Skill · em Dados, IA e pesquisa

networkx

Comprehensive toolkit for creating, analyzing, and visualizing complex networks and graphs in Python. Use when working with network/graph data structures, analyzing relationships between entities, computing graph algorithms (shortest paths, centrality, clustering), detecting communities, generating…

Procedência

Antes de instalar

6 arquivos · 56,7 KB · só texto, nenhum script

Instalar na sua CLI

O comando baixa a versão fixada (commit 57f899e) direto da origem, para a pasta que a CLI lê. Precisa de curl (macOS e Linux); no Windows não há comando, porque o Rook Labs é para macOS.

Claude Code

Neste projeto: instala em .claude/skills/networkx/.

d=".claude/skills/networkx"
u="https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/cli-tool/components/skills/scientific/networkx"
curl -fsSL --create-dirs \
  -o "$d/SKILL.md" "$u/SKILL.md" \
  -o "$d/references/algorithms.md" "$u/references/algorithms.md" \
  -o "$d/references/generators.md" "$u/references/generators.md" \
  -o "$d/references/graph-basics.md" "$u/references/graph-basics.md" \
  -o "$d/references/io.md" "$u/references/io.md" \
  -o "$d/references/visualization.md" "$u/references/visualization.md" \
  -o "$d/LICENSE" "https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/LICENSE"

Global: instala em ~/.claude/skills/networkx/.

d="$HOME/.claude/skills/networkx"
u="https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/cli-tool/components/skills/scientific/networkx"
curl -fsSL --create-dirs \
  -o "$d/SKILL.md" "$u/SKILL.md" \
  -o "$d/references/algorithms.md" "$u/references/algorithms.md" \
  -o "$d/references/generators.md" "$u/references/generators.md" \
  -o "$d/references/graph-basics.md" "$u/references/graph-basics.md" \
  -o "$d/references/io.md" "$u/references/io.md" \
  -o "$d/references/visualization.md" "$u/references/visualization.md" \
  -o "$d/LICENSE" "https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/LICENSE"

Codex

Neste projeto: instala em .agents/skills/networkx/.

d=".agents/skills/networkx"
u="https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/cli-tool/components/skills/scientific/networkx"
curl -fsSL --create-dirs \
  -o "$d/SKILL.md" "$u/SKILL.md" \
  -o "$d/references/algorithms.md" "$u/references/algorithms.md" \
  -o "$d/references/generators.md" "$u/references/generators.md" \
  -o "$d/references/graph-basics.md" "$u/references/graph-basics.md" \
  -o "$d/references/io.md" "$u/references/io.md" \
  -o "$d/references/visualization.md" "$u/references/visualization.md" \
  -o "$d/LICENSE" "https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/LICENSE"

Global: instala em ~/.agents/skills/networkx/.

d="$HOME/.agents/skills/networkx"
u="https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/cli-tool/components/skills/scientific/networkx"
curl -fsSL --create-dirs \
  -o "$d/SKILL.md" "$u/SKILL.md" \
  -o "$d/references/algorithms.md" "$u/references/algorithms.md" \
  -o "$d/references/generators.md" "$u/references/generators.md" \
  -o "$d/references/graph-basics.md" "$u/references/graph-basics.md" \
  -o "$d/references/io.md" "$u/references/io.md" \
  -o "$d/references/visualization.md" "$u/references/visualization.md" \
  -o "$d/LICENSE" "https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/LICENSE"

Antigravity

Neste projeto: instala em .agents/skills/networkx/.

d=".agents/skills/networkx"
u="https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/cli-tool/components/skills/scientific/networkx"
curl -fsSL --create-dirs \
  -o "$d/SKILL.md" "$u/SKILL.md" \
  -o "$d/references/algorithms.md" "$u/references/algorithms.md" \
  -o "$d/references/generators.md" "$u/references/generators.md" \
  -o "$d/references/graph-basics.md" "$u/references/graph-basics.md" \
  -o "$d/references/io.md" "$u/references/io.md" \
  -o "$d/references/visualization.md" "$u/references/visualization.md" \
  -o "$d/LICENSE" "https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/LICENSE"

Global: instala em ~/.gemini/antigravity-cli/skills/networkx/.

d="$HOME/.gemini/antigravity-cli/skills/networkx"
u="https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/cli-tool/components/skills/scientific/networkx"
curl -fsSL --create-dirs \
  -o "$d/SKILL.md" "$u/SKILL.md" \
  -o "$d/references/algorithms.md" "$u/references/algorithms.md" \
  -o "$d/references/generators.md" "$u/references/generators.md" \
  -o "$d/references/graph-basics.md" "$u/references/graph-basics.md" \
  -o "$d/references/io.md" "$u/references/io.md" \
  -o "$d/references/visualization.md" "$u/references/visualization.md" \
  -o "$d/LICENSE" "https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/LICENSE"

Peça ao Rook

Já usa o Rook Labs? Cole no chat do Rook: instale a skill https://rooklabs.sh/marketplace/cct.networkx

Prévia do SKILL.md

---
name: networkx
description: Comprehensive toolkit for creating, analyzing, and visualizing complex networks and graphs in Python. Use when working with network/graph data structures, analyzing relationships between entities, computing graph algorithms (shortest paths, centrality, clustering), detecting communities, generating synthet…
---

# NetworkX

## Overview

NetworkX is a Python package for creating, manipulating, and analyzing complex networks and graphs. Use this skill when working with network or graph data structures, including social networks, biological networks, transportation systems, citation networks, knowledge graphs, or any system involving relationships betwee…

## When to Use This Skill

Invoke this skill when tasks involve:

- **Creating graphs**: Building network structures from data, adding nodes and edges with attributes
- **Graph analysis**: Computing centrality measures, finding shortest paths, detecting communities, measuring clustering
- **Graph algorithms**: Running standard algorithms like Dijkstra's, PageRank, minimum spanning trees, maximum flow
- **Network generation**: Creating synthetic networks (random, scale-free, small-world models) for testing or simulation
- **Graph I/O**: Reading from or writing to various formats (edge lists, GraphML, JSON, CSV, adjacency matrices)
- **Visualization**: Drawing and customizing network visualizations with matplotlib or interactive libraries
- **Network comparison**: Checking isomorphism, computing graph metrics, analyzing structural properties

## Core Capabilities

### 1. Graph Creation and Manipulation

NetworkX supports four main graph types:
- **Graph**: Undirected graphs with single edges
- **DiGraph**: Directed graphs with one-way connections
- **MultiGraph**: Undirected graphs allowing multiple edges between nodes
- **MultiDiGraph**: Directed graphs with multiple edges

Create graphs by:
```python
import networkx as nx

# Create empty graph
G = nx.Graph()
…

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