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========
Glossary
========
Before we dive into the concepts, let's clarify the terminology we'll be using:
.. list-table::
:header-rows: 0
* - Directed Acyclic Graph (DAG)
- A `directed acyclic graph <https://en.wikipedia.org/wiki/Directed\_acyclic\_graph>`_ is a computer \
science/mathematics term for representing the world with "nodes" and "edges", where "edges" only flow in one \
direction. It is called a graph because it can be drawn and visualized.
* - Dataflow
- The organization of functions and dependencies. This is a DAG -- it's directed (one function is running before \
the other), acyclic, (there are no cycles, i.e., no function runs before itself), and a graph (it is easily \
naturally represented by nodes and edges) and can be represented visually. See :doc:`node`.
* - Node |
Hamilton node |
Transform
- A single step in the dataflow DAG representing a computation -- usually 1:1 with functions but decorators break that \
pattern -- in which case multiple transforms trace back to a single function. See :doc:`node`.
* - Function |
Python function |
Hamilton function |
Node definition
- A Python function written by a user to create a single node (in the standard case) or \
many (using function modifiers). See :doc:`node`.
* - Module |
Python module
- Python code organized into a ``.py`` file. exte function written by a user to create a
single node (in the standard case) or many (using function modifiers). See :doc:`node`.
* - Driver |
Hamilton Driver
- An object that loads Python modules to build a dataflow. It is responsible for visualizing and executing the \
dataflow. See :doc:`driver`.
* - script |
runner |
driver code
- The piece of code where you create the Driver and execute the dataflow to get results.
* - Config
- Data that dictates the way the DAG is constructed. See :doc:`driver`.
* - Function modifiers |
Decorators
- A function that modifies how your Hamilton function is compiled into a Hamilton node. See :doc:`function-modifiers`.