Search Results for "live-graph"

Luigi is a Python (3.6, 3.7, 3.8, 3.9 tested) package that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization, handling failures, command line integration, and much more. The purpose of Luigi is to address all the plumbing typically associated with long-running batch processes. You want to chain many tasks, automate them, and failures will happen. These tasks can be anything, but are typically long running things like Hadoop...

...The project is structured around clear, executable Python scripts and Jupyter notebooks that demonstrate regression, classification, convolutional networks, recurrent networks, autoencoders, and generative adversarial networks, which gives learners practical exposure to real machine learning tasks. Each example explains PyTorch’s dynamic computation graph, optimization techniques, and core abstractions in a way that is accessible and reproducible. Contributors and authors integrate visual and coded examples so readers can see both the theory and the implementation side-by-side.

General purpose build tool. Key features: Flexible and scalable for large projects Dynamic dependency graph Batch build support Distributed build scripts (no fixed project structure) Support any build target types (files, strings, URLs, remote resources etc.) Conditional options Scons like build scripts (but don't compatible)

Ubuntu based GNU/Linux system, use Gnome Shell. Easy for learn Linux and programming. All software of everyday use. Wine and Virtual Machine for use other OS.

Dagger evaluates file dependencies in a directed-acyclic-graph (DAG) like GNU make, but timestamps or hashes can be used on a per-file basis when evaluating which file nodes are up to date or stale. Use fast timestamp comparisons on large files when hashing is too slow, and hashing on small files. When hashing is used, it's stored in either a text file or sqlite database (in-memory at runtime is optional).

An advanced incremental build system written in Python, introducing support for automatic dependency and recipe discovery. It supports single- and multi-threaded builds. It requires Python v2.6 and pybfc and, natively supports all POSIX systems.