Sirius Prediction Market API
Python wrapper for the Sirius Prediction Market API on RapidAPI.
Access real-time prediction markets, AI-generated trading signals, market sentiment, sports odds, weather data, and cross-platform odds comparison — all from a single, zero-dependency package.
Installation
pip install sirius-prediction-api
Quick Start
from sirius_prediction_api import SiriusAPI
api = SiriusAPI("your-rapidapi-key")
# Check API status
print(api.health())
# Get active prediction markets
markets = api.markets()
for market in markets:
print(market["question"], market["odds"])
Get Your API Key
- Go to RapidAPI - Sirius Prediction Market API
- Subscribe to a plan (free tier available)
- Copy your
X-RapidAPI-Keyfrom the dashboard
Endpoints
Free Tier
api = SiriusAPI("your-key")
# Active prediction markets with odds
markets = api.markets()
# Trading signals with optional filters
signals = api.signals(limit=10, layer="L1", min_gap=0.10)
# Historical signals with outcomes
history = api.signals_history()
# Market sentiment — Fear & Greed + long/short ratios
sentiment = api.sentiment()
# Sports odds (ESPN + Kalshi)
sports = api.sports()
# Weather-related prediction data
weather = api.weather()
# Cross-platform odds comparison
odds = api.odds()
Basic Tier
# Bot performance — win rate, PnL, track record
performance = api.performance()
# Full trade history with entry/exit details
trades = api.trades()
Pro Tier
# AI brain — optimization decisions and reasoning
brain = api.brain()
Signal Layers
The API provides signals from multiple detection layers:
| Layer | Source | Description |
|---|---|---|
| L1 | Price lag | Cross-platform price discrepancies |
| L2 | News | News-driven market moves |
| L3 | Weather | Weather-based predictions |
| L4 | Kalshi | Kalshi platform arbitrage |
| L5 | Sports | ESPN + Kalshi sports signals |
Filter by layer:
# Only price-lag signals with at least 10% gap
signals = api.signals(layer="L1", min_gap=0.10)
Error Handling
The library raises specific exceptions for different error types:
from sirius_prediction_api import (
SiriusAPI,
SiriusAuthError,
SiriusForbiddenError,
SiriusRateLimitError,
SiriusAPIError,
)
api = SiriusAPI("your-key")
try:
brain = api.brain()
except SiriusAuthError:
print("Invalid API key")
except SiriusForbiddenError:
print("Upgrade your plan for this endpoint")
except SiriusRateLimitError:
print("Rate limited — slow down or upgrade")
except SiriusAPIError as e:
print(f"API error [{e.status_code}]: {e.message}")
| Exception | HTTP Code | Meaning |
|---|---|---|
SiriusAuthError |
401 | Invalid or missing API key |
SiriusForbiddenError |
403 | Endpoint not in your tier |
SiriusNotFoundError |
404 | Resource not found |
SiriusRateLimitError |
429 | Rate limit exceeded |
SiriusServerError |
5xx | Server-side error |
SiriusAPIError |
any | Base class for all errors |
Configuration
api = SiriusAPI(
api_key="your-key",
timeout=60, # request timeout in seconds (default: 30)
)
Requirements
- Python 3.8+
- Zero dependencies — uses only
urllib.requestfrom the standard library
License
MIT
Metadata
Release files for sirius-prediction-api 1.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| sirius_prediction_api-1.1.0.tar.gz | 9.7 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| sirius_prediction_api-1.1.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 17.9 kB
Release files / sirius_prediction_api-1.1.0.tar.gz
| Download URL | sirius_prediction_api-1.1.0.tar.gz |
|---|---|
| Size | 9.7 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
5a6de503f80bb89cfdb1990c1f1e07421de3e68dbf5c74d69c537f3306d0904e
|
|
BLAKE2b-256 checksum How to use checksums |
b8ad12d510dece30bff64e572d9fdd91274ff1ca21ab56b93119a2bfb034aa42
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.12.3
|
Release files / sirius_prediction_api-1.1.0-py3-none-any.whl
| Download URL | sirius_prediction_api-1.1.0-py3-none-any.whl |
|---|---|
| Size | 8.2 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
f0edcf8b5c7b9f2ed43634f944ffd1cc8cfa0c6e5cca5809b3d3b5520b07d6a6
|
|
BLAKE2b-256 checksum How to use checksums |
5007cabb42f600c023e633157cbd083ffeb94447979bd034ec7d54b1f29fd169
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.12.3
|
Security for sirius-prediction-api 1.1.0
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.