Houdini 20.5 Executing tasks with PDG/TOPs
The classes and functions in the Python pdgutils package are intended for use both in PDG nodes and scripts as well as out-of-process job scripts.
Explains the basic concepts behind TOP networks and what you can do with them.
How to use the unique network editor features of TOP networks.
TOP attributes are like point attributes, You can use them to set parameters in Houdini nodes called by the work items.
Best practices for input/output file paths in TOP networks.
A quick guide to the most commonly used TOP nodes.
It is often necessary to describe in the network what jobs must finish before other jobs can begin.
Cooking/Executing the TOP network
How to cause the TOP network to actually do the work and produce the results specified by the network.
External configuration and data
How to read external configuration and source data in TOPs and use it to drive work.
The Wedge node creates a work item for each variation of one or more attributes you specify.
Descriptions of each PDG example file and where to find them.
How to wrap external functionality in a TOP node.
Work items track the results created by their work. Each result is tagged with a type.
The PDG Path Map manages the mapping of paths between file systems.
You can use for-each blocks to process looping, sequential chains of operations on work items.
Services blocks let you define a section of work items that should run using a shared Service process
PDG services manages pools of persistent Houdini sessions that can be used to reduce work item cooking time.
Integrating PDG with render farm schedulers
How to use different schedulers to schedule and execute work.
Visualizing work item performance
How to visualize the relative cook times (or file output sizes) of work items in the network.
You can register a Python function to handle events from a PDG node or graph
Useful general information and best practices for working with TOPs.
Troubleshooting PDG scheduler issues on the farm
Useful information to help you troubleshoot scheduling PDG work items on the farm.
Standalone application or limited license for working with PDG-specific workflows.
TOP nodes define a workflow where data is fed into the network, turned into work items and manipulated by different nodes. Many nodes represent external processes that can be run on the local machine or a server farm.
Processor nodes generate work items that can be executed by a scheduler
Partitioner nodes group multiple upstream work items into single partitions.
Scheduler nodes execute work items
PDG uses file tags to determine the type of an output file.
The classes and functions in the Python pdg package for working with dependency graphs.
Python API used by job scripts.
The classes and functions in the Python pdgutils package are intended for use both in PDG nodes and scripts as well as out-of-process job scripts.