txt && python example.py

See zipline/README.md for setup and the included Policy Rate Divergence strategy (EUR/USD carry driven by central-bank rate differentials).

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CCXT Integration

Use FXMacroData through the CCXT unified interface. The adapter implements the standard CCXT exchange API so you can plug FXMacroData into any existing CCXT-based trading or analysis workflow.

cd ccxt      && pip install -r requirements.txt && python example.py

See ccxt/README.md for setup and usage. Supported CCXT methods:

• load_markets() — 30 FX pairs + XAU/USD, XAG/USD, XPT/USD
• fetch_ohlcv(symbol, '1d', since, limit) — daily mid-market candles
• fetch_ticker(symbol) / fetch_tickers(symbols) — latest rates
• fetch_macro_indicator(currency, indicator) — macro extension

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Quick start (run any app locally)

# Python apps (pick one)
cd streamlit   && pip install -r requirements.txt && streamlit run app.py
cd gradio      && pip install -r requirements.txt && python app.py
cd dash        && pip install -r requirements.txt && python app.py
cd panel       && pip install -r requirements.txt && panel serve app.py --autoreload
cd flask       && pip install -r requirements.txt && python app.py
cd fastapi     && pip install -r requirements.txt && uvicorn app:app --reload --port 8010
cd backtrader  && pip install -r requirements.txt && python example.py
cd zipline     && pip install -r requirements.txt && python example.py
cd freqtrade   # copy fxmacrodata_ft.py + MacroSignalStrategy.py into user_data/strategies/

# pandas-datareader
cd pandas-datareader && pip install -r requirements.txt && python example.py

# VectorBT Jupyter notebook
cd vectorbt && pip install -r requirements.txt && jupyter notebook fxmacrodata_vectorbt.ipynb

# CCXT macro scanner
cd ccxt      && pip install -r requirements.txt && python example.py

# Next.js app
cd vercel && npm install && npm run dev

# Netlify app
cd netlify-widget && npm install && npm run dev

# FX Trade Setup Studio (static app)
cd pollinations/fx-trade-setup-studio && python -m http.server 8080

# Cloudflare Worker
cd cloudflare-worker && npm install && npm run dev

# QuantConnect / LEAN — copy the fxmacrodata/ package into your LEAN project
# then follow quantconnect/README.md

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Deploy yourself

Streamlit → Streamlit Community Cloud

1. Fork this repo (or push streamlit/ to your own public repo).
2. Go to share.streamlit.io, sign in with GitHub.
3. New app → select repo → set main file to streamlit/app.py.
4. Click Deploy.

Gradio → Hugging Face Spaces

1. Create a Space at huggingface.co/spaces → SDK: Gradio.
2. Upload gradio/app.py and gradio/requirements.txt.
3. Space builds automatically.

Dash → Render

1. Fork this repo.
2. Go to render.com → New Web Service → connect repo.
3. Set root directory to dash/, start command: gunicorn app:server.
4. Or use the included render.yaml blueprint: New → Blueprint → connect repo.

Panel → Hugging Face Spaces (Docker)

1. Create a Space at huggingface.co/spaces → SDK: Docker.
2. Upload panel/app.py, panel/requirements.txt, and panel/Dockerfile.
3. Space builds automatically.

VectorBT → run locally or on JupyterHub

cd vectorbt
pip install -r requirements.txt
jupyter notebook fxmacrodata_vectorbt.ipynb

Or launch on any hosted Jupyter environment (Google Colab, JupyterHub, Binder) by uploading fxmacrodata_vectorbt.ipynb and requirements.txt.

Vercel → Vercel

Or manually: vercel.com → Add New → Project → import repo → root directory: vercel/.

Flask / FastAPI → Render or Railway

1. Push flask/ or fastapi/ to your public examples repo.
2. Create a new service on Render/Railway.
3. Set start command:
   • Flask: gunicorn app:app
   • FastAPI: uvicorn app:app --host 0.0.0.0 --port $PORT
4. Add FXMACRODATA_API_KEY as an environment variable only if you need protected endpoints.

Netlify Functions

1. Import the repo into Netlify.
2. Set base directory to netlify-widget/.
3. Add optional environment variable: FXMACRODATA_API_KEY.
4. Deploy and share your .netlify.app URL.

Cloudflare Worker

1. Deploy cloudflare-worker/ via wrangler deploy.
2. Add optional secret with wrangler secret put FXMACRODATA_API_KEY.
3. Use the Worker URL from any frontend widget.

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API key (optional)

All apps accept an API key at runtime via a sidebar input. To pre-configure:

Platform	Method
Streamlit Cloud	Settings → Secrets → FXMACRODATA_API_KEY = "key"
HF Spaces	Settings → Secrets → FXMACRODATA_API_KEY
Render	Environment → FXMACRODATA_API_KEY
Vercel	Settings → Environment Variables → FXMACRODATA_API_KEY

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pandas-datareader Integration

Use FXMacroData as a drop-in data source inside any workflow that already uses pandas-datareader.

cd pandas-datareader && pip install -r requirements.txt && python example.py

See pandas-datareader/README.md for the full guide and two usage patterns:

• Standalone readers — FXMacroDataIndicatorReader, FXMacroDataForexReader, FXMacroDataCommoditiesReader, FXMacroDataCOTReader
• DataReader interface — register once and use pdr.DataReader("USD/inflation", "fxmacrodata", ...)

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API endpoints used

Endpoint	Auth	Used by
GET /v1/announcements/usd/{indicator}	Free	Streamlit, Dash, Gradio, Panel
GET /v1/announcements/{currency}/{indicator}	API key	All
GET /v1/forex/{base}/{quote}	Free	Gradio, Backtrader, VectorBT
GET /v1/calendar/{currency}	Free	Gradio, Vercel
GET /v1/commodities/{indicator}	API key	Panel, Vercel, Backtrader
GET /v1/cot/{currency}	API key	Vercel

Full reference: fxmacrodata.com/documentation

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Links

• FXMacroData
• API Docs
• Subscribe
• API management
• Public examples repository
• Security and key policy
• Public repo publishing playbook