quantumsignals-client 0.2.0

Python client for Quantum Signals APIs (streaming, inference, key management, backtest)

Quantum Signals Client

Python client library for Quantum Signals APIs.

Overview

This package provides a Python client for interacting with Quantum Signals services:

• Streaming: SSE-based signal streaming
• Inference: Model catalog and prediction endpoints
• Key Management: API key CRUD operations
• Backtest: Backtest results and metadata

Configuration

The client reads configuration from environment variables:

# Required:
export QUANTUMSIGNALS_API_KEY=foobar
# Optional, defaults to production URL:
export QUANTUMSIGNALS_BASE_URL=http://localhost:8000

The API key can also be set explicitly:

from signalq.client import Client
client = Client(api_key="foobar")
client.set_api_key("foobar")

Usage

Init

from signalq.client import Client
client = Client()

Fetching Available Models

models = client.get_model_catalog()

Streaming Signals

# Stream real-time signals via SSE
for signal in client.stream_signals():
    print(f"{signal.time} | {signal.symbol}: {signal.signal}")

Backtest Operations

# Get most recent backtest for a model/symbol
backtest = client.get_most_recent_backtest(
    model_hash="abc123",
    symbol="AAPL"
)

# Get backtest metadata
metadata = client.get_backtest_metadata(backtest_id="uuid")

# Get backtest results (JSON, CSV, or Parquet)
results = client.get_backtest_results(
    backtest_id="uuid",
    format="json",
    page=1,
    page_size=100
)

# Get accuracy metrics
accuracy = client.get_backtest_accuracy(
    backtest_id="uuid",
    format="json"
)

Context Manager Usage

# Properly close HTTP connections
with Client() as client:
    client.login()
    models = client.get_model_catalog()
    # Client automatically closes on exit

Development

This is a workspace package in the QS1 monorepo. See the main repository README for development setup.