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Edge

As explained in Build Python Web Apps with Streamlit

A graph edge is a connection between two graph nodes that represents a relationship or execution transition.

An edge is a connection between two nodes in a graph. It represents a relationship, such as friendship, or a transition in which one node’s output becomes another node’s input. section 10.2.2 section 8.2.2

The meaning of an edge depends on the graph being modeled:

  • A social-network edge can represent a relationship between two people; friendship is shown as an undirected connection. section 10.2.2
  • A LangGraph edge is directed, showing which node executes first and where its output may flow next. section 10.2.2
  • Together with nodes and graph state, edges organize an application as a sequence of state-transforming actions. section 10.2.2

A workflow edge

Imagine a LangGraph workflow with one node that retrieves information and another that generates a response. An arrow from the retrieval node to the response node means the response action can receive the retrieval node’s updated state. A similar graph can compute the sum of squares by connecting action nodes in execution order. section 10.2.2

Figure 10.4 In LangGraph, nodes take in the graph state and modify it.

Use the diagram to trace how directed edges connect LangGraph nodes while state moves through the workflow. section 10.2.2

How Build Python Web Apps with Streamlit covers it

How deep it goes
Explains graph connections, direction, execution order, and state transfer without detailing implementation APIs.
Examples
Uses social-network friendships, LangGraph workflows, and a sum-of-squares computation as concrete graph examples.
What it assumes
Assumes no computer-science background and introduces graphs, nodes, edges, and state from plain-language examples.
What you can do after
Apply it via LangGraph to represent which application actions execute next and exchange updated state.
How it connects
Connects graphs with nodes, graph state, workflows, relationships, and breadth-first search.

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This explainer was generated by Manning's knowledge graph from the text of Build Python Web Apps with Streamlit. The section links point to the parts of the book it draws on.