Tutorials#

The tutorials cover specifics features with detailed demonstrations to help understanding the fundamental PyDPF-Core functionalities and clarify some concepts. They are designed to teach how to perform a task, providing explanations at each stage.

It helps to have a Python interpreter for hands-on experience, but all code examples are executed, so the tutorial can be read off-line as well.

For a complete description of all the objects and modules, see the API reference section.

Beginner’s guide#

New to PyDPF-Core? Check our beginner’s tutorials. They offer an overview of basic features and concepts so you can start coding right away.

Data structures

Learn about the different data structures available in DPF.

DPF data structures
Post-processing data basics

Follow a basic post-processing procedure with data transformation, visualization and analysis using PyDPf-Core.

Processing data basics

Common topics#

Importing data

Understand how to represent data in DPF: either from manual input either form result files.

Import Data
Meshes

Learn how to interact with meshes in PyDPF-Core.

Meshes
Processing data with operators and workflows

Learn how to use operators to process your data and build workflows.

Exporting data

Discover the best ways to export data from your manipulations with PyDPF-Core.

Plotting

Explore the different approaches to visualise the data in plots.

Plot
Animations

Explore the different approaches to visualise the data in an animation.

Animate
Mathematical operations

Learn how to perform mathematical operations on data structures.

Mathematics
Custom Python operator and plugin

Discover how to enhance DPF capabilities with custom operators and plugins.

Custom Operators and Plugins
Processing distributed files

Learn how to use PyDPF-Core with distributed result files.

Managing local and remote servers

Learn about the DPF client-server architecture and management of local and remote servers.

Manage licensing

Learn how to manage licensing in PyDPF-Core.