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When to Use grph

grph is a command-line tool for exploring and analyzing graph data. This article helps you understand when graph analysis is the right approach and when grph is the right tool.

What Problems Suit Graph Analysis?​

Graph analysis shines when your data involves relationships between entities. If you can phrase your question as "how does X relate to Y?", graphs might help.

Good Fit: Relationship Questions​

  • "What depends on this package?"
  • "How can I get from A to B?"
  • "Who is most influential?"
  • "What connects these two things?"
  • "What's the impact if this node fails?"

Less Good Fit: Aggregate Questions​

  • "What's the total sales this quarter?" (use SQL/analytics)
  • "What's the average response time?" (use monitoring tools)
  • "How many users signed up?" (use databases)

Real-World Use Cases​

Software Development​

Dependency Analysis

  • "What breaks if I upgrade lodash?"
  • "Are there circular dependencies?"
  • "What's the dependency chain to this package?"

Architecture Understanding

  • "Which services call which?"
  • "What's the blast radius of this API change?"
  • "Which modules are most coupled?"
# Find what depends on a critical package
grph neighbors dependencies.gexf lodash --direction in --depth 2

# Check for cycles
grph components dependencies.gexf --type strongly --list

DevOps & Infrastructure​

Network Topology

  • "What's the path from client to database?"
  • "Which routers are single points of failure?"
  • "What's affected if this node goes down?"

Service Mesh Analysis

  • "How do requests flow through the system?"
  • "Which services are most critical?"
# Find critical network nodes
grph centrality network.gexf --type betweenness --top 10

# Trace request path
grph path services.gexf api-gateway database

Data Engineering​

Lineage Tracking

  • "Where does this data come from?"
  • "What downstream systems use this table?"
  • "What's the transformation path?"
# Find data sources
grph neighbors lineage.gexf final-report --direction in --depth 5

# Find downstream impact
grph neighbors lineage.gexf raw-data --direction out --depth 5

Research & Analysis​

Citation Networks

  • "What are the foundational papers in this field?"
  • "How are these research areas connected?"

Collaboration Networks

  • "Who are the key collaborators?"
  • "Which groups work together?"
# Find influential papers
grph centrality citations.gexf --type pagerank --top 20

Social & Organizational​

Influence Analysis

  • "Who are the key influencers?"
  • "How connected are two people?"

Organizational Analysis

  • "Who are the bridges between teams?"
  • "What's the communication structure?"
# Find organizational connectors
grph centrality org-network.gexf --type betweenness --top 10

# Find common connections
grph common-neighbors org.gexf person-a person-b

Why Command Line?​

grph is a CLI tool. This is intentional:

Strengths of CLI​

  1. Scriptable: Chain with other tools, automate analysis
  2. Fast: No GUI overhead, quick answers
  3. Reproducible: Commands can be documented and rerun
  4. Piping: Use with jq, grep, shell scripts
  5. CI/CD Integration: Add graph checks to pipelines
# Script example: Check for deprecated dependencies
grph nodes deps.gexf --attr deprecated=True --json | jq '.[].id' > deprecated.txt
if [ -s deprecated.txt ]; then
  echo "Warning: Deprecated packages found"
  cat deprecated.txt
fi

When You Might Want Something Else​

  • Visualization: Export to Gephi, D3.js, or other tools
  • Complex queries: Graph databases like Neo4j offer query languages
  • Real-time analysis: Streaming graph tools for live data
  • Very large graphs: Distributed systems like Apache Spark GraphX

The grph Philosophy​

Like grep, but for graphs.

Just as grep lets you quickly search text files, grph lets you quickly explore graph files. It's designed for:

  • Quick answers to graph questions
  • Exploration of unknown graph data
  • Integration with other command-line tools
  • Simple, focused functionality

Getting Started​

If you have graph data and relationship questions, give grph a try:

# Install
pip install grph-cli

# Explore your data
grph info your-graph.gexf
grph nodes your-graph.gexf
grph stats your-graph.gexf

# Start asking questions
grph neighbors your-graph.gexf interesting-node
grph centrality your-graph.gexf --type pagerank --top 10

The tutorials in this documentation use realistic examples that demonstrate grph's capabilities.