moneyfeel-mri 1.0.4

Python client for the MoneyFeel Macro Risk Index API

moneyfeel-mri

Python client for the moneyfeel Macro & Geopolitical Risk Index.

Free programmatic access to the moneyfeel MRI — an institutional-grade macro regime classifier covering 5 regions (GLOBAL, US, EU, ASIA, EM) across 3 timeframes (Daily, Weekly, Monthly), updated daily.

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Installation

pip install moneyfeel-mri

# With pandas support (recommended)
pip install moneyfeel-mri[pandas]

Get a Free API Key

1. Register at moneyfeel.it — free, no credit card
2. Go to your account page
3. Find the MRI API Access section → Generate API Key

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Quick Start

from moneyfeel import MRI

client = MRI("mf_live_YOUR_KEY")

# Current regime — no auth required
current = client.current()
for region in current:
    print(region["region"], region["regime_weekly"], region["score_weekly"])

# Historical data as pandas DataFrame
df = client.history_df("US", "WEEKLY", from_date="2020-01-01")
print(df.tail())

# Latest regime
latest = client.latest("EU", "WEEKLY")
print(f"EU: {latest['regime']} | score={latest['mri_score']}")

# Performance metrics
m = client.metrics("US", "WEEKLY")[0]
print(f"Sharpe: {m['sharpe']} | CAGR: {m['cagr_strategy']}% | MaxDD: {m['max_dd']}%")

# Full CSV download
df_full = client.download("US", "WEEKLY")           # returns DataFrame
client.download("US", "WEEKLY", "us_weekly.csv")    # saves to file

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All Methods

Method	Auth	Description
current()	No	Current regime for all 5 regions
status()	No	API health check
regions()	No	Available regions and timeframes
history(region, tf, from_date, to_date)	Yes	Historical regime data
history_df(region, tf, from_date, to_date)	Yes	Same, as pandas DataFrame
latest(region, tf)	Yes	Most recent regime record
metrics(region, tf)	Yes	Strategy performance KPIs
timeseries(region, tf, from_date)	Yes	Daily return series
timeseries_df(region, tf, from_date)	Yes	Same, as pandas DataFrame
eoy(region, tf)	Yes	Year-by-year returns
drawdowns(region, tf)	Yes	Top 10 drawdown periods
download(region, tf, output_path)	Yes	Full CSV dataset

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Error Handling

from moneyfeel import MRI, MRIAuthError, MRIRateLimitError
import time

client = MRI("mf_live_YOUR_KEY")

try:
    data = client.history("US", "WEEKLY")
except MRIAuthError:
    print("Invalid or revoked key — get a new one at https://moneyfeel.it/conto-iscrizione/")
except MRIRateLimitError as e:
    print(f"Rate limited — retry after {e.retry_after}s")
    time.sleep(e.retry_after)

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Data Coverage

• Regions: GLOBAL · US · EU · ASIA · EM
• Timeframes: DAILY · WEEKLY · MONTHLY
• History: 2007-01-04 to present
• Updated: daily at market close

Rate Limits

Limit	Value
Requests/minute	30
Requests/day	2,000
History	Full (2007+)
Cost	Free

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Links

• 🌐 moneyfeel.it
• 📊 Live Dashboard
• 📖 API Documentation
• 🔑 Get API Key

License

CC BY-NC 4.0 — free for research and non-commercial use.