krl-network-analysis 0.2.0

Economic network analysis tools for the Khipu Intelligence Suite

KRL Network Analysis

Version: 1.0.0
License: Apache-2.0
Python: ≥3.9
Status: Production ✅

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SECTION A — Executive & Strategic Overview

What This Repository Does

KRL Network Analysis provides economic network analysis tools. It implements:

1. Network Construction — Build networks from economic data
2. Centrality Analysis — Identify key actors and bottlenecks
3. Community Detection — Discover economic clusters
4. Shock Propagation — Model cascading effects
5. Supply Chain Risk — Identify vulnerabilities

Current Maturity Level: PRODUCTION ✅

Criterion	Status
Core network methods	✅ Yes
Centrality analysis	✅ Yes
Test coverage	✅ 79.7% (2166/2718 lines)
Branch coverage	✅ 73.5% (929/1264 branches)
Documentation	✅ Yes

This is the best-tested repository in the KRL suite.

Strategic Dependencies

• Upstream: krl-premium-backend (API access)
• Downstream: None
• Peer: krl-geospatial-tools (network + spatial overlap)

Known Gaps

1. Coverage gap to 80% — Close but not quite at target
2. Branch coverage 73.5% — Good but could improve

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SECTION B — Product, Marketing & Sales Intelligence

Network Capabilities (Verified)

Capability	Status
Economic network construction	✅
Centrality measures	✅
Community detection	✅
Temporal network analysis	✅
Shock propagation modeling	✅
Supply chain vulnerability	✅
Network visualization	✅

Capabilities Safe to Reference in Sales

✅ Can claim:

• "Economic network analysis"
• "Supply chain risk assessment"
• "Shock propagation modeling"
• "Input-output network analysis"
• "Trade network analysis"
• "~80% test coverage"

Differentiators

1. Economic focus — Designed for economic networks, not generic graphs
2. Supply chain analysis — Built-in vulnerability detection
3. Shock modeling — Cascade effect simulation
4. High quality — Best test coverage in KRL suite

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SECTION C — Engineering & Development Brief

Tech Stack

Component	Technology
Language	Python ≥3.9
Graphs	networkx
Visualization	plotly, matplotlib
Data	pandas, numpy
Testing	pytest

How to Run

pip install -e ".[dev]"
pytest tests/ -v --cov=src

Key Modules

Module	Purpose
construction/	Build networks from data
centrality/	Centrality measures
community/	Community detection
dynamics/	Temporal analysis
risk/	Vulnerability assessment
visualization/	Network plots

Quality Metrics

Coverage: 79.7% (2166/2718 lines)
Branch:   73.5% (929/1264 branches)

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SECTION D — Operational & Governance Notes

Maintenance Risks

Risk	Severity	Mitigation
Coverage gap to 80%	LOW	Add edge case tests
Branch coverage gap	LOW	Improve conditional coverage

Ownership

• Team: KR-Labs Engineering
• Escalation: [e-mail]

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Last updated: December 14, 2025 — Forensic audit verified 79.7% coverage