check_ticker
Deterministic Market Snapshot & Price Validation
check_ticker is a deterministic market‑snapshot tool designed for automation pipelines, monitoring systems, and operators who require reproducible, audit‑transparent price checks. It performs lightweight market‑data retrieval, validates response integrity, normalizes price‑change fields, and produces structured output suitable for dashboards and monitoring environments.
Frozen Binary Distribution
All NMS_Tools, including check_ticker, are distributed as standalone frozen executables. They run directly without requiring a Python installation, virtual environment, or external dependencies. This ensures consistent behavior across systems and allows demos and integrations to call the tools exactly as shipped.
Overview
check_ticker provides a reproducible inspection pipeline for market‑data providers. It validates provider availability, response structure, price fields, and change metrics using deterministic logic consistent across environments. The tool is built around three principles:
- Determinism — same inputs → same output
- Reproducibility — no environment‑dependent behavior
- Audit Transparency — explicit, structured, operator‑grade output
Key Features
- Deterministic market‑data request handling
- Price, change, and percent‑change validation
- Structured JSON output for automation pipelines
- Provider‑integrity and schema validation
- Timestamp normalization
Market Inspection
- Deterministic provider request with strict timeout behavior
- Explicit evaluation of price, change, and percent‑change fields
- Normalization of provider output into operator‑friendly categories
- Response schema validation and error classification
Deterministic Behavior
- No implicit retries or fallback providers
- Consistent output across all environments
- Structured JSON for automation pipelines
- Operator‑grade verbose mode for diagnostics
Architecture Overview
1. Request Layer
Performs a deterministic provider request with strict timeout and explicit error classification. Connection failures return UNKNOWN/CRITICAL states with clear diagnostic messages.
2. Response Parsing Layer
Extracts price, change, percent‑change, timestamp, and provider fields. All fields are normalized for reproducibility.
3. Validation Layer
- Price‑field validation
- Change and percent‑change normalization
- Schema and field‑presence verification
4. Output Layer
Produces deterministic JSON or verbose output. All fields are explicit and audit‑transparent.
Current Status
- Version: 1.0.0
- Edition: Community Edition (public)
- Platform: Linux / Python 3.x
- Dependencies: requests
Example JSON Output
{
"symbol": "AAPL",
"price": 227.15,
"change": -1.32,
"percent_change": -0.58,
"timestamp": "2026-08-24T08:59:00-05:00",
"provider": "yahoo"
}
Roadmap
Near‑Term
- Extended provider‑integrity validation
- Additional price‑change metrics
Mid‑Term
- Structured response‑time metrics
- Multi‑provider fallback (deterministic)
Long‑Term
- Cross‑suite correlation with check_weather.py
- Market‑based alerting thresholds
Why check_ticker Exists
Traditional ticker checkers often produce inconsistent output, rely on provider‑specific quirks, or provide limited visibility into price‑change fields. check_ticker solves this by applying deterministic engineering principles:
- explicit validation
- reproducible output
- audit‑transparent reporting
- no hidden behavior or implicit assumptions
Links
Related Projects
License
This check_ticker is part of the NMS_Tools suite and is released under the MIT License. See the LICENSE file in the repository for full terms.
Contact
If you'd like to reach out, feel free to email me at ldmcclatchey@linktechengineering.net or connect with me on LinkedIn: linkedin.com/in/leonmcclatchey .